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Regular Expression Denial of Service (ReDoS) via `$regex` query in LiveQuery

High
mtrezza published GHSA-mf3j-86qx-cq5j Mar 7, 2026

Package

npm parse-server (npm)

Affected versions

>= 9.0.0 < 9.5.0-alpha.14
< 8.6.11

Patched versions

9.5.0-alpha.14
8.6.11

Description

Impact

A malicious client can subscribe to a LiveQuery with a crafted $regex pattern that causes catastrophic backtracking, blocking the Node.js event loop. This makes the entire Parse Server unresponsive, affecting all clients. Any Parse Server deployment with LiveQuery enabled is affected. The attacker only needs the application ID and JavaScript key, both of which are public in client-side apps.

This only affects LiveQuery subscription matching, which evaluates regex in JavaScript on the Node.js event loop. Normal REST and GraphQL queries are not affected because their regex is evaluated by the database engine.

Patches

Regex evaluation in LiveQuery subscription matching now runs in an isolated VM context with a configurable timeout via a new Parse Server option `liveQuery.regexTimeout, with defaults 100 ms. A regex that exceeds the timeout is treated as non-matching.

The protection adds approximately 50 microseconds of overhead per regex evaluation. For most applications this is negligible, but it can add up if there is a very large number of LiveQuery subscriptions that use $regex on the same class. For example, 10,000 concurrent regex subscriptions would add approximately 500ms of processing time per object save event on that class. Set liveQuery.regexTimeout: 0 to disable the protection and use native regex evaluation without overhead.

Workarounds

Use the beforeSubscribe Cloud Code hook to reject any LiveQuery subscription that contains a $regex operator. Note that this also blocks the LiveQuery startsWith, endsWith, and contains query methods, as they use $regex internally.

// Repeat for each class that is used with LiveQuery
Parse.Cloud.beforeSubscribe('MyClass', request => {
  const where = request.query._where || {};
  for (const value of Object.values(where)) {
    if (value?.$regex) {
      throw new Parse.Error(Parse.Error.OPERATION_FORBIDDEN, '$regex not allowed in LiveQuery subscriptions');
    }
  }
});

References

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 Present
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:P/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

CVE ID

CVE-2026-30925

Weaknesses

Inefficient Regular Expression Complexity

The product uses a regular expression with an inefficient, possibly exponential worst-case computational complexity that consumes excessive CPU cycles. Learn more on MITRE.

Credits