CVE-2026-31224: snorkel · Deserialization of Untrusted Data
Affects snorkelSource CVE Database V5
Not known to be exploited · CVSS 8.8 High.
Data as of 26 Oct 2026, 17:16 UTC
- EPSS
- 0.3% chance of exploitation in 30 days – higher than 33% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:HExploitation evidence
Disclosed: evidence found.
CVE published 12 May 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.
What to do
Affected software
| Product | Affected | Fixed in |
|---|---|---|
PyPIsnorkelpkg:pypi/snorkelOther threats | Affected
| Fixed in– |
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
Until an official fix is available, users should avoid loading untrusted model files with the vulnerable MultitaskClassifier.load() method. If possible, manually verify or modify the code to use torch.load() with weights_only=True to mitigate the risk of arbitrary code execution.
Description
The snorkel library up to version 0.10.0 has an insecure deserialization vulnerability in the MultitaskClassifier.load() method. This method uses torch.load() without the security-restrictive weights_only=True parameter, allowing arbitrary Python object deserialization via Pickle. A remote attacker can exploit this by supplying a crafted model file, potentially leading to arbitrary code execution when the file is loaded.