CVE-2020-13092: Scikit learn Scikit-learn Deserialization Of Untrusted Data Vulnerability

CRITICAL
Advisory Identifier: GHSA-jjw5-xxj6-pcv5
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CVSS 9.8
CWE-502
Published
Advisory Summary

CVE-2020-13092 is a CRITICAL (CVSS 9.8) scikit-learn deserialization of untrusted data vulnerability (CWE-502: Deserialization of Untrusted Data) affecting Scikit learn libraries in the PyPI ecosystem. The issue involves scikit-learn deserialization of untrusted data. Remediation is available in the latest vendor maintenance releases.

CVE-2020-13092 at a Glance

CVE Identifier CVE-2020-13092
GHSA Identifier GHSA-jjw5-xxj6-pcv5
Severity CRITICAL
CVSS v3.1 Base Score 9.8
CWE Classification CWE-502: Deserialization of Untrusted Data
Affected Product Scikit learn
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 9.8

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity High (I:H)
Availability High (A:H)

How to Fix CVE-2020-13092

To remediate this vulnerability, upgrade all affected Scikit learn dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

scikit-learn fixed: Latest secure release 
pip install scikit-learn>=Latest secure release
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show scikit-learn

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2020-13092, inspect your installed packages using pip:

pip show scikit-learn

Analyze the terminal output to locate any version of Scikit learn in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than the patched release), your application is affected.

Note: The pip show scikit-learn command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-502: Deserialization of Untrusted Data, where the product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid. In Scikit learn, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

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.

CVE-2020-13092 Affected Scikit learn Versions

1 component(s)
Product / Package Ecosystem Affected Versions Fixed Version
scikit-learn
pypi/scikit-learn
PyPI
≤ 0.23.0

References

NVD — CVE-2020-13092 NVD
https://nvd.nist.gov/vuln/detail/CVE-2020-13092
Scikit learn Source Repository REPOSITORY
https://github.com/0FuzzingQ/vuln/blob/master/sklearn%20unserialize.md
Scikit learn Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/scikit-learn/PYSEC-2020-107.yaml
Scikit learn Source Repository REPOSITORY
https://github.com/scikit-learn/scikit-learn
scikit-learn.org/stable/modules/mode... WEB
https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations

Frequently Asked Questions

What is CVE-2020-13092?
CVE-2020-13092 is a security vulnerability in Scikit learn involving scikit-learn Deserialization of Untrusted Data under CWE-502: Deserialization of Untrusted Data.
Which Scikit learn versions are affected?
Affected versions include releases prior to current release patches across affected packages: scikit-learn.
What version fixes CVE-2020-13092?
Upgrading to current release patches (or the latest patched release for your respective branch) resolves the vulnerability.
Is scikit-learn affected?
Yes, scikit-learn is affected in releases prior to Latest secure release. Upgrade your dependency to Latest secure release or later.
What is the CVSS score of CVE-2020-13092?
CVE-2020-13092 has a CVSS v3.1 base score of 9.8 (CRITICAL) with vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H.
What CWE is associated with CVE-2020-13092?
CVE-2020-13092 is classified under CWE-502: Deserialization of Untrusted Data (The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.).
How can I check PyPI dependencies for CVE-2020-13092?
Run the dependency tree command: 'pip show scikit-learn'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-jjw5-xxj6-pcv5",
  "modified" : "2024-10-22T17:21:50Z",
  "published" : "2022-05-24T17:17:59Z",
  "aliases" : [ "CVE-2020-13092" ],
  "summary" : "scikit-learn Deserialization of Untrusted Data",
  "details" : "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`.\nNOTE: 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.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "scikit-learn"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "last_affected" : "0.23.0"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2020-13092"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/0FuzzingQ/vuln/blob/master/sklearn%20unserialize.md"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/scikit-learn/PYSEC-2020-107.yaml"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/scikit-learn/scikit-learn"
  }, {
    "type" : "WEB",
    "url" : "https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-502" ],
    "severity" : "CRITICAL",
    "github_reviewed" : true,
    "github_reviewed_at" : "2024-04-22T22:55:41Z",
    "nvd_published_at" : "2020-05-15T19:15:00Z"
  }
}