Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:NSummary
CVE-2023-35924 is a high-severity SQL Injection (CWE-89) vulnerability in Glpi-Project Glpi. 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 1% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
GLPI, an open-source IT asset management application, contains a SQL injection vulnerability (CWE-89) in its native inventory endpoint. The flaw affects versions 10.0.0 through 10.0.7 and carries a CVSS 3.1 score of 8.6. By default the endpoint accepts unauthenticated requests, allowing remote attackers to submit crafted inventory data that is processed directly in database queries.
An unauthenticated network attacker can leverage the endpoint to extract arbitrary data from the GLPI database. The attack requires no user interaction and results in a confidentiality breach that affects resources beyond the vulnerable component itself, while leaving integrity and availability untouched.
The project addressed the issue in release 10.0.8. Official advisories recommend upgrading to that version or, as a temporary workaround, disabling the native inventory feature. The associated EPSS score has remained flat at 0.1785 with no material increase since disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-39915
Vulnerability Data
GLPI is a free asset and IT management software package. Starting in version 10.0.0 and prior to version 10.0.8, GLPI inventory endpoint can be used to drive a SQL injection attack. By default, GLPI inventory endpoint requires no authentication. Version…
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10.0.8 has a patch for this issue. As a workaround, one may disable native inventory.
- 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.