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-2026-7316 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 31% 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 Protocol-Specific Risks 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 tracked as CVE-2026-7316 affects the eiliyaabedini aider-mcp project up to commit 667b914301aada695aab0e46d1fb3a7d5e32c8af. The issue resides in an unknown function within the aider_mcp.py file of the code_with_ai component, where manipulation of the working_dir and editable_files arguments permits injection of operating system commands. The project follows a rolling release model, so no discrete version numbers are provided for affected or fixed releases. The flaw is classified under CWE-74 and CWE-77 and carries a CVSS 4.0 score of 5.5 with network attack vector and no required privileges or user interaction.
Remote attackers can exploit the weakness without authentication to execute arbitrary commands on the host running the affected component. Publicly disclosed proof-of-concept material indicates that successful exploitation can alter or access files and processes within the scope of the running application, though the CVSS metrics reflect only limited impacts to confidentiality, integrity, and availability.
The GitHub repository and associated issue tracker contain the disclosure report, yet the maintainer has not responded to the early notification. No official patches, workarounds, or mitigation guidance have been published.
The EPSS score has remained low, moving only from a peak of 0.0218 to a current value of 0.0212.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-26153
Vulnerability Data
A vulnerability has been found in eiliyaabedini aider-mcp up to 667b914301aada695aab0e46d1fb3a7d5e32c8af. Affected is an unknown function of the file aider_mcp.py of the component code_with_ai. The manipulation of the argument working_dir/editable_files leads to command injection. The attack may be initiated remotely.…
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The exploit has been disclosed to the public and may be used. This product uses a rolling release model to deliver continuous updates. As a result, specific version information for affected or updated releases is not available. The project was informed of the problem early through an issue report but has not responded yet.
- CWE(s)
AI Security AnalysisAI
- AI Category
- AI Agent Protocols and Integrations
- Risk Domain
- Protocol-Specific Risks
- 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
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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.