Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2023-3197 is a critical-severity SQL Injection (CWE-89) vulnerability in Inspireui Mstore Api. 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 11% 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.
The MStore API plugin for WordPress is vulnerable to unauthenticated blind SQL injection via the 'id' parameter in versions up to and including 4.0.1. The flaw stems from insufficient escaping of user-supplied input and inadequate preparation of SQL queries, allowing attackers to inject additional clauses into existing database statements. The issue is tracked as CWE-89 and carries a CVSS 3.1 score of 9.8.
Unauthenticated remote attackers can exploit the vulnerability over the network without any credentials or user interaction. Successful exploitation enables extraction of sensitive database contents and, given the high impact metrics, may also permit modification or deletion of data, resulting in full compromise of the confidentiality, integrity, and availability of the affected WordPress site.
The referenced Wordfence advisory and WordPress plugin changeset 2929891 indicate that the vendor addressed the issue by updating the affected helper file in the MStore API repository; site administrators should apply the patched version beyond 4.0.1. The EPSS score reached a peak of 0.3996 after disclosure before settling at the current value of 0.2957.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-43875
Vulnerability Data
The MStore API plugin for WordPress is vulnerable to Unauthenticated Blind SQL Injection via the 'id' parameter in versions up to, and including, 4.0.1 due to insufficient escaping on the user supplied parameters and lack of sufficient preparation on the…
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existing SQL query. This makes it possible for unauthenticated attackers to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database.
- 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.