Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:H/SC:N/SI:H/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-75913 is a high-severity External Control of File Name or Path (CWE-73) vulnerability. Its CVSS base score is 8.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data from Local System (T1005); ranked at the 26th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as AI Agent Protocols and Integrations; in the LLM/Generative AI Risks risk domain.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and AC-3 (Access Enforcement) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-60971
Vulnerability Data
CodeWhale (codewhale / codewhale-tui) versions >= 0.8.41 and < 0.8.64 contain an argument injection vulnerability in the git_show tool. The model-supplied rev parameter is passed unvalidated into the git show argv without an --end-of-options sentinel, so a value beginning with…
more
--output= is interpreted as a git flag. Because the tool is registered as auto-approved and advertised as read-only, an attacker (via a malicious repository combined with prompt injection) can cause an unprompted arbitrary file write at the privilege of the invoking user, targeting sensitive files such as ~/.ssh/authorized_keys, ~/.bashrc, or ~/.gitconfig. Fixed in 0.8.64 by adding rev validation.
- CWE(s)
AI Security AnalysisAI
- AI Category
- AI Agent Protocols and Integrations
- Risk Domain
- LLM/Generative AI Risks
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: prompt injection
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V5.3.2
Mitigating Controls (NIST 800-53 r5) AI
Input validation directly rejects or sanitizes untrusted path strings before they reach filesystem operations.
Enforces authorization checks on the actual resource accessed, blocking unauthorized files even when a malicious path is supplied.
Least-privilege limits the set of files or directories any subject can affect, shrinking the blast radius of a path-control flaw.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing can detect path-traversal issues but does not itself implement preventive controls.
Secure development lifecycle mandates input validation and path-handling controls that directly prevent external file/path manipulation.
Application security requirements explicitly call for controls against untrusted input influencing file operations.
Secure architecture principles discourage unsafe path construction but do not prescribe concrete file-name controls.
Secure coding standards require canonicalization, allow-listing, and bounds checks on file paths, directly eliminating CWE-73.
Information access restriction limits which files can be reached, indirectly reducing impact of path manipulation.