Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2026-23492 is a high-severity SQL Injection (CWE-89) vulnerability in Pimcore Pimcore. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 35th percentile by exploit likelihood (below the median); 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-2026-23492 is a SQL injection vulnerability (CWE-89) affecting Pimcore, an open-source Data & Experience Management Platform. Versions prior to 12.3.1 and 11.5.14 contain an incomplete patch in the Admin Search Find API, building on mitigations from CVE-2023-30848 that removed SQL comments (--) and caught syntax errors. This fix is insufficient, enabling blind SQL injection via payloads that bypass those checks and allow inference of database information through the admin interface.
An authenticated attacker with low privileges (PR:L) can exploit this vulnerability remotely (AV:N) with low attack complexity (AC:L) and no user interaction (UI:N). Exploitation leads to database information disclosure via blind techniques and carries high impacts on confidentiality, integrity, and availability (C:H/I:H/A:H), as reflected in its CVSS v3.1 base score of 8.8 (S:U).
Pimcore addresses this issue in versions 12.3.1 and 11.5.14. Mitigation details are provided in the patching commit at https://github.com/pimcore/pimcore/commit/25ad8674886f2b938243cbe13e33e204a2e35cc3 and the GitHub security advisory at https://github.com/pimcore/pimcore/security/advisories/GHSA-qvr7-7g55-69xj.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-2449
Vulnerability Data
Pimcore is an Open Source Data & Experience Management Platform. Prior to 12.3.1 and 11.5.14, an incomplete SQL injection patch in the Admin Search Find API allows an authenticated attacker to perform blind SQL injection. Although CVE-2023-30848 attempted to mitigate…
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SQL injection by removing SQL comments (--) and catching syntax errors, the fix is insufficient. Attackers can still inject SQL payloads that do not rely on comments and infer database information via blind techniques. This vulnerability affects the admin interface and can lead to database information disclosure. This vulnerability is fixed in 12.3.1 and 11.5.14.
- 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.