CVE-2024-37288
Published: 09 September 2024
Summary
CVE-2024-37288 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Elastic Kibana. Its CVSS base score is 9.9 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 16.4% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Enterprise AI Assistants; in the Other ATLAS/OWASP Terms risk domain; MITRE ATLAS techniques in scope: Obtain Capabilities (AML.T0016), AI Model Inference API Access (AML.T0040), LLM Prompt Injection (AML.T0051).
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-36561
Vulnerability details
A deserialization issue in Kibana can lead to arbitrary code execution when Kibana attempts to parse a YAML document containing a crafted payload. This issue only affects users that use Elastic Security’s built-in AI tools https://www.elastic.co/guide/en/security/current/ai-for-security.html and have configured an…
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Amazon Bedrock connector https://www.elastic.co/guide/en/security/current/assistant-connect-to-bedrock.html .
- CWE(s)
AI Security AnalysisAI
- AI Category
- Enterprise AI Assistants
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- The vulnerability specifically impacts users of Elastic Security’s built-in AI tools, including AI assistants configured with an Amazon Bedrock connector for generative AI integration, fitting the Enterprise AI Assistants category.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Deserialization vulnerability in Kibana enables arbitrary remote code execution via crafted YAML payload when parsing documents in Elastic Security AI tools with Amazon Bedrock connector configured, aligning with exploitation of a public-facing web application.
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.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Validates or rejects untrusted serialized data before deserialization occurs.
Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.
Integrity verification of serialized information can detect tampering before deserialization occurs.
Provenance of associated data allows detection of untrusted sources before deserialization or processing occurs.