Raw vector
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2024-5334 is a high-severity External Control of File Name or Path (CWE-73) vulnerability in Stitionai Devika. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data from Local System (T1005); ranked in the top 20% of CVEs by exploit likelihood; 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 Privacy and Disclosure 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.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2024-5334 is a local file read vulnerability in the stitionai/devika repository affecting its latest version. The flaw stems from improper handling of the snapshot_path parameter in the /api/get-browser-snapshot endpoint, which permits an attacker to supply an arbitrary path and retrieve file contents from the underlying system. The issue is tracked under CWE-73 and carries a CVSS 3.0 score of 7.5.
An unauthenticated remote attacker can exploit the vulnerability by sending a crafted HTTP request containing a malicious snapshot_path value. Successful exploitation grants read access to any file on the server filesystem, exposing sensitive configuration data, source code, or credentials without requiring user interaction or elevated privileges.
Public references point to a fix merged in commit 6acce21fb08c3d1123ef05df6a33912bf0ee77c2 of the devika repository, which addresses the path-handling logic in the affected endpoint. The same change is referenced in the associated huntr.dev bounty report.
The EPSS score for this CVE currently stands at 0.6275, matching its observed peak.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-46559
Vulnerability Data
A local file read vulnerability exists in the stitionai/devika repository, affecting the latest version. The vulnerability is due to improper handling of the 'snapshot_path' parameter in the '/api/get-browser-snapshot' endpoint. An attacker can exploit this vulnerability by crafting a request with…
more
a malicious 'snapshot_path' parameter, leading to arbitrary file read from the system. This issue impacts the security of the application by allowing unauthorized access to sensitive files on the server.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Enterprise AI Assistants
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- stitionai/devika is an open-source AI agentic software engineer (AI coding assistant), fitting Enterprise AI Assistants; vulnerability reported on AI/ML bug bounty platform huntr.com.
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.