Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2025-63531 is a critical-severity SQL Injection (CWE-89) vulnerability in Shridharshukl Blood Bank Management System. Its CVSS base score is 10.0 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 49th 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-2025-63531 is a SQL injection vulnerability (CWE-89) affecting Blood Bank Management System version 1.0, specifically within the receiverLogin.php component. The application fails to properly sanitize user-supplied input in SQL queries involving the remail and rpassword fields, allowing attackers to inject arbitrary SQL code. Published on 2025-12-01, it carries a CVSS v3.1 base score of 10.0 (AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:N), marking it as critical.
Remote attackers require no privileges, authentication, or user interaction to exploit this vulnerability over the network with low complexity. By manipulating the remail and rpassword fields during login attempts, they can bypass authentication mechanisms and gain unauthorized access to the system, potentially leading to high impacts on confidentiality and integrity across the affected scope.
Advisories and related resources, including potential exploit details and the source code repository, are available at the following references: https://drive.google.com/file/d/12yeOXW_sN69QjsQtW0_k9AGqozi1s0di/view?usp=sharing, https://github.com/Shridharshukl/Blood-Bank-Management-System, and https://github.com/kiwi865/CVEs/blob/main/CVE-2025-63531.md. No specific patches or mitigation steps are detailed in the primary description.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-199995
Vulnerability Data
A SQL injection vulnerability exists in the Blood Bank Management System 1.0 within the receiverLogin.php component. The application fails to properly sanitize user-supplied input in SQL queries, allowing an attacker to inject arbitrary SQL code. By manipulating the remail and…
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rpassword fields, an attacker can bypass authentication and gain unauthorized access to the system.
- 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.