Last tested: 24 Jun, 2018

sinopia vulnerabilities

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sinopia (latest)

Published 17 Mar, 2018

Known vulnerabilities5
Vulnerable paths6
Dependencies231

Regular Expression Denial of Service (DoS)

medium severity

Detailed paths

  • Introduced through: sinopia@1.4.0 > handlebars@2.0.0 > uglify-js@2.3.6

Overview

The parse() function in the uglify-js package prior to version 2.6.0 is vulnerable to regular expression denial of service (ReDoS) attacks when long inputs of certain patterns are processed.

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade to version 2.6.0 or greater. If a direct dependency update is not possible, use snyk wizard to patch this vulnerability.

References

Cross-site Scripting (XSS)

medium severity

Detailed paths

  • Introduced through: sinopia@1.4.0 > handlebars@2.0.0

Overview

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

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

Details

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

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

There are a few types of XSS:

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

Example:

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

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

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

References

Regular Expression Denial of Service (DoS)

high severity

Detailed paths

  • Introduced through: sinopia@1.4.0 > minimatch@1.0.0

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

Regular Expression Denial of Service (ReDoS)

low severity

Detailed paths

  • Introduced through: sinopia@1.4.0 > express@5.0.0-alpha.6 > send@0.15.6 > mime@1.3.4
  • Introduced through: sinopia@1.4.0 > express@5.0.0-alpha.6 > serve-static@1.12.6 > send@0.15.6 > mime@1.3.4

Overview

mime is a comprehensive, compact MIME type module.

Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS). It uses regex the following regex /.*[\.\/\\]/ in its lookup, which can cause a slowdown of 2 seconds for 50k characters.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Many Regular Expression implementations may reach extreme situations that cause 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.

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

Improper minification of non-boolean comparisons

high severity

Detailed paths

  • Introduced through: sinopia@1.4.0 > handlebars@2.0.0 > uglify-js@2.3.6

Overview

uglify-js is a JavaScript parser, minifier, compressor and beautifier toolkit.

Tom MacWright discovered that UglifyJS versions 2.4.23 and earlier are affected by a vulnerability which allows a specially crafted Javascript file to have altered functionality after minification. This bug was demonstrated by Yan to allow potentially malicious code to be hidden within secure code, activated by minification.

Details

In Boolean algebra, DeMorgan's laws describe the relationships between conjunctions (&&), disjunctions (||) and negations (!). In Javascript form, they state that:

 !(a && b) === (!a) || (!b)
 !(a || b) === (!a) && (!b)

The law does not hold true when one of the values is not a boolean however.

Vulnerable versions of UglifyJS do not account for this restriction, and erroneously apply the laws to a statement if it can be reduced in length by it.

Consider this authentication function:

function isTokenValid(user) {
    var timeLeft =
        !!config && // config object exists
        !!user.token && // user object has a token
        !user.token.invalidated && // token is not explicitly invalidated
        !config.uninitialized && // config is initialized
        !config.ignoreTimestamps && // don't ignore timestamps
        getTimeLeft(user.token.expiry); // > 0 if expiration is in the future

    // The token must not be expired
    return timeLeft > 0;
}

function getTimeLeft(expiry) {
  return expiry - getSystemTime();
}

When minified with a vulnerable version of UglifyJS, it will produce the following insecure output, where a token will never expire:

( Formatted for readability )

function isTokenValid(user) {
    var timeLeft = !(                       // negation
        !config                             // config object does not exist
        || !user.token                      // user object does not have a token
        || user.token.invalidated           // token is explicitly invalidated
        || config.uninitialized             // config isn't initialized
        || config.ignoreTimestamps          // ignore timestamps
        || !getTimeLeft(user.token.expiry)  // > 0 if expiration is in the future
    );
    return timeLeft > 0
}

function getTimeLeft(expiry) {
    return expiry - getSystemTime()
}

Remediation

Upgrade UglifyJS to version 2.4.24 or higher.

References

Vulnerable versions of sinopia

Fixed in 1.0.0

Uninitialized Memory Exposure

high severity

Detailed paths

  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > express-session@1.11.3 > uid-safe@2.0.0 > base64-url@1.2.1

Overview

base64-url Base64 encode, decode, escape and unescape for URL applications.

Affected versions of this package are vulnerable to Uninitialized Memory Exposure. An attacker may extract sensitive data from uninitialized memory or may cause a DoS by passing in a large number, in setups where typed user input can be passed (e.g. from JSON).

Details

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

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

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

Remediation

Upgrade base64-url to version 2.0.0 or higher. Note This is vulnerable only for Node <=4

References

Regular Expression Denial of Service (DoS)

high severity

Detailed paths

  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > compression@1.5.2 > accepts@1.2.13 > negotiator@0.5.3
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > serve-index@1.7.3 > accepts@1.2.13 > negotiator@0.5.3

Overview

negotiator is an HTTP content negotiator for Node.js. Versions prior to 0.6.1 are vulnerable to Regular expression Denial of Service (ReDoS) attack when parsing "Accept-Language" http header.

An attacker can provide a long value in the Accept-Language header, which nearly matches the pattern being matched. This will cause the regular expression matching to take a long time, all the while occupying the thread and preventing it from processing other requests. By repeatedly sending multiple such requests, the attacker can make the server unavailable (a Denial of Service attack).

Details

The Regular expression Denial of Service (ReDoS) is a Denial of Service attack, that exploits the fact that most Regular Expression implementations may reach extreme situations that cause them to work very slowly (exponentially related to input size). An attacker can then cause a program using a Regular Expression to enter these extreme situations and then hang for a very long time. [1]

Remediation

Upgrade negotiator to version 0.6.1 or greater.

References

Regular Expression Denial of Service (ReDoS)

low severity

Detailed paths

  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > debug@2.1.0
  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > engine.io@1.5.4 > debug@1.0.3
  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > socket.io-parser@2.2.4 > debug@0.7.4
  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > socket.io-client@1.3.7 > socket.io-parser@2.2.4 > debug@0.7.4
  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > socket.io-client@1.3.7 > debug@0.7.4
  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > socket.io-adapter@0.3.1 > socket.io-parser@2.2.2 > debug@0.7.4
  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > socket.io-adapter@0.3.1 > debug@1.0.2
  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > socket.io-client@1.3.7 > engine.io-client@1.5.4 > debug@1.0.4
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > debug@2.2.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > body-parser@1.13.3 > debug@2.2.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > connect-timeout@1.6.2 > debug@2.2.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > compression@1.5.2 > debug@2.2.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > debug@2.2.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > express-session@1.11.3 > debug@2.2.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > finalhandler@0.4.0 > debug@2.2.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > send@0.13.0 > debug@2.2.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > morgan@1.6.1 > debug@2.2.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > serve-index@1.7.3 > debug@2.2.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > serve-static@1.10.3 > send@0.13.2 > 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 (ReDoS)

low severity

Detailed paths

  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > debug@2.1.0 > ms@0.6.2
  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > engine.io@1.5.4 > debug@1.0.3 > ms@0.6.2
  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > socket.io-client@1.3.7 > engine.io-client@1.5.4 > debug@1.0.4 > ms@0.6.2
  • Introduced through: karma@0.13.2 > socket.io@1.3.7 > socket.io-adapter@0.3.1 > debug@1.0.2 > ms@0.6.2
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > body-parser@1.13.3 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > connect-timeout@1.6.2 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > compression@1.5.2 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > express-session@1.11.3 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > finalhandler@0.4.0 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > send@0.13.0 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > morgan@1.6.1 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > serve-index@1.7.3 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > serve-static@1.10.3 > send@0.13.2 > debug@2.2.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > connect-timeout@1.6.2 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > send@0.13.0 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > serve-static@1.10.3 > send@0.13.2 > ms@0.7.1
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > serve-favicon@2.3.2 > ms@0.7.2

Overview

ms is a tiny millisecond conversion utility.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an incomplete fix for previously reported vulnerability npm:ms:20151024. The fix limited the length of accepted input string to 10,000 characters, and turned to be insufficient making it possible to block the event loop for 0.3 seconds (on a typical laptop) with a specially crafted string passed to ms() function.

Proof of concept

ms = require('ms');
ms('1'.repeat(9998) + 'Q') // Takes about ~0.3s

Note: Snyk's patch for this vulnerability limits input length to 100 characters. This new limit was deemed to be a breaking change by the author. Based on user feedback, we believe the risk of breakage is very low, while the value to your security is much greater, and therefore opted to still capture this change in a patch for earlier versions as well. Whenever patching security issues, we always suggest to run tests on your code to validate that nothing has been broken.

For more information on Regular Expression Denial of Service (ReDoS) attacks, go to our blog.

Disclosure Timeline

  • Feb 9th, 2017 - Reported the issue to package owner.
  • Feb 11th, 2017 - Issue acknowledged by package owner.
  • April 12th, 2017 - Fix PR opened by Snyk Security Team.
  • May 15th, 2017 - Vulnerability published.
  • May 16th, 2017 - Issue fixed and version 2.0.0 released.
  • May 21th, 2017 - Patches released for versions >=0.7.1, <=1.0.0.

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade ms to version 2.0.0 or higher.

References

Regular Expression Denial of Service (ReDoS)

medium severity

Detailed paths

  • Introduced through: hapi@0.13.2 > semver@1.1.0
  • Introduced through: sinopia@0.13.2 > semver@3.0.1

Overview

npm is a package manager for javascript.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The semver module uses regular expressions when parsing a version string. For a carefully crafted input, the time it takes to process these regular expressions is not linear to the length of the input. Since the semver module did not enforce a limit on the version string length, an attacker could provide a long string that would take up a large amount of resources, potentially taking a server down. This issue therefore enables a potential Denial of Service attack. This is a slightly differnt variant of a typical Regular Expression Denial of Service (ReDoS) vulnerability.

Details

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

Update to a version 4.3.2 or greater. From the issue description [2]: "Package version can no longer be more than 256 characters long. This prevents a situation in which parsing the version number can use exponentially more time and memory to parse, leading to a potential denial of service."

References

Regular Expression Denial of Service (ReDoS)

high severity

Detailed paths

  • Introduced through: sinopia@0.13.2 > express@3.21.2 > fresh@0.3.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > fresh@0.3.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > send@0.13.0 > fresh@0.3.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > serve-favicon@2.3.2 > fresh@0.3.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > serve-static@1.10.3 > send@0.13.2 > fresh@0.3.0

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

Prototype Override Protection Bypass

high severity

Detailed paths

  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > body-parser@1.13.3 > qs@4.0.0
  • Introduced through: sinopia@0.13.2 > express@3.21.2 > connect@2.30.2 > qs@4.0.0

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

Fixed in 0.12.0

Symlink File Overwrite

high severity

Detailed paths

  • Introduced through: sinopia@0.11.3 > tar.gz@0.1.1 > tar@0.1.20

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