Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:NSummary
CVE-2023-0594 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Grafana Grafana. Its CVSS base score is 7.3 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
Grafana, an open-source monitoring and observability platform, contains a stored cross-site scripting vulnerability in its trace view visualization that has existed since the 7.0 release branch. The flaw stems from insufficient sanitization of span attributes and resources, which are rendered without escaping when expanded in the visualization, allowing arbitrary JavaScript to be stored and later executed in users' browsers.
An authenticated user with the Editor role can modify a trace view panel to embed malicious JavaScript in span attributes. When a user with higher privileges, such as an Administrator, subsequently views the affected dashboard, the script executes in their context, enabling vertical privilege escalation such as password changes or other administrative actions.
The official Grafana advisory recommends upgrading to versions 8.5.21, 9.2.13, or 9.3.8 to remediate the issue; a corresponding NetApp advisory (NTAP-20230331-0007) addresses affected downstream products.
EPSS scores for the vulnerability rose from a low baseline to a peak of 0.5200 on 2026-02-03 before receding to the current value of 0.3664, indicating measurable post-disclosure exploitation interest.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-1146
Vulnerability Data
Grafana is an open-source platform for monitoring and observability. Starting with the 7.0 branch, Grafana had a stored XSS vulnerability in the trace view visualization. The stored XSS vulnerability was possible due the value of a span's attributes/resources were not…
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properly sanitized and this will be rendered when the span's attributes/resources are expanded. An attacker needs to have the Editor role in order to change the value of a trace view visualization to contain JavaScript. This means that vertical privilege escalation is possible, where a user with Editor role can change to a known password for a user having Admin role if the user with Admin role executes malicious JavaScript viewing a dashboard. Users may upgrade to version 8.5.21, 9.2.13 and 9.3.8 to receive a fix.
- 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.