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CVE-2019-16785 (GCVE-0-2019-16785)

Vulnerability from cvelistv5 – Published: 2019-12-20 23:00 – Updated: 2024-08-05 01:24
VLAI
Title
HTTP Request Smuggling: LF vs CRLF handling in Waitress
Summary
Waitress through version 1.3.1 implemented a "MAY" part of the RFC7230 which states: "Although the line terminator for the start-line and header fields is the sequence CRLF, a recipient MAY recognize a single LF as a line terminator and ignore any preceding CR." Unfortunately if a front-end server does not parse header fields with an LF the same way as it does those with a CRLF it can lead to the front-end and the back-end server parsing the same HTTP message in two different ways. This can lead to a potential for HTTP request smuggling/splitting whereby Waitress may see two requests while the front-end server only sees a single HTTP message. This issue is fixed in Waitress 1.4.0.
CWE
  • CWE-444 - Inconsistent Interpretation of HTTP Requests ('HTTP Request Smuggling')
Impacted products
Vendor Product Version CPE status
Pylons Waitress Affected: <= 1.3.1 , ≤ 1.3.1 (custom)
guessed Create a notification for this product.
Show details on NVD website

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          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "url": "https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/LYEOTGWJZVKPRXX2HBNVIYWCX73QYPM5/"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
              "Patch",
              "Third Party Advisory"
            ],
            "url": "https://www.oracle.com/security-alerts/cpuapr2022.html"
          }
        ],
        "sourceIdentifier": "security-advisories@github.com",
        "vulnStatus": "Modified",
        "weaknesses": [
          {
            "description": [
              {
                "lang": "en",
                "value": "CWE-444"
              }
            ],
            "source": "security-advisories@github.com",
            "type": "Secondary"
          },
          {
            "description": [
              {
                "lang": "en",
                "value": "CWE-444"
              }
            ],
            "source": "nvd@nist.gov",
            "type": "Primary"
          }
        ]
      }
    },
    "redhat_vex": {
      "aggregate_severity": "Important",
      "current_release_date": "2026-07-03T02:07:15+00:00",
      "cve": "CVE-2019-16785",
      "id": "CVE-2019-16785",
      "initial_release_date": "2019-12-20T00:00:00+00:00",
      "product_status:fixed": "13",
      "product_status:known_affected": "7",
      "source": "Red Hat CSAF VEX",
      "status": "final",
      "title": "waitress: HTTP request smuggling through LF vs CRLF handling",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2019/cve-2019-16785.json",
      "version": "3"
    }
  }
}



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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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Detection rules are retrieved from Rulezet.

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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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