* test(replay): add approval round-trip fixtures (Phase 2 of #2828) First fixture-driven Layer 1 (replay) coverage of the full v1 approval cycle: pause -> user resolution -> resume. Companion to the existing no_done_emitted_while_awaiting_approval test in e2e_response_order.rs, which covers the pause but not the resume. Three scenarios: - approval_yes: user approves -> tool runs once -> final LLM response - approval_no: user denies -> tool does NOT run -> agent surfaces a built-in rejection message (no follow-up LLM call, by design) - approval_always: allow-always on first call -> second call runs without re-prompting, exactly one ApprovalNeeded total Uses a test-only NeedsApprovalProbe tool with ApprovalRequirement::UnlessAutoApproved registered via TestRig::with_extra_tools, with auto_approve_tools(false) so the agent actually pauses for resolution. The deny-path discovery (no LLM follow-up on rejection) is documented in the test so future readers don't reintroduce the trailing text step. Updates tests/fixtures/llm_traces/README.md to list the new fixtures. Bumps approvals coverage in the harness-testing matrix from ~ to (closer to) full at Layer 1. * test(replay): expand approval coverage with 4 missing scenarios Adds the four approval scenarios that the original three-test set omitted, completing the state-space matrix across ApprovalRequirement variants, the master kill-switch config, and submission-routing edge cases. New tests (all in tests/e2e_approval_traces.rs): - always_requirement_ignores_allow_always_persistence ApprovalRequirement::Always is the unbypassable hard floor — even an 'allow-always' resolution must NOT skip the pause on subsequent calls of an Always-tool. Two pauses for two calls. - slash_approve_routes_as_approval_response '/approve' is parsed as Submission::ApprovalResponse even though bare 'yes' downgrades to UserInput when nothing is pending. Pins the divergent routing in submission.rs. - bare_yes_with_no_pending_approval_is_user_input Bare 'yes' with no pending approval must downgrade to UserInput and reach the LLM as a normal user message. Asserts the routing layer in agent_loop.rs performs the downgrade (parser is stateless). - config_auto_approve_bypasses_unless_auto_approved Agent-config auto_approve_tools=true is the master kill-switch — no ApprovalNeeded is ever emitted, even for UnlessAutoApproved tools. Also adds AlwaysApprovalProbe (mirrors NeedsApprovalProbe but returns ApprovalRequirement::Always) and three fixtures: - approval_always_floor.json - approval_slash.json - approval_bare_yes_no_pending.json README updated to list the new fixtures. Phase 2 of #2828. * test(replay): add auth-gate round-trip fixtures (Phase 2 of #2828) Five replay fixtures covering the engine v2 auth-gate state space: - auth_credential_provided: happy path (CredentialProvided -> resume) - auth_cancelled: user rejects (Cancelled -> resume) - auth_retry_invalid_then_valid: invalid credential, retry path - auth_external_callback: ExternalCallback submission path - auth_gate_request_id: AuthRequired populates request_id (v2 only) Probe tool: MockActivateTool (name "tool_activate") with scriptable output queue, installed via TestRegistry::replace_for_test to bypass PROTECTED_TOOL_NAMES. Planted minimal SKILL.md provides the credential spec needed by AuthManager's submit_auth_token path (otherwise the auth flow short-circuits with "Extension not installed"). Rig additions: - send_gate_auth_resolution(request_id, AuthGateResolution) - send_external_callback(request_id) - with_test_tool_override(tool) builder - TestChannel::channel_name / user_id accessors Serialization: all auth-gate tests share engine_v2_test_lock() (per-file static Mutex) because engine v2 uses a process-global OnceLock<RwLock<Option<EngineState>>>. Fixtures omit tools_used / all_tools_succeeded because engine v2 suppresses ToolStarted/ToolCompleted events when a tool output becomes a gate pause; verification uses the mock's internal execution counter instead. * test(router): cover auth fallback caller path (Phase 2 of #2828) * test(harness): add gateway-ops trace replay runner (#643, Phase 2 of #2828) Introduces Trace/TraceOperation/TraceExpectation types and TraceRunner that replays an ordered sequence of tool invocations against a libSQL test DB. The runner creates ActionRecords via the same save_action path gateway handlers use and matches outcomes against declared expectations. This is the inverse of the agentic TraceLlm harness: where TraceLlm replays an LLM stream and asserts the agent re-produces tool calls, TraceRunner replays caller-dispatched tool calls and asserts the Tool -> ActionRecord -> save_action pipeline matches expectations. Deliverables: - tests/support/trace_runner.rs: Trace, TraceOperation, TraceExpectation (Success { assertions } / Failure { error_contains }), TraceResult (with job_id for DB cross-checks), TraceFailure, TraceRunner with replay(). Assertion DSL supports eq / contains_text / fields (dot-path). - tests/e2e_gateway_trace_harness.rs: 7 integration tests covering echo roundtrip, idempotency, unknown-tool failure, mix assertions, forced mismatch detection, DB persistence via get_job_actions, and cross-run determinism. - tests/fixtures/gateway_traces/: 4 JSON fixtures + README documenting the wire format and the deferred settings_* / extension_* roadmap (blocked on #640 and network-stub work respectively). Pitfalls addressed: - Parent agent_jobs row is created via save_job before the first save_action; job_actions.job_id has a FK to agent_jobs(id) ON DELETE CASCADE that would otherwise fail. - Deterministic-field check in the determinism test excludes id / executed_at / duration (intentionally variable across replays). - ToolError has no NotFound variant; missing-tool lookups are reported via ExecutionFailed("tool not registered: {name}") so Failure expectations can substring-match on "not registered". * fix: address review findings (iteration 1)
IronClaw
Your secure personal AI assistant, always on your side
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Philosophy • Features • Installation • Configuration • Security • Architecture
Philosophy
IronClaw is built on a simple principle: your AI assistant should work for you, not against you.
In a world where AI systems are increasingly opaque about data handling and aligned with corporate interests, IronClaw takes a different approach:
- Your data stays yours - All information is stored locally, encrypted, and never leaves your control
- Transparency by design - Open source, auditable, no hidden telemetry or data harvesting
- Self-expanding capabilities - Build new tools on the fly without waiting for vendor updates
- Defense in depth - Multiple security layers protect against prompt injection and data exfiltration
IronClaw is the AI assistant you can actually trust with your personal and professional life.
Features
Security First
- WASM Sandbox - Untrusted tools run in isolated WebAssembly containers with capability-based permissions
- Credential Protection - Secrets are never exposed to tools; injected at the host boundary with leak detection
- Prompt Injection Defense - Pattern detection, content sanitization, and policy enforcement
- Endpoint Allowlisting - HTTP requests only to explicitly approved hosts and paths
Always Available
- Multi-channel - REPL, HTTP webhooks, WASM channels (Telegram, Slack), and web gateway
- Docker Sandbox - Isolated container execution with per-job tokens and orchestrator/worker pattern
- Web Gateway - Browser UI with real-time SSE/WebSocket streaming
- Routines - Cron schedules, event triggers, webhook handlers for background automation
- Heartbeat System - Proactive background execution for monitoring and maintenance tasks
- Parallel Jobs - Handle multiple requests concurrently with isolated contexts
- Self-repair - Automatic detection and recovery of stuck operations
Self-Expanding
- Dynamic Tool Building - Describe what you need, and IronClaw builds it as a WASM tool
- MCP Protocol - Connect to Model Context Protocol servers for additional capabilities
- Plugin Architecture - Drop in new WASM tools and channels without restarting
Persistent Memory
- Hybrid Search - Full-text + vector search using Reciprocal Rank Fusion
- Workspace Filesystem - Flexible path-based storage for notes, logs, and context
- Identity Files - Maintain consistent personality and preferences across sessions
Installation
Prerequisites
- Rust 1.92+
- PostgreSQL 15+ with pgvector extension
- NEAR AI account (authentication handled via setup wizard)
Download or Build
Visit Releases page to see the latest updates.
Install via Windows Installer (Windows)
Download the Windows Installer and run it.
Install via powershell script (Windows)
irm https://github.com/nearai/ironclaw/releases/latest/download/ironclaw-installer.ps1 | iex
Install via shell script (macOS, Linux, Windows/WSL)
curl --proto '=https' --tlsv1.2 -LsSf https://github.com/nearai/ironclaw/releases/latest/download/ironclaw-installer.sh | sh
Install via Homebrew (macOS/Linux)
brew install ironclaw
Compile the source code (Cargo on Windows, Linux, macOS)
Install it with cargo, just make sure you have Rust installed on your computer.
# Clone the repository
git clone https://github.com/nearai/ironclaw.git
cd ironclaw
# Build
cargo build --release
# Run tests
cargo test
For full release (after modifying channel sources), run ./scripts/build-all.sh to rebuild channels first.
Database Setup
# Create database
createdb ironclaw
# Enable pgvector
psql ironclaw -c "CREATE EXTENSION IF NOT EXISTS vector;"
Configuration
Run the setup wizard to configure IronClaw:
ironclaw onboard
The wizard handles database connection, NEAR AI authentication (via browser OAuth),
and secrets encryption (using your system keychain). Settings are persisted in the
connected database; bootstrap variables (e.g. DATABASE_URL, LLM_BACKEND) are
written to ~/.ironclaw/.env so they are available before the database connects.
Alternative LLM Providers
IronClaw defaults to NEAR AI but supports many LLM providers out of the box. Built-in providers include Anthropic, OpenAI, GitHub Copilot, Google Gemini, MiniMax, Mistral, and Ollama (local). OpenAI-compatible services like OpenRouter (300+ models), Together AI, Fireworks AI, and self-hosted servers (vLLM, LiteLLM) are also supported.
Select your provider in the wizard, or set environment variables directly:
# Example: MiniMax (built-in, 204K context)
LLM_BACKEND=minimax
MINIMAX_API_KEY=...
# Example: OpenAI-compatible endpoint
LLM_BACKEND=openai_compatible
LLM_BASE_URL=https://openrouter.ai/api/v1
LLM_API_KEY=sk-or-...
LLM_MODEL=anthropic/claude-sonnet-4
See docs/capabilities/llm-providers.md for a full provider guide.
Security
IronClaw implements defense in depth to protect your data and prevent misuse.
WASM Sandbox
All untrusted tools run in isolated WebAssembly containers:
- Capability-based permissions - Explicit opt-in for HTTP, secrets, tool invocation
- Endpoint allowlisting - HTTP requests only to approved hosts/paths
- Credential injection - Secrets injected at host boundary, never exposed to WASM code
- Leak detection - Scans requests and responses for secret exfiltration attempts
- Rate limiting - Per-tool request limits to prevent abuse
- Resource limits - Memory, CPU, and execution time constraints
WASM ──► Allowlist ──► Leak Scan ──► Credential ──► Execute ──► Leak Scan ──► WASM
Validator (request) Injector Request (response)
Prompt Injection Defense
External content passes through multiple security layers:
- Pattern-based detection of injection attempts
- Content sanitization and escaping
- Policy rules with severity levels (Block/Warn/Review/Sanitize)
- Tool output wrapping for safe LLM context injection
Data Protection
- All data stored locally in your PostgreSQL database
- Secrets encrypted with AES-256-GCM
- No telemetry, analytics, or data sharing
- Full audit log of all tool executions
Architecture
┌────────────────────────────────────────────────────────────────┐
│ Channels │
│ ┌──────┐ ┌──────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ REPL │ │ HTTP │ │WASM Channels│ │ Web Gateway │ │
│ └──┬───┘ └──┬───┘ └──────┬──────┘ │ (SSE + WS) │ │
│ │ │ │ └──────┬──────┘ │
│ └─────────┴──────────────┴────────────────┘ │
│ │ │
│ ┌─────────▼─────────┐ │
│ │ Agent Loop │ Intent routing │
│ └────┬──────────┬───┘ │
│ │ │ │
│ ┌──────────▼────┐ ┌──▼───────────────┐ │
│ │ Scheduler │ │ Routines Engine │ │
│ │(parallel jobs)│ │(cron, event, wh) │ │
│ └──────┬────────┘ └────────┬─────────┘ │
│ │ │ │
│ ┌─────────────┼────────────────────┘ │
│ │ │ │
│ ┌───▼─────┐ ┌────▼────────────────┐ │
│ │ Local │ │ Orchestrator │ │
│ │Workers │ │ ┌───────────────┐ │ │
│ │(in-proc)│ │ │ Docker Sandbox│ │ │
│ └───┬─────┘ │ │ Containers │ │ │
│ │ │ │ ┌───────────┐ │ │ │
│ │ │ │ │Worker / CC│ │ │ │
│ │ │ │ └───────────┘ │ │ │
│ │ │ └───────────────┘ │ │
│ │ └─────────┬───────────┘ │
│ └──────────────────┤ │
│ │ │
│ ┌───────────▼──────────┐ │
│ │ Tool Registry │ │
│ │ Built-in, MCP, WASM │ │
│ └──────────────────────┘ │
└────────────────────────────────────────────────────────────────┘
Core Components
| Component | Purpose |
|---|---|
| Agent Loop | Main message handling and job coordination |
| Router | Classifies user intent (command, query, task) |
| Scheduler | Manages parallel job execution with priorities |
| Worker | Executes jobs with LLM reasoning and tool calls |
| Orchestrator | Container lifecycle, LLM proxying, per-job auth |
| Web Gateway | Browser UI with chat, memory, jobs, logs, extensions, routines |
| Routines Engine | Scheduled (cron) and reactive (event, webhook) background tasks |
| Workspace | Persistent memory with hybrid search |
| Safety Layer | Prompt injection defense and content sanitization |
Usage
Engine v2 is opt-in right now. If you want to run the new engine instead of the legacy agent loop, start IronClaw with ENGINE_V2=true. See Engine v2 architecture for more details.
# First-time setup (configures database, auth, etc.)
ironclaw onboard
# Start interactive REPL
cargo run
# Start interactive REPL with engine v2
ENGINE_V2=true cargo run
# Engine v2 with debug logging
ENGINE_V2=true RUST_LOG=ironclaw=debug cargo run
Development
# Format code
cargo fmt
# Lint
cargo clippy --all --benches --tests --examples --all-features
# Run tests
createdb ironclaw_test
cargo test
# Run specific test
cargo test test_name
- Channels: See docs/channels/overview.mdx for setup of Telegram, Discord, and other channels.
- Changing channel sources: Run
./channels-src/telegram/build.shbeforecargo buildso the updated WASM is bundled.
OpenClaw Heritage
IronClaw is a Rust reimplementation inspired by OpenClaw. See FEATURE_PARITY.md for the complete tracking matrix.
Key differences:
- Rust vs TypeScript - Native performance, memory safety, single binary
- WASM sandbox vs Docker - Lightweight, capability-based security
- PostgreSQL vs SQLite - Production-ready persistence
- Security-first design - Multiple defense layers, credential protection
License
Licensed under either of:
- Apache License, Version 2.0 (LICENSE-APACHE)
- MIT License (LICENSE-MIT)
at your option.
