CVE-2024-6396
Aimstack Aim 3.19.3
Raw vector
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-6396 is a critical-severity Path Traversal: '\..\filename' (CWE-29) vulnerability in Aimstack Aim. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 1% 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 Other AI Platforms; 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.
A vulnerability exists in the `_backup_run` function of aimhubio/aim version 3.19.3. It stems from improper handling of the `run_hash` and `repo.path` parameters, enabling path traversal that permits writing to arbitrary file locations on the server. The issue is tracked as CWE-29 and carries a CVSS 3.0 score of 9.8.
Unauthenticated remote attackers can supply crafted values to these parameters, allowing them to overwrite any file on the host, exfiltrate arbitrary data, cause denial of service through critical file replacement, and potentially achieve remote code execution.
The referenced Huntr bounty report details the flaw but does not describe available patches or specific mitigation steps in the supplied information. The associated EPSS score stands at 0.8870 with a recorded peak of 0.9099, indicating sustained exploitation interest since disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-47502
Vulnerability Data
A vulnerability in the `_backup_run` function in aimhubio/aim version 3.19.3 allows remote attackers to overwrite any file on the host server and exfiltrate arbitrary data. The vulnerability arises due to improper handling of the `run_hash` and `repo.path` parameters, which can…
more
be manipulated to create and write to arbitrary file paths. This can lead to denial of service by overwriting critical system files, loss of private data, and potential remote code execution.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other AI Platforms
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Aim (aimhubio/aim) is an open-source platform for tracking, visualizing, and managing machine learning experiments, fitting under 'Other Platforms' as an ML experiment tracking tool.
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Input validation directly neutralizes the '\..\filename' sequence before pathname resolution occurs.
Access enforcement denies requests that resolve outside the intended directory even when the traversal sequence is present.
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 path sanitization that block this traversal vector.
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 discover path-traversal flaws but does not itself prevent them in production code.
Application security requirements can mandate input validation and path canonicalization to block traversal sequences.
Secure architecture principles include directory sandboxing and safe file-access design that mitigate path traversal.
Secure coding standards directly require neutralizing path traversal sequences such as '\..\filename'.