Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:LSummary
CVE-2025-50979 is a high-severity SQL Injection (CWE-89) vulnerability in Nodebb Nodebb. Its CVSS base score is 8.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 6% 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-2025-50979 is a SQL injection vulnerability in NodeBB version 4.3.0, specifically affecting the search-categories API endpoint at /api/v3/search/categories. The search query parameter is not properly sanitized, permitting unauthenticated remote attackers to inject boolean-based blind and PostgreSQL error-based payloads. This flaw, published on 2025-08-27, is categorized under CWE-89 and carries a CVSS v3.1 base score of 8.6 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:L).
Unauthenticated attackers can exploit this vulnerability remotely over the network with low attack complexity and no user interaction or privileges required. Exploitation enables high confidentiality impact, such as extracting sensitive data from the underlying PostgreSQL database through blind SQL injection techniques, alongside low impacts to integrity and availability.
A proof-of-concept demonstrating the vulnerability is available at https://github.com/4rdr/proofs/blob/main/info/NodeBB-v4.3.0.-SQL-Injection-via-search-parameter.md, which security practitioners should review for additional technical details on exploitation and potential mitigations.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-25915
Vulnerability Data
NodeBB v4.3.0 is vulnerable to SQL injection in its search-categories API endpoint (/api/v3/search/categories). The search query parameter is not properly sanitized, allowing unauthenticated, remote attackers to inject boolean-based blind and PostgreSQL error-based payloads.
- 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.