GHSA-FJ7X-Q9J7-G6Q6

Vulnerability from github – Published: 2024-03-19 06:30 – Updated: 2024-03-20 15:24
VLAI
Summary
Black vulnerable to Regular Expression Denial of Service (ReDoS)
Details

Versions of the package black before 24.3.0 are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Exploiting this vulnerability is possible when running Black on untrusted input, or if you habitually put thousands of leading tab characters in your docstrings.

Severity
5.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "black"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "24.3.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2024-21503"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333",
      "CWE-75"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2024-03-20T15:24:01Z",
    "nvd_published_at": "2024-03-19T05:15:09Z",
    "severity": "MODERATE"
  },
  "details": "Versions of the package black before 24.3.0 are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.\n\nExploiting this vulnerability is possible when running Black on untrusted input, or if you habitually put thousands of leading tab characters in your docstrings.",
  "id": "GHSA-fj7x-q9j7-g6q6",
  "modified": "2024-03-20T15:24:01Z",
  "published": "2024-03-19T06:30:52Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-21503"
    },
    {
      "type": "WEB",
      "url": "https://github.com/psf/black/commit/f00093672628d212b8965a8993cee8bedf5fe9b8"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/psf/black"
    },
    {
      "type": "WEB",
      "url": "https://github.com/psf/black/releases/tag/24.3.0"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/black/PYSEC-2024-48.yaml"
    },
    {
      "type": "WEB",
      "url": "https://security.snyk.io/vuln/SNYK-PYTHON-BLACK-6256273"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Black vulnerable to Regular Expression Denial of Service (ReDoS)"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.





Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

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.



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.