Arbitrary code execution via pmdarima pickle loading
Published Jun 4, 2024 · Updated Aug 2, 2024
Unsafe deserialization in MLflow 1.24.0 and later allows remote attackers to execute arbitrary code through an uploaded pmdarima model. The pmdarima._load_model function passes the downloaded model binary directly to pickle.load, which invokes attacker-controlled reduction logic during object reconstruction. Execution requires an end user to load or otherwise interact with the malicious model, and the code runs with that user's process privileges.
Summary
What happened
Unsafe deserialization in MLflow 1.24.0 and later allows remote attackers to execute arbitrary code through an uploaded pmdarima model. The pmdarima._load_model function passes the downloaded model binary directly to pickle.load, which invokes attacker-controlled reduction logic during object reconstruction. Execution requires an end user to load or otherwise interact with the malicious model, and the code runs with that user's process privileges.
The record
- CVE
- CVE-2024-37055
- Published
- Jun 4, 2024
- Updated
- Aug 2, 2024
- Vendor
- MLflow Project
- Product
- MLflow
- Classifications
- CWE-502, CAPEC-586, T1204.002
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- Jun 4, 2024CVE publishedPublication date reported by the CVE source.
- Aug 2, 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?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=1.24.0 <=*
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
- HiddenLayer pmdarima malicious-model 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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