CVE-2025-64495
Published: 08 November 2025
Summary
CVE-2025-64495 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Openwebui Open Webui. Its CVSS base score is 8.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique JavaScript (T1059.007); ranked at the 1.6th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Privacy and Disclosure risk domain.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-38257
Vulnerability details
Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. In versions 0.6.34 and below, the functionality that inserts custom prompts into the chat window is vulnerable to DOM XSS when 'Insert Prompt as Rich Text' is…
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enabled, since the prompt body is assigned to the DOM sink .innerHtml without sanitisation. Any user with permissions to create prompts can abuse this to plant a payload that could be triggered by other users if they run the corresponding / command to insert the prompt. This issue is fixed in version 0.6.35.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: artificial intelligence, open webui
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Stored DOM XSS enables arbitrary JavaScript execution (T1059.007, T1203) in victim browsers for session token theft from localStorage (T1539, ATO) and chained API abuse for admin RCE (T1068).
Affected Assets
Mitigating Controls
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.