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Underscore has unlimited recursion in _.flatten and _.isEqual, potential for DoS attack

High severity GitHub Reviewed Published Mar 3, 2026 in jashkenas/underscore • Updated May 5, 2026

Package

npm underscore (npm)

Affected versions

<= 1.13.7

Patched versions

1.13.8

Description

Impact

In simple words, some programs that use _.flatten or _.isEqual could be made to crash. Someone who wants to do harm may be able to do this on purpose. This can only be done if the program has special properties. It only works in Underscore versions up to 1.13.7. A more detailed explanation follows.

In affected versions of Underscore, the _.flatten and _.isEqual functions use recursion without a depth limit. Under very specific conditions, detailed below, an attacker could exploit this in a Denial of Service (DoS) attack by triggering a stack overflow.

A proof of concept (PoC) for this type of attack with _.isEqual:

const _ = require('underscore');

// build JSON string for nested object ~4500 levels deep
// (for this to be an attack, the JSON would have to come from
// a request or other untrusted input)
let json = '';
for (let i = 0; i < 4500; i++) json += '{"n":';
json += '"x"';
for (let i = 0; i < 4500; i++) json += '}';

// construct two distinct objects with equal shape from the above JSON
const a = JSON.parse(json);
const b = JSON.parse(json);

_.isEqual(a, b); // RangeError: Maximum call stack size exceeded

A proof of concept (PoC) for this type of attack with _.flatten:

const _ = require('underscore');

// build nested array ~4500 levels deep
// (like with _.isEqual, this nested array would have to be sourced
// from an untrusted external source for it to be an attack)
let nested = [];
for (let i = 0; i < 4500; i++) nested = [nested];

_.flatten(nested); // RangeError: Maximum call stack size exceeded

An application that crashes because of this can be restarted, so the bug is most relevant to applications for which continued operation is important, such as server applications. Furthermore, an application is only vulnerable to this type of attack if ALL of the following conditions are met:

  • Untrusted input must be used to create a recursive datastructure, for example using JSON.parse, with no enforced depth limit.
  • The datastructure thus created must be passed to _.flatten or _.isEqual.
  • In the case of _.flatten, the vulnerability can only be exploited if it is possible for a remote client to prepare a datastructure that consists of arrays at all levels AND if no finite depth limit is passed as the second argument to _.flatten.
  • In the case of _.isEqual, the vulnerability can only be exploited if there exists a code path in which two distinct datastructures that were submitted by the same remote client are compared using _.isEqual. For example, if a client submits data that are stored in a database, and the same client can later submit another datastructure that is then compared to the data that were saved in the database previously, OR if a client submits a single request, but its data are parsed twice, creating two non-identical but equivalent datastructures that are then compared.
  • Exceptions originating from the call to _.flatten or _.isEqual, as a result of a stack overflow, are not being caught.

All versions of Underscore up to and including 1.13.7 are affected by this weakness.

Patches

The problem has been patched in version 1.13.8. Upgrading to 1.13.8 or later completely prevents exploitation.

Note: historically, there have been breaking changes in minor releases of Underscore, especially between versions 1.6 and 1.9. However, upgrading from version 1.9 or later to any later 1.x version should be feasible with little or no effort for all users.

Workarounds

A workaround that works for both functions is to enforce a depth limit on the datastructure that is created from untrusted input. A limit of 1000 levels should prevent attacks from being successful on most systems. In systems with highly constrained hardware, we recommend lower limits, for example 100 levels.

Another possible workaround that only works for _.flatten, is to pass a second argument that limits the flattening depth to 1000 or less.

References

References

@jashkenas jashkenas published to jashkenas/underscore Mar 3, 2026
Published to the GitHub Advisory Database Mar 3, 2026
Reviewed Mar 3, 2026
Published by the National Vulnerability Database Mar 3, 2026
Last updated May 5, 2026

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

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(6th percentile)

Weaknesses

Uncontrolled Recursion

The product does not properly control the amount of recursion that takes place, consuming excessive resources, such as allocated memory or the program stack. Learn more on MITRE.

Allocation of Resources Without Limits or Throttling

The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated. Learn more on MITRE.

CVE ID

CVE-2026-27601

GHSA ID

GHSA-qpx9-hpmf-5gmw

Source code

Credits

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