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js-toml Prototype Pollution Vulnerability

High severity GitHub Reviewed Published Aug 3, 2025 in sunnyadn/js-toml • Updated Aug 5, 2025

Package

npm js-toml (npm)

Affected versions

< 1.0.2

Patched versions

1.0.2

Description

A prototype pollution vulnerability in js-toml allows a remote attacker to add or modify properties of the global Object.prototype by parsing a maliciously crafted TOML input.

Impact

The js-toml library is vulnerable to Prototype Pollution. When parsing a TOML string containing the specially crafted key __proto__, an attacker can add or modify properties on the global Object.prototype.

While the js-toml library itself does not contain known vulnerable "gadgets", this can lead to severe security vulnerabilities in applications that use the library. For example, if the consuming application checks for the existence of a property for authorization purposes (e.g., user.isAdmin), this vulnerability could be escalated to an authentication bypass. Other potential impacts in the application include Denial of Service (DoS) or, in some cases, Remote Code Execution (RCE), depending on the application's logic and dependencies.

Any application that uses an affected version of js-toml to parse untrusted input is vulnerable. The severity of the impact, ranging from unexpected behavior to a full security compromise, is dependent on the application's specific code and its handling of object properties.

Patches

This vulnerability has been patched in version 1.0.2.

All users are advised to upgrade to version 1.0.2 or later to mitigate this issue. Users of all prior versions are affected.

Workarounds

If you are unable to upgrade to a patched version, the only mitigation is to ensure that any TOML input being passed to the js-toml library is from a fully trusted source and has been validated to not contain malicious keys.

References

  • This vulnerability was discovered and responsibly disclosed by siunam.

References

@sunnyadn sunnyadn published to sunnyadn/js-toml Aug 3, 2025
Published to the GitHub Advisory Database Aug 4, 2025
Reviewed Aug 4, 2025
Published by the National Vulnerability Database Aug 5, 2025
Last updated Aug 5, 2025

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 None
Subsequent System Impact Metrics
Confidentiality High
Integrity High
Availability High

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:N/SC:H/SI:H/SA:H

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.
(51st percentile)

Weaknesses

Improperly Controlled Modification of Object Prototype Attributes ('Prototype Pollution')

The product receives input from an upstream component that specifies attributes that are to be initialized or updated in an object, but it does not properly control modifications of attributes of the object prototype. Learn more on MITRE.

CVE ID

CVE-2025-54803

GHSA ID

GHSA-65fc-cr5f-v7r2

Source code

Credits

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