mantis-launch

# Campaign Launcher (/mantis-launch) ## System Goal Autonomous Security Review Pipeline Launcher. Initiates end-to-end vulnerability discovery, independent verification, exploit viability analysis, crash reproduction, automated patch generation, and risk calibration campaigns across a target file or entire codebase repository. Automatically detects unconfigured environment placeholders (such as `YOUR_PROJECT_ID` in GCE sandboxes), auto-resolves active credentials and virtualization capabilities, executes fast preflight sanity checks, and applies runtime overrides before running the pipeline. ## Command Definition - **Command:** `/mantis-launch` - **Description:** Launches automated multi-agent vulnerability discovery and validation campaigns. - **Execution Commands:** ```bash python3 "${MANTIS_HOME:-/path/to/mantis}/reference/scripts/launch.py" <target_file_or_dir> [flags...] "${MANTIS_HOME:-/path/to/mantis}/reference/run.sh" <target_file_or_dir> [flags...] ``` **Path Anchoring Requirement (CRITICAL)**: The launch scripts reside within the Mantis installation directory at `reference/scripts/launch.py` and `reference/run.sh`. **You MUST invoke these scripts via an absolute path or via `$MANTIS_HOME`**. NEVER execute `./reference/run.sh` or `python3 reference/scripts/launch.py` using a relative path inside audited target repositories. - **CLI Options:** - `target` (positional): Path to a single source file (e.g. `src/auth.py`) or a root repository directory (e.g. `.` or `/path/to/repo`). - `--sandbox` / `-s`: Override sandbox mechanism (`static-only`, `gvisor`, `microsandbox`, `gce`). - `--model` / `-m`: Override AI model (e.g. `gemini-3.8-flash`, `vertex_ai/claude-opus-5`, `vertex_ai/zai_org/glm-5.2-maas`, `openai/{MODEL_ID}`). - `--api-base`: Custom endpoint URL for OpenAI-compatible LLM deployments (e.g. `http://localhost:8000/v1`). - `--reasoning-effort`: Reasoning effort level (`low`, `medium`, `high`). - `--timeout`: LLM request timeout in seconds. - `--db` / `-d`: Custom path to SQLite knowledge database (default: `knowledge.db`). - `--workflow` / `-w`: Path to custom `workflow.json` layout definition. - `--preflight-only` / `--test` / `--preflight`: Run preflight checks and exit without starting the campaign. - `--probe` / `--probe-llm`: Actively probe LLM reachability and provider credentials during preflight with a minimal test prompt (`test`, max 256 tokens). - `--interactive`: Launch interactive configuration wizard before execution. - `--dry-run`: Display launch plan and indexed files without calling AI models. - `--no-auto-configure`: Disable automatic detection and resolution of default placeholders. ## Automated Auto-Healing & Preflight Before starting a security campaign, `mantis-launch`: 1. **Placeholder Auto-Detection**: Inspects `workflow.json` for unconfigured defaults (e.g. `project: "YOUR_PROJECT_ID"`). 2. **Capability Auto-Healing**: If unconfigured, automatically detects host capabilities (GCP project from `gcloud`, `/dev/kvm` for microVMs, or `runsc` for gVisor) and auto-updates `workflow.json` or falls back safely to `static-only`. 3. **Preflight Sanity Check**: Runs a ~1s preflight check verifying that LLM credentials are valid and the selected sandbox environment is operational. ## Common CLI Workflows ### 1. Launch Standard Review on Target File or Repository ```bash # Scan a specific file "$MANTIS_HOME/reference/run.sh" src/server/auth.py # Scan an entire repository "$MANTIS_HOME/reference/run.sh" . ``` ### 2. Launch with Static Analysis Only (Zero Sandbox Requirements) ```bash "$MANTIS_HOME/reference/run.sh" . --sandbox static-only ``` ### 3. Launch with Specific Model (e.g. Claude or Custom OpenAI Server) ```bash # Vertex AI Claude "$MANTIS_HOME/reference/run.sh" . --model vertex_ai/claude-opus-5 # Local vLLM / Ollama server "$MANTIS_HOME/reference/run.sh" . --model openai/custom-model --api-base http://localhost:8000/v1 ``` ### 4. Verify Preflight Readiness Without Scanning ```bash python3 "$MANTIS_HOME/reference/scripts/launch.py" . --preflight-only ``` ### 5. Inspect Results After Launch All findings, exploit reproduction logs, verified patches, and risk calibration scores are recorded in `knowledge.db`. Query guidance using `mantis-advise`: ```bash python3 "$MANTIS_HOME/reference/scripts/advise.py" --file src/server/auth.py ``` ## Input/Output Contract - **Reads**: - Target source code files (under target path or repository). - `workflow.json` (declarative graph layout and config). - **Writes**: - `knowledge.db` (`findings`, `campaign_artifacts`, `risk_scores`, `learnings` tables). - `sessions.db` (ADK session state trajectories). - Formatted terminal report and execution logs.