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{"repo": "bitr1ft/univex", "files": {"examples/configs/agents/agents.yaml": {"fcf3e1ff8d0eb3cebe90b47d0f7bae8edb47800d": {"t": 1785745212.3023524, "n": 7297, "h": "538d9c9ae55eb3c3", "c": "# ==============================================================================\n# UniVex — Per-Agent Model Configuration\n# ==============================================================================\n# File: examples/configs/agents/agents.yaml\n#\n# Configure a dedicated LLM model, provider, temperature, and token budget\n# for each of the 13 UniVex agent roles.\n#\n# Priority order (highest → lowest):\n# 1. Environment variables (e.g. PLANNER_MODEL=gpt-4o-mini)\n# 2. This YAML file\n# 3. Built-in defaults in agent_model_config.py\n#\n# To activate this file, set:\n# AGENTS_CONFIG_PATH=/path/to/agents.yaml\n# or place it at examples/configs/agents/agents.yaml (auto-detected).\n#\n# Global settings:\n# AGENT_MAX_TOKENS=4096 (default max_tokens for all agents)\n# AGENT_SUMMARY_THRESHOLD=0.75 (context summary trigger threshold)\n# PROXY_URL=socks5://... (route all LLM calls through a proxy)\n# ==============================================================================\n\nagents:\n\n # ----------------------------------------------------------------------------\n # Planner Agent — Decomposes targets into a prioritised attack plan.\n # Requires strong reasoning; GPT-4o or Claude Opus recommended.\n # ----------------------------------------------------------------------------\n planner:\n model: gpt-4o\n provider: openai\n temperature: 0.2\n max_tokens: 4096\n # system_prompt: | # Uncomment to override the built-in system prompt\n # You are a world-class penetration testing strategist ...\n\n # ----------------------------------------------------------------------------\n # Recon Agent — Port scanning, OSINT, HTTP probing, and enumeration.\n # Cost-optimised: GPT-4o-mini is fast and accurate for structured output.\n # ----------------------------------------------------------------------------\n recon:\n model: gpt-4o-mini\n provider: openai\n temperature: 0.1\n max_tokens: 4096\n\n # ----------------------------------------------------------------------------\n # Exploit Agent — Binary exploitation, SQLMap, Metasploit, credential attacks.\n # Requires deep security knowledge; Claude 3.5 Sonnet excels at exploit code.\n # ----------------------------------------------------------------------------\n exploit:\n model: claude-3-5-sonnet-20241022\n provider: anthropic\n temperature: 0.1\n max_tokens: 8192\n\n # ----------------------------------------------------------------------------\n # WebApp Agent — XSS, CSRF, SSRF, IDOR, JWT, API security.\n # GPT-4o provides excellent web attack coverage.\n # ----------------------------------------------------------------------------\n webapp:\n model: gpt-4o\n provider: openai\n temperature: 0.1\n max_tokens: 4096\n\n # ----------------------------------------------------------------------------\n # Report Agent — Deduplication, CVSS scoring, Markdown report generation.\n # Slightly higher temperature for natural prose output.\n # ----------------------------------------------------------------------------\n report:\n model: gpt-4o-mini\n provider: openai\n temperature: 0.3\n max_tokens: 8192\n\n # ----------------------------------------------------------------------------\n # Refiner Agent — Iteratively improves agent outputs for quality.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n refiner:\n model: gpt-4o\n provider: openai\n temperature: 0.2\n max_tokens: 4096\n\n # ----------------------------------------------------------------------------\n # Generator Agent — Payload, wordlist, PoC code, and exploit template creation.\n # Higher temperature for creative content generation.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n generator:\n model: gpt-4o\n provider: openai\n temperature: 0.7\n max_tokens: 8192\n\n # ----------------------------------------------------------------------------\n # Adviser Agent — Expert second opinion on exploit selection, risk, remediation.\n # Claude 3.5 Sonnet for nuanced security advice.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n adviser:\n model: claude-3-5-sonnet-20241022\n provider: anthropic\n temperature: 0.3\n max_tokens: 4096\n\n # ----------------------------------------------------------------------------\n # Reflector Agent — Self-reflection, missed attack surfaces, next-step planning.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n reflector:\n model: gpt-4o\n provider: openai\n temperature: 0.4\n max_tokens: 4096\n\n # ----------------------------------------------------------------------------\n # Enricher Agent — CVE lookup, OWASP mapping, CVSS scoring, remediation.\n # Uses deterministic zero-temperature for factual output.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n enricher:\n model: gpt-4o-mini\n provider: openai\n temperature: 0.0\n max_tokens: 2048\n\n # ----------------------------------------------------------------------------\n # Coder Agent — Exploit code, reverse shells, payloads, tool scripts.\n # Claude 3.5 Sonnet is state-of-the-art for code generation.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n coder:\n model: claude-3-5-sonnet-20241022\n provider: anthropic\n temperature: 0.1\n max_tokens: 8192\n\n # ----------------------------------------------------------------------------\n # Installer Agent — Tool installation guidance, dependency resolution.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n installer:\n model: gpt-4o-mini\n provider: openai\n temperature: 0.2\n max_tokens: 2048\n\n # ----------------------------------------------------------------------------\n # SimpleJSON Agent — Lightweight structured JSON extraction.\n # Deterministic zero-temperature; cheapest model is sufficient.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n simple_json:\n model: gpt-4o-mini\n provider: openai\n temperature: 0.0\n max_tokens: 1024\n\n# ==============================================================================\n# Provider Override Examples\n# ==============================================================================\n# Swap individual agents to alternative providers without changing this file.\n# Just set the relevant environment variables:\n#\n# # Use DeepSeek for cost-effective reasoning:\n# RECON_MODEL=deepseek-chat\n# RECON_PROVIDER=deepseek\n# DEEPSEEK_API_KEY=your-key\n#\n# # Use local vLLM cluster for air-gapped deployment:\n# EXPLOIT_MODEL=llama-3.1-70b-instruct\n# EXPLOIT_PROVIDER=vllm\n# VLLM_BASE_URL=http://localhost:8000/v1\n#\n# # Route all LLM calls through a SOCKS5 proxy:\n# PROXY_URL=socks5://user:pass@proxy.corp.internal:1080\n# ==============================================================================\n"}, "00315852518055d23d39dde91c658e16bca47fce": {"t": 1785748751.0463498, "n": 7297, "h": "538d9c9ae55eb3c3", "c": "# ==============================================================================\n# UniVex — Per-Agent Model Configuration\n# ==============================================================================\n# File: examples/configs/agents/agents.yaml\n#\n# Configure a dedicated LLM model, provider, temperature, and token budget\n# for each of the 13 UniVex agent roles.\n#\n# Priority order (highest → lowest):\n# 1. Environment variables (e.g. PLANNER_MODEL=gpt-4o-mini)\n# 2. This YAML file\n# 3. Built-in defaults in agent_model_config.py\n#\n# To activate this file, set:\n# AGENTS_CONFIG_PATH=/path/to/agents.yaml\n# or place it at examples/configs/agents/agents.yaml (auto-detected).\n#\n# Global settings:\n# AGENT_MAX_TOKENS=4096 (default max_tokens for all agents)\n# AGENT_SUMMARY_THRESHOLD=0.75 (context summary trigger threshold)\n# PROXY_URL=socks5://... (route all LLM calls through a proxy)\n# ==============================================================================\n\nagents:\n\n # ----------------------------------------------------------------------------\n # Planner Agent — Decomposes targets into a prioritised attack plan.\n # Requires strong reasoning; GPT-4o or Claude Opus recommended.\n # ----------------------------------------------------------------------------\n planner:\n model: gpt-4o\n provider: openai\n temperature: 0.2\n max_tokens: 4096\n # system_prompt: | # Uncomment to override the built-in system prompt\n # You are a world-class penetration testing strategist ...\n\n # ----------------------------------------------------------------------------\n # Recon Agent — Port scanning, OSINT, HTTP probing, and enumeration.\n # Cost-optimised: GPT-4o-mini is fast and accurate for structured output.\n # ----------------------------------------------------------------------------\n recon:\n model: gpt-4o-mini\n provider: openai\n temperature: 0.1\n max_tokens: 4096\n\n # ----------------------------------------------------------------------------\n # Exploit Agent — Binary exploitation, SQLMap, Metasploit, credential attacks.\n # Requires deep security knowledge; Claude 3.5 Sonnet excels at exploit code.\n # ----------------------------------------------------------------------------\n exploit:\n model: claude-3-5-sonnet-20241022\n provider: anthropic\n temperature: 0.1\n max_tokens: 8192\n\n # ----------------------------------------------------------------------------\n # WebApp Agent — XSS, CSRF, SSRF, IDOR, JWT, API security.\n # GPT-4o provides excellent web attack coverage.\n # ----------------------------------------------------------------------------\n webapp:\n model: gpt-4o\n provider: openai\n temperature: 0.1\n max_tokens: 4096\n\n # ----------------------------------------------------------------------------\n # Report Agent — Deduplication, CVSS scoring, Markdown report generation.\n # Slightly higher temperature for natural prose output.\n # ----------------------------------------------------------------------------\n report:\n model: gpt-4o-mini\n provider: openai\n temperature: 0.3\n max_tokens: 8192\n\n # ----------------------------------------------------------------------------\n # Refiner Agent — Iteratively improves agent outputs for quality.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n refiner:\n model: gpt-4o\n provider: openai\n temperature: 0.2\n max_tokens: 4096\n\n # ----------------------------------------------------------------------------\n # Generator Agent — Payload, wordlist, PoC code, and exploit template creation.\n # Higher temperature for creative content generation.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n generator:\n model: gpt-4o\n provider: openai\n temperature: 0.7\n max_tokens: 8192\n\n # ----------------------------------------------------------------------------\n # Adviser Agent — Expert second opinion on exploit selection, risk, remediation.\n # Claude 3.5 Sonnet for nuanced security advice.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n adviser:\n model: claude-3-5-sonnet-20241022\n provider: anthropic\n temperature: 0.3\n max_tokens: 4096\n\n # ----------------------------------------------------------------------------\n # Reflector Agent — Self-reflection, missed attack surfaces, next-step planning.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n reflector:\n model: gpt-4o\n provider: openai\n temperature: 0.4\n max_tokens: 4096\n\n # ----------------------------------------------------------------------------\n # Enricher Agent — CVE lookup, OWASP mapping, CVSS scoring, remediation.\n # Uses deterministic zero-temperature for factual output.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n enricher:\n model: gpt-4o-mini\n provider: openai\n temperature: 0.0\n max_tokens: 2048\n\n # ----------------------------------------------------------------------------\n # Coder Agent — Exploit code, reverse shells, payloads, tool scripts.\n # Claude 3.5 Sonnet is state-of-the-art for code generation.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n coder:\n model: claude-3-5-sonnet-20241022\n provider: anthropic\n temperature: 0.1\n max_tokens: 8192\n\n # ----------------------------------------------------------------------------\n # Installer Agent — Tool installation guidance, dependency resolution.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n installer:\n model: gpt-4o-mini\n provider: openai\n temperature: 0.2\n max_tokens: 2048\n\n # ----------------------------------------------------------------------------\n # SimpleJSON Agent — Lightweight structured JSON extraction.\n # Deterministic zero-temperature; cheapest model is sufficient.\n # (Gap Coverage Day 3 — New Agent Role)\n # ----------------------------------------------------------------------------\n simple_json:\n model: gpt-4o-mini\n provider: openai\n temperature: 0.0\n max_tokens: 1024\n\n# ==============================================================================\n# Provider Override Examples\n# ==============================================================================\n# Swap individual agents to alternative providers without changing this file.\n# Just set the relevant environment variables:\n#\n# # Use DeepSeek for cost-effective reasoning:\n# RECON_MODEL=deepseek-chat\n# RECON_PROVIDER=deepseek\n# DEEPSEEK_API_KEY=your-key\n#\n# # Use local vLLM cluster for air-gapped deployment:\n# EXPLOIT_MODEL=llama-3.1-70b-instruct\n# EXPLOIT_PROVIDER=vllm\n# VLLM_BASE_URL=http://localhost:8000/v1\n#\n# # Route all LLM calls through a SOCKS5 proxy:\n# PROXY_URL=socks5://user:pass@proxy.corp.internal:1080\n# ==============================================================================\n"}}}} |