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@hulumi/policies bypasses IAM-role policy checks when the role trusts multiple OIDC providers

High severity GitHub Reviewed Published May 20, 2026 in kerberosmansour/hulumi • Updated Jun 10, 2026

Package

npm @hulumi/policies (npm)

Affected versions

< 1.4.0

Patched versions

1.4.0

Description

Affected: @hulumi/policies < 1.4.0 — Fixed in: 1.4.0 — Severity: High — CWE-697 (Incorrect Comparison)

Summary

AWS IAM trust policies can list more than one federated identity provider — for example, a role that accepts BOTH GitHub Actions OIDC and Google's OIDC. The G_OIDC_1 and G_OIDC_2 policy rules are supposed to flag IAM roles whose GitHub-OIDC trust is too permissive (e.g. wildcard sub: conditions that would let any branch or any pull request assume the role).

The bug: when the role's Principal.Federated field was a JSON array of multiple providers, the rules failed to recognise that GitHub Actions was one of them. The providers list was coerced into a single comma-joined string, the matcher only looked at the start, and the GitHub OIDC hostname was lost in the join. Both rules concluded "this isn't a GitHub-OIDC role" and skipped the wildcard check.

Impact

A trust policy that listed the real GitHub OIDC provider ARN alongside any second provider would slip past both detectors. Consumers using HulumiHardeningPack or HulumiGithubHardeningPack could ship an IAM role with wildcard sub: conditions (allowing untrusted PRs from forks to assume the role) while their policy validation reported the stack as compliant. The G_OIDC_2 detector also failed to mark such roles for the cluster-admin / AdministratorAccess blast-radius check.

Patches

Upgrade to @hulumi/policies@1.4.0. The shared GitHub-OIDC-provider matcher now correctly walks lists of providers — if any element of the list is the real GitHub OIDC ARN, the role is treated as GitHub-OIDC-assumable and the wildcard / blast-radius checks apply.

Workarounds

None reliable — upgrade is the fix.

Resources

  • PR #178 (Cluster A); regression tests at packages/policies/tests/github/{g-oidc-2,github-oidc-issuer}.test.ts.

References

@kerberosmansour kerberosmansour published to kerberosmansour/hulumi May 20, 2026
Published to the GitHub Advisory Database Jun 10, 2026
Reviewed Jun 10, 2026
Last updated Jun 10, 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 High
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:P/PR:N/UI:N/VC:N/VI:H/VA:L/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.
(12th percentile)

Weaknesses

Incorrect Comparison

The product compares two entities in a security-relevant context, but the comparison is incorrect, which may lead to resultant weaknesses. Learn more on MITRE.

CVE ID

CVE-2026-48032

GHSA ID

GHSA-g759-4pxw-6692

Source code

Credits

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