CVE-2024-6960 (GCVE-0-2024-6960)
Vulnerability from cvelistv5 – Published: 2024-07-21 09:55 – Updated: 2024-11-25 12:47
VLAI
EPSS
VEX
Title
H2O deserializes ML models without filtering, potentially allowing execution of malicious code
Summary
The H2O machine learning platform uses "Iced" classes as the primary means of moving Java Objects around the cluster. The Iced format supports inclusion of serialized Java objects. When a model is deserialized, any class is allowed to be deserialized (no class whitelist). An attacker can construct a crafted Iced model that uses Java gadgets and leads to arbitrary code execution when imported to the H2O platform.
Severity
7.5 (High)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-07-24 17:06 UTC
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
JFROG
CNA
References
2 references
| URL | Tags |
|---|---|
| https://research.jfrog.com/vulnerabilities/h2o-mo… | third-party-advisory |
| https://mvnrepository.com/artifact/ai.h2o/h2o-core | product |
Impacted products
2 products
| Vendor | Product | Version | |
|---|---|---|---|
|
Affected:
0
(maven)
|
|||
| mvnrepository | h2o-core |
Affected:
0 , < *
(custom)
cpe:2.3:a:mvnrepository:h2o-core:*:*:*:*:*:*:*:* |
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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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