Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-2039 is a medium-severity Injection (CWE-74) vulnerability in Code-Projects Blood Bank Management System. Its CVSS base score is 5.1 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 40th 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-2025-2039 is a critical SQL injection vulnerability in code-projects Blood Bank Management System version 1.0. The issue affects an unknown function within the file /admin/delete_members.php, where manipulation of the member_id argument enables SQL injection. Published on 2025-03-06, it carries a CVSS v3.1 base score of 4.7 (AV:N/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:L) and is associated with CWE-74 (Improper Neutralization of Special Elements used in an SQL Command) and CWE-89 (SQL Injection).
The vulnerability can be exploited remotely by an attacker with high privileges (PR:H), such as an authenticated admin user. Successful exploitation allows limited impacts: low confidentiality (C:L), integrity (I:L), and availability (A:L) effects, potentially enabling unauthorized data access, modification, or disruption within the database scope. A public exploit disclosure exists, increasing the risk of targeted attacks.
Advisories and related details are available from sources including the project site at https://code-projects.org/, a GitHub proof-of-concept at https://github.com/intercpt/XSS1/blob/main/SQL4.md, and VulDB entries at https://vuldb.com/?ctiid.298782, https://vuldb.com/?id.298782, and https://vuldb.com/?submit.512564, which may provide further guidance on detection or remediation.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-7474
Vulnerability Data
A vulnerability classified as critical has been found in code-projects Blood Bank Management System 1.0. Affected is an unknown function of the file /admin/delete_members.php. The manipulation of the argument member_id leads to sql injection. It is possible to launch the…
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attack remotely. The exploit has been disclosed to the public and may be used.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover SQLi flaws before deployment but does not stop their introduction.
SI-10 directly requires validation of information inputs to reject malformed or special-element content before it reaches downstream parsers.
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 require input validation and output encoding that prevent injection flaws.
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.
Security testing in development catches injection vulnerabilities before release.
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.
Logging supports detection of injection attempts but does not prevent the weakness.
Monitoring activities can identify active injection attacks after they occur.
Secure development life cycle mandates input validation and output encoding that directly prevent injection flaws.