THREATPORT/VULNERABILITY/CVE-2020-28975
HIGH SEVERITY

CVE-2020-28975

Scikit Learn vulnerability

CVSS
7.5
EPSS
3.4%
EPSS pct
88th
Exploited
No known
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 permanence standard) with a large value in the _n_support array. NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.
Affected vendor
Scikit Learn
Affected product
Scikit Learn
CVSS vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Published
2020-11-21

Risk analysis

Based on its CVSS vector, this vulnerability is exploitable over the network, low attack complexity, requiring no privileges, no user interaction. Successful exploitation leads to high impact to availability.

Its EPSS score of 3.4% reflects a lower probability of exploitation activity in the wild over the next 30 days, placing it above 88% of all scored CVEs.

Check your external exposure to CVE-2020-28975

  • Confirm whether Scikit Learn Scikit Learn is running on any internet-facing host or subdomain.
  • Match discovered service fingerprints against the version affected by CVE-2020-28975.
  • Prioritise remediation if the asset is public, business-critical, or near authentication/payment flows.

How ThreatPort helps with CVE-2020-28975

ThreatPort's external attack surface scanner checks your internet-facing assets — agentlessly, from the outside in — for the exposed services and versions that CVE-2020-28975 affects, then prioritises the finding by real risk using CISA KEV and FIRST.org EPSS.

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