Vulnerability Details : CVE-2020-13092
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
Products affected by CVE-2020-13092
- cpe:2.3:a:scikit-learn:scikit-learn:*:*:*:*:*:*:*:*
Exploit prediction scoring system (EPSS) score for CVE-2020-13092
1.00%
Probability of exploitation activity in the next 30 days
EPSS Score History
~ 82 %
Percentile, the proportion of vulnerabilities that are scored at or less
CVSS scores for CVE-2020-13092
| Base Score | Base Severity | CVSS Vector | Exploitability Score | Impact Score | Score Source | First Seen |
|---|---|---|---|---|---|---|
|
7.5
|
HIGH | AV:N/AC:L/Au:N/C:P/I:P/A:P |
10.0
|
6.4
|
NIST | |
|
9.8
|
CRITICAL | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H |
3.9
|
5.9
|
NIST |
CWE ids for CVE-2020-13092
-
The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid.Assigned by: nvd@nist.gov (Primary)
References for CVE-2020-13092
-
https://github.com/0FuzzingQ/vuln/blob/master/sklearn%20unserialize.md
vuln/sklearn unserialize.md at master · 0FuzzingQ/vuln · GitHubExploit;Third Party Advisory
-
https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations
3.4. Model persistence — scikit-learn 0.23.0 documentationThird Party Advisory
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