Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:NSummary
CVE-2025-64459 is a critical-severity SQL Injection (CWE-89) vulnerability in Djangoproject Django. Its CVSS base score is 9.1 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 3% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2025-64459 is a SQL injection vulnerability affecting Django, a Python web framework. It impacts versions 5.1 before 5.1.14, 4.2 before 4.2.26, and 5.2 before 5.2.8, specifically in the ORM methods QuerySet.filter(), QuerySet.exclude(), and QuerySet.get(), as well as the Q() class. The flaw arises when a suitably crafted dictionary, expanded via dictionary expansion, is passed as the _connector argument, enabling SQL injection. Earlier unsupported Django series, such as 5.0.x, 4.1.x, and 3.2.x, were not evaluated but may also be vulnerable. The issue carries a CVSS v3.1 base score of 9.1 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N) and is classified under CWE-89.
Remote attackers require no privileges or user interaction to exploit this vulnerability over the network with low complexity. Exploitation occurs if untrusted input can influence the _connector argument in the affected ORM methods, allowing attackers to inject and execute arbitrary SQL queries. Successful attacks can result in high confidentiality and integrity impacts, such as unauthorized data access, modification, or extraction from the underlying database.
Django's security advisories recommend upgrading to the patched releases: 5.1.14, 4.2.26, or 5.2.8. Details are available in the official security release notes at https://docs.djangoproject.com/en/dev/releases/security/, the django-announce group at https://groups.google.com/g/django-announce, and the November 5, 2025 weblog post at https://www.djangoproject.com/weblog/2025/nov/05/security-releases/. The vulnerability was reported by cyberstan.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-37763
Vulnerability Data
An issue was discovered in 5.1 before 5.1.14, 4.2 before 4.2.26, and 5.2 before 5.2.8. The methods `QuerySet.filter()`, `QuerySet.exclude()`, and `QuerySet.get()`, and the class `Q()`, are subject to SQL injection when using a suitably crafted dictionary, with dictionary expansion, as…
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the `_connector` argument. 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 cyberstan for reporting this issue.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V6.2.5
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover SQLi flaws before deployment but does not stop their introduction.
Input validation directly stops untrusted data from reaching SQL query construction without neutralization.
Secure engineering principles require parameterized queries and input sanitization that structurally eliminate SQLi.
System monitoring can identify attempted SQLi exploitation via anomalous queries after the weakness exists.
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 target injection flaws during coding and review so largely prevent CWE-89 introduction, yet the single broad outcome leaves residual risk from incomplete neutralization techniques or missed edge cases.
Training raises developer awareness of SQLi risks and can reduce introduction likelihood (partial) but removes none of the actual coding flaw's risk by itself since technical neutralization is still required.
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.
The same secure-coding and static-analysis activities surface missing neutralization of SQL metacharacters before the system is accepted.
Early warnings and shared best-practice information help organizations apply the latest remediation techniques against SQL-injection vulnerabilities.
Threat-intelligence feeds that surface new SQL-injection campaigns enable rapid updates to query-construction defenses and detection signatures before exploitation occurs.
Secure-coding rules and security testing phases mandate the use of parameterized queries or equivalent escaping, preventing the construction of dynamic SQL statements from untrusted input.
Language-specific secure coding rules, peer review and SAST together prevent the construction of SQL statements from untrusted data without proper parameterization or escaping.