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Agents Under Siege: How LLM Workflows Invite a New Breed of Cyber Threats

TL;DR for operators A support agent reads a customer email. It checks a CRM record. It calls a refund API. It writes a note into long-term memory. It asks another agent to verify policy. Somewhere in that chain, a malicious instruction hides inside a message, document, issue tracker entry, retrieved snippet, schema, or tool response. The model does not need to become “evil”. It only needs to be helpful in the wrong direction. ...

July 1, 2025 · 16 min · Zelina
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The Conscience Plug-in: Teaching AI Right from Wrong on Demand

TL;DR for operators The paper’s central move is not “we trained a moral model.” It is “we inserted a referee between the agent’s plan and the agent’s action.” That distinction matters. If the architecture works, enterprises do not need to retrain every model whenever compliance, cultural norms, safety rules, or customer-specific constraints change. They can externalise those constraints into machine-readable constitutions and enforce them at runtime. ...

June 18, 2025 · 19 min · Zelina