CVE-2024-45231
Djangoproject Django 4.2.0 – 4.2.16
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:NSummary
CVE-2024-45231 is a medium-severity Observable Discrepancy (CWE-203) vulnerability in Djangoproject Django. Its CVSS base score is 5.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Account Discovery (T1087); ranked in the top 47% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to IA-6 (Authentication Feedback) and SI-11 (Error Handling) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-3135
Vulnerability Data
An issue was discovered in Django v5.1.1, v5.0.9, and v4.2.16. The django.contrib.auth.forms.PasswordResetForm class, when used in a view implementing password reset flows, allows remote attackers to enumerate user e-mail addresses by sending password reset requests and observing the outcome (only…
more
when e-mail sending is consistently failing).
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 1 hardening rule · 1 OS baseline
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Mitigating Controls (NIST 800-53 r5) AI
Obscures authentication feedback so that success/failure differences are not observable to attackers.
Requires error messages to avoid revealing exploitable details, directly stopping observable response discrepancies.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly prevent observable response discrepancies via consistent error handling and timing.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Accurate, synchronized timestamps reduce observable timing discrepancies that an attacker could exploit to infer sensitive information or distinguish between success and failure paths.