Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2023-2756 is a high-severity SQL Injection (CWE-89) vulnerability in Pimcore Customer Management Framework. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 42% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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-2023-2756 is a SQL injection vulnerability, tracked as CWE-89, that affects the pimcore/customer-data-framework GitHub repository in versions prior to 3.3.10. The flaw carries a CVSS 3.1 score of 7.2 with a vector indicating network attack reachability, low complexity, and high privileges required.
An authenticated user with administrative privileges can supply crafted input over the network to execute arbitrary SQL commands, resulting in full compromise of confidentiality, integrity, and availability within the affected customer-data framework component. The issue was disclosed through a huntr.dev bounty and addressed via a specific code change in the repository.
Mitigation guidance centers on applying the patch referenced in the GitHub commit 76df151737b7964ce5169fdf9e27a0ad801757fe, which updates the package to version 3.3.10 or later.
EPSS for the CVE rose materially from a low baseline to a peak of 0.0697 before receding to its current value of 0.0004.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-1441
Vulnerability Data
SQL Injection in GitHub repository pimcore/customer-data-framework prior to 3.3.10.
- 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.