CVE-2020-13092 — scikit-learn (aka sklearn) through 0

scikit-learn (aka sklearn) through 0.23.0 can unserialize and execute commands from an untrusted file that is passed to the joblib.load() function, if __reduce__ makes an os.system call. NOTE: third parties dispute this issue because the joblib.load() function is documented as un

01What is this vulnerability?

scikit-learn (aka sklearn) through 0.23.0 can unserialize and execute commands from an untrusted file that is passed to the joblib.load() function, if __reduce__ makes an os.system call. NOTE: third parties dispute this issue because the joblib.load() function is documented as unsafe and it is the user's responsibility to use the function in a secure manner

02Affected products

Vendor	Product	Versions
n	a / n/a	n/a

03Active exploitation status

Not currently listed on the CISA Known Exploited Vulnerabilities (KEV) catalog. EPSS is the best forward-looking signal — see the EPSS row above.

04Recommended remediation

• Patch to a fixed version listed in the vendor advisory (see references below).
• Mitigate with WAF rules, network egress filters, or feature flags where the patch is not yet available.
• Hunt historical logs for exploitation indicators — see Detection signatures below.

05Technical details

For the full vendor write-up, exploit chains, and reference implementations, see the references list in section 09.

06Detection signatures

Ask SARA in chat to draft a starting detection for this CVE in your stack of choice.

07Related CVEs

No directly-cited follow-up CVEs in the KB record for this advisory. The references list in section 09 carries the vendor cross-references.

08Timeline

• Published: 2020-05-15T18:41:33.000Z
• Last modified: 2024-08-04T12:11:18.980Z

09References

• github.com — https://github.com/0FuzzingQ/vuln/blob/master/sklearn%20unserialize.md
• scikit-learn.org — https://scikit-learn.org/stable/modules/model_persistence.html#security-maintain…