Arbitrary code execution via unsafe pickle deserialization
Published Sep 8, 2025 · Updated Sep 9, 2025
Deserialization of untrusted data in Project MONAI's MONAI 1.5.0 and earlier allows attackers to execute arbitrary code via crafted datasets. The pickle_operations function recursively passes bytes under keys ending in _transforms directly to pickle.loads() without restricting globals. Execution requires a user or application to process attacker-supplied serialized data, and the payload runs with that process's privileges.
Summary
What happened
Deserialization of untrusted data in Project MONAI's MONAI 1.5.0 and earlier allows attackers to execute arbitrary code via crafted datasets. The pickle_operations function recursively passes bytes under keys ending in _transforms directly to pickle.loads() without restricting globals. Execution requires a user or application to process attacker-supplied serialized data, and the payload runs with that process's privileges.
The record
- CVE
- CVE-2025-58757
- Published
- Sep 8, 2025
- Updated
- Sep 9, 2025
- Vendor
- Project MONAI
- Product
- MONAI
- Classifications
- CWE-502, T1204.002
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- Sep 8, 2025CVE publishedPublication date reported by the CVE source.
- Sep 9, 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?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=<= 1.5.0
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
Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.
Weakness, pattern, technique
Public exploit references
- GHSA-p8cm-mm2v-gwjm proof of conceptproof of concept · demonstrated
Labels summarize the accepted research assessment. They do not indicate a test against your environment.
Technologies
Your stack
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Your stack
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