Open-source SDK, live on PyPI

Give your agents autonomy, without giving up control.

Cerbere AG is the runtime security and observability layer for AI agents. Before every tool call runs, it decides whether the action is allowed, needs a human, or is blocked, and it records every decision.

Python SDK
MCP · Claude Code, Cursor and others
app.cerbereag.site
Cerbere AG dashboard: decisions per minute, blocked rate, cost, the latest allowed and blocked agent actions, and top threats
Open source
SDK under Apache 2.0
Published
pip install cerbere-ag
Tested
500+ automated tests
Verifiable
Ed25519-signed decisions
mission

The internet's early years taught us that an open, unguarded system gets exploited. Agentic AI is repeating that lesson, faster.

1995 - the open web

Every new connection was a new exposure.

As homes and offices came online, viruses, worms and bad actors found an unguarded surface. It took firewalls, antivirus and years of hard lessons before connected stopped meaning exposed.

2026 - the agentic era

Every new agent is a new attack surface.

An agent that can read, decide and act can also be hijacked by a poisoned document, a malicious tool response or an injected instruction. Without a layer that checks intent before execution, autonomy becomes risk.

how it works

From agent call to audited decision.

Cerbere AG sits between your agent and its tools. Every call is intercepted, classified, decided on by policy and risk, observed, and written to an audit log. One trace follows it the whole way.

AgentGuard is the name of the open-source engine and Python module inside Cerbere AG.
observability

Full visibility into every agent decision.

Security means nothing without observability. These are real screens from the dashboard. The SDK and policy engine work standalone too, but this is what you get once a collector is running.

Try the Collector
Cerbere AG trace view: a waterfall of four agent calls and the reason the last one, send_email, was held back for approval
Trace waterfall. Every call of a run, its latency, the checks that ran and why an action was held back.
Cerbere AG data flow diagram: a SECRET band flowing into the http_post tool, a CONFIDENTIAL band into send_email, public data into other tools
Data flow. Where each data classification goes, so a secret reaching an external tool stands out.
traces

Every action, not only incidents

Each tool call becomes a trace with its arguments, the checks that ran, the decision and the latency. Allowed actions are recorded too, so you can read the whole behaviour of an agent end to end.

audit trail

Signed, searchable history

Decisions can be cryptographically signed and kept for as long as your plan allows. Filter by agent, tool, verdict or time window when you need to explain what happened.

budgets and alerts

Tokens, cost and drift

Atomic token budgets per agent, trajectory tracking and real time alerts on Gmail or Slack when an agent starts behaving outside its normal path.

integrations

Cerbere AG plugs into the stack you already run.

One policy and telemetry layer across SDKs, providers and agent frameworks.

Python
MCP
HTTPHTTP
Composio
OpenAI
Anthropic
LangGraph
CrewAI
Python
MCP
HTTPHTTP
Composio
OpenAI
Anthropic
LangGraph
CrewAI
see it work

Watch security and observability in action.

install and run
security decisions
benchmark

Measured against a public prompt injection set.

We ran our detection pipeline against a public benchmark and published the full methodology, strengths and weaknesses, including where it still misses.

regex layer
91.5%

recall, 0% false positives

regex + ML
98.1%

recall

ML layer
5% / 33%

false positives, benign / hard negatives

ML layer
~450ms

p95 latency

research

Built on a moving field, not a fixed list.

Agent security research moves fast. Everything that targets your agents today, and where our own benchmark fits into it.

prompt injectionexfiltrationdestructive commandstool poisoningexcessive agencybudget overruns
OWASP GenAI Security Project

Top 10 for LLM Applications, 2026 edition

Prompt injection holds the No. 1 spot again, and excessive agency jumped from 6th to 3rd. Our policy chain targets that shift directly: excessive agency is a permissions problem, not just a detection problem.

Academic benchmarks (InjecAgent, StruQ)

Standalone prompting defenses stay brittle

Tool-integrated agents remain exploitable even under strong system prompts. It's why every call is checked by a layer the agent cannot talk its way around.

deployment

Run it where your agents already run.

local

On your machine

Point the SDK at a local collector. Nothing leaves your network. Ideal for prototyping and small teams getting started.

cloud

Cerbere Cloud

We host the collector and dashboard. Sign up, get an API key, and your agents are covered in minutes with no infrastructure to run.

self hosted license

On your own servers

For high volume or regulated environments: a licensed deployment inside your own infrastructure, with your own data residency and controls.

pricing

Start free. Grow into your agent fleet.

Free
Get to know Cerbere AG
$0
  • ·2 connected agents
  • ·Local deployment only
  • ·Prompt injection and exfiltration checks
  • ·7 day audit trail
  • ·Community support
Start free
Pro
For a small production fleet
$49/mo
  • ·5 connected agents
  • ·Local or cloud deployment
  • ·Real time Gmail and Slack alerts
  • ·90 day audit trail
  • ·Signed security decisions
  • ·Email support
Start with Pro
Team
For multiple teams and agents
$199/mo
  • ·10+ connected agents
  • ·Local and cloud, mixed
  • ·Custom policies per agent
  • ·Unlimited audit trail
  • ·SSO and role based access
  • ·Priority support
Talk to sales
Enterprise
High volume, self hosted
Custom
  • ·Unlimited agents
  • ·Self hosted, your data residency
  • ·SLA and support contract
  • ·Custom retention and policies
  • ·Compliance packages
  • ·Dedicated ops channel
Talk to sales
faq

Frequently Asked Questions

talk to the founders

Questions before you deploy an agent? Ask us directly.