CVE-2017-15010 (GCVE-0-2017-15010)

Vulnerability from cvelistv5 – Published: 2017-10-03 16:00 – Updated: 2024-08-05 19:42
VLAI
Summary
A ReDoS (regular expression denial of service) flaw was found in the tough-cookie module before 2.3.3 for Node.js. An attacker that is able to make an HTTP request using a specially crafted cookie may cause the application to consume an excessive amount of CPU.
CWE
  • n/a
References
Date Public
2017-10-03 00:00
Show details on NVD website

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            "url": "https://access.redhat.com/errata/RHSA-2018:1264"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
              "Issue Tracking",
              "Vendor Advisory"
            ],
            "url": "https://github.com/salesforce/tough-cookie/issues/92"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "url": "https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/6VEBDTGNHVM677SLZDEHMWOP3ISMZSFT/"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
              "Third Party Advisory"
            ],
            "url": "https://nodesecurity.io/advisories/525"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
              "Patch",
              "Third Party Advisory"
            ],
            "url": "https://snyk.io/vuln/npm:tough-cookie:20170905"
          }
        ],
        "sourceIdentifier": "cve@mitre.org",
        "vulnStatus": "Modified",
        "weaknesses": [
          {
            "description": [
              {
                "lang": "en",
                "value": "CWE-400"
              }
            ],
            "source": "nvd@nist.gov",
            "type": "Primary"
          }
        ]
      }
    },
    "redhat_vex": {
      "aggregate_severity": "Moderate",
      "current_release_date": "2026-06-28T11:11:11+00:00",
      "cve": "CVE-2017-15010",
      "id": "CVE-2017-15010",
      "initial_release_date": "2017-09-05T00:00:00+00:00",
      "product_status:fixed": "149",
      "product_status:known_not_affected": "3",
      "source": "Red Hat CSAF VEX",
      "status": "final",
      "title": "nodejs-tough-cookie: Regular expression denial of service",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2017/cve-2017-15010.json",
      "version": "3"
    },
    "suse_vex": {
      "aggregate_severity": "moderate",
      "current_release_date": "2025-07-01T02:30:50Z",
      "cve": "CVE-2017-15010",
      "id": "CVE-2017-15010",
      "initial_release_date": "2023-02-15T04:38:56Z",
      "source": "SUSE CSAF VEX",
      "status": "interim",
      "title": "SUSE CVE CVE-2017-15010",
      "url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2017-15010.json",
      "version": "6"
    }
  }
}



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Taxonomy of the tags.


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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.

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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.


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