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CVE-2026-31223: n/a

0
Unknown
VulnerabilityCVE-2026-31223cvecve-2026-31223
Published: Tue May 12 2026 (05/12/2026, 00:00:00 UTC)
Source: CVE Database V5

Description

The snorkel library thru v0.10.0 contains a critical insecure deserialization vulnerability (CWE-502) in the BaseLabeler.load() method of the BaseLabeler class. The method loads serialized labeler models using the unsafe pickle.load() function on user-supplied file paths without any validation or security controls. Python's pickle module is inherently dangerous for deserializing untrusted data, as it can execute arbitrary code during the deserialization process. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the victim's system when the file is loaded via the vulnerable method.

AI-Powered Analysis

Machine-generated threat intelligence

AILast updated: 05/12/2026, 16:07:33 UTC

Technical Analysis

The snorkel library versions through 0.10.0 contain a critical insecure deserialization vulnerability (CWE-502) in the BaseLabeler.load() method. This method loads serialized labeler models using Python's pickle.load() on user-supplied file paths without any validation or security controls. Since pickle can execute arbitrary code during deserialization, an attacker can craft a malicious pickle file that leads to arbitrary code execution on the victim system when loaded via this method. There is no CVSS score assigned and no vendor advisory or patch information available at this time.

Potential Impact

Exploitation of this vulnerability allows remote attackers to execute arbitrary code on affected systems by supplying a malicious pickle file to the vulnerable BaseLabeler.load() method. This can lead to full system compromise depending on the privileges of the running process. No known exploits in the wild have been reported so far.

Mitigation Recommendations

Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until a fix is available, avoid loading serialized labeler models from untrusted or unauthenticated sources. Consider implementing additional validation or sandboxing around deserialization operations to reduce risk.

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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: 6a034c84cbff5d8610fe99ee

Added to database: 5/12/2026, 3:51:32 PM

Last enriched: 5/12/2026, 4:07:33 PM

Last updated: 5/13/2026, 4:48:14 AM

Views: 6

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