@salesforce-ux/design-system-previewer@3.1.0

Vulnerabilities

24 via 67 paths

Dependencies

136

Source

npm

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Severity
  • 15
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Status
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high severity

Prototype Pollution

  • Vulnerable module: aws-sdk
  • Introduced through: aws-sdk@2.76.0

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 aws-sdk@2.76.0
    Remediation: Upgrade to aws-sdk@2.814.0.

Overview

Affected versions of this package are vulnerable to Prototype Pollution. If an attacker submits a malicious INI file to an application that parses it with loadSharedConfigFiles , they will pollute the prototype on the application. This can be exploited further depending on the context.

PoC by Eugene Lim:

payload.toml:

[__proto__]
polluted = "polluted"

poc.js:

var fs = require('fs')
var sharedIniFileLoader = require('@aws-sdk/shared-ini-file-loader')

async function main() {
var parsed = await sharedIniFileLoader.loadSharedConfigFiles({ filepath: './payload.toml' })
console.log(parsed)
console.log(parsed.__proto__)
console.log({}.__proto__)
console.log(polluted)
}

main()
> node poc.js
{
configFile: { default: { region: 'ap-southeast-1' } },
credentialsFile: {}
}
{ polluted: '"polluted"' }
{ polluted: '"polluted"' }
"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 aws-sdk to version 2.814.0 or higher.

References

high severity

Insecure Randomness

  • Vulnerable module: crypto-browserify
  • Introduced through: aws-sdk@2.76.0

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 aws-sdk@2.76.0 crypto-browserify@1.0.9
    Remediation: Upgrade to aws-sdk@2.178.0.

Overview

crypto-browserify is implementation of crypto for the browser.

Affected versions of the package are vulnerable to Insecure Randomness due to using the cryptographically insecure Math.random(). This function can produce predictable values and should not be used in security-sensitive context.

Details

Computers are deterministic machines, and as such are unable to produce true randomness. Pseudo-Random Number Generators (PRNGs) approximate randomness algorithmically, starting with a seed from which subsequent values are calculated.

There are two types of PRNGs: statistical and cryptographic. Statistical PRNGs provide useful statistical properties, but their output is highly predictable and forms an easy to reproduce numeric stream that is unsuitable for use in cases where security depends on generated values being unpredictable. Cryptographic PRNGs address this problem by generating output that is more difficult to predict. For a value to be cryptographically secure, it must be impossible or highly improbable for an attacker to distinguish between it and a truly random value. In general, if a PRNG algorithm is not advertised as being cryptographically secure, then it is probably a statistical PRNG and should not be used in security-sensitive contexts.

You can read more about node's insecure Math.random() in Mike Malone's post.

Remediation

Upgrade crypto-browserify to version 2.1.11 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: engine.io
  • Introduced through: socket.io@1.7.1

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 engine.io@1.8.1
    Remediation: Upgrade to socket.io@3.0.0.

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: express@4.14.0

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 fresh@0.3.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 send@0.14.1 fresh@0.3.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 serve-static@1.11.2 send@0.14.2 fresh@0.3.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

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

Command Injection

  • Vulnerable module: lodash
  • Introduced through: lodash@4.17.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 lodash@4.17.2
    Remediation: Upgrade to lodash@4.17.21.

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@4.17.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 lodash@4.17.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

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@4.17.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 lodash@4.17.2
    Remediation: Upgrade to lodash@4.17.20.

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: lodash
  • Introduced through: lodash@4.17.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 lodash@4.17.2
    Remediation: Upgrade to lodash@4.17.17.

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@4.17.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 lodash@4.17.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

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

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: parsejson
  • Introduced through: socket.io-client@1.7.2 and socket.io@1.7.1

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 engine.io-client@1.8.2 parsejson@0.0.3
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 engine.io-client@1.8.1 parsejson@0.0.3

Overview

parsejson is a method that parses a JSON string and returns a JSON object.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks. An attacker may pass a specially crafted JSON data, 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

There is no fixed version for parsejson.

References

high severity

Prototype Override Protection Bypass

  • Vulnerable module: qs
  • Introduced through: express@4.14.0

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 qs@6.2.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

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

Denial of Service (DoS)

  • Vulnerable module: socket.io-parser
  • Introduced through: socket.io@1.7.1 and socket.io-client@1.7.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-parser@2.3.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 socket.io-parser@2.3.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-adapter@0.5.0 socket.io-parser@2.3.1
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 socket.io-parser@2.3.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

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: ws
  • Introduced through: socket.io@1.7.1 and socket.io-client@1.7.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 engine.io@1.8.1 ws@1.1.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 engine.io-client@1.8.2 ws@1.1.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 engine.io-client@1.8.1 ws@1.1.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

Overview

ws is a simple to use websocket client, server and console for node.js.

Affected versions of this package are vulnerable to Denial of Service (DoS) attacks. A specially crafted value of the Sec-WebSocket-Extensions header that used Object.prototype property names as extension or parameter names could be used to make a ws server crash.

PoC:

const WebSocket = require('ws');
const net = require('net');

const wss = new WebSocket.Server({ port: 3000 }, function () {
  const payload = 'constructor';  // or ',;constructor'

  const request = [
    'GET / HTTP/1.1',
    'Connection: Upgrade',
    'Sec-WebSocket-Key: test',
    'Sec-WebSocket-Version: 8',
    `Sec-WebSocket-Extensions: ${payload}`,
    'Upgrade: websocket',
    '\r\n'
  ].join('\r\n');

  const socket = net.connect(3000, function () {
    socket.resume();
    socket.write(request);
  });
});

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 ws to version 1.1.5, 3.3.1 or higher.

References

high severity
new

Access Restriction Bypass

  • Vulnerable module: xmlhttprequest-ssl
  • Introduced through: socket.io-client@1.7.2 and socket.io@1.7.1

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 engine.io-client@1.8.2 xmlhttprequest-ssl@1.5.3
    Remediation: Upgrade to socket.io-client@2.4.0.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 engine.io-client@1.8.1 xmlhttprequest-ssl@1.5.3
    Remediation: Upgrade to socket.io@2.4.0.

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: socket.io-client@1.7.2 and socket.io@1.7.1

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 engine.io-client@1.8.2 xmlhttprequest-ssl@1.5.3
    Remediation: Upgrade to socket.io-client@2.4.0.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 engine.io-client@1.8.1 xmlhttprequest-ssl@1.5.3
    Remediation: Upgrade to socket.io@2.4.0.

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

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: lodash@4.17.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 lodash@4.17.2
    Remediation: Upgrade to lodash@4.17.16.

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@4.17.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 lodash@4.17.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

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@4.17.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 lodash@4.17.2
    Remediation: Upgrade to lodash@4.17.21.

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@4.17.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 lodash@4.17.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

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

Insecure Defaults

  • Vulnerable module: socket.io
  • Introduced through: socket.io@1.7.1

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1
    Remediation: Upgrade to socket.io@2.4.0.

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

Insecure Randomness

  • Vulnerable module: ws
  • Introduced through: socket.io@1.7.1 and socket.io-client@1.7.2

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 engine.io@1.8.1 ws@1.1.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 engine.io-client@1.8.2 ws@1.1.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 engine.io-client@1.8.1 ws@1.1.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

Overview

ws is a simple to use websocket client, server and console for node.js.

Affected versions of the package use the cryptographically insecure Math.random() which can produce predictable values and should not be used in security-sensitive context.

Details

Computers are deterministic machines, and as such are unable to produce true randomness. Pseudo-Random Number Generators (PRNGs) approximate randomness algorithmically, starting with a seed from which subsequent values are calculated.

There are two types of PRNGs: statistical and cryptographic. Statistical PRNGs provide useful statistical properties, but their output is highly predictable and forms an easy to reproduce numeric stream that is unsuitable for use in cases where security depends on generated values being unpredictable. Cryptographic PRNGs address this problem by generating output that is more difficult to predict. For a value to be cryptographically secure, it must be impossible or highly improbable for an attacker to distinguish between it and a truly random value. In general, if a PRNG algorithm is not advertised as being cryptographically secure, then it is probably a statistical PRNG and should not be used in security-sensitive contexts.

You can read more about node's insecure Math.random() in Mike Malone's post.

Remediation

Upgrade ws to version 1.1.2 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: debug
  • Introduced through: express@4.14.0, socket.io@1.7.1 and others

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 debug@2.2.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 finalhandler@0.5.0 debug@2.2.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 send@0.14.1 debug@2.2.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-parser@2.3.1 debug@2.2.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 socket.io-parser@2.3.1 debug@2.2.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 serve-static@1.11.2 send@0.14.2 debug@2.2.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-adapter@0.5.0 socket.io-parser@2.3.1 debug@2.2.0
    Remediation: Open PR to patch debug@2.2.0.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 socket.io-parser@2.3.1 debug@2.2.0
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 debug@2.3.3
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 debug@2.3.3
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 engine.io@1.8.1 debug@2.3.3
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-adapter@0.5.0 debug@2.3.3
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 debug@2.3.3
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 engine.io-client@1.8.2 debug@2.3.3
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 engine.io-client@1.8.1 debug@2.3.3
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

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: mime
  • Introduced through: express@4.14.0

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 send@0.14.1 mime@1.3.4
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 serve-static@1.11.2 send@0.14.2 mime@1.3.4
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

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: ms
  • Introduced through: express@4.14.0, socket.io@1.7.1 and others

Detailed paths

  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 send@0.14.1 ms@0.7.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 finalhandler@0.5.0 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 send@0.14.1 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-parser@2.3.1 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 socket.io-parser@2.3.1 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 serve-static@1.11.2 send@0.14.2 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-adapter@0.5.0 socket.io-parser@2.3.1 debug@2.2.0 ms@0.7.1
    Remediation: Open PR to patch ms@0.7.1.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 socket.io-parser@2.3.1 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 express@4.14.0 serve-static@1.11.2 send@0.14.2 ms@0.7.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 engine.io@1.8.1 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-adapter@0.5.0 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io-client@1.7.2 engine.io-client@1.8.2 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.
  • Introduced through: @salesforce-ux/design-system-previewer@3.1.0 socket.io@1.7.1 socket.io-client@1.7.1 engine.io-client@1.8.1 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to @salesforce-ux/design-system-previewer@3.2.2.

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