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version: "1.0.0" name: mantis-configure description: >- Configures and validates Mantis pipeline environments, sandbox mechanisms, and AI models. Use to set up workflow.json, auto-detect host capabilities, switch between sandboxes (static-only, gvisor, microsandbox, gce), select AI models, and run fast 1-2s preflight tests. Don't use for scanning source code or running attack campaigns.


Pipeline Configurator (/mantis-configure)

System Goal

Environment and Model Configurator. Configures workflow.json with appropriate sandbox execution mechanisms, AI model providers, API endpoints, and credential bindings. Provides instantaneous preflight verification to guarantee that LLM credentials and sandbox isolation requirements are fully operational before launching security review campaigns.

Command Definition

  • Command: /mantis-configure
  • Description: Configures Mantis pipeline settings (sandboxes, models,

credentials, preflight validation) in workflow.json.

  • Execution Command:

``bash python3 "${MANTIS_HOME:-/path/to/mantis}/reference/scripts/configure.py" [flags...] ``

Path Anchoring Requirement (CRITICAL): The configuration script resides within the Mantis installation directory at reference/scripts/configure.py. You MUST invoke this script via an absolute path or via `$MANTIS_HOME`. NEVER execute python3 reference/scripts/configure.py using a relative path inside audited target repositories.

  • CLI Options:
  • --sandbox / -s: Sandbox mechanism (static-only, gvisor,

microsandbox, gce).

  • --model / -m: Default LLM model (e.g. gemini-3.7-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 servers (e.g.

http://localhost:8000/v1).

  • --reasoning-effort: Reasoning effort level (low, medium, high).
  • --timeout: LLM request timeout in seconds.
  • --project / -p: GCP Project ID (for GCE sandbox or Vertex AI routing).
  • --zone / -z: GCP Zone (e.g. us-central1-b).
  • --image / -i: Sandbox image name (e.g. mantis-sandbox-image or

mantis-sandbox:latest).

  • --subnet: GCE Subnet name (e.g. mantis-isolated-subnet).
  • --workdir: Sandbox guest workdir (default: /workspace).
  • --workflow / -w: Path to workflow.json (defaults to auto-discovery).
  • --db / -d: Path to SQLite knowledge database (default: knowledge.db).
  • --auto: Auto-detects host capabilities and configures optimal settings

automatically.

  • --save: Explicitly saves configuration changes to workflow.local.json.
  • --save-tracked / --global: Saves configuration changes directly to base

workflow.json.

  • --interactive: Interactive step-by-step terminal wizard.
  • --test / --preflight: Executes fast (1-2s) static validation tests

verifying LLM configuration format and sandbox readiness.

  • --probe / --probe-llm: Actively probes LLM reachability, provider

credentials, and client dependencies with a minimal test prompt (test, max 256 tokens).

  • --show: Displays current configuration and diagnostic status.
  • --dry-run: Simulates configuration changes without modifying files.
  • --update-nodes: Updates all agent nodes in workflow.json to use the

specified default model.

  • --json: Outputs configuration status and preflight diagnostics in JSON.

Supported Sandbox Mechanisms

SandboxDescriptionIsolation LevelRequirements
static-onlyStatic analysis only; reproducer and dynamic patching disabled.Zero Host RiskNone (Always available)
gvisorNetworkless OCI container executed under Google gVisor (runsc).Process & Kernel sandboxdocker or podman with runsc registered
microsandboxEphemeral Linux microVM with hardware virtualization.Virtual Machine/dev/kvm read/write access
gceHardened ephemeral Google Compute Engine VM via IAP SSH tunnel.Cloud Hypervisorgcloud CLI, active GCP auth & project

Supported Model Providers

  1. Gemini Models (Google / Vertex AI):
  • gemini-3.7-flash, gemini-3.5-flash-lite
  • vertex_ai/gemini-3.7-flash, vertex_ai/gemini-3.5-flash-lite
  1. Claude Models (Vertex AI Model Garden):
  • vertex_ai/claude-opus-5
  1. MaaS & Open Source Models (Vertex Model Garden):
  • vertex_ai/zai_org/glm-5.2-maas
  1. Custom OpenAI-Compatible Endpoints:
  • openai/{MODEL_ID} or vertex_ai/openai/{MODEL_ID}
  • Supports custom --api-base (e.g. vLLM, Ollama, LiteLLM proxy),

--reasoning-effort, and --timeout.

Common CLI Workflows

1. Fast Preflight Verification (~1s) & Active Reachability Probe

Check if LLM configuration and sandbox requirements are operational:

bash
# Fast static validation (~1s):
python3 "$MANTIS_HOME/reference/scripts/configure.py" --test
# Active live reachability probe against LLM provider:
python3 "$MANTIS_HOME/reference/scripts/configure.py" --test --probe

2. Auto-Detect and Configure

Automatically inspect host capabilities (/dev/kvm, docker/runsc, gcloud) and select the best available sandbox:

bash
python3 "$MANTIS_HOME/reference/scripts/configure.py" --auto

3. Switch to Static Analysis (Zero Dependencies)

bash
python3 "$MANTIS_HOME/reference/scripts/configure.py" --sandbox static-only

4. Configure gVisor Container Sandbox

bash
python3 "$MANTIS_HOME/reference/scripts/configure.py" --sandbox gvisor --image mantis-sandbox:latest

5. Configure GCE Ephemeral Cloud Sandbox

bash
python3 "$MANTIS_HOME/reference/scripts/configure.py" --sandbox gce --project my-gcp-project --zone us-central1-b

6. Switch AI Model to Claude or Custom Endpoint

bash
# Vertex AI Claude
python3 "$MANTIS_HOME/reference/scripts/configure.py" --model vertex_ai/claude-opus-5
# Custom Local vLLM / OpenAI server
python3 "$MANTIS_HOME/reference/scripts/configure.py" --model openai/my-model --api-base http://localhost:8000/v1

7. Interactive Configuration Wizard

bash
python3 "$MANTIS_HOME/reference/scripts/configure.py" --interactive

Python API Reference

When invoked programmatically from Python:

python
from scripts.configure import (
detect_capabilities,
ensure_configured,
ensure_configured_async,
is_default_or_unconfigured,
run_preflight_checks,
run_preflight_checks_async,
update_workflow_config,
)
# 1. Check if configuration contains default placeholders
is_unconf, issues = is_default_or_unconfigured(config)
# 2. Run fast preflight checks (sync or async)
ok, messages = run_preflight_checks(config, test_llm=True, test_sandbox=True)
# or: ok, messages = await run_preflight_checks_async(config)
# 3. Ensure configured (auto-resolves defaults if unconfigured)
valid_config = ensure_configured(auto=True)
# or: valid_config = await ensure_configured_async(auto=True)

Input/Output Contract

  • Reads:
  • workflow.json and optional workflow.local.json overlay
  • Host environment (virtualization devices, container engines, cloud CLI

credentials)

  • Writes:
  • workflow.local.json (or workflow.json when --save-tracked is set)
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