CVE-2026-31237: n/a
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction.
AI Analysis
Technical Summary
CVE-2026-31237 describes an insecure deserialization vulnerability in the Ludwig framework through version 0.10.4. The predict() method accepts a dataset file path and determines the file format automatically. If the file is a pickle file, it is loaded via pandas.read_pickle() without any security checks, enabling arbitrary Python object deserialization. This can be exploited remotely by providing a crafted pickle file, resulting in arbitrary code execution on the host system running the prediction.
Potential Impact
Successful exploitation allows an attacker to execute arbitrary code on the system running the Ludwig prediction service. This can lead to full system compromise depending on the privileges of the Ludwig process. There are no known exploits in the wild at this time.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until an official fix is available, avoid using untrusted pickle files with the predict() method or disable support for pickle file inputs if possible.
CVE-2026-31237: n/a
Description
The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-31237 describes an insecure deserialization vulnerability in the Ludwig framework through version 0.10.4. The predict() method accepts a dataset file path and determines the file format automatically. If the file is a pickle file, it is loaded via pandas.read_pickle() without any security checks, enabling arbitrary Python object deserialization. This can be exploited remotely by providing a crafted pickle file, resulting in arbitrary code execution on the host system running the prediction.
Potential Impact
Successful exploitation allows an attacker to execute arbitrary code on the system running the Ludwig prediction service. This can lead to full system compromise depending on the privileges of the Ludwig process. There are no known exploits in the wild at this time.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until an official fix is available, avoid using untrusted pickle files with the predict() method or disable support for pickle file inputs if possible.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- mitre
- Date Reserved
- 2026-03-09T00:00:00.000Z
- Cvss Version
- null
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a036531cbff5d861008c1c3
Added to database: 5/12/2026, 5:36:49 PM
Last enriched: 5/12/2026, 7:38:24 PM
Last updated: 5/13/2026, 4:30:33 AM
Views: 2
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