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CVE-2026-5766 (GCVE-0-2026-5766)

Vulnerability from cvelistv5 – Published: 2026-05-05 14:49 – Updated: 2026-05-06 15:25
VLAI
Title
Potential denial-of-service vulnerability in ASGI requests via file upload limit bypass
Summary
An issue was discovered in 6.0 before 6.0.5 and 5.2 before 5.2.14. ASGI requests with a missing or understated `Content-Length` header can bypass the `FILE_UPLOAD_MAX_MEMORY_SIZE` limit, potentially loading large files into memory and causing service degradation. As a reminder, Django expects a limit to be configured at the web server level rather than solely relying on `FILE_UPLOAD_MAX_MEMORY_SIZE`. Earlier, unsupported Django series (such as 5.0.x, 4.1.x, and 3.2.x) were not evaluated and may also be affected. Django would like to thank Kyle Agronick for reporting this issue.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-05-05 17:03 UTC
CWE
  • CWE-130 - Improper Handling of Length Parameter Inconsistency
Assigner
Impacted products
Vendor Product Version CPE status
djangoproject Django Affected: 6.0 , < 6.0.5 (python)
Unaffected: 6.0.5 (python)
Affected: 5.2 , < 5.2.14 (python)
Unaffected: 5.2.14 (python)
guessed Create a notification for this product.
Date Public
2026-05-05 09:00
Show details on NVD website

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              "url": "https://groups.google.com/g/django-announce"
            },
            {
              "name": "Django security releases issued: 6.0.5 and 5.2.14",
              "tags": [
                "vendor-advisory"
              ],
              "url": "https://www.djangoproject.com/weblog/2026/may/05/security-releases/"
            }
          ],
          "source": {
            "discovery": "EXTERNAL"
          },
          "timeline": [
            {
              "lang": "en",
              "time": "2024-05-12T10:32:17.000Z",
              "value": "Initial report received."
            },
            {
              "lang": "en",
              "time": "2026-04-07T10:32:20.000Z",
              "value": "Vulnerability confirmed."
            },
            {
              "lang": "en",
              "time": "2026-05-05T09:00:00.000Z",
              "value": "Security release issued."
            }
          ],
          "title": "Potential denial-of-service vulnerability in ASGI requests via file upload limit bypass",
          "x_generator": {
            "engine": "cvelib 1.8.0"
          }
        }
      },
      "cveMetadata": {
        "assignerOrgId": "6a34fbeb-21d4-45e7-8e0a-62b95bc12c92",
        "assignerShortName": "DSF",
        "cveId": "CVE-2026-5766",
        "datePublished": "2026-05-05T14:49:19.715Z",
        "dateReserved": "2026-04-07T19:29:07.042Z",
        "dateUpdated": "2026-05-05T14:49:19.715Z",
        "state": "PUBLISHED"
      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.2"
    }
  }
}



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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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