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path-to-regexp outputs backtracking regular expressions

High severity GitHub Reviewed Published Sep 9, 2024 in pillarjs/path-to-regexp • Updated Sep 12, 2024

Package

npm path-to-regexp (npm)

Affected versions

< 0.1.10
>= 0.2.0, < 1.9.0
>= 2.0.0, < 3.3.0
>= 7.0.0, < 8.0.0
>= 4.0.0, < 6.3.0

Patched versions

0.1.10
1.9.0
3.3.0
8.0.0
6.3.0

Description

Impact

A bad regular expression is generated any time you have two parameters within a single segment, separated by something that is not a period (.). For example, /:a-:b.

Patches

For users of 0.1, upgrade to 0.1.10. All other users should upgrade to 8.0.0.

These versions add backtrack protection when a custom regex pattern is not provided:

They do not protect against vulnerable user supplied capture groups. Protecting against explicit user patterns is out of scope for old versions and not considered a vulnerability.

Version 7.1.0 can enable strict: true and get an error when the regular expression might be bad.

Version 8.0.0 removes the features that can cause a ReDoS.

Workarounds

All versions can be patched by providing a custom regular expression for parameters after the first in a single segment. As long as the custom regular expression does not match the text before the parameter, you will be safe. For example, change /:a-:b to /:a-:b([^-/]+).

If paths cannot be rewritten and versions cannot be upgraded, another alternative is to limit the URL length. For example, halving the attack string improves performance by 4x faster.

Details

Using /:a-:b will produce the regular expression /^\/([^\/]+?)-([^\/]+?)\/?$/. This can be exploited by a path such as /a${'-a'.repeat(8_000)}/a. OWASP has a good example of why this occurs, but the TL;DR is the /a at the end ensures this route would never match but due to naive backtracking it will still attempt every combination of the :a-:b on the repeated 8,000 -a.

Because JavaScript is single threaded and regex matching runs on the main thread, poor performance will block the event loop and can lead to a DoS. In local benchmarks, exploiting the unsafe regex will result in performance that is over 1000x worse than the safe regex. In a more realistic environment using Express v4 and 10 concurrent connections, this translated to average latency of ~600ms vs 1ms.

References

References

@blakeembrey blakeembrey published to pillarjs/path-to-regexp Sep 9, 2024
Published by the National Vulnerability Database Sep 9, 2024
Published to the GitHub Advisory Database Sep 9, 2024
Reviewed Sep 9, 2024
Last updated Sep 12, 2024

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:P

EPSS score

0.045%
(17th percentile)

Weaknesses

CVE ID

CVE-2024-45296

GHSA ID

GHSA-9wv6-86v2-598j

Source code

Credits

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