Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/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-2025-71324 is a high-severity External Control of File Name or Path (CWE-73) vulnerability in Flowiseai Flowise. Its CVSS base score is 8.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data from Local System (T1005); ranked in the top 30% 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 LLM Application Platforms.
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.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-210336
Vulnerability Data
Flowise before 3.0.6 contains an arbitrary file read vulnerability in the chatId parameter of the /api/v1/get-upload-file and /api/v1/openai-assistants-file/download endpoints. The chatId value is not validated and is passed to streamStorageFile(), where a fallback file-lookup path constructed without the orgId is…
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evaluated after the storage-directory containment check, allowing path traversal beyond the intended storage directory. Unauthenticated attackers can read sensitive files such as /root/.flowise/database.sqlite, exposing all database content in the default configuration.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- N/A
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: openai
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.