Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/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-2025-63532 is a critical-severity SQL Injection (CWE-89) vulnerability in Shridharshukl Blood Bank Management System. Its CVSS base score is 9.6 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 32th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
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-2025-63532 is a SQL injection vulnerability (CWE-89) affecting Blood Bank Management System 1.0, specifically within the cancel.php component. Published on 2025-12-01T16:15:55.800, it carries a CVSS v3.1 base score of 9.6 (AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:N). The vulnerability arises because the application does not properly sanitize user-supplied input in SQL queries, enabling attackers to inject arbitrary SQL code through manipulation of the search field.
An attacker with low privileges (PR:L) can exploit this vulnerability remotely over the network (AV:N) with low attack complexity (AC:L) and without requiring user interaction (UI:N). Successful exploitation alters the scope (S:C) and results in high impacts to confidentiality (C:H) and integrity (I:H), with no availability impact (A:N). By injecting SQL via the search field, the attacker can bypass authentication mechanisms and gain unauthorized access to the system.
Advisories and additional details are available in the provided references, including a Google Drive document at https://drive.google.com/file/d/12yeOXW_sN69QjsQtW0_k9AGqozi1s0di/view?usp=sharing, the Blood Bank Management System GitHub repository at https://github.com/Shridharshukl/Blood-Bank-Management-System, and a CVE-specific page at https://github.com/kiwi865/CVEs/blob/main/CVE-2025-63532.md.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-199994
Vulnerability Data
A SQL injection vulnerability exists in the Blood Bank Management System 1.0 within the cancel.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 search field,…
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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.