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go-git's improper parsing of specially crafted objects may lead to inconsistent interpretation compared to upstream Git

High severity GitHub Reviewed Published May 6, 2026 in go-git/go-git • Updated Jun 8, 2026

Package

gomod github.com/go-git/go-git/v5 (Go)

Affected versions

< 5.19.0

Patched versions

5.19.0
gomod github.com/go-git/go-git/v6 (Go)
>= 6.0.0-alpha.1, <= 6.0.0-alpha.2
6.0.0-alpha.3

Description

Impact

go-git may parse malformed Git objects in a way that differs from upstream Git. When commit or tag objects contain ambiguous or malformed headers, go-git’s decoded representation may expose values differently from how Git itself would interpret or reject the same object.

Additionally, go-git’s commit signing and verification logic operates over commit data reconstructed from go-git’s parsed representation rather than the original raw object bytes. As a result, go-git may sign or verify a commit payload that is not byte-for-byte equivalent to the object stored in the repository.

This can cause a signature to appear valid for a commit whose displayed or effective metadata differs from the object that was intended to be signed.

Patches

Users should upgrade to a patched version in order to mitigate this vulnerability. Versions prior to v5 are likely to be affected, users are recommended to upgrade to a supported go-git version.

Credit

Thanks to @bugbunny-research (https://bugbunny.ai/) for reporting this to sigstore/gitsign, and to @wlynch, @patzielinski and @adityasaky for coordinating the disclosure with the go-git project. 🙇 🥇

Thanks to @wayphinder for reporting this to the go-git project. 🙇

References

@pjbgf pjbgf published to go-git/go-git May 6, 2026
Published to the GitHub Advisory Database May 11, 2026
Reviewed May 11, 2026
Published by the National Vulnerability Database May 27, 2026
Last updated Jun 8, 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 High
Attack Requirements None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity High
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity High
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:H/AT:N/PR:L/UI:N/VC:N/VI:H/VA:N/SC:N/SI:H/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.
(0th percentile)

Weaknesses

Incorrect Behavior Order: Validate Before Canonicalize

The product validates input before it is canonicalized, which prevents the product from detecting data that becomes invalid after the canonicalization step. Learn more on MITRE.

Insufficient Verification of Data Authenticity

The product does not sufficiently verify the origin or authenticity of data, in a way that causes it to accept invalid data. Learn more on MITRE.

CVE ID

CVE-2026-45022

GHSA ID

GHSA-389r-gv7p-r3rp

Source code

Credits

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