Practical guidance on securing AI agents, tools, and the systems they act on, written by the team building the trust layer for AI agents.
Insurance AI sits across underwriting, claims, and customer data at once, so a single bad model decision can touch pricing fairness, fraud exposure, and regulated data in the same incident.
Healthcare AI security has to protect protected health information and clinical decision quality at the same time, across systems that were never designed with either in mind.
Financial services AI touches money movement, underwriting, and account data at once, so security controls need to cover transaction integrity and regulated data together, not separately.
A practical, grouped checklist covering identity, scoping, approvals, credentials, and emergency controls for reviewing whether an AI agent's access is actually safe.
A kill switch for an AI agent needs to stop it immediately across every path it can act through, and emergency access needs its own tightly controlled process.
Auditing who authorized an AI action means reconstructing the user, agent, policy decision, and approval that led to it, from a record that can't be edited after the fact.
Credentials leak out of agentic systems through prompts, logs, memory, and tool outputs more often than through a classic breach, because agents handle secrets as text.
Privilege escalation by an AI agent happens when it accumulates access beyond its intended scope, often through chained tool calls rather than a single obvious grant.
Separation of duties splits a sensitive workflow across multiple agents or an agent and a human, so no single actor can both initiate and approve the same action.
Revoking an AI agent's access needs to take effect immediately across every credential and delegated token it holds, not on the next scheduled refresh cycle.
Time-bound permissions grant an AI agent access only for the duration a task genuinely needs, so standing access doesn't outlive the reason it was ever granted.
Transaction limits cap how much value or how many actions an AI agent can move before a hard stop kicks in, enforced outside the model where a prompt can't argue past it.
