MLflow Statsmodels load can run code after user action (CVE-2024-37052)
Original title: ZDI-26-845: MLflow Statsmodels _load_model Deserialization of Untrusted Data Remote Code Execution Vulnerability
The target must open a malicious page or file; ZDI rates the flaw CVSS 7.8.
ZDI published ZDI-26-845 for unsafe deserialization in MLflow’s Statsmodels _load_model path that can lead to remote code execution. Exploitation requires the target to visit a malicious page or open a malicious file. ZDI assigned CVSS 7.8 and CVE-2024-37052. Versions, a fix, and known attacks are not stated.
Unconfirmed: Affected versions, a patch, and real-world exploitation are not stated.
- User interaction is required to exploit the flaw.
- The issue is deserialization of untrusted data in _load_model.
- ZDI assigned a CVSS rating of 7.8.
- The listed CVE is CVE-2024-37052 under advisory ZDI-26-845.
Impact: Remote code execution after the user opens malicious content
| Product | Affected |
|---|---|
| MLflow | — |
- CVEs
- CVE-2024-37052
- Products
- MLflow
- Organizations
- Zero Day Initiative
Vulnerabilities mentioned
All| CVE | Vulnerability | CVSS | EPSS | Signals | Published |
|---|---|---|---|---|---|
| CVE-2024-37052 | Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn… | 8.8 | <1% | PoC |
From the original article
This vulnerability allows remote attackers to execute arbitrary code on affected installations of MLflow. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The ZDI has assigned a CVSS rating of 7.
zerodayinitiative.com
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