AI安全网关

response = client.models.generate_content(
    model="gemini-3-flash-preview",
    contents=f"Analyze this URL for security threats: {url}",
    config=types.GenerateContentConfig(
        # Gemini 3 unique: thinking + tools + structured output
        thinking_config=types.ThinkingConfig(thinking_level="high"),
        tools=[
            types.Tool(url_context=types.UrlContext()),       # Browse the URL
            types.Tool(google_search=types.GoogleSearch()),    # Search threat intel
        ],
        response_mime_type="application/json",
        response_schema=WebSecurityVerdict,  # Typed verdict
        temperature=1.0,  # Gemini 3 recommended
        max_output_tokens=4096,
    ),
)
verdict = WebSecurityVerdict.model_validate_json(response.text)

Input:  https://rope.odakyu.qpon/login
Output: {
  "classification": "phishing",
  "confidence": 0.93,
  "causal_chain": [
    {"step": 1, "action": "Domain impersonates brand 'odakyu'",
     "consequence": "Not the legitimate odakyu railway site"},
    {"step": 2, "action": "Hosted on .qpon (high-abuse TLD)",
     "consequence": "TLD is commonly used for scam/phishing sites"}
  ],
  "attack_narrative": "PHISHING: 'rope.odakyu.qpon' impersonates the brand 'odakyu' on a .qpon domain...",
  "mcp_specific_threats": ["Brand impersonation: 'odakyu' on .qpon. AI agents must not trust credentials."]
}

POST /api/web-sandbox/agent-scan  {"url": "https://suspicious-site.tk"}

Gemini 3 Agent Loop:
  Turn 1: "Let me check the domain for DGA patterns"
    → calls check_dga(domain="suspicious-site.tk")
    → result: {is_dga: false, entropy: 3.2}

  Turn 2: "TLD .tk is suspicious, let me check reputation"
    → calls check_tld_reputation(domain="suspicious-site.tk", tld="tk")
    → result: {category: "suspicious"}

  Turn 3: "Let me search for known threats on this domain"
    → uses Google Search grounding

  Final: Synthesizes all tool results → WebSecurityVerdict
    {classification: "phishing", confidence: 0.87, tools_called: 3}

curl -X POST http://localhost:4100/api/web-sandbox/compare \
  -H "Content-Type: application/json" \
  -d '{"url": "https://xkjhwqe.tk/payload"}'

# Clone and setup
git clone https://github.com/minorumochizuki2015-ship-it/mcp-gateway-gemini3.git
cd mcp-gateway-gemini3
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

# Demo mode (no auth required, instant start)
MCP_GATEWAY_DEMO_MODE=true \
MCP_GATEWAY_ADMIN_TOKEN=demo \
python -m uvicorn src.mcp_gateway.gateway:app --host 127.0.0.1 --port 4100

# Open Dashboard → Click "Run Live Pipeline"
# http://127.0.0.1:4100/docs/ui_poc/dashboard.html

export GOOGLE_API_KEY="your-api-key"
MCP_GATEWAY_ADMIN_TOKEN=your-token \
python -m uvicorn src.mcp_gateway.gateway:app --host 127.0.0.1 --port 4100

mkdir -p .local
echo "your-admin-token" > .local/admin_token.txt
echo "your-upstream-key" > .local/upstream_api_key.txt

GOOGLE_API_KEY="your-api-key" docker compose up --build
# Dashboard: http://localhost:4100

# 1. Create secrets in Secret Manager
echo -n "your-admin-token" | gcloud secrets create admin-token --data-file=-
echo -n "your-api-key" | gcloud secrets create google-api-key --data-file=-

# 2. Deploy with Cloud Build
gcloud builds submit --config=cloudbuild.yaml

# 3. Access your public URL
gcloud run services describe mcp-gateway --format='value(status.url)'

                    +------------------+
                    |   AI Clients     |
                    | (ChatGPT/Claude  |
                    |  /Gemini CLI)    |
                    +--------+---------+
                             |
                    +--------v---------+
                    |   MCP Gateway    |  ← Python FastAPI
                    |  + Dashboard UI  |    6-layer security pipeline
                    +--+--+--+--+-----+
                       |  |  |  |
          +------------+  |  |  +------------+
          |               |  |               |
   +------v------+ +-----v------+ +----v-----+ +------v------+
   | AI Council  | | Semantic   | | RedTeam  | | Causal Web  |
   | (Gemini 3)  | | Scanner    | | Gen+Eval | | Sandbox     |
   |             | | (Gemini 3) | |(Gemini 3)| | (Gemini 3)  |
   +------+------+ +-----+------+ +----+-----+ +------+------+
          |               |             |              |
          +-------+-------+------+------+------+-------+
                  |              |              |
         +--------v-------+ +---v--------------v---+
         | Evidence Trail  | | Memory Ledger (SSOT) |
         | (JSONL)         | | Hash-based dedup     |
         +-----------------+ +---------------------+

# 416 tests
python -m pytest tests/ -v

# Gemini integration tests only
python -m pytest tests/test_council.py tests/test_scanner.py \
  tests/test_redteam.py tests/test_causal_sandbox.py -v

# Rule-based only (no API key needed)
python scripts/benchmark.py

# Full comparison with Gemini 3
GOOGLE_API_KEY=xxx python scripts/benchmark.py --gemini

{"event": "source_sink_check", "decision": "deny", "server_id": "evil-mcp", "reason": "untrusted_to_restricted_sink"}
{"event": "council_decision", "eval_method": "gemini", "verdict_confidence": 0.95}
{"event": "causal_web_scan", "classification": "phishing", "confidence": 0.92, "recommended_action": "block"}
{"event": "attack_detection", "code": "tool_shadowing", "tool_name": "read_fi1e", "status": "blocked"}

mkdir -p .local
echo "your-admin-token" > .local/admin_token.txt
echo "your-upstream-key" > .local/upstream_api_key.txt
echo "your-google-api-key" > .local/google_api_key.txt

docker compose up --build

src/mcp_gateway/
  gateway.py          # FastAPI gateway (4900+ lines) — routing, policy, SSE pipeline
  ai_council.py       # Gemini 3 → CouncilVerdict
  scanner.py          # Static + Semantic + Advanced Attack Detection
  redteam.py          # Attack generation + safety evaluation
  causal_sandbox.py   # Evidence-based web security (Gemini 3)
  mcp_security_server.py # MCP Security Server (stdio + HTTP transport)
  sanitizer.py        # Multi-level prompt injection defense
  evidence.py         # JSONL evidence trail + Memory Ledger
  ssot/               # Memory Ledger (persistent SSOT) + Durable Streams
  registry.py         # MCP server registration and management

docs/ui_poc/          # Dashboard UI (9 pages, bilingual EN/JA)
Dockerfile            # Cloud Run deployment
docker-compose.yml    # One-command full stack deployment
cloudbuild.yaml       # Google Cloud Build config

Agent calls: browser_navigate(url="https://suspicious-site.tk/login")
                │
                ▼
   ┌─────────────────────────┐
   │  1. Extract URL params  │  url, uri, href, target, destination, page
   │  2. Fast scan (<5ms)    │  DGA, TLD, brand, SSRF check
   │  3. Deep scan (if warn) │  DOM + a11y + Gemini 3 analysis
   └─────────────────────────┘
                │
         ┌──────┴──────┐
         │             │
    ✅ Allow      ❌ Block
    Forward to    Return 403 +
    upstream      evidence trail

# Initialize
curl -X POST http://localhost:4100/mcp/security \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{}}'

# Check URL safety (fast scan)
curl -X POST http://localhost:4100/mcp/security \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"check_url","arguments":{"url":"https://example.com"}}}'

# Full security scan with Gemini causal analysis
curl -X POST http://localhost:4100/mcp/security \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"scan_report","arguments":{"url":"https://suspicious-site.tk"}}}'

python -m src.mcp_gateway.mcp_security_server
# Reads/writes JSON-RPC 2.0 with Content-Length framing (LSP-style)

# Quick URL check via REST
curl -X POST http://localhost:4100/api/web-sandbox/scan \
  -H "Content-Type: application/json" \
  -d '{"url":"https://suspicious-site.tk"}'

# MCP tool call interception
curl -X POST http://localhost:4100/api/mcp/intercept \
  -H "Content-Type: application/json" \
  -d '{"method":"tools/call","params":{"name":"fetch","arguments":{"url":"https://evil.tk"}}}'