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PYSEC-2024-318

Vulnerability from pysec - Published: 2024-06-27 19:15 - Updated: 2026-07-13 05:48
VLAI
Details

A Regular Expression Denial of Service (ReDoS) vulnerability exists in the latest version of gaizhenbiao/chuanhuchatgpt. The vulnerability is located in the filter_history function within the utils.py module. This function takes a user-provided keyword and attempts to match it against chat history filenames using a regular expression search. Due to the lack of sanitization or validation of the keyword parameter, an attacker can inject a specially crafted regular expression, leading to a denial of service condition. This can cause severe degradation of service performance and potential system unavailability.

Impacted products
Name purl
chuanhuchatgpt pkg:pypi/chuanhuchatgpt
Aliases

{
  "affected": [
    {
      "ecosystem_specific": {},
      "package": {
        "ecosystem": "PyPI",
        "name": "chuanhuchatgpt",
        "purl": "pkg:pypi/chuanhuchatgpt"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "last_affected": "20240410"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "3.2.5"
      ]
    }
  ],
  "aliases": [
    "CVE-2024-6038"
  ],
  "details": "A Regular Expression Denial of Service (ReDoS) vulnerability exists in the latest version of gaizhenbiao/chuanhuchatgpt. The vulnerability is located in the filter_history function within the utils.py module. This function takes a user-provided keyword and attempts to match it against chat history filenames using a regular expression search. Due to the lack of sanitization or validation of the keyword parameter, an attacker can inject a specially crafted regular expression, leading to a denial of service condition. This can cause severe degradation of service performance and potential system unavailability.",
  "id": "PYSEC-2024-318",
  "modified": "2026-07-13T05:48:14.300439Z",
  "published": "2024-06-27T19:15:19.040Z",
  "references": [
    {
      "type": "FIX",
      "url": "https://github.com/gaizhenbiao/chuanhuchatgpt/commit/fcdd5fd6b05ef537a1db185ab115758d87e1ba3f"
    },
    {
      "type": "EVIDENCE",
      "url": "https://huntr.com/bounties/d41cca0a-82bc-4cbf-a52a-928d304fb42d"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}



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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

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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.
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  • 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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