ai-chat
Pass
Audited by Gen Agent Trust Hub on Aug 6, 2026
Risk Level: SAFEPROMPT_INJECTION
Full Analysis
- [PROMPT_INJECTION]: The implementation patterns for the Angular chat interface include a vulnerability surface for Indirect Prompt Injection through unsafe content rendering.
- Ingestion points: Untrusted data enters the agent context through the
ChatInputComponent(user input) and the streaming response chunks processed inChatComponent(external AI data). - Boundary markers: The UI uses role-based message bubbles to separate user and assistant content, but these are for display only and do not provide programmatic instruction isolation for the agent.
- Capability inventory: The skill utilizes
HttpClientfor network requests and themarkedlibrary for markdown parsing. - Sanitization: A significant sanitization failure was identified in
reference/streaming-patterns.md. TheStreamingMessageComponentusesDomSanitizer.bypassSecurityTrustHtmlto render the output of the markdown parser. This explicitly disables Angular's built-in Cross-Site Scripting (XSS) protections. If an attacker-controlled AI response contains malicious HTML or script tags that pass through the markdown parser, they will be executed in the user's browser context.
Audit Metadata