Plan
active
Research: Prompt Injection Attacks on Single and Multi-Agent AI Systems
- Engineer — Learn: Academic research showing how prompt injection can propagate across multi-agent architectures and leak sensitive data — no PoC or active exploitation, but directly relevant to engineers building LLM pipelines or agent-based workflows who should design for prompt isolation and trust boundaries between agents.
- SOC/IR — Learn: No IOCs, no ATT&CK mappings, and no evidence of active exploitation, so no immediate detection work; worth filing as context for environments that have deployed AI agents, where inter-agent communication channels represent an emerging and largely unmonitored attack surface.
- Leader — Plan: This research reinforces that AI agent deployments in enterprise workflows carry systemic risk from prompt injection; use it this quarter to drive a policy on approved AI agent frameworks and required security review before production deployment, before controls are needed.
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