AgentShield is the control plane your AI agents have been missing. Define what agents can do, audit everything they touch, and stop them the moment they go off-script.
When an agent calls delete_record(), that request goes directly to your database — bypassing every LLM gateway and text filter on the market. AgentShield intercepts at the tool call layer, where the real risk lives.
Every agent gets a cryptographic identity token. No anonymous processes. No untracked actions. If it isn't registered, it doesn't run.
Write a declarative YAML policy per agent — exactly which tools it can call, which data schemas it can access, and what rate limits apply.
Every tool call is evaluated against policy in <10ms. Allowed calls proceed. Blocked calls trigger alerts. Everything is written to an immutable audit log.
These aren't hypothetical scenarios. They are the failure modes that engineering and security teams are discovering after deploying autonomous AI agents.
A summarizer agent attempted to delete a user record — a tool it was never meant to have. Policy enforcement blocked it before execution.
Malicious instructions embedded in external web content attempted to hijack the agent mid-session. Detected and sanitized before reaching the LLM context.
An analytics agent included SSN and payment card data in its output. AgentShield's PII scanner detected and redacted the sensitive fields before delivery.
An agent entered an infinite fetch loop that would have cost thousands in API bills. Rate limiting triggered at the configured threshold, killing the loop before damage was done.
A compromised agent attempted to impersonate the orchestrator to gain elevated permissions. Cryptographic chain-of-trust validation caught the forged token instantly.
A code assistant accidentally included live AWS and GitHub credentials in its output. Pattern scanning detected and redacted both before the response left the system.
A single pane of glass across every agent, every policy, every action — with live alerts and one-click kill switch.
Every capability designed specifically for how AI agents work — not retrofitted from LLM chatbot tooling.
Short-lived, cryptographically signed identity tokens scoped per session. Every agent session is bounded and revocable. Kill any agent instantly.
Declarative YAML policies evaluated in under 10ms. Tool allowlists, data schema ACLs, rate limits per tool, time-boxed permissions. Deny-by-default.
Every action written to a tamper-evident, cryptographically signed log. Chain of custody from the originating human through every agent that touched the task.
Validate cryptographic trust chains in multi-agent systems. Prevents lateral movement and agent impersonation attacks when agents delegate to sub-agents.
Rolling baseline profiles per agent. Anomaly detection on call frequency, data volume, and tool sequences. Prompt injection detection. Get paged before incidents.
Ready-to-submit artifacts for EU AI Act, NIST AI RMF, SOC 2 Type II, and ISO/IEC 42001. Stop building compliance documentation by hand.
One line of code. Drop-in SDK for every major agent framework. No architectural changes required.
# Before: Unprotected agent from langchain import Agent agent = Agent( model="claude-sonnet-4-6", tools=[read_ticket, update_ticket, send_email] ) agent.run(task) # After: Protected by AgentShield from langchain import Agent from agentshield import shield # ← one import agent = shield( Agent(model="claude-sonnet-4-6", tools=[...]), agent_id="customer-support-v2", environment="production" ) agent.run(task) # Every tool call now gated, audited, and monitored
AgentShield generates the audit artifacts and governance evidence that regulators and auditors actually ask for.
Satisfies Article 9 (risk management) and Article 12 (record-keeping) for high-risk AI deployments. Human-in-the-loop gates for regulated actions.
Maps to GOVERN, MAP, MEASURE, and MANAGE functions. Provides operational controls and audit artifacts for AI RMF compliance attestation.
AgentShield itself is SOC 2 Type II certified. Our controls help your organization satisfy SOC 2 requirements for AI systems handling customer data.
The emerging international standard for AI management systems. Our governance model maps directly to its requirements for AI risk and accountability.
Start free. Scale as your agent fleet grows. No per-seat fees — you pay for what your agents use.
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