Remote code execution via distributed pickle deserialization
Published Mar 20, 2025 · Updated Mar 20, 2025
Unsafe deserialization in OpenMMLab MMDetection 3.3.0 allows remote attackers to execute arbitrary code through distributed training. The all_reduce_dict API applies pickle.loads() to data broadcast by other distributed workers without validating the serialized object. An unauthenticated attacker able to join or reach the distributed training network can run code with the compromised worker's privileges.
Summary
What happened
Unsafe deserialization in OpenMMLab MMDetection 3.3.0 allows remote attackers to execute arbitrary code through distributed training. The all_reduce_dict API applies pickle.loads() to data broadcast by other distributed workers without validating the serialized object. An unauthenticated attacker able to join or reach the distributed training network can run code with the compromised worker's privileges.
The record
- CVE
- CVE-2024-12044
- Published
- Mar 20, 2025
- Updated
- Mar 20, 2025
- Vendor
- OpenMMLab
- Product
- MMDetection
- Classifications
- CWE-502, T1210
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- Mar 20, 2025CVE publishedPublication date reported by the CVE source.
- Mar 20, 2025Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
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- Affected versionversion=unspecified <=latest
What conditions does exploitation require?
What is affected?
Published CVSS scores
CVSS describes severity. EPSS estimates exploitation probability.
Attacks
What attackers are doing with it
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Weakness, pattern, technique
Public exploit references
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Technologies
Your stack
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Your stack
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