Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:NSummary
CVE-2026-29187 is a high-severity SQL Injection (CWE-89) vulnerability in Open-Emr Openemr. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 39th 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-2026-29187 is a Blind SQL Injection vulnerability (CWE-89) affecting OpenEMR, a free and open source electronic health records and medical practice management application. The issue resides in the Patient Search functionality at /interface/new/new_search_popup.php in versions prior to 8.0.0.3. It enables attackers to execute arbitrary SQL commands by manipulating HTTP parameter keys rather than values, earning a CVSS v3.1 base score of 8.1 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N).
An authenticated attacker with low privileges can exploit this vulnerability over the network with low complexity and no user interaction required. Successful exploitation allows extraction of sensitive data or modification of database contents, resulting in high impacts to confidentiality and integrity, though availability remains unaffected.
Mitigation is addressed in OpenEMR version 8.0.0.3, which includes a patch as detailed in the project's GitHub security advisory (GHSA-2r7h-xm8v-m872), release notes, and the specific commit c61887aa7c83e83b3282db05246f1c00de3aa21d. Security practitioners should upgrade to this version promptly to remediate the vulnerability.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-16008
Vulnerability Data
OpenEMR is a free and open source electronic health records and medical practice management application. Prior to version 8.0.0.3, a Blind SQL Injection vulnerability exists in the Patient Search functionality (/interface/new/new_search_popup.php). The vulnerability allows an authenticated attacker to execute arbitrary…
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SQL commands by manipulating the HTTP parameter keys rather than the values. Version 8.0.0.3 contains a patch.
- 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.