@bigcommerce/stencil-cli@1.15.5

Vulnerabilities

97 via 436 paths

Dependencies

1044

Source

npm

Find, fix and prevent vulnerabilities in your code.

Severity
  • 3
  • 43
  • 40
  • 11
Status
  • 97
  • 0
  • 0

critical severity

Arbitrary File Write via Archive Extraction (Zip Slip)

  • Vulnerable module: decompress-zip
  • Introduced through: jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 decompress-zip@0.1.0

Overview

decompress-zip extracts the contents of the ZIP archive file.

Affected versions of this package are vulnerable to Arbitrary File Write via Archive Extraction (Zip Slip). The package will extract files outside of the scope of the specified target directory because there is no validation that file extraction stays within the defined target path.

Details

It is exploited using a specially crafted zip archive, that holds path traversal filenames. When exploited, a filename in a malicious archive is concatenated to the target extraction directory, which results in the final path ending up outside of the target folder. For instance, a zip may hold a file with a "../../file.exe" location and thus break out of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.

The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicous file will result in traversing out of the target folder, ending up in /root/.ssh/ overwriting the authorized_keys file:


+2018-04-15 22:04:29 ..... 19 19 good.txt

+2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys

Remediation

Upgrade decompress-zip to version 0.2.2, 0.3.2 or higher.

References

critical severity

Arbitrary Code Execution

  • Vulnerable module: front-matter
  • Introduced through: front-matter@1.0.0

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 front-matter@1.0.0
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.

Overview

front-matter is a package that extracts meta data (front-matter) from documents.

Affected versions of this package are vulnerable to Arbitrary Code Execution due to the default usage of the function yaml.load() of the package js-yaml instead of its secure replacement , yaml.safeLoad().

Remediation

Upgrade front-matter to version 4.0.1 or higher.

References

critical severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: lodash@3.10.1, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 upath@0.1.7 lodash@3.10.1
    Remediation: Upgrade to upath@1.0.2.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git easy-extender@2.3.2 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 inquirer@0.9.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 inquirer@0.8.5 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 lodash@1.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 zip-stream@0.5.2 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution in zipObjectDeep due to an incomplete fix for CVE-2020-8203.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.20 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: ajv
  • Introduced through: eslint@2.13.1, less@2.7.3 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 eslint@2.13.1 table@3.8.3 ajv@4.11.8
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 less@2.7.3 request@2.81.0 har-validator@4.2.1 ajv@4.11.8
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git localtunnel@1.8.3 request@2.81.0 har-validator@4.2.1 ajv@4.11.8
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 request@2.81.0 har-validator@4.2.1 ajv@4.11.8
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

ajv is an Another JSON Schema Validator

Affected versions of this package are vulnerable to Prototype Pollution. A carefully crafted JSON schema could be provided that allows execution of other code by prototype pollution. (While untrusted schemas are recommended against, the worst case of an untrusted schema should be a denial of service, not execution of code.)

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade ajv to version 6.12.3 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: ammo
  • Introduced through: glue@2.4.0 and hapi@8.8.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 ammo@2.0.4
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 ammo@1.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 inert@2.1.6 ammo@1.0.1

Overview

ammo is a HTTP Range processing utilities. Note This package is deprecated and is now maintained as @hapi/ammo.

Affected versions of this package are vulnerable to Denial of Service (DoS). The Range HTTP header parser has a vulnerability which will cause the function to throw a system error if the header is set to an invalid value. Because hapi is not expecting the function to ever throw, the error is thrown all the way up the stack. If no unhandled exception handler is available, the application will exist, allowing an attacker to shut down services.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

There is no fixed version for ammo.

References

high severity
new

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ansi-regex
  • Introduced through: eslint@2.13.1, npm@2.15.12 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 eslint@2.13.1 table@3.8.3 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 npmlog@4.1.2 gauge@2.7.4 wide-align@1.1.3 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 npm-registry-client@7.2.1 npmlog@3.1.2 gauge@2.6.0 wide-align@1.1.3 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 node-gyp@3.8.0 npmlog@4.1.2 gauge@2.7.4 wide-align@1.1.3 string-width@2.1.1 strip-ansi@4.0.0 ansi-regex@3.0.0

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to the sub-patterns [[\\]()#;?]* and (?:;[-a-zA-Z\\d\\/#&.:=?%@~_]*)*.

PoC

import ansiRegex from 'ansi-regex';

for(var i = 1; i <= 50000; i++) {
    var time = Date.now();
    var attack_str = "\u001B["+";".repeat(i*10000);
    ansiRegex().test(attack_str)
    var time_cost = Date.now() - time;
    console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ansi-regex to version 6.0.1, 5.0.1 or higher.

References

high severity

Remote Memory Exposure

  • Vulnerable module: bl
  • Introduced through: archiver@0.14.4, jspm@0.15.7 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 tar-stream@1.1.5 bl@0.9.5
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 request@2.53.0 bl@0.9.5
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 request@2.53.0 bl@0.9.5
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 request@2.74.0 bl@1.1.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

bl is a library that allows you to collect buffers and access with a standard readable buffer interface.

Affected versions of this package are vulnerable to Remote Memory Exposure. If user input ends up in consume() argument and can become negative, BufferList state can be corrupted, tricking it into exposing uninitialized memory via regular .slice() calls.

PoC by chalker

const { BufferList } = require('bl')
const secret = require('crypto').randomBytes(256)
for (let i = 0; i < 1e6; i++) {
  const clone = Buffer.from(secret)
  const bl = new BufferList()
  bl.append(Buffer.from('a'))
  bl.consume(-1024)
  const buf = bl.slice(1)
  if (buf.indexOf(clone) !== -1) {
    console.error(`Match (at ${i})`, buf)
  }
}

Remediation

Upgrade bl to version 2.2.1, 3.0.1, 4.0.3, 1.2.3 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: content
  • Introduced through: hapi@8.8.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 content@1.0.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 pez@1.0.0 content@1.0.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.

Overview

content is a HTTP Content-* headers parsing

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks. An attacker may pass a specially crafted Content-Type or Content-Disposition header, causing the server to hang. This can cause an impact of about 10 seconds matching time for data 180 characters long.

Disclosure Timeline

  • Feb 5th, 2018 - Initial Disclosure to package owner
  • Feb 5th, 2018 - Initial Response from package owner
  • Feb 28th, 2018 - Fix issued
  • Mar 5th, 2018 - Vulnerability published

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade content to versions 3.0.7, 4.0.4 or higher

References

high severity

Denial of Service (DoS)

  • Vulnerable module: engine.io
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git socket.io@2.0.4 engine.io@3.1.5

Overview

engine.io is a realtime engine behind Socket.IO. It provides the foundation of a bidirectional connection between client and server

Affected versions of this package are vulnerable to Denial of Service (DoS) via a POST request to the long polling transport.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

  • High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

  • Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade engine.io to version 4.0.0 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: fresh
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git serve-static@1.12.2 send@0.15.2 fresh@0.5.0

Overview

fresh is HTTP response freshness testing.

Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks. A Regular Expression (/ *, */) was used for parsing HTTP headers and take about 2 seconds matching time for 50k characters.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade fresh to version 0.5.2 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: handlebars
  • Introduced through: handlebars@3.0.8 and @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 handlebars@3.0.8
    Remediation: Upgrade to @bigcommerce/stencil-cli@2.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars@3.0.8

Overview

handlebars is an extension to the Mustache templating language.

Affected versions of this package are vulnerable to Prototype Pollution. Templates may alter an Objects' prototype, thus allowing an attacker to execute arbitrary code on the server.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade handlebars to version 4.0.14, 4.1.2 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: handlebars
  • Introduced through: handlebars@3.0.8 and @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 handlebars@3.0.8
    Remediation: Upgrade to @bigcommerce/stencil-cli@2.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars@3.0.8

Overview

handlebars is a extension to the Mustache templating language.

Affected versions of this package are vulnerable to Prototype Pollution. Templates may alter an Object's __proto__ and __defineGetter__ properties, which may allow an attacker to execute arbitrary code on the server through crafted payloads.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade handlebars to version 4.3.0, 3.8.0 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: hapi
  • Introduced through: glue@2.4.0 and hapi@8.8.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1

Overview

hapi is a HTTP Server framework.

Affected versions of this package are vulnerable to Denial of Service (DoS). The CORS request handler has a vulnerability which will cause the function to throw a system error if the header contains some invalid values. If no unhandled exception handler is available, the application will exist, allowing an attacker to shut down services.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

There is no fixed version for hapi.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: hapi
  • Introduced through: hapi@8.8.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.

Overview

Sending a purposefully crafted invalid date in the If-Modified-Since or Last-Modified header will cause the Hapi server to err but keep the socket open (the socket will time out after 2 minutes by default). This allows an attacker to quickly exhaust the sockets on the server, making it unavailable (a Denial of Service attack).

The vulnerability is caused by the combination of two bugs. First, the underlying V8 engine throws an exception when processing the specially crafted date, instead of stating the date is invalid as it should. Second, the Hapi server does not handle the exception well, leading to the socket remaining open.

Upgrading Hapi will address the second issue and thus fix the vulnerability.

References

high severity

Uninitialized Memory Exposure

  • Vulnerable module: https-proxy-agent
  • Introduced through: github@8.2.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 github@8.2.1 https-proxy-agent@1.0.0
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.

Overview

https-proxy-agent provides an http.Agent implementation that connects to a specified HTTP or HTTPS proxy server, and can be used with the built-in https module.

Affected versions of this package are vulnerable to Uninitialized Memory Exposure and Denial of Service (DoS) attacks due to passing unsanitized options to Buffer(arg).

Uninitialized memory Exposre PoC by ChALKer

// listen with: nc -l -p 8080

var url = require('url');
var https = require('https');
var HttpsProxyAgent = require('https-proxy-agent');

var proxy = {
  protocol: 'http:',
  host: "127.0.0.1",
  port: 8080
};

proxy.auth = 500; // a number as 'auth'
var opts = url.parse('https://example.com/');
var agent = new HttpsProxyAgent(proxy);
opts.agent = agent;
https.get(opts);

Details

The Buffer class on Node.js is a mutable array of binary data, and can be initialized with a string, array or number.

const buf1 = new Buffer([1,2,3]);
// creates a buffer containing [01, 02, 03]
const buf2 = new Buffer('test');
// creates a buffer containing ASCII bytes [74, 65, 73, 74]
const buf3 = new Buffer(10);
// creates a buffer of length 10

The first two variants simply create a binary representation of the value it received. The last one, however, pre-allocates a buffer of the specified size, making it a useful buffer, especially when reading data from a stream. When using the number constructor of Buffer, it will allocate the memory, but will not fill it with zeros. Instead, the allocated buffer will hold whatever was in memory at the time. If the buffer is not zeroed by using buf.fill(0), it may leak sensitive information like keys, source code, and system info.

Remediation

Upgrade https-proxy-agent to version 2.2.0 or higher. Note This is vulnerable only for Node <=4

References

high severity

Command Injection

  • Vulnerable module: lodash
  • Introduced through: lodash@3.10.1, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 upath@0.1.7 lodash@3.10.1
    Remediation: Upgrade to upath@1.0.2.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git easy-extender@2.3.2 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 inquirer@0.9.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 inquirer@0.8.5 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 lodash@1.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 zip-stream@0.5.2 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Command Injection via template.

PoC

var _ = require('lodash');

_.template('', { variable: '){console.log(process.env)}; with(obj' })()

Remediation

Upgrade lodash to version 4.17.21 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: lodash@3.10.1, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 upath@0.1.7 lodash@3.10.1
    Remediation: Upgrade to upath@1.0.2.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git easy-extender@2.3.2 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 inquirer@0.9.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 inquirer@0.8.5 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 lodash@1.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 zip-stream@0.5.2 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution. The function defaultsDeep could be tricked into adding or modifying properties of Object.prototype using a constructor payload.

PoC by Snyk

const mergeFn = require('lodash').defaultsDeep;
const payload = '{"constructor": {"prototype": {"a0": true}}}'

function check() {
    mergeFn({}, JSON.parse(payload));
    if (({})[`a0`] === true) {
        console.log(`Vulnerable to Prototype Pollution via ${payload}`);
    }
  }

check();

For more information, check out our blog post

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.12 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: lodash@3.10.1, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 upath@0.1.7 lodash@3.10.1
    Remediation: Upgrade to upath@1.0.2.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git easy-extender@2.3.2 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 inquirer@0.9.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 inquirer@0.8.5 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 lodash@1.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 zip-stream@0.5.2 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution via the setWith and set functions.

PoC by awarau

  • Create a JS file with this contents:
    lod = require('lodash')
    lod.setWith({}, "__proto__[test]", "123")
    lod.set({}, "__proto__[test2]", "456")
    console.log(Object.prototype)
    
  • Execute it with node
  • Observe that test and test2 is now in the Object.prototype.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.17 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: lodash@3.10.1, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 upath@0.1.7 lodash@3.10.1
    Remediation: Upgrade to upath@1.0.2.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git easy-extender@2.3.2 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 inquirer@0.9.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 inquirer@0.8.5 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 lodash@1.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 zip-stream@0.5.2 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution. The functions merge, mergeWith, and defaultsDeep could be tricked into adding or modifying properties of Object.prototype. This is due to an incomplete fix to CVE-2018-3721.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.11 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash.merge
  • Introduced through: lab@5.18.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 lodash.merge@3.3.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.

Overview

lodash.merge is a Lodash method _.merge exported as a Node.js module.

Affected versions of this package are vulnerable to Prototype Pollution. The functions merge, mergeWith, and defaultsDeep could be tricked into adding or modifying properties of Object.prototype. This is due to an incomplete fix to CVE-2018-3721.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash.merge to version 4.6.2 or higher.

References

high severity

Command Injection

  • Vulnerable module: lodash.template
  • Introduced through: @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 helper-markdown@0.2.2 remarkable@1.7.4 autolinker@0.28.1 gulp-header@1.8.12 lodash.template@4.5.0
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 helper-md@0.2.2 remarkable@1.7.4 autolinker@0.28.1 gulp-header@1.8.12 lodash.template@4.5.0

Overview

lodash.template is a The Lodash method _.template exported as a Node.js module.

Affected versions of this package are vulnerable to Command Injection via template.

PoC

var _ = require('lodash');

_.template('', { variable: '){console.log(process.env)}; with(obj' })()

Remediation

There is no fixed version for lodash.template.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: minimatch
  • Introduced through: recursive-readdir@1.3.0, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 recursive-readdir@1.3.0 minimatch@0.3.0
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 messageformat@0.2.2 glob@3.2.11 minimatch@0.3.0
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 minimatch@0.2.14
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 glob@3.1.21 minimatch@0.2.14
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 glob@4.3.5 minimatch@2.0.10
    Remediation: Upgrade to archiver@0.15.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 traceur@0.0.88 glob@4.3.5 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 jslint@0.9.8 glob@4.5.3 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 systemjs-builder@0.10.6 traceur@0.0.88 glob@4.3.5 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 rimraf@2.3.4 glob@4.5.3 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 minimatch@2.0.10
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 systemjs-builder@0.10.6 traceur@0.0.88 glob@4.3.5 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

minimatch is a minimal matching utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via complicated and illegal regexes.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade minimatch to version 3.0.2 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: minimatch
  • Introduced through: recursive-readdir@1.3.0, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 recursive-readdir@1.3.0 minimatch@0.3.0
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 messageformat@0.2.2 glob@3.2.11 minimatch@0.3.0
    Remediation: Open PR to patch minimatch@0.3.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 minimatch@0.2.14
    Remediation: Open PR to patch minimatch@0.2.14.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 glob@3.1.21 minimatch@0.2.14
    Remediation: Open PR to patch minimatch@0.2.14.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 glob@4.3.5 minimatch@2.0.10
    Remediation: Upgrade to archiver@0.15.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 traceur@0.0.88 glob@4.3.5 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 jslint@0.9.8 glob@4.5.3 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 systemjs-builder@0.10.6 traceur@0.0.88 glob@4.3.5 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 rimraf@2.3.4 glob@4.5.3 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 minimatch@2.0.10
    Remediation: Open PR to patch minimatch@2.0.10.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 systemjs-builder@0.10.6 traceur@0.0.88 glob@4.3.5 minimatch@2.0.10
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

minimatch is a minimal matching utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS).

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade minimatch to version 3.0.2 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: node.extend
  • Introduced through: jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 rmdir@1.1.0 node.flow@1.2.3 node.extend@1.0.8

Overview

node.extend is a port of jQuery.extend that actually works on node.js.

Affected versions of this package are vulnerable to Prototype Pollution. An attacker could inject arbitrary properties onto Object.prototype.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade node.extend to version 1.1.7, 2.0.1 or higher.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: npm
  • Introduced through: npm@2.15.12

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

npm is a package manager for JavaScript.

Affected versions of this package are vulnerable to Arbitrary File Overwrite. It fails to prevent existing globally-installed binaries to be overwritten by other package installations. For example, if a package was installed globally and created a serve binary, any subsequent installs of packages that also create a serve binary would overwrite the first binary. This only affects files in /usr/local/bin.

For npm, this behaviour is still allowed in local installations and also through install scripts. This vulnerability bypasses a user using the --ignore-scripts install option.

Details

A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.

Directory Traversal vulnerabilities can be generally divided into two types:

  • Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.

st is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public route.

If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.

curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa

Note %2e is the URL encoded version of . (dot).

  • Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as Zip-Slip.

One way to achieve this is by using a malicious zip archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.

The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicious file will result in traversing out of the target folder, ending up in /root/.ssh/ overwriting the authorized_keys file:

2018-04-15 22:04:29 .....           19           19  good.txt
2018-04-15 22:04:42 .....           20           20  ../../../../../../root/.ssh/authorized_keys

Remediation

Upgrade npm to version 6.13.4 or higher.

References

high severity

Arbitrary File Write

  • Vulnerable module: npm
  • Introduced through: npm@2.15.12

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

npm is a package manager for JavaScript.

Affected versions of this package are vulnerable to Arbitrary File Write. It fails to prevent access to folders outside of the intended node_modules folder through the bin field.

For npm, a properly constructed entry in the package.json bin field would allow a package publisher to modify and/or gain access to arbitrary files on a user’s system when the package is installed. This behaviour is possible through install scripts. This vulnerability bypasses a user using the --ignore-scripts install option.

Details

A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.

Directory Traversal vulnerabilities can be generally divided into two types:

  • Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.

st is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public route.

If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.

curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa

Note %2e is the URL encoded version of . (dot).

  • Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as Zip-Slip.

One way to achieve this is by using a malicious zip archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.

The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicious file will result in traversing out of the target folder, ending up in /root/.ssh/ overwriting the authorized_keys file:

2018-04-15 22:04:29 .....           19           19  good.txt
2018-04-15 22:04:42 .....           20           20  ../../../../../../root/.ssh/authorized_keys

Remediation

Upgrade npm to version 6.13.3 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: npm-user-validate
  • Introduced through: npm@2.15.12

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 npm-user-validate@0.1.5
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

npm-user-validate is an User validations for npm

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The regex that validates user emails took exponentially longer to process long input strings beginning with @ characters.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade npm-user-validate to version 1.0.1 or higher.

References

high severity
new

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: nth-check
  • Introduced through: cheerio@0.19.0

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 css-select@1.0.0 nth-check@1.0.2

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) mainly due to the sub-pattern \s*(?:([+-]?)\s*(\d+))? in RE_NTH_ELEMENT with quantified overlapping adjacency.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade nth-check to version 2.0.1 or higher.

References

high severity

Prototype Pollution

  • Vulnerable module: object-path
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git eazy-logger@3.0.2 tfunk@3.1.0 object-path@0.9.2

Overview

object-path is a package to access deep properties using a path

Affected versions of this package are vulnerable to Prototype Pollution. The setPath function can be used to add/modify properties of the Object prototype.

PoC

const setPath = require('object-path-set');
const obj = {};
console.log("Before : " + obj.polluted);
setPath({}, '__proto__.polluted', 'yes');
console.log("After : " + obj.polluted);

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade object-path to version 0.11.5 or higher.

References

high severity

Prototype Override Protection Bypass

  • Vulnerable module: qs
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git, hapi@8.8.1 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git qs@6.2.1
    Remediation: Open PR to patch qs@6.2.1.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 qs@4.0.0
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 qs@4.0.0
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 request@2.53.0 qs@2.3.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 request@2.53.0 qs@2.3.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

qs is a querystring parser that supports nesting and arrays, with a depth limit.

Affected versions of this package are vulnerable to Prototype Override Protection Bypass. By default qs protects against attacks that attempt to overwrite an object's existing prototype properties, such as toString(), hasOwnProperty(),etc.

From qs documentation:

By default parameters that would overwrite properties on the object prototype are ignored, if you wish to keep the data from those fields either use plainObjects as mentioned above, or set allowPrototypes to true which will allow user input to overwrite those properties. WARNING It is generally a bad idea to enable this option as it can cause problems when attempting to use the properties that have been overwritten. Always be careful with this option.

Overwriting these properties can impact application logic, potentially allowing attackers to work around security controls, modify data, make the application unstable and more.

In versions of the package affected by this vulnerability, it is possible to circumvent this protection and overwrite prototype properties and functions by prefixing the name of the parameter with [ or ]. e.g. qs.parse("]=toString") will return {toString = true}, as a result, calling toString() on the object will throw an exception.

Example:

qs.parse('toString=foo', { allowPrototypes: false })
// {}

qs.parse("]=toString", { allowPrototypes: false })
// {toString = true} <== prototype overwritten

For more information, you can check out our blog.

Disclosure Timeline

  • February 13th, 2017 - Reported the issue to package owner.
  • February 13th, 2017 - Issue acknowledged by package owner.
  • February 16th, 2017 - Partial fix released in versions 6.0.3, 6.1.1, 6.2.2, 6.3.1.
  • March 6th, 2017 - Final fix released in versions 6.4.0,6.3.2, 6.2.3, 6.1.2 and 6.0.4

    Remediation

    Upgrade qs to version 6.0.4, 6.1.2, 6.2.3, 6.3.2 or higher.

    References

  • GitHub Commit
  • GitHub Issue

high severity
new

Prototype Pollution

  • Vulnerable module: set-value
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git and jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 readdirp@2.2.1 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 liftoff@2.5.0 findup-sync@2.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 readdirp@2.2.1 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 union-value@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 liftoff@2.5.0 findup-sync@2.0.0 micromatch@3.1.10 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 union-value@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 readdirp@2.2.1 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 liftoff@2.5.0 findup-sync@2.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 readdirp@2.2.1 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 liftoff@2.5.0 findup-sync@2.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 readdirp@2.2.1 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 liftoff@2.5.0 findup-sync@2.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 readdirp@2.2.1 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 union-value@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 liftoff@2.5.0 findup-sync@2.0.0 micromatch@3.1.10 braces@2.3.2 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 union-value@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 readdirp@2.2.1 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 union-value@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 liftoff@2.5.0 findup-sync@2.0.0 micromatch@3.1.10 extglob@2.0.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 union-value@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 readdirp@2.2.1 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 union-value@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 liftoff@2.5.0 findup-sync@2.0.0 micromatch@3.1.10 nanomatch@1.2.13 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 union-value@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 readdirp@2.2.1 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 liftoff@2.5.0 findup-sync@2.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 readdirp@2.2.1 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 union-value@1.0.1 set-value@2.0.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 liftoff@2.5.0 findup-sync@2.0.0 micromatch@3.1.10 extglob@2.0.4 expand-brackets@2.1.4 snapdragon@0.8.2 base@0.11.2 cache-base@1.0.1 union-value@1.0.1 set-value@2.0.1

Overview

set-value is a package that creates nested values and any intermediaries using dot notation ('a.b.c') paths.

Affected versions of this package are vulnerable to Prototype Pollution. A type confusion vulnerability can lead to a bypass of CVE-2019-10747 when the user-provided keys used in the path parameter are arrays.

PoC

const set = require("set-value")

// set({}, ['__proto__','polluted'], 'yes');
// console.log(polluted); // Error: Cannot set unsafe key: "__proto__"

set({}, [['__proto__'],'polluted'], 'yes');
console.log(polluted);

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade set-value to version 4.0.1 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: socket.io-parser
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git socket.io@2.0.4 socket.io-parser@3.1.3
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git browser-sync-ui@1.0.1 socket.io-client@2.0.4 socket.io-parser@3.1.3
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git socket.io@2.0.4 socket.io-client@2.0.4 socket.io-parser@3.1.3

Overview

socket.io-parser is a socket.io protocol parser

Affected versions of this package are vulnerable to Denial of Service (DoS) via a large packet because a concatenation approach is used.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

  • High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

  • Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade socket.io-parser to version 3.3.2, 3.4.1 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: subtext
  • Introduced through: glue@2.4.0 and hapi@8.8.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 subtext@3.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1

Overview

subtext is a HTTP payload parsing library. Deprecated. Note: This package is deprecated and is now maintained as @hapi/subtext

Affected versions of this package are vulnerable to Denial of Service (DoS). The package fails to enforce the maxBytes configuration for payloads with chunked encoding that are written to the file system. This allows attackers to send requests with arbitrary payload sizes, which may exhaust system resources.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

  • High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

  • Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

There is no fixed version for subtext.

References

high severity

Prototype Pollution

  • Vulnerable module: subtext
  • Introduced through: glue@2.4.0 and hapi@8.8.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 subtext@3.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1

Overview

subtext is a HTTP payload parsing library. Deprecated. Note: This package is deprecated and is now maintained as @hapi/subtext

Affected versions of this package are vulnerable to Prototype Pollution. A multipart payload can be constructed in a way that one of the parts’ content can be set as the entire payload object’s prototype. If this prototype contains data, it may bypass other validation rules which enforce access and privacy. If this prototype evaluates to null, it can cause unhandled exceptions when the request payload is accessed.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

There is no fixed version for subtext.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: npm@2.15.12, @bigcommerce/stencil-styles@1.1.0 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 node-gyp@3.8.0 tar@2.2.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 tar@1.0.3
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 tar@1.0.3

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Overwrite. This is due to insufficient symlink protection. node-tar aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.

This logic is insufficient when extracting tar files that contain both a directory and a symlink with the same name as the directory. This order of operations results in the directory being created and added to the node-tar directory cache. When a directory is present in the directory cache, subsequent calls to mkdir for that directory are skipped. However, this is also where node-tar checks for symlinks occur. By first creating a directory, and then replacing that directory with a symlink, it is possible to bypass node-tar symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location and subsequently extracting arbitrary files into that location.

Remediation

Upgrade tar to version 3.2.3, 4.4.15, 5.0.7, 6.1.2 or higher.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: npm@2.15.12, @bigcommerce/stencil-styles@1.1.0 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 node-gyp@3.8.0 tar@2.2.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 tar@1.0.3
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 tar@1.0.3

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Overwrite. This is due to insufficient absolute path sanitization.

node-tar aims to prevent extraction of absolute file paths by turning absolute paths into relative paths when the preservePaths flag is not set to true. This is achieved by stripping the absolute path root from any absolute file paths contained in a tar file. For example, the path /home/user/.bashrc would turn into home/user/.bashrc.

This logic is insufficient when file paths contain repeated path roots such as ////home/user/.bashrc. node-tar only strips a single path root from such paths. When given an absolute file path with repeating path roots, the resulting path (e.g. ///home/user/.bashrc) still resolves to an absolute path.

Remediation

Upgrade tar to version 3.2.2, 4.4.14, 5.0.6, 6.1.1 or higher.

References

high severity

Arbitrary File Overwrite

  • Vulnerable module: tar
  • Introduced through: jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 tar@1.0.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 tar@1.0.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Overwrite. Extracting tarballs containing a hard-link to a file that already exists in the system, and a file that matches the hard-link may overwrite system's files with the contents of the extracted file.

Remediation

Upgrade tar to version 2.2.2, 4.4.2 or higher.

References

high severity
new

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: npm@2.15.12, @bigcommerce/stencil-styles@1.1.0 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 node-gyp@3.8.0 tar@2.2.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 tar@1.0.3
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 tar@1.0.3

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Write. node-tar aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.

This logic was insufficient when extracting tar files that contained both a directory and a symlink with the same name as the directory, where the symlink and directory names in the archive entry used backslashes as a path separator on posix systems. The cache checking logic used both \ and / characters as path separators. However, \ is a valid filename character on posix systems.

By first creating a directory, and then replacing that directory with a symlink, it is possible to bypass node-tar symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location. This can lead to extracting arbitrary files into that location, thus allowing arbitrary file creation and overwrite.

Additionally, a similar confusion could arise on case-insensitive filesystems. If a tar archive contained a directory at FOO, followed by a symbolic link named foo, then on case-insensitive file systems, the creation of the symbolic link would remove the directory from the filesystem, but not from the internal directory cache, as it would not be treated as a cache hit. A subsequent file entry within the FOO directory would then be placed in the target of the symbolic link, thinking that the directory had already been created.

Remediation

Upgrade tar to version 6.1.7, 5.0.8, 4.4.16 or higher.

References

high severity
new

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: npm@2.15.12, @bigcommerce/stencil-styles@1.1.0 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 node-gyp@3.8.0 tar@2.2.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 tar@1.0.3
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 tar@1.0.3

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Write. node-tar aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.

This logic is insufficient when extracting tar files that contain two directories and a symlink with names containing unicode values that normalized to the same value. Additionally, on Windows systems, long path portions would resolve to the same file system entities as their 8.3 "short path" counterparts. A specially crafted tar archive can include directories with two forms of the path that resolve to the same file system entity, followed by a symbolic link with a name in the first form, lastly followed by a file using the second form. This leads to bypassing node-tar symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location and extracting arbitrary files into that location.

Remediation

Upgrade tar to version 6.1.9, 5.0.10, 4.4.18 or higher.

References

high severity
new

Arbitrary File Write

  • Vulnerable module: tar
  • Introduced through: npm@2.15.12, @bigcommerce/stencil-styles@1.1.0 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 node-gyp@3.8.0 tar@2.2.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 tar@1.0.3
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 tar@1.0.3

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Arbitrary File Write. node-tar aims to guarantee that any file whose location would be outside of the extraction target directory is not extracted. This is, in part, accomplished by sanitizing absolute paths of entries within the archive, skipping archive entries that contain .. path portions, and resolving the sanitized paths against the extraction target directory.

This logic is insufficient on Windows systems when extracting tar files that contain a path that is not an absolute path, but specify a drive letter different from the extraction target, such as C:some\path. If the drive letter does not match the extraction target, for example D:\extraction\dir, then the result of path.resolve(extractionDirectory, entryPath) resolves against the current working directory on the C: drive, rather than the extraction target directory.

Additionally, a .. portion of the path can occur immediately after the drive letter, such as C:../foo, and is not properly sanitized by the logic that checks for .. within the normalized and split portions of the path.

Note: This only affects users of node-tar on Windows systems.

Remediation

Upgrade tar to version 6.1.9, 5.0.10, 4.4.18 or higher.

References

high severity

Symlink File Overwrite

  • Vulnerable module: tar
  • Introduced through: jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 tar@1.0.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 tar@1.0.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Symlink File Overwrite. It does not properly normalize symbolic links pointing to targets outside the extraction root. As a result, packages may hold symbolic links to parent and sibling directories and overwrite those files when the package is extracted.

Remediation

Upgrade tar to version 2.0.0 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: trim-newlines
  • Introduced through: @bigcommerce/stencil-styles@1.1.0

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 meow@3.7.0 trim-newlines@1.0.0

Overview

trim-newlines is a Trim newlines from the start and/or end of a string

Affected versions of this package are vulnerable to Denial of Service (DoS) via the end() method.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

  • High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

  • Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade trim-newlines to version 3.0.1, 4.0.1 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ua-parser-js
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git ua-parser-js@0.7.12

Overview

ua-parser-js is a lightweight JavaScript-based user-agent string parser.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in multiple regexes (see linked commit for more info).

Proof of Concept by Miguel de Moura

jsconst ua_parser = require('ua-parser-js');const N_SIZE = 5000;const MALICIOUS_UA = `android;;Trio${' '.repeat(N_SIZE)}buil`;// Trigger ReDoSua_parser(MALICIOUS_UA);

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ua-parser-js to version 0.7.23 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ua-parser-js
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git ua-parser-js@0.7.12

Overview

ua-parser-js is a lightweight JavaScript-based user-agent string parser.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the regex for Redmi Phones and Mi Pad Tablets UA.

POC by Yeting Li

var blank = " ";
for (let i = 1; i < 5000; i++) {
blank = blank + " ";
}

str_mi = "android1mipad" + blank + "!";
str_mi = str_mi + +blank + "!";
mi = /android.+(mi[s-_]*(?:pad)(?:[s_]*[ws]+))s+build/i;

var count_mi = 0;
for (let i = 0; i < 10; i++) {
var time = Date.now();
mi.test(str_mi);
var len = Date.now() - time;
count_mi = count_mi + len;
console.log("mi:" + blank.length + ": " + len)
}
console.log(count_mi / 10);

str_redmi = "android1redminote" + blank + "!";
redmi = /android.+(redmi[s-_]*(?:note)?(?:[s_]*[ws]+))s+build/i;
var count_redmi = 0;
for (let i = 0; i < 10; i++) {
var time = Date.now();
redmi.test(str_redmi);
var len = Date.now() - time;
count_redmi = count_redmi + len;
console.log("redmi:" + blank.length + ": " + len)
}
console.log(count_redmi / 10);

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ua-parser-js to version 0.7.22 or higher.

References

high severity

Access Restriction Bypass

  • Vulnerable module: xmlhttprequest-ssl
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git browser-sync-ui@1.0.1 socket.io-client@2.0.4 engine.io-client@3.1.6 xmlhttprequest-ssl@1.5.5
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git socket.io@2.0.4 socket.io-client@2.0.4 engine.io-client@3.1.6 xmlhttprequest-ssl@1.5.5

Overview

xmlhttprequest-ssl is a fork of xmlhttprequest.

Affected versions of this package are vulnerable to Access Restriction Bypass. The package disables SSL certificate validation by default, because rejectUnauthorized (when the property exists but is undefined) is considered to be false within the https.request function of Node.js. In other words, no certificate is ever rejected.

PoC

const XMLHttpRequest = require('xmlhttprequest-ssl');

var xhr = new XMLHttpRequest();        /* pass empty object in version 1.5.4 to work around bug */

xhr.open("GET", "https://self-signed.badssl.com/");
xhr.addEventListener('readystatechange', () => console.log('ready state:', xhr.status));
xhr.addEventListener('loadend', loadend);

function loadend()
{
  console.log('loadend:', xhr);
  if (xhr.status === 0 && xhr.statusText.code === 'DEPTH_ZERO_SELF_SIGNED_CERT')
    console.log('test passed: self-signed cert rejected');
  else
    console.log('*** test failed: self-signed cert used to retrieve content');
}

xhr.send();

Remediation

Upgrade xmlhttprequest-ssl to version 1.6.1 or higher.

References

high severity

Arbitrary Code Injection

  • Vulnerable module: xmlhttprequest-ssl
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git browser-sync-ui@1.0.1 socket.io-client@2.0.4 engine.io-client@3.1.6 xmlhttprequest-ssl@1.5.5
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git socket.io@2.0.4 socket.io-client@2.0.4 engine.io-client@3.1.6 xmlhttprequest-ssl@1.5.5

Overview

xmlhttprequest-ssl is a fork of xmlhttprequest.

Affected versions of this package are vulnerable to Arbitrary Code Injection. Provided requests are sent synchronously (async=False on xhr.open), malicious user input flowing into xhr.send could result in arbitrary code being injected and run.

POC

const { XMLHttpRequest } = require("xmlhttprequest")

const xhr = new XMLHttpRequest()
xhr.open("POST", "http://localhost.invalid/", false /* use synchronize request */)
xhr.send("\\');require(\"fs\").writeFileSync(\"/tmp/aaaaa.txt\", \"poc-20210306\");req.end();//")

Remediation

Upgrade xmlhttprequest-ssl to version 1.6.2 or higher.

References

medium severity

Cross-site Scripting (XSS)

  • Vulnerable module: autolinker
  • Introduced through: @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 helper-markdown@0.2.2 remarkable@1.7.4 autolinker@0.28.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 helper-md@0.2.2 remarkable@1.7.4 autolinker@0.28.1

Overview

autolinker is an Utility to Automatically Link URLs, Email Addresses, Phone Numbers, Twitter handles, and Hashtags in a given block of text/HTML.

Affected versions of this package are vulnerable to Cross-site Scripting (XSS) due to it not sanitizing user input passed to the innerHTML tags.

Details

A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.

This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.

Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.

Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as &lt; and > can be coded as &gt; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.

The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.

Types of attacks

There are a few methods by which XSS can be manipulated:

Type Origin Description
Stored Server The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link.
Reflected Server The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser.
DOM-based Client The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data.
Mutated The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters.

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

This section describes the top best practices designed to specifically protect your code:

  • Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
  • Convert special characters such as ?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.
  • Give users the option to disable client-side scripts.
  • Redirect invalid requests.
  • Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
  • Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
  • Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.

Remediation

Upgrade autolinker to version 3.14.0 or higher.

References

medium severity

Denial of Service (DoS)

  • Vulnerable module: autolinker
  • Introduced through: @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 helper-markdown@0.2.2 remarkable@1.7.4 autolinker@0.28.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 helper-md@0.2.2 remarkable@1.7.4 autolinker@0.28.1

Overview

autolinker is an Utility to Automatically Link URLs, Email Addresses, Phone Numbers, Twitter handles, and Hashtags in a given block of text/HTML.

Affected versions of this package are vulnerable to Denial of Service (DoS) due to an unterminated img src.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade autolinker to version 3.0.0 or higher.

References

medium severity

Improper input validation

  • Vulnerable module: call
  • Introduced through: hapi@8.8.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 call@2.0.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.

Overview

call is the primary HTTP router of the hapi framework.

The vulnerability arise from undefined values inside a path (last segment being an exception) making their way into components that do not care for values being undefined (eg. the database layer).

For example, the request URI /delete/company// may incorrectly match a route looking for /delete/company/{company}/. By itself, the bad match is not a vulnerability. However, depending on the remaining logic in the application, such a bad match may result in skipping a protection mechanisms. In the above example, if the route translates to a DB delete command, it might delete all the companies from the db.

Remediation

Upgrade to version 3.0.2 or higher.

References

https://github.com/hapijs/hapi/issues/3228 https://github.com/hapijs/call/commit/9570eee5358b4383715cc6a13cb95971678efd30

medium severity

Time of Check Time of Use (TOCTOU)

  • Vulnerable module: chownr
  • Introduced through: npm@2.15.12

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 chownr@1.0.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

chownr is a package that takes the same arguments as fs.chown()

Affected versions of this package are vulnerable to Time of Check Time of Use (TOCTOU). Affected versions of this package are vulnerable toTime of Check Time of Use (TOCTOU) attacks.

It does not dereference symbolic links and changes the owner of the link, which can trick it into descending into unintended trees if a non-symlink is replaced by a symlink at a critical moment:

      fs.lstat(pathChild, function(er, stats) {
        if (er)
          return cb(er)
        if (!stats.isSymbolicLink())
          chownr(pathChild, uid, gid, then)

Remediation

Upgrade chownr to version 1.1.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: content
  • Introduced through: hapi@8.8.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 content@1.0.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 pez@1.0.0 content@1.0.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.

Overview

content is HTTP Content-* headers parsing.

Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks. An attacker may pass a specially crafted Content-Type or Content-Disposition header, causing the server to hang.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade content to version 3.0.6 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: css-what
  • Introduced through: cheerio@0.19.0

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 css-select@1.0.0 css-what@1.0.0

Overview

css-what is an a CSS selector parser

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via attribute parsing.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade css-what to version 5.0.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: glob-parent
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git and @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 glob-parent@2.0.0
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 anymatch@1.3.2 micromatch@2.3.11 parse-glob@3.0.4 glob-base@0.3.0 glob-parent@2.0.0

Overview

glob-parent is a package that helps extracting the non-magic parent path from a glob string.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The enclosure regex used to check for strings ending in enclosure containing path separator.

PoC by Yeting Li

var globParent = require("glob-parent")
function build_attack(n) {
var ret = "{"
for (var i = 0; i < n; i++) {
ret += "/"
}

return ret;
}

globParent(build_attack(5000));

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade glob-parent to version 5.1.2 or higher.

References

medium severity

Cross-site Scripting (XSS)

  • Vulnerable module: handlebars
  • Introduced through: handlebars@3.0.8 and @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 handlebars@3.0.8
    Remediation: Upgrade to @bigcommerce/stencil-cli@2.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars@3.0.8
    Remediation: Open PR to patch handlebars@3.0.8.

Overview

handlebars provides the power necessary to let you build semantic templates.

When using attributes without quotes in a handlebars template, an attacker can manipulate the input to introduce additional attributes, potentially executing code. This may lead to a Cross-site Scripting (XSS) vulnerability, assuming an attacker can influence the value entered into the template. If the handlebars template is used to render user-generated content, this vulnerability may escalate to a persistent XSS vulnerability.

Details

Cross-Site Scripting (XSS) attacks occur when an attacker tricks a user’s browser to execute malicious JavaScript code in the context of a victim’s domain. Such scripts can steal the user’s session cookies for the domain, scrape or modify its content, and perform or modify actions on the user’s behalf, actions typically blocked by the browser’s Same Origin Policy.

These attacks are possible by escaping the context of the web application and injecting malicious scripts in an otherwise trusted website. These scripts can introduce additional attributes (say, a "new" option in a dropdown list or a new link to a malicious site) and can potentially execute code on the clients side, unbeknown to the victim. This occurs when characters like < > " ' are not escaped properly.

There are a few types of XSS:

  • Persistent XSS is an attack in which the malicious code persists into the web app’s database.
  • Reflected XSS is an which the website echoes back a portion of the request. The attacker needs to trick the user into clicking a malicious link (for instance through a phishing email or malicious JS on another page), which triggers the XSS attack.
  • DOM-based XSS is an that occurs purely in the browser when client-side JavaScript echoes back a portion of the URL onto the page. DOM-Based XSS is notoriously hard to detect, as the server never gets a chance to see the attack taking place.

Example:

Assume handlebars was used to display user comments and avatar, using the following template: <img src={{avatarUrl}}><pre>{{comment}}</pre>

If an attacker spoofed their avatar URL and provided the following value: http://evil.org/avatar.png onload=alert(document.cookie)

The resulting HTML would be the following, triggering the script once the image loads: <img src=http://evil.org/avatar.png onload=alert(document.cookie)><pre>Gotcha!</pre>

References

medium severity

Prototype Pollution

  • Vulnerable module: handlebars
  • Introduced through: handlebars@3.0.8 and @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 handlebars@3.0.8
    Remediation: Upgrade to @bigcommerce/stencil-cli@2.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars@3.0.8

Overview

handlebars is an extension to the Mustache templating language.

Affected versions of this package are vulnerable to Prototype Pollution when selecting certain compiling options to compile templates coming from an untrusted source.

POC

<script src="https://cdn.jsdelivr.net/npm/handlebars@latest/dist/handlebars.js"></script> 
<script> 
// compile the template 

var s2 = `{{'a/.") || alert("Vulnerable Handlebars JS when compiling in compat mode'}}`; 
var template = Handlebars.compile(s2, { 
compat: true 
}); 
// execute the compiled template and print the output to the console console.log(template({})); 
</script>

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade handlebars to version 4.7.7 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: handlebars
  • Introduced through: handlebars@3.0.8 and @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 handlebars@3.0.8
    Remediation: Upgrade to @bigcommerce/stencil-cli@2.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars@3.0.8

Overview

handlebars is an extension to the Mustache templating language.

Affected versions of this package are vulnerable to Prototype Pollution. Prototype access to the template engine allows for potential code execution.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade handlebars to version 4.6.0 or higher.

References

medium severity

Remote Code Execution (RCE)

  • Vulnerable module: handlebars
  • Introduced through: handlebars@3.0.8 and @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 handlebars@3.0.8
    Remediation: Upgrade to @bigcommerce/stencil-cli@2.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars@3.0.8

Overview

handlebars is an extension to the Mustache templating language.

Affected versions of this package are vulnerable to Remote Code Execution (RCE) when selecting certain compiling options to compile templates coming from an untrusted source.

POC

<script src="https://cdn.jsdelivr.net/npm/handlebars@latest/dist/handlebars.js"></script> 
<script> 
// compile the template 
var s = ` 
{{#with (__lookupGetter__ "__proto__")}} 
{{#with (./constructor.getOwnPropertyDescriptor . "valueOf")}} 
{{#with ../constructor.prototype}} 
{{../../constructor.defineProperty . "hasOwnProperty" ..}} 
{{/with}} 
{{/with}} 
{{/with}} 
{{#with "constructor"}} 
{{#with split}} 
{{pop (push "alert('Vulnerable Handlebars JS when compiling in strict mode');")}} 
{{#with .}} 
{{#with (concat (lookup join (slice 0 1)))}} 
{{#each (slice 2 3)}} 
{{#with (apply 0 ../..)}} 
{{.}} 
{{/with}} 
{{/each}} 
{{/with}} 
{{/with}} 
{{/with}} 
{{/with}} 
`;
var template = Handlebars.compile(s, { 
strict: true 
}); 
// execute the compiled template and print the output to the console console.log(template({})); 
</script>

Remediation

Upgrade handlebars to version 4.7.7 or higher.

References

medium severity

Potentially loose security restrictions

  • Vulnerable module: hapi
  • Introduced through: hapi@8.8.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.

Overview

Security restrictions (e.g. origin) get overridden by less restrictive defaults (i.e. all origins) in cases when server level, connection level or route level CORS configurations are combined.

References

medium severity

Prototype Pollution

  • Vulnerable module: hoek
  • Introduced through: hoek@2.16.3, boom@2.10.1 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 confidence@1.4.2 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 good@5.1.2 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 good-console@4.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 confidence@1.4.2 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to confidence@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 topo@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 joi@6.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 joi@6.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 good@5.1.2 good-reporter@3.1.0 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 good-console@4.1.0 good-reporter@3.1.0 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 good@5.1.2 joi@5.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 accept@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 ammo@1.0.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 call@2.0.2 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 catbox@4.3.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 catbox-memory@1.1.2 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 h2o2@4.0.2 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 heavy@3.0.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 inert@2.1.6 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 iron@2.1.3 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 kilt@1.1.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 mimos@2.0.2 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 shot@1.7.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 statehood@2.1.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 vision@2.0.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 bossy@1.0.3 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 accept@1.1.0 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 ammo@1.0.1 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 call@2.0.2 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 catbox@4.3.0 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 h2o2@4.0.2 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 heavy@3.0.1 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 inert@2.1.6 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 iron@2.1.3 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 statehood@2.1.1 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 vision@2.0.1 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 less@2.7.3 request@2.81.0 hawk@3.1.3 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 request@2.74.0 hawk@3.1.3 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 joi@6.10.1 topo@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 joi@6.10.1 topo@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 good@5.1.2 joi@5.1.0 topo@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 catbox@4.3.0 joi@6.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 h2o2@4.0.2 joi@6.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 heavy@3.0.1 joi@6.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 inert@2.1.6 joi@6.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 statehood@2.1.1 joi@6.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 vision@2.0.1 joi@6.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 inert@2.1.6 ammo@1.0.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 h2o2@4.0.2 wreck@6.3.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 wreck@6.3.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 statehood@2.1.1 iron@2.1.3 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 content@1.0.2 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 pez@1.0.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 iron@2.1.3 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 statehood@2.1.1 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 less@2.7.3 request@2.81.0 hawk@3.1.3 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 request@2.74.0 hawk@3.1.3 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 inert@2.1.6 ammo@1.0.1 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 h2o2@4.0.2 wreck@6.3.0 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 wreck@6.3.0 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 statehood@2.1.1 iron@2.1.3 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 content@1.0.2 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 pez@1.0.0 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 less@2.7.3 request@2.81.0 hawk@3.1.3 sntp@1.0.9 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 request@2.74.0 hawk@3.1.3 sntp@1.0.9 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git localtunnel@1.8.3 request@2.81.0 hawk@3.1.3 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 request@2.81.0 hawk@3.1.3 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 catbox@4.3.0 joi@6.10.1 topo@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 h2o2@4.0.2 joi@6.10.1 topo@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 heavy@3.0.1 joi@6.10.1 topo@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 inert@2.1.6 joi@6.10.1 topo@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 statehood@2.1.1 joi@6.10.1 topo@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 vision@2.0.1 joi@6.10.1 topo@1.1.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 pez@1.0.0 content@1.0.2 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 pez@1.0.0 b64@2.0.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 pez@1.0.0 nigel@1.0.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 request@2.53.0 hawk@2.3.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 request@2.53.0 hawk@2.3.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 less@2.7.3 request@2.81.0 hawk@3.1.3 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 request@2.74.0 hawk@3.1.3 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 statehood@2.1.1 iron@2.1.3 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git localtunnel@1.8.3 request@2.81.0 hawk@3.1.3 boom@2.10.1 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 request@2.81.0 hawk@3.1.3 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 pez@1.0.0 content@1.0.2 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 request@2.53.0 hawk@2.3.1 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 request@2.53.0 hawk@2.3.1 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git localtunnel@1.8.3 request@2.81.0 hawk@3.1.3 sntp@1.0.9 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 request@2.81.0 hawk@3.1.3 sntp@1.0.9 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 request@2.53.0 hawk@2.3.1 sntp@1.0.9 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 request@2.53.0 hawk@2.3.1 sntp@1.0.9 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1 subtext@1.1.1 pez@1.0.0 nigel@1.0.1 vise@1.0.0 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git localtunnel@1.8.3 request@2.81.0 hawk@3.1.3 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Open PR to patch hoek@2.16.3.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 request@2.81.0 hawk@3.1.3 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 request@2.53.0 hawk@2.3.1 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 request@2.53.0 hawk@2.3.1 cryptiles@2.0.5 boom@2.10.1 hoek@2.16.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 hoek@3.0.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 iron@3.0.1 hoek@3.0.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 joi@7.3.0 hoek@3.0.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 shot@2.0.1 hoek@3.0.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 statehood@3.1.0 hoek@3.0.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 subtext@3.0.2 hoek@3.0.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 statehood@3.1.0 iron@3.0.1 hoek@3.0.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 glue@2.4.0 hapi@11.1.4 statehood@3.1.0 joi@7.3.0 hoek@3.0.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.

Overview

hoek is an Utility methods for the hapi ecosystem.

Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.

PoC by Olivier Arteau (HoLyVieR)

var Hoek = require('hoek');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';

var a = {};
console.log("Before : " + a.oops);
Hoek.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade hoek to version 4.2.1, 5.0.3 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: hosted-git-info
  • Introduced through: npm@2.15.12

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 hosted-git-info@2.1.5
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

hosted-git-info is a Provides metadata and conversions from repository urls for Github, Bitbucket and Gitlab

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via regular expression shortcutMatch in the fromUrl function in index.js. The affected regular expression exhibits polynomial worst-case time complexity.

PoC by Yeting Li

var hostedGitInfo = require("hosted-git-info")
function build_attack(n) {
    var ret = "a:"
    for (var i = 0; i < n; i++) {
        ret += "a"
    }
    return ret + "!";
}

for(var i = 1; i <= 5000000; i++) {
   if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       var parsedInfo = hostedGitInfo.fromUrl(attack_str)
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade hosted-git-info to version 3.0.8, 2.8.9 or higher.

References

medium severity

Denial of Service (DoS)

  • Vulnerable module: http-proxy
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git http-proxy@1.15.2

Overview

http-proxy is a library that HTTP proxying for the masses.

Affected versions of this package are vulnerable to Denial of Service (DoS). HTTP requests with long bodies can crash the proxy sever via triggering an ERR_HTTP_HEADERS_SENT unhandled exception.

Note This vulnerability is only viable if proxy server uses the proxyReq.setHeader function to set headers in the proxy request.

PoC by Grant Murphy

A proxy server on http://localhost:3000, using the following curl request will trigger the unhandled exception:

curl -XPOST http://localhost:3000 -d "$(python -c 'print("x"*1025)')"

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

  • High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

  • Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade http-proxy to version 1.18.1 or higher.

References

medium severity

Timing Attack

  • Vulnerable module: http-signature
  • Introduced through: jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 request@2.53.0 http-signature@0.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 request@2.53.0 http-signature@0.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

http-signature is a reference implementation of Joyent's HTTP Signature scheme.

Affected versions of the package are vulnerable to Timing Attacks due to time-variable comparison of signatures.

The library implemented a character to character comparison, similar to the built-in string comparison mechanism, ===, and not a time constant string comparison. As a result, the comparison will fail faster when the first characters in the signature are incorrect. An attacker can use this difference to perform a timing attack, essentially allowing them to guess the signature one character at a time.

You can read more about timing attacks in Node.js on the Snyk blog.

Remediation

Upgrade http-signature to version 1.0.0 or higher.

References

medium severity

Man-in-the-Middle (MitM)

  • Vulnerable module: https-proxy-agent
  • Introduced through: github@8.2.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 github@8.2.1 https-proxy-agent@1.0.0
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.

Overview

https-proxy-agent is a module that provides an http.Agent implementation that connects to a specified HTTP or HTTPS proxy server, and can be used with the built-in https module.

Affected versions of this package are vulnerable to Man-in-the-Middle (MitM). When targeting a HTTP proxy, https-proxy-agent opens a socket to the proxy, and sends the proxy server a CONNECT request. If the proxy server responds with something other than a HTTP response 200, https-proxy-agent incorrectly returns the socket without any TLS upgrade. This request data may contain basic auth credentials or other secrets, is sent over an unencrypted connection. A suitably positioned attacker could steal these secrets and impersonate the client.

PoC by Kris Adler

var url = require('url');
var https = require('https');
var HttpsProxyAgent = require('https-proxy-agent');

var proxyOpts = url.parse('http://127.0.0.1:80');
var opts = url.parse('https://www.google.com');
var agent = new HttpsProxyAgent(proxyOpts);
opts.agent = agent;
opts.auth = 'username:password';
https.get(opts);

Remediation

Upgrade https-proxy-agent to version 2.2.3 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: lodash@3.10.1, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 upath@0.1.7 lodash@3.10.1
    Remediation: Upgrade to upath@1.0.2.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git easy-extender@2.3.2 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 inquirer@0.9.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 inquirer@0.8.5 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 lodash@1.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 zip-stream@0.5.2 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution. The function zipObjectDeep can be tricked into adding or modifying properties of the Object prototype. These properties will be present on all objects.

PoC

const _ = require('lodash');
_.zipObjectDeep(['__proto__.z'],[123])
console.log(z) // 123

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.16 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: lodash@3.10.1, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 upath@0.1.7 lodash@3.10.1
    Remediation: Upgrade to upath@1.0.2.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git easy-extender@2.3.2 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 inquirer@0.9.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 inquirer@0.8.5 lodash@3.10.1
    Remediation: Open PR to patch lodash@3.10.1.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 lodash@1.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 zip-stream@0.5.2 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.

PoC by Olivier Arteau (HoLyVieR)

var _= require('lodash');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';

var a = {};
console.log("Before : " + a.oops);
_.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash to version 4.17.5 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: lodash
  • Introduced through: lodash@3.10.1, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 upath@0.1.7 lodash@3.10.1
    Remediation: Upgrade to upath@1.0.2.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git easy-extender@2.3.2 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 inquirer@0.9.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 inquirer@0.8.5 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 lodash@1.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 zip-stream@0.5.2 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the toNumber, trim and trimEnd functions.

POC

var lo = require('lodash');

function build_blank (n) {
var ret = "1"
for (var i = 0; i < n; i++) {
ret += " "
}

return ret + "1";
}

var s = build_blank(50000)
var time0 = Date.now();
lo.trim(s)
var time_cost0 = Date.now() - time0;
console.log("time_cost0: " + time_cost0)

var time1 = Date.now();
lo.toNumber(s)
var time_cost1 = Date.now() - time1;
console.log("time_cost1: " + time_cost1)

var time2 = Date.now();
lo.trimEnd(s)
var time_cost2 = Date.now() - time2;
console.log("time_cost2: " + time_cost2)

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade lodash to version 4.17.21 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: lodash
  • Introduced through: lodash@3.10.1, @bigcommerce/stencil-paper@2.0.28 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 cheerio@0.19.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 inquirer@0.8.5 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 upath@0.1.7 lodash@3.10.1
    Remediation: Upgrade to upath@1.0.2.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git easy-extender@2.3.2 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 inquirer@0.9.0 lodash@3.10.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint-plugin-hapi@1.2.2 no-shadow-relaxed@1.0.1 eslint@0.24.1 inquirer@0.8.5 lodash@3.10.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 gaze@0.5.2 globule@0.1.0 lodash@1.0.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 archiver@0.14.4 zip-stream@0.5.2 lodash@3.2.0
    Remediation: Upgrade to archiver@1.0.0.

Overview

lodash is a modern JavaScript utility library delivering modularity, performance, & extras.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It parses dates using regex strings, which may cause a slowdown of 2 seconds per 50k characters.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade lodash to version 4.17.11 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash.merge
  • Introduced through: lab@5.18.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1 lodash.merge@3.3.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.

Overview

lodash.merge is a Lodash method _.merge exported as a Node.js module.

Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.

PoC by Olivier Arteau (HoLyVieR)

var _= require('lodash');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';

var a = {};
console.log("Before : " + a.oops);
_.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade lodash.merge to version 4.6.2 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: minimist
  • Introduced through: handlebars@3.0.8 and @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 handlebars@3.0.8 optimist@0.6.1 minimist@0.0.10
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars@3.0.8 optimist@0.6.1 minimist@0.0.10

Overview

minimist is a parse argument options module.

Affected versions of this package are vulnerable to Prototype Pollution. The library could be tricked into adding or modifying properties of Object.prototype using a constructor or __proto__ payload.

PoC by Snyk

require('minimist')('--__proto__.injected0 value0'.split(' '));
console.log(({}).injected0 === 'value0'); // true

require('minimist')('--constructor.prototype.injected1 value1'.split(' '));
console.log(({}).injected1 === 'value1'); // true

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade minimist to version 0.2.1, 1.2.3 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: moment
  • Introduced through: good-console@4.1.0

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 good-console@4.1.0 moment@2.8.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.

Overview

moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.

An attacker can provide a long value to the duration function, which nearly matches the pattern being matched. This will cause the regular expression matching to take a long time, all the while occupying the event loop and preventing it from processing other requests and making the server unavailable (a Denial of Service attack).

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade moment to version 2.11.2 or greater.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: moment
  • Introduced through: good-console@4.1.0

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 good-console@4.1.0 moment@2.8.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.

Overview

moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.

Affected versions of the package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks for any locale that has separate format and standalone options and format input can be controlled by the user.

An attacker can provide a specially crafted input to the format function, which nearly matches the pattern being matched. This will cause the regular expression matching to take a long time, all the while occupying the event loop and preventing it from processing other requests and making the server unavailable (a Denial of Service attack).

Disclosure Timeline

  • October 19th, 2016 - Reported the issue to package owner.
  • October 19th, 2016 - Issue acknowledged by package owner.
  • October 24th, 2016 - Issue fixed and version 2.15.2 released.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

References

medium severity

Access Restriction Bypass

  • Vulnerable module: npm
  • Introduced through: npm@2.15.12

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

npm is a package manager for JavaScript.

Affected versions of this package are vulnerable to Access Restriction Bypass. It might allow local users to bypass intended filesystem access restrictions due to ownerships of /etc and /usr directories are being changed unexpectedly, related to a "correctMkdir" issue.

Remediation

Upgrade npm to version 5.7.1 or higher.

References

medium severity

Insertion of Sensitive Information into Log File

  • Vulnerable module: npm
  • Introduced through: npm@2.15.12

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

npm is a package manager for JavaScript.

Affected versions of this package are vulnerable to Insertion of Sensitive Information into Log File. The CLI supports URLs like <protocol>://[<user>[:<password>]@]<hostname>[:<port>][:][/]<path>. The password value is not redacted and is printed to stdout and also to any generated log files.

Remediation

Upgrade npm to version 6.14.6 or higher.

References

medium severity
new

Prototype Pollution

  • Vulnerable module: object-path
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git eazy-logger@3.0.2 tfunk@3.1.0 object-path@0.9.2

Overview

object-path is a package to access deep properties using a path

Affected versions of this package are vulnerable to Prototype Pollution. A type confusion vulnerability can lead to a bypass of CVE-2020-15256 when the path components used in the path parameter are arrays. In particular, the condition currentPath === '__proto__' returns false if currentPath is ['__proto__']. This is because the === operator returns always false when the type of the operands is different.

PoC

const objectPath = require('object-path');

objectPath.withInheritedProps.set({}, [['__proto__'], 'polluted'], 'yes');
console.log(polluted); // yes

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

Upgrade object-path to version 0.11.6 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: postcss
  • Introduced through: @bigcommerce/stencil-styles@1.1.0

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 postcss@5.2.18
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 autoprefixer@6.7.7 postcss@5.2.18

Overview

postcss is a PostCSS is a tool for transforming styles with JS plugins.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via getAnnotationURL() and loadAnnotation() in lib/previous-map.js. The vulnerable regexes are caused mainly by the sub-pattern \/\*\s*# sourceMappingURL=(.*).

PoC

var postcss = require("postcss")
function build_attack(n) {
    var ret = "a{}"
    for (var i = 0; i < n; i++) {
        ret += "/*# sourceMappingURL="
    }
    return ret + "!";
}

// postcss.parse('a{}/*# sourceMappingURL=a.css.map */')
for(var i = 1; i <= 500000; i++) {
    if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
        try{
            postcss.parse(attack_str)
            var time_cost = Date.now() - time;
            console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
            }
        catch(e){
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms");
        }
    }
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade postcss to version 8.2.13, 7.0.36 or higher.

References

medium severity

Remote Memory Exposure

  • Vulnerable module: request
  • Introduced through: jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 request@2.53.0
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 request@2.53.0
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

request is a simplified http request client.

Affected versions of this package are vulnerable to Remote Memory Exposure. A potential remote memory exposure vulnerability exists in request. If a request uses a multipart attachment and the body type option is number with value X, then X bytes of uninitialized memory will be sent in the body of the request.

Note that while the impact of this vulnerability is high (memory exposure), exploiting it is likely difficult, as the attacker needs to somehow control the body type of the request. One potential exploit scenario is when a request is composed based on JSON input, including the body type, allowing a malicious JSON to trigger the memory leak.

Details

Constructing a Buffer class with integer N creates a Buffer of length N with non zero-ed out memory. Example:

var x = new Buffer(100); // uninitialized Buffer of length 100
// vs
var x = new Buffer('100'); // initialized Buffer with value of '100'

Initializing a multipart body in such manner will cause uninitialized memory to be sent in the body of the request.

Proof of concept

var http = require('http')
var request = require('request')

http.createServer(function (req, res) {
  var data = ''
  req.setEncoding('utf8')
  req.on('data', function (chunk) {
    console.log('data')
    data += chunk
  })
  req.on('end', function () {
    // this will print uninitialized memory from the client
    console.log('Client sent:\n', data)
  })
  res.end()
}).listen(8000)

request({
  method: 'POST',
  uri: 'http://localhost:8000',
  multipart: [{ body: 1000 }]
},
function (err, res, body) {
  if (err) return console.error('upload failed:', err)
  console.log('sent')
})

Remediation

Upgrade request to version 2.68.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver
  • Introduced through: jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 traceur@0.0.88 semver@2.3.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 systemjs-builder@0.10.6 traceur@0.0.88 semver@2.3.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 systemjs-builder@0.10.6 traceur@0.0.88 semver@2.3.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

semver is a semantic version parser used by npm.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS).

Overview

npm is a package manager for javascript.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The semver module uses regular expressions when parsing a version string. For a carefully crafted input, the time it takes to process these regular expressions is not linear to the length of the input. Since the semver module did not enforce a limit on the version string length, an attacker could provide a long string that would take up a large amount of resources, potentially taking a server down. This issue therefore enables a potential Denial of Service attack. This is a slightly differnt variant of a typical Regular Expression Denial of Service (ReDoS) vulnerability.

Details

<>

Remediation

Update to a version 4.3.2 or greater. From the issue description [2]: "Package version can no longer be more than 256 characters long. This prevents a situation in which parsing the version number can use exponentially more time and memory to parse, leading to a potential denial of service."

References

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade semver to version 4.3.2 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: set-getter
  • Introduced through: @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 lazy-cache@2.0.2 set-getter@0.1.1
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 create-frame@1.0.0 lazy-cache@2.0.2 set-getter@0.1.1

Overview

set-getter is a Create nested getter properties and any intermediary dot notation ('a.b.c') paths

Affected versions of this package are vulnerable to Prototype Pollution. Allows an attacker to cause a denial of service and may lead to remote code execution.

Details

Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as _proto_, constructor and prototype. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.

There are two main ways in which the pollution of prototypes occurs:

  • Unsafe Object recursive merge
  • Property definition by path

Unsafe Object recursive merge

The logic of a vulnerable recursive merge function follows the following high-level model:

merge (target, source)

  foreach property of source

    if property exists and is an object on both the target and the source

      merge(target[property], source[property])

    else

      target[property] = source[property]

When the source object contains a property named _proto_ defined with Object.defineProperty() , the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object and the source of Object as defined by the attacker. Properties are then copied on the Object prototype.

Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source).

lodash and Hoek are examples of libraries susceptible to recursive merge attacks.

Property definition by path

There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)

If the attacker can control the value of “path”, they can set this value to _proto_.myValue. myValue is then assigned to the prototype of the class of the object.

Types of attacks

There are a few methods by which Prototype Pollution can be manipulated:

Type Origin Short description
Denial of service (DoS) Client This is the most likely attack.
DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf).
The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object. In this case, the code fails and is likely to cause a denial of service.
For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail.
Remote Code Execution Client Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation.
For example: eval(someobject.someattr). In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code.
Property Injection Client The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens.
For example: if a codebase checks privileges for someuser.isAdmin, then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true, they can then achieve admin privileges.

Affected environments

The following environments are susceptible to a Prototype Pollution attack:

  • Application server
  • Web server

How to prevent

  1. Freeze the prototype— use Object.freeze (Object.prototype).
  2. Require schema validation of JSON input.
  3. Avoid using unsafe recursive merge functions.
  4. Consider using objects without prototypes (for example, Object.create(null)), breaking the prototype chain and preventing pollution.
  5. As a best practice use Map instead of Object.

For more information on this vulnerability type:

Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018

Remediation

There is no fixed version for set-getter.

References

medium severity

Insecure Defaults

  • Vulnerable module: socket.io
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git socket.io@2.0.4

Overview

socket.io is a node.js realtime framework server.

Affected versions of this package are vulnerable to Insecure Defaults due to CORS Misconfiguration. All domains are whitelisted by default.

Remediation

Upgrade socket.io to version 2.4.0 or higher.

References

medium severity

Uninitialized Memory Exposure

  • Vulnerable module: tunnel-agent
  • Introduced through: npm@2.15.12 and jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 request@2.74.0 tunnel-agent@0.4.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 request@2.53.0 tunnel-agent@0.4.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 request@2.53.0 tunnel-agent@0.4.3
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

tunnel-agent is HTTP proxy tunneling agent. Affected versions of the package are vulnerable to Uninitialized Memory Exposure.

A possible memory disclosure vulnerability exists when a value of type number is used to set the proxy.auth option of a request request and results in a possible uninitialized memory exposures in the request body.

This is a result of unobstructed use of the Buffer constructor, whose insecure default constructor increases the odds of memory leakage.

Details

Constructing a Buffer class with integer N creates a Buffer of length N with raw (not "zero-ed") memory.

In the following example, the first call would allocate 100 bytes of memory, while the second example will allocate the memory needed for the string "100":

// uninitialized Buffer of length 100
x = new Buffer(100);
// initialized Buffer with value of '100'
x = new Buffer('100');

tunnel-agent's request construction uses the default Buffer constructor as-is, making it easy to append uninitialized memory to an existing list. If the value of the buffer list is exposed to users, it may expose raw server side memory, potentially holding secrets, private data and code. This is a similar vulnerability to the infamous Heartbleed flaw in OpenSSL.

Proof of concept by ChALkeR

require('request')({
  method: 'GET',
  uri: 'http://www.example.com',
  tunnel: true,
  proxy:{
      protocol: 'http:',
      host:"127.0.0.1",
      port:8080,
      auth:80
  }
});

You can read more about the insecure Buffer behavior on our blog.

Similar vulnerabilities were discovered in request, mongoose, ws and sequelize.

Remediation

Upgrade tunnel-agent to version 0.6.0 or higher. Note This is vulnerable only for Node <=4

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ua-parser-js
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git ua-parser-js@0.7.12

Overview

ua-parser-js is a lightweight JavaScript-based user-agent string parser.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). Within src/ua-parser.js, the browser regex is vulnerable to exponential backtracking.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ua-parser-js to version 0.7.24 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ua-parser-js
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git ua-parser-js@0.7.12

Overview

ua-parser-js is a Lightweight JavaScript-based user-agent string parser.

Affected versions of the package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks via the `getOS() function.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ua-parser-js to version 0.7.16 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ua-parser-js
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git ua-parser-js@0.7.12

Overview

ua-parser-js is Lightweight JavaScript-based user-agent string parser.

Affected versions of the package are vulnerable to Regular Expression Denial of Service (ReDoS).

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ua-parser-js to version 0.7.18 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: uglify-js
  • Introduced through: jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 uglify-js@2.4.24
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

The parse() function in the uglify-js package prior to version 2.6.0 is vulnerable to regular expression denial of service (ReDoS) attacks when long inputs of certain patterns are processed.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade to version 2.6.0 or greater. If a direct dependency update is not possible, use snyk wizard to patch this vulnerability.

References

medium severity

Arbitrary Code Injection

  • Vulnerable module: underscore
  • Introduced through: @bigcommerce/stencil-paper@2.0.28 and jsonlint@1.6.3

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 messageformat@0.2.2 underscore@1.5.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jsonlint@1.6.3 nomnom@1.8.1 underscore@1.6.0

Overview

underscore is a JavaScript's functional programming helper library.

Affected versions of this package are vulnerable to Arbitrary Code Injection via the template function, particularly when the variable option is taken from _.templateSettings as it is not sanitized.

PoC

const _ = require('underscore');
_.templateSettings.variable = "a = this.process.mainModule.require('child_process').execSync('touch HELLO')";
const t = _.template("")();

Remediation

Upgrade underscore to version 1.13.0-2, 1.12.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ws
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git socket.io@2.0.4 engine.io@3.1.5 ws@3.3.3
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git browser-sync-ui@1.0.1 socket.io-client@2.0.4 engine.io-client@3.1.6 ws@3.3.3
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git socket.io@2.0.4 socket.io-client@2.0.4 engine.io-client@3.1.6 ws@3.3.3

Overview

ws is a simple to use websocket client, server and console for node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). A specially crafted value of the Sec-Websocket-Protocol header can be used to significantly slow down a ws server.

##PoC

for (const length of [1000, 2000, 4000, 8000, 16000, 32000]) {
  const value = 'b' + ' '.repeat(length) + 'x';
  const start = process.hrtime.bigint();

  value.trim().split(/ *, */);

  const end = process.hrtime.bigint();

  console.log('length = %d, time = %f ns', length, end - start);
}

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ws to version 7.4.6, 6.2.2, 5.2.3 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: braces
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git and @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git micromatch@2.3.11 braces@1.8.5
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 micromatch@2.3.11 braces@1.8.5
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git chokidar@1.7.0 anymatch@1.3.2 micromatch@2.3.11 braces@1.8.5

Overview

braces is a Bash-like brace expansion, implemented in JavaScript.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (^\{(,+(?:(\{,+\})*),*|,*(?:(\{,+\})*),+)\}) in order to detects empty braces. This can cause an impact of about 10 seconds matching time for data 50K characters long.

Disclosure Timeline

  • Feb 15th, 2018 - Initial Disclosure to package owner
  • Feb 16th, 2018 - Initial Response from package owner
  • Feb 18th, 2018 - Fix issued
  • Feb 19th, 2018 - Vulnerability published

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade braces to version 2.3.1 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: debug
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git connect@3.5.0 debug@2.2.0
    Remediation: Open PR to patch debug@2.2.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git serve-index@1.8.0 debug@2.2.0
    Remediation: Open PR to patch debug@2.2.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git connect@3.5.0 finalhandler@0.5.0 debug@2.2.0
    Remediation: Open PR to patch debug@2.2.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git localtunnel@1.8.3 debug@2.6.8
    Remediation: Open PR to patch debug@2.6.8.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git serve-static@1.12.2 send@0.15.2 debug@2.6.4
    Remediation: Open PR to patch debug@2.6.4.

Overview

debug is a JavaScript debugging utility modelled after Node.js core's debugging technique..

debug uses printf-style formatting. Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks via the the %o formatter (Pretty-print an Object all on a single line). It used a regular expression (/\s*\n\s*/g) in order to strip whitespaces and replace newlines with spaces, in order to join the data into a single line. This can cause a very low impact of about 2 seconds matching time for data 50k characters long.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade debug to version 2.6.9, 3.1.0 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: eslint
  • Introduced through: eslint@2.13.1 and lab@5.18.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 eslint@2.13.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 lab@5.18.1 eslint@1.5.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.

Overview

eslint is a pluggable linting utility for JavaScript and JSX

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). This can cause an impact of about 10 seconds matching time for data 100k characters long.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade eslint to version 4.18.2 or higher.

References

low severity

CORS Bypass

  • Vulnerable module: hapi
  • Introduced through: hapi@8.8.1

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 hapi@8.8.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.23.0.

Overview

Hapi v11.0.0 and below have an incorrect implementation of the CORS protocol, and allow for configurations that, at best, return inconsistent headers and, at worst, cross-origin activities that are expected to be forbidden.

Details

If the connection has CORS enabled but one route has it off, and the route is not GET, the OPTIONS prefetch request will return the default CORS headers and then the actual request will go through and return no CORS headers. This defeats the purpose of turning CORS on the route.

Remediation

Upgrade to a version 11.0.0 or greater.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: hawk
  • Introduced through: jspm@0.15.7

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 request@2.53.0 hawk@2.3.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 request@2.53.0 hawk@2.3.1
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

hawk is an HTTP authentication scheme using a message authentication code (MAC) algorithm to provide partial HTTP request cryptographic verification.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

You can read more about Regular Expression Denial of Service (ReDoS) on our blog.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: mime
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git serve-static@1.12.2 send@0.15.2 mime@1.3.4
    Remediation: Open PR to patch mime@1.3.4.

Overview

mime is a comprehensive, compact MIME type module.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It uses regex the following regex /.*[\.\/\\]/ in its lookup, which can cause a slowdown of 2 seconds for 50k characters.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade mime to version 1.4.1, 2.0.3 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: moment
  • Introduced through: good-console@4.1.0

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 good-console@4.1.0 moment@2.8.4
    Remediation: Upgrade to @bigcommerce/stencil-cli@3.0.0.

Overview

moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (/[0-9]*['a-z\u00A0-\u05FF\u0700-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF]+|[\u0600-\u06FF\/]+(\s*?[\u0600-\u06FF]+){1,2}/i) in order to parse dates specified as strings. This can cause a very low impact of about 2 seconds matching time for data 50k characters long.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade moment to version 2.19.3 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ms
  • Introduced through: browser-sync@git://github.com/bigcommerce/browser-sync.git

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git connect@3.5.0 debug@2.2.0 ms@0.7.1
    Remediation: Open PR to patch ms@0.7.1.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git serve-index@1.8.0 debug@2.2.0 ms@0.7.1
    Remediation: Open PR to patch ms@0.7.1.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git connect@3.5.0 finalhandler@0.5.0 debug@2.2.0 ms@0.7.1
    Remediation: Open PR to patch ms@0.7.1.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git serve-static@1.12.2 send@0.15.2 debug@2.6.4 ms@0.7.3
    Remediation: Open PR to patch ms@0.7.3.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 browser-sync@git://github.com/bigcommerce/browser-sync.git serve-static@1.12.2 send@0.15.2 ms@1.0.0
    Remediation: Open PR to patch ms@1.0.0.

Overview

ms is a tiny millisecond conversion utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an incomplete fix for previously reported vulnerability npm:ms:20151024. The fix limited the length of accepted input string to 10,000 characters, and turned to be insufficient making it possible to block the event loop for 0.3 seconds (on a typical laptop) with a specially crafted string passed to ms() function.

Proof of concept

ms = require('ms');
ms('1'.repeat(9998) + 'Q') // Takes about ~0.3s

Note: Snyk's patch for this vulnerability limits input length to 100 characters. This new limit was deemed to be a breaking change by the author. Based on user feedback, we believe the risk of breakage is very low, while the value to your security is much greater, and therefore opted to still capture this change in a patch for earlier versions as well. Whenever patching security issues, we always suggest to run tests on your code to validate that nothing has been broken.

For more information on Regular Expression Denial of Service (ReDoS) attacks, go to our blog.

Disclosure Timeline

  • Feb 9th, 2017 - Reported the issue to package owner.
  • Feb 11th, 2017 - Issue acknowledged by package owner.
  • April 12th, 2017 - Fix PR opened by Snyk Security Team.
  • May 15th, 2017 - Vulnerability published.
  • May 16th, 2017 - Issue fixed and version 2.0.0 released.
  • May 21th, 2017 - Patches released for versions >=0.7.1, <=1.0.0.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade ms to version 2.0.0 or higher.

References

low severity

Unauthorized File Access

  • Vulnerable module: npm
  • Introduced through: npm@2.15.12

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.

Overview

npm is a package manager for JavaScript.

Affected versions of this package are vulnerable to Unauthorized File Access. It is possible for packages to create symlinks to files outside of thenode_modules folder through the bin field upon installation.

For npm, a properly constructed entry in the package.json bin field would allow a package publisher to create a symlink pointing to arbitrary files on a user’s system when the package is installed. This behaviour is possible through install scripts. This vulnerability bypasses a user using the --ignore-scripts install option.

Remediation

Upgrade npm to version 6.13.3 or higher.

References

low severity

Cross-site Scripting (XSS)

  • Vulnerable module: striptags
  • Introduced through: @bigcommerce/stencil-paper@2.0.28

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-paper@2.0.28 handlebars-helpers@0.8.4 striptags@2.2.1

Overview

striptags is a PHP strip_tags in Node.js

Affected versions of this package are vulnerable to Cross-site Scripting (XSS). It might cause striptags to concatenate unsanitized strings when an array-like object is passed in as the html parameter. This can be abused by an attacker who can control the shape of their input, e.g. if query parameters are passed directly into the function.

Details

A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.

This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.

Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.

Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as &lt; and > can be coded as &gt; in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.

The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.

Types of attacks

There are a few methods by which XSS can be manipulated:

Type Origin Description
Stored Server The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link.
Reflected Server The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser.
DOM-based Client The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data.
Mutated The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters.

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

This section describes the top best practices designed to specifically protect your code:

  • Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
  • Convert special characters such as ?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.
  • Give users the option to disable client-side scripts.
  • Redirect invalid requests.
  • Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
  • Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
  • Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.

Remediation

Upgrade striptags to version 3.2.0 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: tar
  • Introduced through: npm@2.15.12, @bigcommerce/stencil-styles@1.1.0 and others

Detailed paths

  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 npm@2.15.12 node-gyp@3.6.3 tar@2.2.2
    Remediation: Upgrade to @bigcommerce/stencil-cli@1.22.0.
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 @bigcommerce/stencil-styles@1.1.0 @bigcommerce/node-sass@git://github.com/bigcommerce-labs/node-sass.git#v3.4.4 node-gyp@3.8.0 tar@2.2.2
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-github@0.11.6 tar@1.0.3
  • Introduced through: @bigcommerce/stencil-cli@1.15.5 jspm@0.15.7 jspm-npm@0.21.4 tar@1.0.3

Overview

tar is a full-featured Tar for Node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). When stripping the trailing slash from files arguments, the f.replace(/\/+$/, '') performance of this function can exponentially degrade when f contains many / characters resulting in ReDoS.

This vulnerability is not likely to be exploitable as it requires that the untrusted input is being passed into the tar.extract() or tar.list() array of entries to parse/extract, which would be unusual.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade tar to version 6.1.4, 5.0.8, 4.4.16 or higher.

References