CVE-2024-6095 (GCVE-0-2024-6095)
Vulnerability from cvelistv5 – Published: 2024-07-06 17:48 – Updated: 2024-08-01 21:33
VLAI
EPSS
VEX
Title
SSRF and Partial LFI in /models/apply Endpoint in mudler/localai
Summary
A vulnerability in the /models/apply endpoint of mudler/localai versions 2.15.0 allows for Server-Side Request Forgery (SSRF) and partial Local File Inclusion (LFI). The endpoint supports both http(s):// and file:// schemes, where the latter can lead to LFI. However, the output is limited due to the length of the error message. This vulnerability can be exploited by an attacker with network access to the LocalAI instance, potentially allowing unauthorized access to internal HTTP(s) servers and partial reading of local files. The issue is fixed in version 2.17.
Severity
5.8 (Medium)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-07-07 19:17 UTC
CWE
- CWE-918 - Server-Side Request Forgery (SSRF)
Assigner
References
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| mudler | mudler/localai |
Affected:
unspecified , < 2.17
(custom)
|
guessed | |
| mudler | localai |
Affected:
2.15.0 , < 2.17.0
(custom)
cpe:2.3:a:mudler:localai:2.15.0:*:*:*:*:*:*:* |
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Sightings
| Author | Source | Type | Date | Other |
|---|
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Vulnerability timeline
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
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They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.