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CVE-2025-54412VulnerabilityPublished Updated

CVE-2025-54412: skops · Insufficient Type Distinction

Affects skopsSource CVE Database V5

0

Not known to be exploited · CVSS 8.7 High : upgrade to 0.12.0 soon.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 4.0 base score
8.7High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.1% chance of exploitation in 30 days – higher than 4% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 0.12.0
CVSS:4.0/AV:L/AC:L/AT:P/PR:N/UI:A/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 26 Jul 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq 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 2026-10-25.

What to do

Upgrade skops to 0.12.0.

Affected software

ProductAffectedFixed in
PyPIskopspkg:pypi/skopsOther threatsAffected
  • <0.12.0
Fixed in
  • 0.12.0

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

European organizations should immediately audit their environments to identify any use of skops versions below 0.12.0. The primary mitigation is to upgrade skops to version 0.12.0 or later, where the vulnerability is fixed. Additionally, organizations should implement strict access controls to limit local access to systems running skops, reducing the risk of exploitation by unauthorized users. Monitoring and logging of operator method invocations within skops workflows can help detect anomalous or suspicious activity indicative of exploitation attempts. Incorporating runtime application self-protection (RASP) or behavior-based anomaly detection tools in data science environments may provide early warning of code reuse attacks. Educating data scientists and developers about the risks of executing untrusted code and enforcing code review policies for model sharing workflows will further reduce exposure. Finally, organizations should maintain up-to-date incident response plans that include scenarios involving machine learning pipeline compromises.

Description

skops is a Python library which helps users share and ship their scikit-learn based models. Versions 0.11.0 and below contain a inconsistency in the OperatorFuncNode which can be exploited to hide the execution of untrusted operator methods. This can then be used in a code reuse attack to invoke seemingly safe functions and escalate to arbitrary code execution with minimal and misleading trusted types. This is fixed in version 0.12.0.

References

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