CVE-2024-3584
Published: 30 May 2024
Summary
CVE-2024-3584 is a high-severity Improper Input Validation (CWE-20) vulnerability in Qdrant Qdrant. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 39.7% 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 Similarity Search; in the Other ATLAS/OWASP Terms risk domain; MITRE ATLAS techniques in scope: AI Supply Chain Compromise (AML.T0010), External Harms (AML.T0048).
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-2207
Vulnerability details
qdrant/qdrant version 1.9.0-dev is vulnerable to path traversal due to improper input validation in the `/collections/{name}/snapshots/upload` endpoint. By manipulating the `name` parameter through URL encoding, an attacker can upload a file to an arbitrary location on the system, such as…
more
`/root/poc.txt`. This vulnerability allows for the writing and overwriting of arbitrary files on the server, potentially leading to a full takeover of the system. The issue is fixed in version 1.9.0.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Similarity Search
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Qdrant is a vector database specifically designed for similarity search and storing embeddings in AI/ML applications, and the vulnerability affects its core server endpoints for collections and snapshots.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Path traversal in public-facing upload endpoint (T1190) enables arbitrary file writes, facilitating ingress of tools/malware directly to desired filesystem locations (T1105, T1608.001, T1608.002) for persistence, execution, or takeover.
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.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.