CVE-2024-5185 (GCVE-0-2024-5185)
Vulnerability from cvelistv5 – Published: 2024-05-29 13:00 – Updated: 2024-09-03 17:48
VLAI
EPSS
VEX
Title
Data Poisoning in EmbedAI
Summary
The EmbedAI application is susceptible to security issues that enable Data Poisoning attacks. This weakness could result in the application becoming compromised, leading to unauthorized entries or data poisoning attacks, which are delivered by a CSRF vulnerability due to the absence of a secure session management implementation and weak CORS policies weakness. An attacker can direct a user to a malicious webpage that exploits a CSRF vulnerability within the EmbedAI application. By leveraging this CSRF vulnerability, the attacker can deceive the user into inadvertently uploading and integrating incorrect data into the application’s language model.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-08-05 19:28 UTC
CWE
- CWE-352 - Cross-Site Request Forgery (CSRF)
Assigner
SNPS
CNA
References
1 reference
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| SamurAIGPT | EmbedAI |
Affected:
0 , ≤ b2ad64a85aaec6c301ead16ce5865edaf13be608
(git)
|
Date Public
2024-05-29 13:00
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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
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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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