CVE-2025-4779
Published: 07 July 2025
Summary
CVE-2025-4779 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Lunary Lunary. Its CVSS base score is 6.1 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 31.2% of CVEs by exploit likelihood; 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 Other ATLAS/OWASP Terms risk domain.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-20219
Vulnerability details
lunary-ai/lunary versions prior to 1.9.24 are vulnerable to stored cross-site scripting (XSS). An unauthenticated attacker can inject malicious JavaScript into the `v1/runs/ingest` endpoint by adding an empty `citations` field, triggering a code path where `dangerouslySetInnerHTML` is used to render attacker-controlled…
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text. This vulnerability allows the execution of arbitrary JavaScript in the context of the user's browser, potentially leading to session hijacking, data theft, or other malicious actions.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: ai, lunary
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Unauthenticated stored XSS via public API endpoint enables exploitation of public-facing application (T1190), content injection (T1659), arbitrary JavaScript execution (T1059.007), and facilitates stealing web session cookies (T1539) and browser credentials (T1555.003) for session hijacking and data theft.
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.