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go.uuid has Predictable UUID Identifiers

Critical severity GitHub Reviewed Published May 10, 2021 in apptainer/sif • Updated Sep 19, 2024

Package

gomod github.com/satori/go.uuid (Go)

Affected versions

>= 1.2.1-0.20180103161547-0ef6afb2f6cd, < 1.2.1-0.20180404165556-75cca531ea76

Patched versions

1.2.1-0.20180404165556-75cca531ea76

Description

CVE Description for go.uuid

A flaw was found in github.com/satori/go.uuid in versions from commit 0ef6afb2f6cdd6cdaeee3885a95099c63f18fc8c to d91630c8510268e75203009fe7daf2b8e1d60c45. Due to insecure randomness in the g.rand.Read function the generated UUIDs are predictable for an attacker.

Update on 19 September 2024 -- This vulnerability never existed in sif

The official NIST CVE-2021-3538 record says:

A flaw was found in github.com/satori/go.uuid in versions from commit 0ef6afb2f6cdd6cdaeee3885a95099c63f18fc8c to d91630c8510268e75203009fe7daf2b8e1d60c45.

That commit and that fix were never in a tagged release of satori/go.uuid, and prior to this announcement sif had used the last tag, 1.2.0. The NIST record says version 1.2.0 was vulnerable, but that's not true. So sif was never vulnerable to this. Also, beginning with version 2.0.0, sif does not use satori/go.uuid anymore.

This update was made in response to issue #243 which has more details.

The original, incorrect sif vulnerability description is below.

Impact

The siftool new command produces predictable UUID identifiers due to insecure randomness in the version of the github.com/satori/go.uuid module used as a dependency.

Patches

A patch is available in version >= v1.2.2 of the module. Users are encouraged to upgrade.

Fixed by apptainer/sif#90

Workarounds

Users passing CreateInfo struct should ensure the ID field is generated using a version of github.com/satori/go.uuid that is not vulnerable to this issue. Unfortunately, the latest tagged release is vulnerable to this issue. One way to obtain a non-vulnerable version is:

go get -u github.com/satori/go.uuid@v1.2.1-0.20180404165556-75cca531ea76

References

satori/go.uuid#73

For more information

If you have any questions or comments about this advisory:

Open an issue in https://github.com/hpcng/sif/issues

References

@cclerget cclerget published to apptainer/sif May 10, 2021
Published by the National Vulnerability Database Jun 2, 2021
Published to the GitHub Advisory Database Feb 7, 2023
Reviewed Feb 7, 2023
Last updated Sep 19, 2024

Severity

Critical

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 High
Integrity High
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:H/VI:H/VA:H/SC:N/SI:N/SA:N

EPSS score

0.245%
(65th percentile)

Weaknesses

CVE ID

CVE-2021-3538

GHSA ID

GHSA-33m6-q9v5-62r7

Source code

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