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cert-manager ha a potential slowdown / DoS when parsing specially crafted PEM inputs

Moderate severity GitHub Reviewed Published Nov 20, 2024 in cert-manager/cert-manager • Updated Nov 22, 2024

Package

gomod github.com/cert-manager/cert-manager (Go)

Affected versions

< 1.12.14
>= 1.13.0-alpha.0, < 1.15.4
>= 1.16.0-alpha.0, < 1.16.2

Patched versions

1.12.14
1.15.4
1.16.2

Description

Impact

cert-manager packages which call the standard library pem.Decode() function can take a long time to process specially crafted invalid PEM data.

If an attacker is able to modify PEM data which cert-manager reads (e.g. in a Secret resource), they may be able to use large amounts of CPU in the cert-manager controller pod to effectively create a denial-of-service (DoS) vector for cert-manager in the cluster.

Secrets are limited in size to 1MiB, which reduces the impact of this issue; it was discovered through an ~856kB fuzz test input which causes pem.Decode to take roughly 750ms to reject the input on an M2 Max Macbook Pro. By way of comparison, a valid PEM-encoded 4096-bit RSA key takes roughly 70µs to parse on the same machine.

Given the required size of PEM data needed to present a realistic DoS vector, an attacker would need to create or insert many different large sized resources in the cluster, and so the best secondary defense is to ensure that sensible limits are placed via RBAC.

This issue affects all versions of cert-manager to have been released since at least v0.1.0 (since pem.Decode is core functionality for cert-manager). All supported releases are patched.

Patches

The fixed versions are v1.16.2, v1.15.4 and v1.12.14.

Workarounds

Ensure that RBAC is scoped correctly in your cluster. If a user is able to modify resources containing PEM data to be able to exploit this, it's like that those permissions are a bigger security threat than this issue - especially for Secret resources.

References

References

@SgtCoDFish SgtCoDFish published to cert-manager/cert-manager Nov 20, 2024
Published to the GitHub Advisory Database Nov 20, 2024
Reviewed Nov 20, 2024
Last updated Nov 22, 2024

Severity

Moderate

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 Low
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:N/VI:N/VA:L/SC:N/SI:N/SA:N

Weaknesses

No CWEs

CVE ID

No known CVE

GHSA ID

GHSA-r4pg-vg54-wxx4

Source code

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