Code execution via untrusted joblib model loading
Published May 15, 2020 · Updated Aug 4, 2024
Unsafe deserialization in scikit-learn 0.23.0 and earlier allows attackers to execute commands by loading an untrusted joblib model file. joblib.load uses the pickle protocol, which invokes attacker-controlled reduce callables such as os.system while reconstructing objects. Exploitation requires an application or user to load the crafted artifact; scikit-learn documents this behavior as unsafe by design, and the CVE is disputed.
Summary
What happened
Unsafe deserialization in scikit-learn 0.23.0 and earlier allows attackers to execute commands by loading an untrusted joblib model file. joblib.load uses the pickle protocol, which invokes attacker-controlled reduce callables such as os.system while reconstructing objects. Exploitation requires an application or user to load the crafted artifact; scikit-learn documents this behavior as unsafe by design, and the CVE is disputed.
The record
- CVE
- CVE-2020-13092
- Published
- May 15, 2020
- Updated
- Aug 4, 2024
- Vendor
- Unknown vendor
- Product
- Unknown product
- Classifications
- CWE-502, T1059
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- May 15, 2020CVE publishedPublication date reported by the CVE source.
- Aug 4, 2024Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
What conditions does exploitation require?
What is affected?
Affected products and versions are unavailable in this record.
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
- scikit-learn unserialize proof of conceptproof of concept · unverified
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Technologies
Your stack
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Your stack
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