Last tested: 01 Aug, 2018

gulp-sass vulnerabilities

Gulp plugin for sass

View on npm

gulp-sass (latest)

Published 25 Apr, 2018

Known vulnerabilities2
Vulnerable paths5
Dependencies259

Prototype Pollution

low severity

Detailed paths

  • Introduced through: gulp-sass@4.0.1 > node-sass@4.9.2 > node-gyp@3.7.0 > request@2.81.0 > hawk@3.1.3 > hoek@2.16.3
  • Introduced through: gulp-sass@4.0.1 > node-sass@4.9.2 > node-gyp@3.7.0 > request@2.81.0 > hawk@3.1.3 > boom@2.10.1 > hoek@2.16.3
  • Introduced through: gulp-sass@4.0.1 > node-sass@4.9.2 > node-gyp@3.7.0 > request@2.81.0 > hawk@3.1.3 > cryptiles@2.0.5 > boom@2.10.1 > hoek@2.16.3
  • Introduced through: gulp-sass@4.0.1 > node-sass@4.9.2 > node-gyp@3.7.0 > request@2.81.0 > hawk@3.1.3 > sntp@1.0.9 > hoek@2.16.3

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);

Remediation

Upgrade hoek to versions 4.2.1, 5.0.3 or higher.

References

Insecure Randomness

medium severity

Detailed paths

  • Introduced through: gulp-sass@4.0.1 > node-sass@4.9.2 > node-gyp@3.7.0 > request@2.81.0 > hawk@3.1.3 > cryptiles@2.0.5

Overview

cryptiles is a package for general crypto utilities.

Affected versions of this package are vulnerable to Insecure Randomness. The randomDigits() method is supposed to return a cryptographically strong pseudo-random data string, but it was biased to certain digits. An attacker could be able to guess the created digits.

Remediation

Upgrade to version 4.1.2 and higher.

References

Vulnerable versions of gulp-sass

Fixed in 2.0.0

Command Injection

high severity

Detailed paths

  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > shelljs@0.3.0

Overview

shelljs is a portable Unix shell commands for Node.js.

Affected version of this package are vulnerable to Command Injection. It is possible to invoke commands from shell.exec() from external sources, allowing an attacker to inject arbitrary commands.

Remediation

There is no fix version for shelljs.

References

Uninitialized Memory Exposure

medium severity

Detailed paths

  • Introduced through: bower@1.3.3 > bower-registry-client@0.2.4 > request@2.51.0 > tunnel-agent@0.4.3
  • Introduced through: bower@1.3.3 > insight@0.3.1 > request@2.27.0 > tunnel-agent@0.3.0
  • Introduced through: bower@1.3.3 > request@2.34.0 > tunnel-agent@0.3.0
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > pangyp@2.3.3 > request@2.51.0 > tunnel-agent@0.4.3

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

Symlink File Overwrite

high severity

Detailed paths

  • Introduced through: bower@1.3.3 > tar@0.1.20
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > pangyp@2.3.3 > tar@1.0.3

Overview

The tar module prior to version 2.0.0 does not properly normalize symbolic links pointing to targets outside the extraction root. As a result, packages may hold symbolic links to parent and sibling directories and overwrite those files when the package is extracted.

Remediation

Upgrade to version 2.0.0 or greater. If a direct dependency update is not possible, use snyk wizard to patch this vulnerability.

References

Remote Memory Exposure

medium severity

Detailed paths

  • Introduced through: bower@1.3.3 > bower-registry-client@0.2.4 > request@2.51.0
  • Introduced through: bower@1.3.3 > insight@0.3.1 > request@2.27.0
  • Introduced through: bower@1.3.3 > request@2.34.0
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > pangyp@2.3.3 > request@2.51.0

Overview

request is a simplified http request client. 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.

If a direct dependency update is not possible, use snyk wizard to patch this vulnerability.

References

Regular Expression Denial of Service (ReDoS)

low severity

Detailed paths

  • Introduced through: socket.io@1.3.3 > debug@2.1.0
  • Introduced through: socket.io@1.3.3 > engine.io@1.5.1 > debug@1.0.3
  • Introduced through: socket.io@1.3.3 > socket.io-parser@2.2.3 > debug@0.7.4
  • Introduced through: socket.io@1.3.3 > socket.io-client@1.3.3 > socket.io-parser@2.2.3 > debug@0.7.4
  • Introduced through: socket.io@1.3.3 > socket.io-client@1.3.3 > debug@0.7.4
  • Introduced through: socket.io@1.3.3 > socket.io-adapter@0.3.1 > socket.io-parser@2.2.2 > debug@0.7.4
  • Introduced through: socket.io@1.3.3 > socket.io-adapter@0.3.1 > debug@1.0.2
  • Introduced through: socket.io@1.3.3 > socket.io-client@1.3.3 > engine.io-client@1.5.1 > debug@1.0.4
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > mocha@2.5.3 > debug@2.2.0

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

Regular Expression Denial of Service (DoS)

low severity

Detailed paths

  • Introduced through: bower@1.3.3 > bower-registry-client@0.2.4 > request@2.51.0 > hawk@1.1.1
  • Introduced through: bower@1.3.3 > insight@0.3.1 > request@2.27.0 > hawk@1.0.0
  • Introduced through: bower@1.3.3 > request@2.34.0 > hawk@1.0.0
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > pangyp@2.3.3 > request@2.51.0 > hawk@1.1.1

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

Regular Expression Denial of Service (DoS)

high severity

Detailed paths

  • Introduced through: bower@1.3.3 > fstream-ignore@0.0.10 > minimatch@0.3.0
  • Introduced through: bower@1.3.3 > glob@3.2.11 > minimatch@0.3.0
  • Introduced through: nodemon@1.3.3 > minimatch@0.3.0
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > gaze@0.5.2 > globule@0.1.0 > minimatch@0.2.14
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > gaze@0.5.2 > globule@0.1.0 > glob@3.1.21 > minimatch@0.2.14
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > mocha@2.5.3 > glob@3.2.11 > minimatch@0.3.0
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > sass-graph@1.3.0 > glob@4.5.3 > minimatch@2.0.10
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > pangyp@2.3.3 > glob@4.3.5 > minimatch@2.0.10
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > pangyp@2.3.3 > minimatch@2.0.10

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

Prototype Override Protection Bypass

high severity

Detailed paths

  • Introduced through: bower@1.3.3 > bower-registry-client@0.2.4 > request@2.51.0 > qs@2.3.3
  • Introduced through: bower@1.3.3 > insight@0.3.1 > request@2.27.0 > qs@0.6.6
  • Introduced through: bower@1.3.3 > request@2.34.0 > qs@0.6.6
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > pangyp@2.3.3 > request@2.51.0 > qs@2.3.3

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

Regular Expression Denial of Service (ReDoS)

low severity

Detailed paths

  • Introduced through: socket.io@1.3.3 > debug@2.1.0 > ms@0.6.2
  • Introduced through: socket.io@1.3.3 > engine.io@1.5.1 > debug@1.0.3 > ms@0.6.2
  • Introduced through: socket.io@1.3.3 > socket.io-client@1.3.3 > engine.io-client@1.5.1 > debug@1.0.4 > ms@0.6.2
  • Introduced through: socket.io@1.3.3 > socket.io-adapter@0.3.1 > debug@1.0.2 > ms@0.6.2
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > mocha@2.5.3 > debug@2.2.0 > ms@0.7.1

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

Arbitrary Code Injection

high severity

Detailed paths

  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > mocha@2.5.3 > growl@1.9.2

Overview

growl is a package adding Growl support for Nodejs.

Affected versions of the 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

Timing Attack

medium severity

Detailed paths

  • Introduced through: bower@1.3.3 > bower-registry-client@0.2.4 > request@2.51.0 > http-signature@0.10.1
  • Introduced through: bower@1.3.3 > insight@0.3.1 > request@2.27.0 > http-signature@0.10.1
  • Introduced through: bower@1.3.3 > request@2.34.0 > http-signature@0.10.1
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > pangyp@2.3.3 > request@2.51.0 > http-signature@0.10.1

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

Prototype Pollution

low severity

Detailed paths

  • Introduced through: bower@1.3.3 > inquirer@0.4.1 > lodash@2.4.2
  • Introduced through: bower@1.3.3 > insight@0.3.1 > inquirer@0.4.1 > lodash@2.4.2
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > gaze@0.5.2 > globule@0.1.0 > lodash@1.0.2
  • Introduced through: gulp-sass@1.3.3 > node-sass@2.1.1 > sass-graph@1.3.0 > lodash@2.4.2

Overview

lodash is a 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);

Remediation

Upgrade lodash to version 4.17.5 or higher.

References

Fixed in 1.2.0

Regular Expression Denial of Service (DoS)

medium severity

Detailed paths

  • Introduced through: socket.io@1.1.0 > engine.io@1.4.0 > debug@1.0.3 > ms@0.6.2
  • Introduced through: gulp-sass@1.1.0 > node-sass@0.9.6 > mocha@1.21.5 > debug@2.0.0 > ms@0.6.2

Overview

ms is a tiny milisecond conversion utility.

Affected versions of this package are vulnerable to a Regular expression Denial of Service (ReDoS) attack when converting a time period string (i.e. "2 days", "1h") into milliseconds integer. A malicious user could pas extremely long strings to ms(), causing the server take a long time to process, subsequently blocking the event loop for that extended period.

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 0.7.1.

If direct dependency upgrade is not possible, use snyk wizard to patch this vulnerability.

References