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@hulumi/drift: Drift classifier fails open on adapter errors and over-promotes Mixed verdicts

High severity GitHub Reviewed Published May 20, 2026 in kerberosmansour/hulumi

Package

npm @hulumi/drift (npm)

Affected versions

< 1.4.0

Patched versions

1.4.0

Description

Affected: @hulumi/drift < 1.4.0 — Fixed in: 1.4.0 — Severity: Medium — CWE-755 (Improper Handling of Exceptional Conditions)

Summary

@hulumi/drift runs four adapters that each ask a different question about whether a resource has drifted (Pulumi-state diff, provider-version change, CloudTrail event, etc.). A classifier combines the adapters' answers into a verdict like None / none, ConsoleBreakGlass / high, or Mixed / high, and caches the verdict for 6 hours by default.

Two related bugs from one root cause — the classifier only read each adapter's detected: true/false field and ignored whether the adapter itself succeeded:

  1. Cached "all clear" on adapter failure. When an adapter failed (e.g. transient network error from the Automation API), the classifier read detected: false, concluded "no drift", and cached the verdict as None / none for 6 hours. A single transient failure could mask real console-break-glass mutations for the rest of the window.
  2. Mixed verdicts without real evidence. The Mixed / high and ConsoleBreakGlass / high verdicts (incident severity) could fire on the "the CloudTrail probe round-tripped successfully" signal rather than actual evidence that anything had been changed via the console. Normal provider-API churn could end up falsely escalated to incident severity.

Impact

Consumers running drift detection in CI / cron could see transient adapter failures silently cached as "all clear" — masking real attacks for up to six hours — or see ordinary provider-version churn falsely promoted to incident severity. Either way, the verdict source was unreliable for downstream incident workflows that gate on it.

Patches

Upgrade to @hulumi/drift@1.4.0. Classifier-only fix (the TLA+-verified 6-row verdict matrix is byte-identical):

  • adapter failures now fail closed to Unknown / low, and degraded verdicts are not written to the cache;
  • the Mixed / ConsoleBreakGlass promotion now requires real CloudTrail event evidence rather than probe liveness.

Workarounds

Setting options.minConfidence: "medium" on the classifier call prevents the degraded None / none from being cached (it doesn't meet the threshold), partially mitigating case (1). No workaround for case (2).

Resources

  • PR #178 (Cluster D); regression tests in packages/drift/tests/classifier-fail-closed.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

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 Passive
Vulnerable System Impact Metrics
Confidentiality None
Integrity High
Availability Low
Subsequent System Impact Metrics
Confidentiality None
Integrity High
Availability Low

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:P/VC:N/VI:H/VA:L/SC:N/SI:H/SA:L

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

Improper Handling of Exceptional Conditions

The product does not handle or incorrectly handles an exceptional condition. Learn more on MITRE.

CVE ID

CVE-2026-48036

GHSA ID

GHSA-32g3-35g9-wc9g

Source code

Credits

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