Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:NSummary
CVE-2023-2566 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Open-Emr Openemr. Its CVSS base score is 4.8 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 42th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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-2023-2566 is a stored cross-site scripting vulnerability (CWE-79) affecting the openemr/openemr repository prior to version 7.0.1. The flaw carries a CVSS 3.1 score of 4.8 with the vector AV:N/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:N, indicating a network-reachable issue that requires high privileges and user interaction while producing limited confidentiality and integrity impact with changed scope.
An authenticated user holding administrative privileges can inject persistent malicious scripts into the application. When another user views the affected content, the script executes in that user's browser context, enabling actions such as limited data theft or unauthorized modifications within the application's security boundary.
The referenced commit a2adac7320dfc631b1da688c3b04f54b8240fc7b in the OpenEMR repository addresses the issue, and the associated huntr.dev report documents the coordinated disclosure. Upgrading to version 7.0.1 or applying the equivalent patch therefore constitutes the primary mitigation. The EPSS score has remained flat at 0.2332 with no reported real-world exploitation.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-34044
Vulnerability Data
Cross-site Scripting (XSS) - Stored in GitHub repository openemr/openemr prior to 7.0.1.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.
Validates web inputs to reject script-related content that could produce XSS.
Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.
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 introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
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.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.
Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.
Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.