Analysis
Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection
First reported · Discovered arxiv.org
Page published
Earliest dated coverage: 3 Nov 2026 · First observed: 9 Nov 2026 · Latest dated coverage: 3 Nov 2026
Coverage timeline
Single-source analysis — one report is available.
Why it matters
Prompt injection can turn documents, websites, emails, and search results into unauthorized instructions, making permission limits and trust boundaries essential for tool-enabled AI agents.
Harvard Chan School’s glossary explains how prompt injection causes AI applications to mistake untrusted content for authoritative instructions, potentially redirecting outputs, tool calls, or information disclosure. The entry synthesizes existing research and recommends clear trust boundaries, restricted permissions, careful handling of confidential data, and review before consequential actions.