As AI adoption becomes the new normal, security risks are reaching record numbers, with new breaches and vulnerabilities surfacing every day. Security teams may be overwhelmed in managing these new threats as they pop up, particularly when it comes to Agentic AI. Where should they even start their threat modeling?

Agent Goal Hijack occurs when an attacker manipulates an agent's objectives or decision pathways. Unlike traditional LLM attacks that focus on altering a single response, ASI01 targets the planning logic of the agent.
Agents rely on natural-language instructions, so they often can’t reliably distinguish between a legitimate command from a developer and malicious content embedded in a retrieved document or email.
EchoLeak: A "zero-click" attack where a crafted email silently triggers an AI (like Microsoft 365 Copilot) to exfiltrate confidential files and chat logs without any user interaction.
Goal-Lock Drift: A malicious calendar invite injects recurring instructions that subtly reweight the agent's objectives every morning, steering it toward unauthorized approvals.
Financial Manipulation: A malicious prompt override tricks a financial agent into transferring funds directly to an attacker's account.
OWASP recommends a "Least Agency" approach which avoids unnecessary autonomy.
Key Strategies:
As we continue to adopt AI agents at scale, understanding and mitigating Agent Goal Hijack is absolutely essential for the next generation of secure automation.
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