agent-firewall
Agent Firewall
Уровень безопасности на основе политик для ИИ-агентов и MCP-инструментов.
Agent Firewall располагается между ИИ-агентом и инструментами, к которым он может получить доступ. Каждый запрос к инструменту оценивается на соответствие политикам безопасности, прежде чем ему будет разрешено выполниться.
Что он делает
Разрешает доверенные действия инструментов
Запрещает опасные действия
Требует одобрения человека для чувствительных действий
Проверяет аргументы инструментов
Остаётся закрытым при отсутствии совпадающей политики
Разрешает конфликты политик, применяя самое строгое ограничение
Журналирует решения по безопасности
Защищает реальные вызовы MCP-инструментов
Related MCP server: NORNR MCP Control
Архитектура
AI Agent
|
v
MCP Client
|
v
Agent Firewall
|
+-- ALLOW ------+
| |
+-- DENY |
| v
+-- APPROVAL -> MCP Server
|
v
External Tool
The firewall evaluates a request before the MCP tool is called.
Example Policy
Policies are defined in policies.yaml.
rules:
- tool: github.get_file_contents
action: allow
- tool: github.delete_file
action: deny
- tool: payments.send
amount_gt: 100
action: approval
- tool: payments.send
amount_gte: 1000
action: deny
The firewall uses the strongest applicable restriction:
allow < approval < deny
Security Behavior
The firewall fails closed when no matching policy exists.
Invalid payment values are rejected, including:
Negative values
Zero
Strings
Missing amounts
NaN
Infinity
Booleans
Lists
Dictionaries
MCP Integration
Agent Firewall has been tested against a real GitHub MCP server.
Tested behavior:
github.get_file_contents
|
+--> ALLOW
|
v
GitHub MCP Server
|
v
README.md
A protected operation is blocked before the MCP server receives the request:
github.delete_file
|
v
Agent Firewall
|
+--> DENY
|
X
MCP tool is never called
Installation
Clone the repository and create a virtual environment:
python -m venv .venv
Activate it on Windows:
.venv\Scripts\Activate.ps1
Install dependencies:
pip install -r requirements.txt
Running Tests
Run the complete test suite:
pytest
The current test suite includes unit, policy, security, and real MCP integration tests.
Project Structure
agent-firewall/
├── firewall/
│ └── engine.py
├── tests/
│ └── test_engine.py
├── policies.yaml
├── mcp_firewall.py
├── mcp_test_client.py
├── test_attacks.py
├── test_firewall.py
├── test_github_mcp.py
├── test_policy_attacks.py
├── test_policy_conflicts.py
├── requirements.txt
└── README.md
Status
This is an early v0.1 prototype.
The project is currently focused on policy enforcement, MCP integration, security testing, and establishing a reliable authorization layer for AI agents.
Security
This project is experimental software. Do not use it as the sole security control for production systems without independently reviewing and testing the implementation.
License
License to be added.
Then save it and run:
```powershell
pytest
If 16 passed, commit it:
git add README.md
git commit -m "Improve project documentation"
git pushThis server cannot be deployed
Maintenance
Related MCP Connectors
MCP enforcement layer that intercepts AI agent actions and blocks rule violations before execution.
- gatewayOAuthai.sealgate
MCP gateway with runtime security policy, tool-call-level control, and audit of agent actions.
Runtime permission, approval, and audit layer for AI agent tool execution.
Security gateway for AI agents: policy, approval, and audited execution, no secrets shared.
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