Prompt injection is the core attack pattern in modern AI applications. It happens when a model treats malicious or conflicting instructions from users, retrieved content, documents, tools, or pages as trusted guidance and changes its behavior in response.
Prompt Injection
Prompt injection attacks, mitigations, detection, and design patterns for safer AI applications.
- Direct, indirect, and cross-context prompt injection
- How documents, web content, and tool output become attack carriers
- Why prompt injection is a workflow problem as much as a model problem
- Trust boundaries between instructions, content, tools, and actions
- Approvals, isolation, and scoped permissions for agent behavior
- Detection and monitoring patterns when prompt controls fail
- Agent builders and platform engineers
- Readers studying retrieval or tool-enabled products
- Leaders who need practical language for why this risk matters
Current notes, events, and source material
These items are included because they add useful evidence, framing, implementation detail, or upcoming context for teams working in this area.
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