Solutions / Agentic AI
Secure the agents you're shipping.
Agents act like users, at machine scale, with real credentials and real tools. Cerberus gives every agent an identity, a history, and a verdict, in the same pipeline as your human traffic.
Same credentials
An agent and its user share a token. Only behavior tells them apart.
Machine scale
Thousands of tool calls a minute. Point-event tools drown.
New surface
MCP servers and tool chains your WAF was never built to see.
How it works
A compromised agent gives itself away.
The plan was to summarize invoices. The call graph reached for secrets and a remote host. That divergence is the signal.
Illustrative product interface. The figures shown are an example of how Cerberus presents a detection, not benchmark or performance results.
Coverage
What Cerberus catches in agentic traffic.
Six failure modes specific to agents and MCP, handled in the same pipeline as the rest of your traffic.
Compromised agents
An agent with valid credentials acting against its intent. Caught by behavior, not by signature.
MCP tool poisoning
Malicious or manipulated tool definitions steering an agent's calls. Instrumented at the tool boundary.
Data exfiltration via tools
Sensitive reads chained into outbound calls. The chain itself is the anomaly.
Excessive agency
Agents reaching far beyond their task. Scope drift scored against the declared plan.
Prompt injection to action
Injected instructions that turn into real tool calls. Detected where intent meets execution.
Shadow MCP servers
Undocumented tool endpoints and agents discovered across your API surface.
AI-native
Not retrofitted. Built for this.
Agentic traffic and MCP tool calls run through the same instrumentation as the rest of your API traffic. Same identity, same scoring, same history, from day one, not bolted onto a legacy WAF.
FAQ
Common questions
What are agentic AI threats?
Agentic AI threats are attacks that use or target autonomous AI agents: prompt injection that turns into real tool calls, poisoned MCP tools steering behavior, agents drifting far beyond their task, and data exfiltration chained through legitimate credentials. The common thread is valid traffic doing invalid things, which is why signature-based tools miss it.
How does Cerberus detect a compromised agent?
Every agent gets an identity, a behavioral history, and a per-action verdict in the same pipeline as your human traffic. Cerberus compares what the agent set out to do against what it actually calls. When a support agent starts bulk-reading customer records or posting data to an unknown host, the divergence is scored and the verdict follows in seconds.
What is the agent kill switch?
When Cerberus confirms an agent is compromised, it cuts that agent off mid-chain, revoking its ability to act before the next tool call completes. The term is not standardized across vendors, so the question worth asking any of us is what the control actually stops: whether it revokes credentials the agent already holds rather than only preventing new ones, whether it halts queued and in-flight actions, and whether enforcement sits outside the agent's own runtime so the agent cannot reason around it.
Which OWASP agentic risks does Cerberus cover?
The behavioral path maps to Agent Goal Hijacking (ASI01), ranked first in the OWASP Top 10 for Agentic Applications 2026, plus excessive agency, tool misuse, and data exfiltration through tool chains. Token and tool-call burn maps to LLM10:2025 Unbounded Consumption. Cerberus scores observable behavior rather than model internals, so coverage does not depend on the agent framework in use.
Do I need to change my agent framework?
No. Cerberus instruments the boundary where agent actions become API and tool calls, so it works with any framework and any agent gateway. Integration is the same gateway-or-SDK path as the rest of the platform, live in minutes.
Ship agents. Keep the trust.
See Cerberus read your own traffic, human and agentic, in one walkthrough tailored to your stack.