Vulnerability in Scikit-learn
CVE-2020-28975
svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 0.23.2 and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model pe…
EPSS: 0.034 (87.6th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 7.5 (High). Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H.
Affected products
- Scikit-learn
- N/a — versions n/a
Public proof-of-concept exploits
References
- cve@mitre.org (Exploit, Third Party Advisory, Issue Tracking)
- cve@mitre.org (Exploit, Third Party Advisory)
- cve@mitre.org (mailing-list, Mailing List, Third Party Advisory)
- cve@mitre.org (Exploit, VDB Entry, Third Party Advisory)
- cve@mitre.org (Patch, Third Party Advisory)
- cve@mitre.org (vendor-advisory, Third Party Advisory)
Frequently asked questions
- What is CVE-2020-28975?
- CVE-2020-28975 is a high-severity vulnerability in Scikit-learn. CVSS score: 7.5/10. Published 2020-11-21.
- How severe is CVE-2020-28975?
- High severity. CVSS v3 base score is 7.5 out of 10.
- Is CVE-2020-28975 known to be exploited?
- 3 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.