CVE-2023-37472
SQLi in Eng Knowage 6.1.0 – 8.1.8
Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-37472 is a high-severity SQL Injection (CWE-89) vulnerability in Eng Knowage. Its CVSS base score is 7.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 49% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-41367
Vulnerability Data
Knowage is an open source suite for business analytics. The application often use user supplied data to create HQL queries without prior sanitization. An attacker can create specially crafted HQL queries that will break subsequent SQL queries generated by the…
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Hibernate engine. The endpoint `_/knowage/restful-services/2.0/documents/listDocument_` calls the `_countBIObjects_` method of the `_BIObjectDAOHibImpl_` object with the user supplied `_label_` parameter without prior sanitization. This can lead to SQL injection in the backing database. Other injections have been identified in the application as well. An authenticated attacker with low privileges could leverage this vulnerability in order to retrieve sensitive information from the database, such as account credentials or business information. This issue has been addressed in version 8.1.8. Users are advised to upgrade. There are no known workarounds for this vulnerability.
- 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
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
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.