Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2026-25746 is a high-severity SQL Injection (CWE-89) vulnerability in Open-Emr Openemr. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 13% of CVEs by exploit likelihood; 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-2026-25746 is a SQL injection vulnerability (CWE-89) affecting OpenEMR, a free and open source electronic health records and medical practice management application. The flaw exists in the prescription listing functionality due to insufficient input validation and impacts all versions prior to 8.0.0. Published on 2026-02-25, it carries a CVSS v3.1 base score of 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H), indicating high severity with network accessibility, low attack complexity, and significant impacts on confidentiality, integrity, and availability.
Authenticated attackers with low privileges can exploit this vulnerability remotely over the network without user interaction. By injecting malicious SQL payloads into the prescription listing interface, they can manipulate database queries, potentially extracting sensitive patient data, modifying records, or disrupting service availability.
Mitigation is addressed in OpenEMR version 8.0.0, which resolves the input validation issue. Relevant code locations include library/classes/Controller.class.php (line 77), controller.php (line 6), controllers/C_Prescription.class.php (line 180), and library/classes/Prescription.class.php (line 1148), as detailed in the project's GitHub repository. A proof-of-concept is available at https://github.com/ChrisSub08/CVE-2026-25746_SqlInjectionVulnerabilityOpenEMR7.0.4.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-8714
Vulnerability Data
OpenEMR is a free and open source electronic health records and medical practice management application. Versions prior to 8.0.0 contain a SQL injection vulnerability in prescription that can be exploited by authenticated attackers. The vulnerability exists due to insufficient input…
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validation in the prescription listing functionality. Version 8.0.0 fixes the vulnerability.
- 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.