Files
ironclaw/README.md
Coffee f948e11293 feat: wechat channel (#1666)
* Add Weixin channel with QR login and web setup flow

* Add Weixin interactive login integration tests

* Rename Weixin channel integration to WeChat

* Add WeChat typing indicators to the DM channel

* Fix WeChat extension status and login i18n

* Add WeChat image messaging and QR login polish

* Fix web auth event type after AppEvent migration

* Add WeChat inbound file and voice attachment support

* Add SILK voice fallback and WeChat polling diagnostics

* chore: lock file

* fix: error params

* fix: remove logs

* Remove redundant serde defaults from optional fields

* Add configurable WeChat merge windows and clean debug logs

* Add WeChat video and file media parity

* Treat video uploads as documents and fix web test fixtures

* Harden WeChat login randomness and add regression tests

* Harden WeChat login base URL and dedupe inbound messages

* Handle missing WeChat ret fields as errors

* Harden WeChat safety checks and secret fallback handling

* chore: fmt

* Update pairing store setup in wasm channel tests

* chore: fmt

* chore: fmt

* Harden WeChat host routing and login base URL validation

* docs

* Fix merge leftovers in web and extension tests

* Streamline WeChat QR login flow in web UI

* Remove stray image event_id and fix wrapper tests

* chore: fmt

* Improve WeChat media handling and image delivery

* Send WeChat attachments before text responses

* Handle WeChat owner scope and skip empty emitted messages

* Send generated images as inline channel attachments

* Scope WeChat channel credentials to bound users

* chore: fmt

* Release WeChat login lock during polling

* Handle missing WeChat getUpdates ret as normal

* Add requires_binding to bridge test fixtures

* chore(wechat): isolate silk-rs in standalone ironclaw-silk-decoder helper

Move all SILK decoding into a workspace-excluded crate
(`crates/ironclaw_silk_decoder/`) and invoke it from the host as a
subprocess over stdin/stdout. The main `cargo build` no longer pulls
`silk-rs` (and its `bindgen`/`libclang` build chain), addressing the
review concern flagged on PR #1666 by zmanian and Copilot.

Behavior is unchanged when the helper is installed: WeChat voice
attachments are transcoded SILK→WAV and `mime_type` rewritten to
`audio/wav`. Without the helper, the existing graceful-degrade path
preserves raw `audio/silk` bytes and logs that the decoder is missing.

The host looks up the helper in this order:
1. `IRONCLAW_SILK_DECODER` env var
2. Sibling of the running `ironclaw` executable
3. `ironclaw-silk-decoder` on `$PATH`

Caller-level tests use a Unix shell stub binary (under `tempfile`) to
drive the spawn-binary path through `maybe_transcode_wechat_silk_attachment`,
covering success, decoder-failure (caller fallback), non-RIFF rejection,
and empty-input cases.

WIP: this is the native-binary variant. A WASM-target follow-up may
replace the native binary with a single `silk-decoder.wasm` artifact
matching the WeChat channel distribution pattern.

https://claude.ai/code/session_01C5cjqPY1PkVRexraKWmmsz

* chore(silk-decoder): mark crate as standalone, commit lockfile

Add an explicit empty `[workspace]` table so cargo treats the crate as
its own root rather than trying to inherit the IronClaw workspace.
Without this, `cargo build --manifest-path crates/ironclaw_silk_decoder/Cargo.toml`
errors with "current package believes it's in a workspace when it's not".

Commit the standalone Cargo.lock for reproducible builds of the helper.

https://claude.ai/code/session_01C5cjqPY1PkVRexraKWmmsz

* fix(silk-decoder): address clippy::question_mark + assertions_on_constants

Two lints the Clippy job flagged on the silk-decoder host integration:

1. `question_mark` — replace `if let Err(error) = writer.await.map_err(...)?
   { return Err(error); }` with `writer.await.map_err(...)??;`. Same
   semantics, idiomatic.
2. `assertions_on_constants` — promote the runtime
   `assert!(MAX_DECODED_WAV_BYTES >= MAX_ATTACHMENT_BYTES)` invariant
   to a `const _: () = assert!(...)` so it's checked at compile time
   and doesn't burn a test slot.

No behavioral change.

https://claude.ai/code/session_01C5cjqPY1PkVRexraKWmmsz

* fix(silk-decoder/tests): serialize env-var mutation via lock_env

Three async stub-binary tests and two resolve-command tests all mutate
the same `IRONCLAW_SILK_DECODER` env var. Under cargo's parallel
test threads they trampled each other, causing flaky failures (each
test passed in isolation, two failed when run together). The CI
"Run Tests" job hit this on the latest commit.

Adopt the existing `crate::config::helpers::lock_env()` mutex pattern
already used by shell.rs, llm/recording.rs, pairing/approval.rs,
restart.rs, etc. EnvGuard now holds the lock as a field so the env
var stays restored before another test takes the lock; ordering is
guaranteed because Drop runs the custom restoration body before
field-drop releases the mutex.

Verified locally: all 13 channels::wasm::attachment_hydration tests
pass with the default parallel test runner.

https://claude.ai/code/session_01C5cjqPY1PkVRexraKWmmsz

* chore(silk-decoder): switch silk-rs -> silk-codec 0.2.0

silk-codec is a sibling fork of the same upstream Skype SILK SDK
sources used by silk-rs, but newer and better-maintained:

- bindgen 0.72 (vs silk-rs's 0.59 from 2021)
- cc 1.2 (vs older)
- thiserror 2.0
- Identical decode_silk(src, sample_rate) -> Result<Vec<u8>, SilkError>
  signature; both implementations skip the 0x02 Tencent flag and
  require the "#!SILK_V3" header, so behavior on WeChat voice notes
  is unchanged.

This is purely a tooling refresh in the standalone helper crate. The
main IronClaw build still has zero SILK / libclang dependency. The
host's subprocess invocation, capability gating, size caps, and
graceful-degrade-to-raw-SILK fallback are all unchanged.

Verified locally:
- crates/ironclaw_silk_decoder: 6/6 unit tests pass
- ironclaw lib: 13/13 attachment_hydration tests pass (parallel runner)
- cargo fmt --check: clean

Note: PR #1666's spec-compatibility comment in Cargo.toml previously
named silk-rs; the renamed comment in this commit reflects the new
dependency. No other host code references either crate by name.

https://claude.ai/code/session_01C5cjqPY1PkVRexraKWmmsz

---------

Co-authored-by: Robert Yan <46699230+think-in-universe@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
2026-05-07 14:19:41 +00:00

15 KiB

IronClaw

IronClaw

Your secure personal AI assistant, always on your side

License: MIT OR Apache-2.0 Telegram: @ironclawAI Reddit: r/ironclawAI gitcgr

English | 简体中文 | Русский | 日本語 | 한국어

PhilosophyFeaturesInstallationConfigurationSecurityArchitecture


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)
  • libclang and a working C toolchain if you build the WeChat voice/SILK path from source

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.

Optional: WeChat voice notes (audio/silk) require the standalone ironclaw-silk-decoder helper to be transcribable. It's excluded from the default workspace build because silk-codec pulls in bindgen/libclang. Build it separately with ./crates/ironclaw_silk_decoder/build.sh (needs libclang + a C toolchain) and put the resulting binary on $PATH, beside the ironclaw binary, or pointed at by IRONCLAW_SILK_DECODER. Without it, voice messages are still delivered — just as raw audio/silk blobs.

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.sh before cargo build so 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:

at your option.