First reported howtoharden.com
Analysis · latest
First reported auth0.com
Agentic Loops and Multi-Agent Graphs Expand AI Prompt Injection Risk
Auth0 published an analysis arguing that the most serious AI agent security risks stem from architectural choices—specifically agentic loops and multi-agent graphs—rather than the model alone. In loop-based systems attacker-controlled external content can be fed back into an agent's reasoning to persist and compound malicious instructions, while multi-agent graphs create trust-boundary failures where a compromised agent passes tainted instructions downstream; the report cites 2024 'Prompt Infection' research showing prompt injection can self-replicate across connected agents and recommends controls like step/time budgets, approval gates, scoped permissions, and treating tool output as untrusted. Details →How the wire is made
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