CVE-2024-5712
Published: 28 June 2024
Summary
CVE-2024-5712 is a high-severity CSRF (CWE-352) vulnerability in Stitionai Devika. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 37.5th 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 Enterprise AI Assistants; in the Other ATLAS/OWASP Terms risk domain; MITRE ATLAS techniques in scope: External Harms (AML.T0048).
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-46880
Vulnerability details
A Cross-Site Request Forgery (CSRF) vulnerability was identified in the stitionai/devika application, affecting the latest version. This vulnerability allows attackers to perform unauthorized actions in the context of a victim's browser, such as deleting projects or changing application settings, without…
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any CSRF protection implemented. Successful exploitation disrupts the integrity and availability of the application and its data.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Enterprise AI Assistants
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- stitionai/devika is an open-source AI coding assistant (Devika AI) that understands codebases and performs development tasks, fitting 'Enterprise AI Assistants'. Reported on AI/ML bug bounty platform huntr.com, confirming AI relevance. Vulnerability is CSRF in the web application.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
CSRF vulnerability enables exploitation of public-facing web application (T1190) to perform unauthorized actions including project deletion, facilitating data destruction (T1485).
MITRE ATLAS TechniquesAI
MITRE ATLAS techniques
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
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.
Awareness training educates users on avoiding untrusted links and actions that can be exploited via CSRF.
Requiring user re-entry of credentials for sensitive actions prevents automated forgery of requests without active user participation.
Security testing regimens explicitly include checks for missing or ineffective anti-CSRF protections in web applications.
Detects anomalous request patterns consistent with cross-site request forgery.