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-2026-7157 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-2026-7157 affects disler aider-mcp-server up to commit b2516fa466d0d851932da92ee6d0e66946db9efc. The flaw resides in an unspecified function within src/aider_mcp_server/server.py of the aider_ai_code component and is triggered by improper handling of the relative_editable_files argument. It is classified under CWE-74 and CWE-77, carries a CVSS 4.0 score of 5.5, and impacts a project that follows a rolling-release model with no discrete version identifiers supplied for affected builds.
Remote attackers can exploit the issue without authentication or user interaction by supplying crafted input to the relative_editable_files parameter, resulting in arbitrary command execution. Successful exploitation yields limited effects on confidentiality, integrity, and availability. Publicly available exploit code has been released, and the vendor was notified via an issue report but has not issued a response or patch.
Advisories hosted on VulDB and the project repository note the absence of coordinated remediation and provide no mitigation guidance beyond the original disclosure. The associated EPSS score has remained essentially flat, moving only from 0.0212 to a peak of 0.0218.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-25924
Vulnerability Data
A flaw has been found in disler aider-mcp-server up to b2516fa466d0d851932da92ee6d0e66946db9efc. Affected by this vulnerability is an unknown functionality of the file src/aider_mcp_server/server.py of the component aider_ai_code. This manipulation of the argument relative_editable_files causes command injection. Remote exploitation of the…
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attack is possible. The exploit has been published and may be used. This product follows a rolling release approach for continuous delivery, so version details for affected or updated releases are not provided. 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.