06eeea3dee
Some checks failed
Invert the agent model: the agent IS the computer. The message pump becomes the kernel, handlers are sandboxed apps, and all access is mediated by the platform. Phase 1 — Container foundation: - Multi-stage Dockerfile (python:3.12-slim, non-root user, /data volume) - deploy/entrypoint.py with --dry-run config validation - docker-compose.yml (cap_drop ALL, read_only, no-new-privileges) - docker-compose.dev.yml overlay for development - CI Docker build smoke test Phase 2 — Security hardening: - xml_pipeline/security/ module with default-deny container mode - Permission gate: per-listener tool allowlist enforcement - Network policy: egress control (only declared LLM backend domains) - Shell tool: disabled in container mode - File tool: restricted to /data and /config in container mode - Fetch tool: integrates network egress policy - Config loader: parses security and network YAML sections Phase 3 — Management plane: - Agent app (port 8080): minimal /health, /inject, /ws only - Management app (port 9090): full API, audit log, dashboard - SQLite-backed audit log for tool invocations and security events - Static web dashboard (no framework, WebSocket-driven) - CLI --split flag for dual-port serving All 439 existing tests pass with zero regressions. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> |
||
|---|---|---|
| .. | ||
| listeners | ||
| organism_identity | ||
| schema | ||
| __init__.py | ||
| agents.py | ||
| features.py | ||
| initial_config.signed.xml | ||
| loader.py | ||
| split_loader.py | ||
| template.py | ||