CVE-2024-30163
SQLi in Invisioncommunity 4.4.0 – 4.7.16
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-30163 is a critical-severity SQL Injection (CWE-89) vulnerability in Invisioncommunity Invisioncommunity. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 5% 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-2024-30163 is a SQL injection vulnerability in Invision Community versions prior to 4.7.16. The flaw resides in the _categoryView() method of applications/nexus/modules/front/store/store.php, where the filter request parameter is passed directly into SQL queries without adequate sanitization, enabling CWE-89 injection.
Unauthenticated remote attackers can exploit the issue over the network to perform blind SQL injection. Successful exploitation grants full read, write, and delete access to the underlying database, corresponding to the CVSS 9.8 rating that reflects no required authentication, privileges, or user interaction.
The vendor addressed the flaw in the 4.7.16 release, as noted in the official Invision Community release notes. Public full-disclosure posts on Seclists reference the same patch version for remediation.
The associated EPSS score has remained stable at its peak value of 0.4637 with no material upward trajectory after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-28099
Vulnerability Data
Invision Community before 4.7.16 allow SQL injection via the applications/nexus/modules/front/store/store.php IPS\nexus\modules\front\store\_store::_categoryView() method, where user input passed through the filter request parameter is not properly sanitized before being used to execute SQL queries. This can be exploited by unauthenticated attackers to…
more
carry out Blind SQL Injection attacks.
- 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.