seneca@0.5.17

Vulnerabilities 24 via 52 paths
Dependencies 117
Source npm
Package seneca

Find, fix and prevent vulnerabilities in your code.

Severity
  • 8
  • 12
  • 4
Status
  • 24
  • 0
  • 0
high severity

Arbitrary Code Injection

  • Vulnerable module: growl
  • Introduced through: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 mocha@1.18.2 growl@1.7.0
    Remediation: Upgrade to seneca@0.5.18.

Overview

growl is a package adding Growl support for Nodejs.

Affected versions of this package are vulnerable to Arbitrary Code Injection due to unsafe use of the eval() function. Node.js provides the eval() function by default, and is used to translate strings into Javascript code. An attacker can craft a malicious payload to inject arbitrary commands.

Remediation

Upgrade growl to version 1.10.0 or higher.

References

high severity

Denial of Service (Memory Exhaustion)

  • Vulnerable module: qs
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 qs@0.6.6
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 qs@0.6.6
    Remediation: Upgrade to seneca@3.0.0.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 qs@0.6.6
    Remediation: Upgrade to seneca@0.5.18.

Overview

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

Affected versions of this package are vulnerable to Denial of Service (Memory Exhaustion). During parsing, the qs module may create a sparse area (an array where no elements are filled), and grow that array to the necessary size based on the indices used on it. An attacker can specify a high index value in a query string, thus making the server allocate a respectively big array. Truly large values can cause the server to run out of memory and cause it to crash - thus enabling a Denial-of-Service attack.

Remediation

Upgrade qs to version 1.0.0 or higher.

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

References

high severity

Prototype Override Protection Bypass

  • Vulnerable module: qs
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 qs@0.6.6
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 qs@0.6.6
    Remediation: Upgrade to seneca@3.0.0.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 qs@0.6.6
    Remediation: Upgrade to seneca@0.6.0.

Overview

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

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 6.4.0 or higher. Note: The fix was backported to the following versions 6.3.2, 6.2.3, 6.1.2, 6.0.4.

References

high severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 fivebeans@1.1.1 lodash@2.4.2

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: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 fivebeans@1.1.1 lodash@2.4.2

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 (DoS)

  • Vulnerable module: minimatch
  • Introduced through: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 mocha@1.18.2 glob@3.2.3 minimatch@0.2.14
    Remediation: Upgrade to seneca@0.5.18.

Overview

minimatch is a minimalistic matching library used for converting glob expressions into JavaScript RegExp objects. Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Many Regular Expression implementations may reach edge cases that causes them to work very slowly (exponentially related to input size), allowing an attacker to exploit this and can cause the program to enter these extreme situations by using a specially crafted input and cause the service to excessively consume CPU, resulting in a Denial of Service.

An attacker can provide a long value to the minimatch function, which nearly matches the pattern being matched. This will cause the regular expression matching to take a long time, all the while occupying the event loop and preventing it from processing other requests and making the server unavailable (a Denial of Service attack).

You can read more about Regular Expression Denial of Service (ReDoS) on our blog.

Remediation

Upgrade minimatch to version 3.0.2 or greater.

References

high severity

Regular Expression Denial of Service (DoS)

  • Vulnerable module: negotiator
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 compression@1.0.0 negotiator@0.3.0
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 compression@1.0.0 negotiator@0.3.0
    Remediation: Upgrade to seneca@3.0.0.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 serve-index@1.0.1 negotiator@0.4.2
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 serve-index@1.0.1 negotiator@0.4.2
    Remediation: Upgrade to seneca@3.0.0.

Overview

negotiator is an HTTP content negotiator for Node.js.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (DoS) when parsing Accept-Language http header.

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 negotiator to version 0.6.1 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: fresh
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 fresh@0.2.2
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 fresh@0.2.2
    Remediation: Upgrade to seneca@3.0.0.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 serve-static@1.1.0 send@0.3.0 fresh@0.2.4
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 serve-static@1.1.0 send@0.3.0 fresh@0.2.4
    Remediation: Upgrade to seneca@3.0.0.

Overview

fresh is HTTP response freshness testing.

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

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade fresh to version 0.5.2 or higher.

References

medium severity

Arbitrary Code Injection

  • Vulnerable module: morgan
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 morgan@1.0.0
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 morgan@1.0.0
    Remediation: Upgrade to seneca@3.0.0.

Overview

An attacker could use the format parameter to inject arbitrary commands.

References

medium severity

Cross-site Scripting due to improper file and directory names escaping

  • Vulnerable module: serve-index
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 serve-index@1.0.1
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 serve-index@1.0.1
    Remediation: Upgrade to seneca@3.0.0.

Overview

serve-index Serves pages that contain directory listings for a given path.

Affected versions of this package are vulnerable to Cross-site Scripting (XSS) attacks. When using serve-index middleware, file and directory names are not escaped in HTML output. If a remote attcker can influence these names, it may trigger a persistent XSS attack.

Details

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

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

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

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

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

Types of attacks

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

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

Affected environments

The following environments are susceptible to an XSS attack:

  • Web servers
  • Application servers
  • Web application environments

How to prevent

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

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

Remediation

Upgrade to version 1.6.3 or greater

References

medium severity

Denial of Service (Event Loop Blocking)

  • Vulnerable module: qs
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 qs@0.6.6
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 qs@0.6.6
    Remediation: Upgrade to seneca@3.0.0.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 qs@0.6.6
    Remediation: Upgrade to seneca@0.5.18.

Overview

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

Affected versions of this package are vulnerable to Denial of Service (DoS). When parsing a string representing a deeply nested object, qs will block the event loop for long periods of time. Such a delay may hold up the server's resources, keeping it from processing other requests in the meantime, thus enabling a Denial-of-Service attack.

Remediation

Update qs to version 1.0.0 or higher. In these versions, qs enforces a max object depth (along with other limits), limiting the event loop length and thus preventing such an attack.

References

medium severity

Directory Traversal

  • Vulnerable module: send
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 serve-static@1.1.0 send@0.3.0
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 serve-static@1.1.0 send@0.3.0
    Remediation: Upgrade to seneca@3.0.0.

Overview

send is a library for streaming files from the file system.

Affected versions of this package are vulnerable to Directory-Traversal attacks due to insecure comparison. When relying on the root option to restrict file access a malicious user may escape out of the restricted directory and access files in a similarly named directory. For example, a path like /my-secret is consedered fine for the root /my.

Details

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

Directory Traversal vulnerabilities can be generally divided into two types:

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

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

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

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

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

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

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

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

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

Remediation

Upgrade to a version greater than or equal to 0.8.4.

References

medium severity

Non-Constant Time String Comparison

  • Vulnerable module: cookie-signature
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 cookie-signature@1.0.3
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 cookie-signature@1.0.3
    Remediation: Upgrade to seneca@0.5.19.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 cookie-parser@1.0.1 cookie-signature@1.0.3
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 cookie-parser@1.0.1 cookie-signature@1.0.3
    Remediation: Upgrade to seneca@0.5.19.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 express-session@1.0.2 cookie-signature@1.0.3
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 express-session@1.0.2 cookie-signature@1.0.3
    Remediation: Upgrade to seneca@0.5.19.

Overview

'cookie-signature' is a library for signing cookies.

Versions before 1.0.4 of the library use the built-in string comparison mechanism, ===, and not a time constant string comparison. As a result, the comparison will fail faster when the first characters in the token are incorrect. An attacker can use this difference to perform a timing attack, essentially allowing them to guess the secret one character at a time.

You can read more about timing attacks in Node.js on the Snyk blog: https://snyk.io/blog/node-js-timing-attack-ccc-ctf/

Remediation

Upgrade to 1.0.4 or greater.

References

medium severity

Prototype Pollution

  • Vulnerable module: hoek
  • Introduced through: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 hawk@1.0.0 hoek@0.9.1
    Remediation: Upgrade to seneca@0.6.0.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 hawk@1.0.0 boom@0.4.2 hoek@0.9.1
    Remediation: Upgrade to seneca@0.6.0.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 hawk@1.0.0 sntp@0.2.4 hoek@0.9.1
    Remediation: Upgrade to seneca@0.6.0.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 hawk@1.0.0 cryptiles@0.2.2 boom@0.4.2 hoek@0.9.1
    Remediation: Upgrade to seneca@0.6.0.

Overview

hoek is a Utility methods for the hapi ecosystem.

Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.

PoC by Olivier Arteau (HoLyVieR)

var Hoek = require('hoek');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';

var a = {};
console.log("Before : " + a.oops);
Hoek.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);

Details

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 hoek to version 4.2.1, 5.0.3 or higher.

References

medium severity

Prototype Pollution

  • Vulnerable module: lodash
  • Introduced through: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 fivebeans@1.1.1 lodash@2.4.2

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: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 fivebeans@1.1.1 lodash@2.4.2

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

Remote Memory Exposure

  • Vulnerable module: request
  • Introduced through: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0
    Remediation: Upgrade to seneca@0.6.0.

Overview

request is a simplified http request client.

Affected versions of this package are vulnerable to Remote Memory Exposure. A potential remote memory exposure vulnerability exists in request. If a request uses a multipart attachment and the body type option is number with value X, then X bytes of uninitialized memory will be sent in the body of the request.

Note that while the impact of this vulnerability is high (memory exposure), exploiting it is likely difficult, as the attacker needs to somehow control the body type of the request. One potential exploit scenario is when a request is composed based on JSON input, including the body type, allowing a malicious JSON to trigger the memory leak.

Details

Constructing a Buffer class with integer N creates a Buffer of length N with non zero-ed out memory. Example:

var x = new Buffer(100); // uninitialized Buffer of length 100
// vs
var x = new Buffer('100'); // initialized Buffer with value of '100'

Initializing a multipart body in such manner will cause uninitialized memory to be sent in the body of the request.

Proof of concept

var http = require('http')
var request = require('request')

http.createServer(function (req, res) {
  var data = ''
  req.setEncoding('utf8')
  req.on('data', function (chunk) {
    console.log('data')
    data += chunk
  })
  req.on('end', function () {
    // this will print uninitialized memory from the client
    console.log('Client sent:\n', data)
  })
  res.end()
}).listen(8000)

request({
  method: 'POST',
  uri: 'http://localhost:8000',
  multipart: [{ body: 1000 }]
},
function (err, res, body) {
  if (err) return console.error('upload failed:', err)
  console.log('sent')
})

Remediation

Upgrade request to version 2.68.0 or higher.

References

medium severity

Root Path Disclosure

  • Vulnerable module: send
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 serve-static@1.1.0 send@0.3.0
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 serve-static@1.1.0 send@0.3.0
    Remediation: Upgrade to seneca@3.0.0.

Overview

Send is a library for streaming files from the file system as an http response. It supports partial responses (Ranges), conditional-GET negotiation, high test coverage, and granular events which may be leveraged to take appropriate actions in your application or framework.

Affected versions of this package are vulnerable to a Root Path Disclosure.

Remediation

Upgrade send to version 0.11.1 or higher. If a direct dependency update is not possible, use snyk wizard to patch this vulnerability.

References

medium severity

Timing Attack

  • Vulnerable module: http-signature
  • Introduced through: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 http-signature@0.10.1
    Remediation: Upgrade to seneca@0.6.0.

Overview

http-signature is a reference implementation of Joyent's HTTP Signature scheme.

Affected versions of the package are vulnerable to Timing Attacks due to time-variable comparison of signatures.

The library implemented a character to character comparison, similar to the built-in string comparison mechanism, ===, and not a time constant string comparison. As a result, the comparison will fail faster when the first characters in the signature are incorrect. An attacker can use this difference to perform a timing attack, essentially allowing them to guess the signature one character at a time.

You can read more about timing attacks in Node.js on the Snyk blog.

Remediation

Upgrade http-signature to version 1.0.0 or higher.

References

medium severity

Uninitialized Memory Exposure

  • Vulnerable module: tunnel-agent
  • Introduced through: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 tunnel-agent@0.3.0
    Remediation: Upgrade to seneca@0.6.0.

Overview

tunnel-agent is HTTP proxy tunneling agent. Affected versions of the package are vulnerable to Uninitialized Memory Exposure.

A possible memory disclosure vulnerability exists when a value of type number is used to set the proxy.auth option of a request request and results in a possible uninitialized memory exposures in the request body.

This is a result of unobstructed use of the Buffer constructor, whose insecure default constructor increases the odds of memory leakage.

Details

Constructing a Buffer class with integer N creates a Buffer of length N with raw (not "zero-ed") memory.

In the following example, the first call would allocate 100 bytes of memory, while the second example will allocate the memory needed for the string "100":

// uninitialized Buffer of length 100
x = new Buffer(100);
// initialized Buffer with value of '100'
x = new Buffer('100');

tunnel-agent's request construction uses the default Buffer constructor as-is, making it easy to append uninitialized memory to an existing list. If the value of the buffer list is exposed to users, it may expose raw server side memory, potentially holding secrets, private data and code. This is a similar vulnerability to the infamous Heartbleed flaw in OpenSSL.

Proof of concept by ChALkeR

require('request')({
  method: 'GET',
  uri: 'http://www.example.com',
  tunnel: true,
  proxy:{
      protocol: 'http:',
      host:"127.0.0.1",
      port:8080,
      auth:80
  }
});

You can read more about the insecure Buffer behavior on our blog.

Similar vulnerabilities were discovered in request, mongoose, ws and sequelize.

Remediation

Upgrade tunnel-agent to version 0.6.0 or higher. Note This is vulnerable only for Node <=4

References

low severity

Information Exposure

  • Vulnerable module: seneca
  • Introduced through: seneca@0.5.17

Detailed paths

  • Introduced through: seneca@0.5.17
    Remediation: Upgrade to seneca@3.9.0.

Overview

seneca is a Node.js toolkit for Microservice architectures.

Affected versions of this package are vulnerable to Information Exposure. When a process using Seneca crashes, it prints out all of its environment variables.

Remediation

Upgrade seneca to version 3.9.0 or higher.

References

low severity

Open Redirect

  • Vulnerable module: serve-static
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 serve-static@1.1.0
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 serve-static@1.1.0
    Remediation: Upgrade to seneca@3.0.0.

Overview

When using serve-static middleware version < 1.7.2 and it's configured to mount at the root, it creates an open redirect on the site.

Source: Node Security Project

Details

For example:

If a user visits http://example.com//www.google.com/%2e%2e they will be redirected to //www.google.com/%2e%2e, which some browsers interpret as http://www.google.com/%2e%2e.

Remediation

  • Update to version 1.7.2 or greater (or 1.6.5 if sticking to the 1.6.x line).
  • Disable redirects if not using the feature with 'redirect: false' option and cannot upgrade.

References

low severity

Regular Expression Denial of Service (DoS)

  • Vulnerable module: hawk
  • Introduced through: seneca-transport@0.1.2

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 hawk@1.0.0
    Remediation: Upgrade to seneca@0.6.0.

Overview

hawk is an HTTP authentication scheme using a message authentication code (MAC) algorithm to provide partial HTTP request cryptographic verification.

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

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

You can read more about Regular Expression Denial of Service (ReDoS) on our blog.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: mime
  • Introduced through: seneca-transport@0.1.2 and seneca-web@0.1.4

Detailed paths

  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 mime@1.2.11
    Remediation: Upgrade to seneca@0.6.0.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 request@2.34.0 form-data@0.1.4 mime@1.2.11
    Remediation: Upgrade to seneca@0.6.0.
  • Introduced through: seneca@0.5.17 seneca-transport@0.1.2 connect@2.14.5 serve-static@1.1.0 send@0.3.0 mime@1.2.11
    Remediation: Upgrade to seneca-transport@0.8.0.
  • Introduced through: seneca@0.5.17 seneca-web@0.1.4 connect@2.14.5 serve-static@1.1.0 send@0.3.0 mime@1.2.11
    Remediation: Upgrade to seneca@3.0.0.

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 versions 1.4.1, 2.0.3 or higher.

References