Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:NSummary
CVE-2026-26192 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Openwebui Open Webui. Its CVSS base score is 7.3 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 9th 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.
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-2026-26192 is a stored cross-site scripting (XSS) vulnerability, classified under CWE-79, affecting Open WebUI, a self-hosted artificial intelligence platform designed to operate entirely offline. In versions prior to 0.7.0, manually modifying chat history enables attackers to set the `html` property within document metadata. This triggers a frontend code path that treats document contents as HTML and renders them inside an iFrame during citation previews, with a CVSS v3.1 base score of 7.3 (AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:N).
An authenticated attacker with low privileges can exploit this by injecting a weaponized HTML payload into a chat's document metadata via chat history modification. The payload executes when a victim previews the citation or views it within a shared chat, potentially leading to high-impact confidentiality and integrity violations, such as session hijacking, data theft, or malicious script execution in the victim's browser context.
The Open WebUI security advisory (GHSA-xc8p-9rr6-97r2) and affected code in CitationModal.svelte confirm that upgrading to version 0.7.0 resolves the issue by addressing the unsafe HTML rendering path.
As a platform for offline AI operations, this vulnerability highlights risks in self-hosted AI interfaces where user-generated content like chat histories and citations can introduce persistent web attacks. No real-world exploitation has been reported.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-7982
Vulnerability Data
Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to version 0.7.0, aanually modifying chat history allows setting the `html` property within document metadata. This causes the frontend to enter a code path that treats…
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document contents as HTML, and render them in an iFrame when the citation is previewed. This allows stored XSS via a weaponized document payload in a chat. The payload also executes when the citation is viewed on a shared chat. Version 0.7.0 fixes the issue.
- 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 Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2
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.
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.