Fennec/.env.example at main · Fennec-AI/Fennec · GitHub

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# Fennec AI Configuration
# Copy this file to .env and fill in your values

# ===================
# LangSmith Tracing (optional)
# ===================
# Enables tracing and monitoring via LangSmith
# Both LANGSMITH_* and LANGCHAIN_* variables are needed for full compatibility

# LangSmith variables (used by LangGraph server)
LANGSMITH_TRACING=false
LANGSMITH_ENDPOINT=https://api.smith.langchain.com
LANGSMITH_API_KEY=
LANGSMITH_PROJECT=fennec-ai

# LangChain variables (used by LangChain SDK)
LANGCHAIN_TRACING_V2=false
LANGCHAIN_API_KEY=
LANGCHAIN_PROJECT=fennec-ai
LANGCHAIN_ENDPOINT=https://api.smith.langchain.com

# ===================
# LLM Provider Config
# ===================
# Options: anthropic, openai, openrouter
LLM_PROVIDER=anthropic
LLM_MODEL=claude-sonnet-4-6

# Optional per-agent model overrides (fall back to LLM_MODEL if unset)
RECON_LLM_MODEL=
ANALYST_LLM_MODEL=
PENTESTER_LLM_MODEL=

# ===================
# API Keys (required)
# ===================
# At least one of these is required based on your LLM_PROVIDER
ANTHROPIC_API_KEY=
OPENAI_API_KEY=
OPENROUTER_API_KEY=

# ===================
# Search APIs (optional)
# ===================
# Enables enhanced search capabilities
TAVILY_API_KEY=
PERPLEXITY_API_KEY=

# ===================
# Docker Config
# ===================
# Default pentest container image. The bundled `linux/` Dockerfile builds a
# Kali image with the common pentest tools preinstalled — see `make build`
# under linux/. You can also use the upstream Kali image directly.
DOCKER_IMAGE=fennec-linux

# ===================
# Agent Model Call Limits
# ===================
# Maximum model (LLM) calls per agent run.
# Recon uses max(RECON_MIN_MODEL_CALLS, recursion_limit // 4).
RECON_MIN_MODEL_CALLS=25
ANALYST_MODEL_CALL_LIMIT=15
PENTESTER_MODEL_CALL_LIMIT=30

# ===================
# Execution
# ===================
# How the agent runs pentest tools:
#   docker (default) — spawn a Kali sibling container per scan (needs Docker)
#   local            — run tools inside the agent process directly
EXECUTION_MODE=docker
# Set to false to force the local executor even when Docker is available.
USE_DOCKER=true
# Assessment depth preset: turbo / balanced / deep
FENNEC_METHOD=balanced
# true to pause for operator approval between hypotheses (human-in-the-loop)
HTLI=false

# ===================
# API Server (optional)
# ===================
# Comma-separated extra CORS origins for the FastAPI server.
# Any localhost port is allowed by default; add hosted origins here.
FENNEC_CORS_ORIGINS=
# JSON blob of credentials for authenticated targets, e.g.
#   {"username": "...", "password": "..."}
FENNEC_AUTH_CREDENTIALS=
# Seed the dashboard with synthetic demo data (handy for screenshots / eval).
FENNEC_DEMO_SEED=false
# Quiet noisy httpx request logs, e.g. WARNING.
HTTPX_LOG_LEVEL=