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Intact: Semantic Isolation to Block Prompt Injection in AI Web Agents
- Engineer — Learn: Novel defensive architecture showing that agents consuming flattened page text inherit no browser-enforced trust boundaries, enabling injected content to hijack LLM actions. Worth studying before deploying any agentic workflow that browses untrusted pages.
- SOC/IR — Learn: The research quantifies how easily injected third-party content captures AI agent authority (73% success on a naive planner), a useful threat model for hunting or scoping risks if your org deploys AI browsing agents.
- Leader — Learn: Useful framing for AI-agent deployment risk: browser agents run with user authority but lack the trust-boundary enforcement of a human operator, a gap worth addressing in your AI acceptable-use policy before broad rollout.
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