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GHSA-jxfp-4rvq-9h9m

HighCVSS 7.5 / 10
Published May 24, 2022·Last modified Dec 3, 2024
Affected Components(0)

No affected components available

Description

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.

Risk Scores
Base Score
7.5

The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker does not need any special privileges or access rights. No user interaction is needed for the attacker to exploit this vulnerability. The impact is confined to the system where the vulnerability exists. There is a high impact on the availability of the system.

Threat Intelligence
6.9

Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.

EPSS
N/A

Probability that this vulnerability will be exploited in the wild within the next 30 days.

Exploit
Not available

We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.

Related Vulnerabilities
  • CVE-2020-28975
    Alias
  • EUVD-2020-0180
    Alias

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