Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:L/A:LSummary
CVE-2025-6023 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Grafana OSS (inferred from references). Its CVSS base score is 7.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 2% of CVEs by exploit likelihood; 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.
An open redirect vulnerability has been identified in Grafana OSS that can be exploited to achieve XSS attacks. The vulnerability was introduced in Grafana v11.5.0 and can be chained with path traversal vulnerabilities to achieve XSS. It is tracked under CWE-79 and CWE-601 with a CVSS 3.1 score of 7.6.
Unauthenticated remote attackers can supply crafted URLs that trigger the open redirect, leading victims to attacker-controlled destinations where malicious scripts execute in the context of the Grafana instance. Successful exploitation can result in theft of sensitive data, session hijacking, or limited modification of application state.
Grafana has published fixes in versions 12.0.2+security-01, 11.6.3+security-01, 11.5.6+security-01, 11.4.6+security-01, and 11.3.8+security-01. The vendor advisory and accompanying blog post recommend immediate upgrade to one of the patched releases and note that the issue affects all prior 11.5.x and later builds prior to these updates. The associated EPSS score has remained low and essentially flat since disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-21861
Vulnerability Data
An open redirect vulnerability has been identified in Grafana OSS that can be exploited to achieve XSS attacks. The vulnerability was introduced in Grafana v11.5.0. The open redirect can be chained with path traversal vulnerabilities to achieve XSS. Fixed in…
more
versions 12.0.2+security-01, 11.6.3+security-01, 11.5.6+security-01, 11.4.6+security-01 and 11.3.8+security-01
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V3.7.2V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
Information flow enforcement can restrict redirects to only approved/trusted destinations, stopping untrusted user-supplied URLs from being followed.
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.
Preventing access to attacker-controlled or malicious sites stops users from being redirected to untrusted locations via open-redirect or phishing links.
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.