CVE-2024-24590
Published: 06 February 2024
Summary
CVE-2024-24590 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Clear Clearml. Its CVSS base score is 8.0 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Client Execution (T1203); ranked in the top 0.7% 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 Platforms; in the Supply Chain and Deployment risk domain; MITRE ATLAS techniques in scope: AI Supply Chain Compromise (AML.T0010).
Deeper analysis
The vulnerability is a deserialization of untrusted data flaw (CWE-502) present in versions 0.17.0 through 1.14.2 of the client SDK for Allegro AI’s ClearML platform. It carries a CVSS 3.1 score of 8.0 and permits a maliciously uploaded artifact to trigger arbitrary code execution on a user’s system upon interaction.
An attacker able to upload artifacts to a ClearML instance can craft a malicious payload that executes with high impact on confidentiality, integrity, and availability when a victim user processes the artifact via the vulnerable SDK. The attack requires low complexity, limited privileges, and user interaction over the network.
The supplied references point to HiddenLayer research on MLOps supply-chain risks but contain no explicit mitigation guidance or patch details. The associated EPSS score stands at 0.8283 with no material rise from a lower baseline.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-0620
Vulnerability details
Deserialization of untrusted data can occur in versions 0.17.0 to 1.14.2 of the client SDK of Allegro AI’s ClearML platform, enabling a maliciously uploaded artifact to run arbitrary code on an end user’s system when interacted with.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- ClearML is an MLOps platform for managing ML workflows, projects, datasets, experiments, and models, fitting 'Other Platforms' as it is a platform for ML operations not covered by more specific categories like frameworks or libraries.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
The deserialization vulnerability (CVE-2024-24590) in ClearML client SDK enables arbitrary code execution via malicious pickle artifacts (T1203), facilitating supply chain compromise of ML development tools and workflows (T1195.001).
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.