Cyber Posture

CVE-2026-45539

High

Published: 15 May 2026

Published
15 May 2026
Modified
15 May 2026
KEV Added
Patch
CVSS Score 7.4 CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:N/A:N
EPSS Score 0.0008 22.6th percentile
Risk Priority 15 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2026-45539 is a high-severity Link Following (CWE-59) vulnerability. Its CVSS base score is 7.4 (High).

Operationally, ranked at the 22.6th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as Machine Learning Libraries.

Threat & Defense Details

Likely Mitigating ControlsAI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

addresses: CWE-200

Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.

addresses: CWE-200

Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.

addresses: CWE-200

Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.

addresses: CWE-200

By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.

addresses: CWE-200

Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.

addresses: CWE-200

Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.

addresses: CWE-200

Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.

addresses: CWE-200

Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.

NVD Description

Microsoft APM is an open-source, community-driven dependency manager for AI agents. From 0.5.4 to 0.12.4, two primitive integrators in apm-cli enumerate package files with bare Path.glob() / Path.rglob() calls and read each match with Path.read_text(), transparently following symbolic links. A…

more

symlink committed inside a remote APM dependency under .apm/prompts/<x>.prompt.md or .apm/agents/<x>.agent.md is preserved verbatim into apm_modules/ on clone and then dereferenced during integration, with the resolved content written as a regular file into the project's deploy directories. The package content_hash, the pre-deploy SecurityGate scan, and apm audit do not flag this. The deploy roots are not added to the auto-generated .gitignore, so the resulting files are staged by git add by default. This vulnerability is fixed in 0.13.0.

Deeper analysisAI

Automated synthesis unavailable for this CVE.

Details

CWE(s)

AI Security AnalysisAI

AI Category
Machine Learning Libraries
Risk Domain
N/A
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Matched keywords: ai

References