Vulnerability-Lookup

PYSEC-2020-107

Vulnerability from pysec - Published: 2020-05-15 19:15 - Updated: 2020-05-19 19:05

Details

** DISPUTED ** 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.

Impacted products

Name	purl
scikit-learn	pkg:pypi/scikit-learn

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "scikit-learn",
        "purl": "pkg:pypi/scikit-learn"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.23.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.9",
        "0.10",
        "0.11",
        "0.12",
        "0.12.1",
        "0.13",
        "0.13.1",
        "0.14a1",
        "0.14",
        "0.14.1",
        "0.15.0b1",
        "0.15.0b2",
        "0.15.0",
        "0.15.1",
        "0.15.2",
        "0.16b1",
        "0.16.0",
        "0.16.1",
        "0.17b1",
        "0.17",
        "0.17.1",
        "0.18rc2",
        "0.18",
        "0.18.1",
        "0.18.2",
        "0.19b2",
        "0.19.0",
        "0.19.1",
        "0.19.2",
        "0.20rc1",
        "0.20.0",
        "0.20.1",
        "0.20.2",
        "0.20.3",
        "0.20.4",
        "0.21rc2",
        "0.21.0",
        "0.21.1",
        "0.21.2",
        "0.21.3",
        "0.22rc2.post1",
        "0.22rc3",
        "0.22",
        "0.22.1",
        "0.22.2",
        "0.22.2.post1",
        "0.23.0rc1",
        "0.23.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2020-13092",
    "GHSA-jjw5-xxj6-pcv5"
  ],
  "details": "** DISPUTED ** 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\u0027s responsibility to use the function in a secure manner.",
  "id": "PYSEC-2020-107",
  "modified": "2020-05-19T19:05:00Z",
  "published": "2020-05-15T19:15:00Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/0FuzzingQ/vuln/blob/master/sklearn%20unserialize.md"
    },
    {
      "type": "WEB",
      "url": "https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-jjw5-xxj6-pcv5"
    }
  ]
}

CVE-2020-13092 (GCVE-0-2020-13092)

Vulnerability from cvelistv5 – Published: 2020-05-15 18:41 – Updated: 2024-08-04 12:11 Disputed

Summary

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

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

2 references

URL	Tags
https://github.com/0FuzzingQ/vuln/blob/master/skl…	x_refsource_MISC
https://scikit-learn.org/stable/modules/model_per…	x_refsource_MISC

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "providerMetadata": {
          "dateUpdated": "2024-08-04T12:11:18.980Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
          "shortName": "CVE"
        },
        "references": [
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://github.com/0FuzzingQ/vuln/blob/master/sklearn%20unserialize.md"
          },
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "n/a",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "n/a"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "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\u0027s responsibility to use the function in a secure manner"
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "description": "n/a",
              "lang": "en",
              "type": "text"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2020-05-18T11:16:54.000Z",
        "orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
        "shortName": "mitre"
      },
      "references": [
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/0FuzzingQ/vuln/blob/master/sklearn%20unserialize.md"
        },
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations"
        }
      ],
      "tags": [
        "disputed"
      ],
      "x_legacyV4Record": {
        "CVE_data_meta": {
          "ASSIGNER": "cve@mitre.org",
          "ID": "CVE-2020-13092",
          "STATE": "PUBLIC"
        },
        "affects": {
          "vendor": {
            "vendor_data": [
              {
                "product": {
                  "product_data": [
                    {
                      "product_name": "n/a",
                      "version": {
                        "version_data": [
                          {
                            "version_value": "n/a"
                          }
                        ]
                      }
                    }
                  ]
                },
                "vendor_name": "n/a"
              }
            ]
          }
        },
        "data_format": "MITRE",
        "data_type": "CVE",
        "data_version": "4.0",
        "description": {
          "description_data": [
            {
              "lang": "eng",
              "value": "** DISPUTED ** 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\u0027s responsibility to use the function in a secure manner."
            }
          ]
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "n/a"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://github.com/0FuzzingQ/vuln/blob/master/sklearn%20unserialize.md",
              "refsource": "MISC",
              "url": "https://github.com/0FuzzingQ/vuln/blob/master/sklearn%20unserialize.md"
            },
            {
              "name": "https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations",
              "refsource": "MISC",
              "url": "https://scikit-learn.org/stable/modules/model_persistence.html#security-maintainability-limitations"
            }
          ]
        }
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
    "assignerShortName": "mitre",
    "cveId": "CVE-2020-13092",
    "datePublished": "2020-05-15T18:41:33.000Z",
    "dateReserved": "2020-05-15T00:00:00.000Z",
    "dateUpdated": "2024-08-04T12:11:18.980Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

GHSA-JJW5-XXJ6-PCV5

Vulnerability from github – Published: 2022-05-24 17:17 – Updated: 2024-10-22 17:21

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. 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.

Severity

9.8 (Critical)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "scikit-learn"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "last_affected": "0.23.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2020-13092"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2024-04-22T22:55:41Z",
    "nvd_published_at": "2020-05-15T19:15:00Z",
    "severity": "CRITICAL"
  },
  "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\u0027s responsibility to use the function in a secure manner.",
  "id": "GHSA-jjw5-xxj6-pcv5",
  "modified": "2024-10-22T17:21:50Z",
  "published": "2022-05-24T17:17:59Z",
  "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"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "scikit-learn Deserialization of Untrusted Data"
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.

Action not permitted

PYSEC-2020-107

CVE-2020-13092 (GCVE-0-2020-13092)

GHSA-JJW5-XXJ6-PCV5

Tags

Sightings

Nomenclature

Related by attack behaviour