CVE-2025-3467
Published: 07 July 2025
Summary
CVE-2025-3467 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Langgenius Dify. Its CVSS base score is 5.4 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 36.7th 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-2025-20208
Vulnerability details
An XSS vulnerability exists in langgenius/dify versions prior to 1.1.3, specifically affecting Firefox browsers. This vulnerability allows an attacker to obtain the administrator's token by sending a payload in the published chat. When the administrator views the conversation content through…
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the monitoring/log function using Firefox, the XSS vulnerability is triggered, potentially exposing sensitive token information to the attacker.
- 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: dify
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
XSS vulnerability enables exploitation of public-facing web application (T1190) to execute JavaScript in admin's Firefox browser, facilitating credential access via stealing web session token/cookie (T1539, T1555.003) and exploitation specifically for credential access (T1212).
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.