CVE-2025-69562
SQLi in Fabian Mobile Shop Management System 1.0
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2025-69562 is a critical-severity SQL Injection (CWE-89) vulnerability in Fabian Mobile Shop Management System. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 38th 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-2025-69562 affects code-projects Mobile Shop Management System 1.0, where a SQL injection vulnerability exists in the /insertmessage.php endpoint through the userid parameter. This flaw, classified under CWE-89, allows attackers to inject malicious SQL code due to insufficient input sanitization or parameterization. The vulnerability carries a CVSS v3.1 base score of 9.8, reflecting its critical severity with network accessibility, low attack complexity, no required privileges or user interaction, and high impacts on confidentiality, integrity, and availability.
Remote, unauthenticated attackers can exploit this vulnerability by sending crafted requests to the vulnerable endpoint, enabling arbitrary SQL query execution against the backend database. Successful exploitation could result in unauthorized data extraction, modification, or deletion, potentially compromising the entire database, including sensitive customer or business information stored in the mobile shop management system.
Advisories and references for mitigation are available at https://gist.github.com/lih28984-commits/a847a034c3bb626904dcc6ab7576257f and https://gitee.com/Z_180yc/zyy/issues/IDC5FU, which security practitioners should consult for detailed patch information, workaround guidance, or updated versions of the software.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-206390
Vulnerability Data
code-projects Mobile Shop Management System 1.0 is vulnerable to SQL Injection in /insertmessage.php via the userid parameter.
- 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.