How severe is CVE-2020-13092?

CVE-2020-13092 has a CVSS 3.x base score of 9.8, rated critical severity. It is exploitable over network with low attack complexity, requires no privileges and no user interaction. Impact on confidentiality is high, integrity high, and availability high.

Is CVE-2020-13092 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 3% (84th percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2020-13092?

CVE-2020-13092 affects Scikit-learn. See the affected-products list for the exact vulnerable versions.

How do I fix CVE-2020-13092?

Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround. Given its critical severity, prioritise patching exposed systems.

When was CVE-2020-13092 published?

CVE-2020-13092 was published on 2020-05-15 and last updated on 2026-06-17.

CVE-2020-13092

CVE-2020-13092 is a critical-severity vulnerability in Scikit-learn with a CVSS 3.x base score of 9.8. It is not currently listed as actively exploited by CISA, and its EPSS exploit-prediction score is low. The underlying weakness is classified as CWE-502.

Key facts

Severity: Critical (CVSS 3.x base score 9.8)
CVSS v2: 7.5
EPSS exploit prediction: 3% (84th percentile)
Actively exploited: Not listed in CISA KEV
Weakness: CWE-502
Affected product: Scikit-learn
Published: 2020-05-15
Last modified: 2026-06-17

Description

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

Frequently asked questions

What is 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
How severe is CVE-2020-13092?: CVE-2020-13092 has a CVSS 3.x base score of 9.8, rated critical severity. It is exploitable over network with low attack complexity, requires no privileges and no user interaction. Impact on confidentiality is high, integrity high, and availability high.
Is CVE-2020-13092 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 3% (84th percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2020-13092?: CVE-2020-13092 affects Scikit-learn. See the affected-products list for the exact vulnerable versions.
How do I fix CVE-2020-13092?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround. Given its critical severity, prioritise patching exposed systems.
When was CVE-2020-13092 published?: CVE-2020-13092 was published on 2020-05-15 and last updated on 2026-06-17.

References

Affected products (1)

cpe:2.3:a:scikit-learn:scikit-learn:*:*:*:*:*:*:*:*

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