Vulnerability-Lookup

GHSA-QWF5-72HQ-PG7X

Vulnerability from github – Published: 2026-08-05 12:31 – Updated: 2026-08-05 12:31

Details

DjangoCRM's massmail module renders user-controlled EmlMessage fields (subject, content) through Django's Template() constructor with no sanitization, in at least three locations: message_previews.py builds an f-string embedding message.subject/message.content directly into a Template() call; email_creators.py passes eml_message.subject directly as a template string to Template(); and helpers.py contains the same f-string interpolation pattern. An authenticated user with mass-mail message edit rights can inject Django template syntax ({{ }} / {% %}) that executes at render time, enabling disclosure of other users' data and password hashes via request context variables, CSRF token forgery, and inclusion of arbitrary registered templates.

Severity

8.1 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N

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{
  "affected": [],
  "aliases": [
    "CVE-2026-71239"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1336"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-05T11:16:26Z",
    "severity": "HIGH"
  },
  "details": "DjangoCRM\u0027s massmail module renders user-controlled EmlMessage fields (subject, content) through Django\u0027s Template() constructor with no sanitization, in at least three locations: message_previews.py builds an f-string embedding message.subject/message.content directly into a Template() call; email_creators.py passes eml_message.subject directly as a template string to Template(); and helpers.py contains the same f-string interpolation pattern. An authenticated user with mass-mail message edit rights can inject Django template syntax ({{ }} / {% %}) that executes at render time, enabling disclosure of other users\u0027 data and password hashes via request context variables, CSRF token forgery, and inclusion of arbitrary registered templates.",
  "id": "GHSA-qwf5-72hq-pg7x",
  "modified": "2026-08-05T12:31:32Z",
  "published": "2026-08-05T12:31:32Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-71239"
    },
    {
      "type": "WEB",
      "url": "https://github.com/DjangoCRM/django-crm"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2026-71239 (GCVE-0-2026-71239)

Vulnerability from cvelistv5 – Published: 2026-08-05 10:56 – Updated: 2026-08-10 11:45

Title

DjangoCRM - Server-Side Template Injection in Mass Mail Message Rendering

Summary

DjangoCRM's massmail module renders user-controlled EmlMessage fields (subject, content) through Django's Template constructor with no sanitization, in at least three locations: message_previews.py builds an f-string embedding message.subject/message.content directly into a Template call; email_creators.py passes eml_message.subject directly as a template string to Template; and helpers.py contains the same f-string interpolation pattern.

Severity

8.1 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N

SSVC

Exploitation: none Automatable: no Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-08-05 12:56 UTC

CWE

CWE-1336 - Improper Neutralization of Special Elements Used in a Template Engine

Assigner

TuranSec redhat root

References

1 reference

URL	Tags
https://github.com/DjangoCRM/django-crm	third-party-advisory

Impacted products

1 product

Vendor	Product	Version
DjangoCRM	django-crm	Affected: 0

Date Public

2026-08-05 10:56

Credits

Mirdavlatov Mira'zam

Show details on NVD website

JSON

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{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2026-71239",
                "options": [
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                  },
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                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-08-05T12:56:04.729854Z",
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          "product": "django-crm",
          "programFiles": [
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            "massmail/utils/email_creators.py",
            "massmail/utils/helpers.py"
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            }
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      "metrics": [
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            "confidentialityImpact": "HIGH",
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          "url": "https://github.com/DjangoCRM/django-crm"
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    "dateReserved": "2026-08-05T10:53:53.175Z",
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    "state": "PUBLISHED"
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  "dataType": "CVE_RECORD",
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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.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

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.