CVE-2026-108147 (GCVE-0-2026-108147)

Vulnerability from cvelistv5 – Published: 2026-11-03 15:41 – Updated: 2026-11-03 18:26
VLAI
Title
Potential memory exhaustion in MultiPartParser via base64-encoded file upload
Summary
An issue was discovered in Django 6.1 before 6.1.3, 6.0.4 before 6.0.10, and 5.2.13 before 5.2.19. `django.http.multipartparser.MultiPartParser` is subject to excessive memory consumption when processing multipart file uploads with base64 `Content-Transfer-Encoding`, which could be buffered entirely in memory before being passed to upload handlers. Earlier, unsupported Django series (such as 5.1.x, 5.0.x, and 4.2.x) were not evaluated and may also be affected. Django would like to thank Ignacy Kujawa for reporting this issue.
Severity
5.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
6.9 (Medium)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
SSVC
Exploitation: none Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-11-03 17:51 UTC
CWE
  • CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
DSF CNA under the mitre root
CNA scorecard B 86/100 over 24 records in the last 180 days details
References
Impacted products
Vendor Product Version CPE status
djangoproject Django Affected: 6.1 , < 6.1.3 (python)
Unaffected: 6.1.3 (python)
Unaffected: 6.0 , < 6.0.4 (python)
Affected: 6.0.4 , < 6.0.10 (python)
Unaffected: 6.0.10 (python)
Unaffected: 5.2 , < 5.2.13 (python)
Affected: 5.2.13 , < 5.2.19 (python)
Unaffected: 5.2.19 (python)
guessed Create a notification for this product.
Date Public
2026-11-03 09:30
Credits
Ignacy Kujawa Jake Howard Natalia Bidart Natalia Bidart Jake Howard Jacob Walls
Show details on NVD website
To clipboard 

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                  "value": "\u003cp\u003eAn issue was discovered in Django 6.1 before 6.1.3, 6.0.4 before 6.0.10, and 5.2.13 before 5.2.19.\u003c/p\u003e\u003cp\u003e\u003ccode\u003edjango.http.multipartparser.MultiPartParser\u003c/code\u003e is subject to excessive memory consumption when processing multipart file uploads with base64 \u003ccode\u003eContent-Transfer-Encoding\u003c/code\u003e, which could be buffered entirely in memory before being passed to upload handlers.\u003c/p\u003e\u003cp\u003eEarlier, unsupported Django series (such as 5.1.x, 5.0.x, and 4.2.x) were not evaluated and may also be affected.\u003c/p\u003e\u003cp\u003eDjango would like to thank Ignacy Kujawa for reporting this issue.\u003c/p\u003e"
                }
              ],
              "value": "An issue was discovered in Django 6.1 before 6.1.3, 6.0.4 before 6.0.10, and 5.2.13 before 5.2.19.\n`django.http.multipartparser.MultiPartParser` is subject to excessive memory consumption when processing multipart file uploads with base64 `Content-Transfer-Encoding`, which could be buffered entirely in memory before being passed to upload handlers.\nEarlier, unsupported Django series (such as 5.1.x, 5.0.x, and 4.2.x) were not evaluated and may also be affected.\nDjango would like to thank Ignacy Kujawa for reporting this issue."
            }
          ],
          "impacts": [
            {
              "capecId": "CAPEC-130",
              "descriptions": [
                {
                  "lang": "en",
                  "value": "CAPEC-130: Excessive Allocation"
                }
              ]
            }
          ],
          "metrics": [
            {
              "other": {
                "content": {
                  "namespace": "https://docs.djangoproject.com/en/dev/internals/security/#security-issue-severity-levels",
                  "value": "low"
                },
                "type": "Django severity rating"
              }
            },
            {
              "cvssV3_1": {
                "baseScore": 5.3,
                "baseSeverity": "MEDIUM",
                "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
                "version": "3.1"
              }
            },
            {
              "cvssV4_0": {
                "baseScore": 6.9,
                "baseSeverity": "MEDIUM",
                "vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
                "version": "4.0"
              }
            }
          ],
          "problemTypes": [
            {
              "descriptions": [
                {
                  "cweId": "CWE-770",
                  "description": "CWE-770: Allocation of Resources Without Limits or Throttling",
                  "lang": "en",
                  "type": "CWE"
                }
              ]
            }
          ],
          "providerMetadata": {
            "dateUpdated": "2026-11-03T15:41:38.167Z",
            "orgId": "6a34fbeb-21d4-45e7-8e0a-62b95bc12c92",
            "shortName": "DSF"
          },
          "references": [
            {
              "name": "Django security archive",
              "tags": [
                "vendor-advisory"
              ],
              "url": "https://docs.djangoproject.com/en/dev/releases/security/"
            },
            {
              "name": "Django releases announcements",
              "tags": [
                "mailing-list"
              ],
              "url": "https://groups.google.com/g/django-announce"
            },
            {
              "tags": [
                "patch"
              ],
              "url": "https://github.com/django/django/commit/5d95d9236fa4ededfb1931c60a65432385ece85f"
            },
            {
              "tags": [
                "patch"
              ],
              "url": "https://github.com/django/django/commit/8b435411f11d69a0dd41a8837654323502e6058e"
            },
            {
              "tags": [
                "patch"
              ],
              "url": "https://github.com/django/django/commit/a29ee4a55acedbe7ba0cb4d2db28c4e4d2848e02"
            },
            {
              "tags": [
                "patch"
              ],
              "url": "https://github.com/django/django/commit/4bd1f59a80adafddbd47527c66d92d6a224244d8"
            },
            {
              "name": "Django security releases issued: 6.1.3, 6.0.10, and 5.2.19",
              "tags": [
                "vendor-advisory"
              ],
              "url": "https://www.djangoproject.com/weblog/2026/nov/03/security-releases/"
            }
          ],
          "source": {
            "discovery": "EXTERNAL"
          },
          "timeline": [
            {
              "lang": "en",
              "time": "2026-09-07T12:00:00.000Z",
              "value": "Initial report received."
            },
            {
              "lang": "en",
              "time": "2026-10-15T00:00:00.000Z",
              "value": "Vulnerability confirmed."
            },
            {
              "lang": "en",
              "time": "2026-11-03T09:30:00.000Z",
              "value": "Security release issued."
            }
          ],
          "title": "Potential memory exhaustion in MultiPartParser via base64-encoded file upload",
          "x_generator": {
            "engine": "cvelib 1.8.0"
          }
        }
      },
      "cveMetadata": {
        "assignerOrgId": "6a34fbeb-21d4-45e7-8e0a-62b95bc12c92",
        "assignerShortName": "DSF",
        "cveId": "CVE-2026-108147",
        "datePublished": "2026-11-03T15:41:38.167Z",
        "dateReserved": "2026-10-09T15:00:14.261Z",
        "dateUpdated": "2026-11-03T18:26:37.685Z",
        "state": "PUBLISHED"
      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.2"
    }
  }
}



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Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.

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.
Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

JSON
How durations are calculated

Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.

Each result shows its source dates. A negative interval means the end event came first; when date-only inputs leave the order open, the result says so. Date-only inputs are approximate. The earliest evidence wins: KEV report dates and sightings are labelled as such. Records describing another vulnerability are listed but never calculated from, and a PoC alone does not establish exploitation. Missing patch evidence does not prove that no patch exists. Filters below change the event list only.

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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.