@tradle/transport@1.0.0

Vulnerabilities

11 via 27 paths

Dependencies

221

Source

npm

Find, fix and prevent vulnerabilities in your code.

Severity
  • 6
  • 3
  • 2
Status
  • 11
  • 0
  • 0

high severity

Remote Memory Exposure

  • Vulnerable module: bl
  • Introduced through: zlorp@2.0.1

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 zlorp@2.0.1 levelup@0.18.6 bl@0.8.2

Overview

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

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

PoC by chalker

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

Remediation

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

References

high severity

Denial of Service (DoS)

  • Vulnerable module: engine.io
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 engine.io@1.8.5
    Remediation: Upgrade to socket.io@3.0.0.

Overview

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

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

Details

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

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

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

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

Two common types of DoS vulnerabilities:

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

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

Remediation

Upgrade engine.io to version 4.0.0 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: parsejson
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-client@1.7.4 engine.io-client@1.8.5 parsejson@0.0.3

Overview

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

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

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

There is no fixed version for parsejson.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: socket.io-parser
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-parser@2.3.1
    Remediation: Upgrade to socket.io@2.2.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-adapter@0.5.0 socket.io-parser@2.3.1
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-client@1.7.4 socket.io-parser@2.3.1
    Remediation: Upgrade to socket.io@2.2.0.

Overview

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

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

Details

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

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

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

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

Two common types of DoS vulnerabilities:

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

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

Remediation

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

References

high severity
new

Access Restriction Bypass

  • Vulnerable module: xmlhttprequest-ssl
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-client@1.7.4 engine.io-client@1.8.5 xmlhttprequest-ssl@1.5.3
    Remediation: Upgrade to socket.io@2.4.0.

Overview

xmlhttprequest-ssl is a fork of xmlhttprequest.

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

PoC

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

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

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

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

xhr.send();

Remediation

Upgrade xmlhttprequest-ssl to version 1.6.1 or higher.

References

high severity

Arbitrary Code Injection

  • Vulnerable module: xmlhttprequest-ssl
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-client@1.7.4 engine.io-client@1.8.5 xmlhttprequest-ssl@1.5.3
    Remediation: Upgrade to socket.io@2.4.0.

Overview

xmlhttprequest-ssl is a fork of xmlhttprequest.

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

POC

const { XMLHttpRequest } = require("xmlhttprequest")

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

Remediation

Upgrade xmlhttprequest-ssl to version 1.6.2 or higher.

References

medium severity

Uninitialized Memory Exposure

  • Vulnerable module: bl
  • Introduced through: zlorp@2.0.1

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 zlorp@2.0.1 levelup@0.18.6 bl@0.8.2

Overview

bl is a storage object for collections of Node Buffers.

A possible memory disclosure vulnerability exists when a value of type number is provided to the append() method and results in concatenation of uninitialized memory to the buffer collection.

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');

bl's append function 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.

const BufferList = require('bl')

var bl = new BufferList()
bl.append(new Buffer('abcd'))
bl.append(new Buffer('efg'))
bl.append('100')
// appends a Buffer holding 100 bytes of uninitialized memory
bl.append(100)                     
bl.append(new Buffer('j'))

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

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

Note This is vulnerable only for Node <=4

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: semver
  • Introduced through: zlorp@2.0.1

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 zlorp@2.0.1 levelup@0.18.6 semver@2.3.2
    Remediation: Open PR to patch semver@2.3.2.

Overview

semver is a semantic version parser used by npm.

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

Overview

npm is a package manager for javascript.

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

Details

<>

Remediation

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

References

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade semver to version 4.3.2 or higher.

References

medium severity

Insecure Defaults

  • Vulnerable module: socket.io
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4
    Remediation: Upgrade to socket.io@2.4.0.

Overview

socket.io is a node.js realtime framework server.

Affected versions of this package are vulnerable to Insecure Defaults due to CORS Misconfiguration. All domains are whitelisted by default.

Remediation

Upgrade socket.io to version 2.4.0 or higher.

References

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: debug
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 debug@2.3.3
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 engine.io@1.8.5 debug@2.3.3
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-adapter@0.5.0 debug@2.3.3
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-client@1.7.4 debug@2.3.3
    Remediation: Upgrade to socket.io@2.0.2.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-client@1.7.4 engine.io-client@1.8.5 debug@2.3.3
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-parser@2.3.1 debug@2.2.0
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-adapter@0.5.0 socket.io-parser@2.3.1 debug@2.2.0
    Remediation: Open PR to patch debug@2.2.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-client@1.7.4 socket.io-parser@2.3.1 debug@2.2.0
    Remediation: Upgrade to socket.io@2.0.0.

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

low severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: ms
  • Introduced through: socket.io@1.7.4

Detailed paths

  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 engine.io@1.8.5 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-adapter@0.5.0 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-client@1.7.4 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to socket.io@2.0.2.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-client@1.7.4 engine.io-client@1.8.5 debug@2.3.3 ms@0.7.2
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-parser@2.3.1 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to socket.io@2.0.0.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-adapter@0.5.0 socket.io-parser@2.3.1 debug@2.2.0 ms@0.7.1
    Remediation: Open PR to patch ms@0.7.1.
  • Introduced through: @tradle/transport@1.0.0 socket.io@1.7.4 socket.io-client@1.7.4 socket.io-parser@2.3.1 debug@2.2.0 ms@0.7.1
    Remediation: Upgrade to socket.io@2.0.0.

Overview

ms is a tiny millisecond conversion utility.

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

Proof of concept

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

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

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

Disclosure Timeline

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

Details

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

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

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

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

This regular expression accomplishes the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

Remediation

Upgrade ms to version 2.0.0 or higher.

References