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Automated recognition mechanism with inadequate detection...

Moderate severity Unreviewed Published Apr 8, 2025 to the GitHub Advisory Database • Updated Apr 8, 2025

Package

No package listed— Suggest a package

Affected versions

Unknown

Patched versions

Unknown

Description

Automated recognition mechanism with inadequate detection or handling of adversarial input perturbations in Windows Hello allows an unauthorized attacker to perform spoofing locally.

References

Published by the National Vulnerability Database Apr 8, 2025
Published to the GitHub Advisory Database Apr 8, 2025
Last updated Apr 8, 2025

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 v3 base metrics

Attack vector
Local
Attack complexity
High
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
High
Availability
None

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:L/AC:H/PR:N/UI:N/S:U/C:N/I:H/A: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.
(7th percentile)

Weaknesses

Automated Recognition Mechanism with Inadequate Detection or Handling of Adversarial Input Perturbations

The product uses an automated mechanism such as machine learning to recognize complex data inputs (e.g. image or audio) as a particular concept or category, but it does not properly detect or handle inputs that have been modified or constructed in a way that causes the mechanism to detect a different, incorrect concept. Learn more on MITRE.

CVE ID

CVE-2025-26644

GHSA ID

GHSA-2f5r-r4jx-hh42

Source code

No known source code

Dependabot alerts are not supported on this advisory because it does not have a package from a supported ecosystem with an affected and fixed version.

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