Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/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-2026-6980 is a medium-severity Injection (CWE-74) vulnerability. Its CVSS base score is 5.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked in the top 25% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as AI Agent Protocols and Integrations; in the Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
A command injection vulnerability exists in Divyanshu-hash GitPilot-MCP up to commit 9ed9f153ba4158a2ad230ee4871b25130da29ffd, specifically in the repo_path function of main.py. Untrusted input supplied to the command argument is passed to an operating system command without sanitization, allowing an attacker to inject and execute arbitrary commands. The product does not use conventional versioning, preventing identification of specific affected or fixed releases, and the vendor did not respond to early disclosure notification.
An unauthenticated remote attacker can exploit the flaw over the network by supplying a crafted command value, resulting in limited impacts to confidentiality, integrity, and availability on the affected system. The issue is tracked under CWE-74 and CWE-77, carries a CVSS 4.0 score of 5.5, and has had a public exploit released.
Public references consist of a GitHub issue and Vuldb entries that document the disclosure but contain no vendor patch, workaround, or mitigation guidance. The associated EPSS score has remained low and essentially flat at approximately 0.021.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-25656
Vulnerability Data
A vulnerability has been found in Divyanshu-hash GitPilot-MCP up to 9ed9f153ba4158a2ad230ee4871b25130da29ffd. This impacts the function repo_path of the file main.py. Such manipulation of the argument command leads to command injection. The attack can be launched remotely. The exploit has been…
more
disclosed to the public and may be used. This product does not use versioning. This is why information about affected and unaffected releases are unavailable. The vendor was contacted early about this disclosure but did not respond in any way.
- CWE(s)
AI Security AnalysisAI
- AI Category
- AI Agent Protocols and Integrations
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: mcp
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
—
V1.2.1V1.2.3V1.2.5V1.2.8
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover command-construction flaws before deployment.
SI-10 directly requires validation of information inputs to reject malformed or special-element content before it reaches downstream parsers.
Secure engineering principles include proper neutralization and safe command construction practices.
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.
Secure SDLC practices directly require input validation and output encoding that prevent injection flaws.
Runtime monitoring of software and data can detect anomalous command execution resulting from injection.
Identifying recorded vulnerabilities enables remediation of command-injection flaws before exploitation.
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.
Secure coding standards require proper escaping and parameterization of commands, directly eliminating CWE-77.
Security testing in development catches injection vulnerabilities before release.
Logging supports detection of injection attempts but does not prevent the weakness.
Monitoring activities can identify active injection attacks after they occur.
Secure development life cycle mandates input validation and output encoding that directly prevent injection flaws.
Application security requirements explicitly call for controls against injection attacks in software design.