* feat(llm): add OpenAI Codex backend config and OAuth session manager Add OpenAiCodex as a new LLM backend variant with config for auth endpoint, API base URL, client ID, and session persistence path. The session manager implements OpenAI's device code auth flow (headless-friendly, no browser required on the server) with automatic token refresh, following the same persistence pattern as the existing NEAR AI session manager. Closes #742 Co-Authored-By: Claude Opus 4.6 <[email protected]> * feat(llm): add Responses API client and token-refreshing decorator Native Responses API client for chatgpt.com/backend-api/codex/responses, the endpoint that works with ChatGPT subscription tokens. Handles SSE streaming, text completions, and tool call round-trips. Token-refreshing decorator wraps the provider to pre-emptively refresh OAuth tokens before API calls and retry once on auth failures. Reports zero cost since billing is through subscription. Co-Authored-By: Claude Opus 4.6 <[email protected]> * feat(llm): wire OpenAI Codex into provider factory, CLI, and setup wizard Connect the new provider to the LLM factory, add openai_codex to the CLI --backend flag, and add it as an option in the onboarding wizard. Co-Authored-By: Claude Opus 4.6 <[email protected]> * fix(llm): address PR #744 review feedback (20 items) Review fixes for the OpenAI Codex provider PR: - Remove dead `generate_pkce()` code (device flow gets PKCE from server) - Fix `refresh_tokens()` to use `.form()` instead of `.json()` per OAuth spec - Inline codex dispatch into `build_provider_chain()` (single async function, no separate `assemble_provider_chain()` helper — matches main's pattern) - Remove Clone from `OpenAiCodexSession`, restrict fields to `pub(crate)` - Propagate HTTP client builder error instead of silent fallback - Redact device code response body from debug log - Change `set_model()` in TokenRefreshingProvider to delegate to inner - Replace hardcoded `/tmp/` test path with `tempfile::tempdir()` - Accept `request_timeout_secs` from config instead of hardcoded 300s - Parse `Retry-After` header on 429 responses (matches nearai_chat.rs pattern) - Reuse `normalize_schema_strict()` for Codex tool definitions - Add warning log for dropped image attachments - Add doc comments on `list_models()` and `include` field - Add `OPENAI_CODEX_API_URL` to `.env.example` - Fix codex error message in `create_llm_provider()` for clarity - Revert unrelated `.worktrees` addition to `.gitignore` - Update `src/llm/CLAUDE.md` with Codex provider docs [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <[email protected]> * fix: address review feedback and harden OpenAI Codex provider (takeover #744) Security: - Add SSRF validation (validate_base_url) on OPENAI_CODEX_AUTH_URL and OPENAI_CODEX_API_URL, matching the pattern used by all other base URL configs (regression test for #1103 included) Correctness: - Add missing cache_write_multiplier() and cache_read_discount() trait delegation in TokenRefreshingProvider - Cap device-code polling backoff at 60s to prevent unbounded interval growth on repeated 429 responses - Default expires_in to 3600s when server returns 0, preventing immediately-expired sessions - Fix pre-existing SseEvent::JobResult missing fallback_deliverable field in job_monitor.rs tests Cleanup: - Extract duplicated make_test_jwt() and test_codex_config() into shared codex_test_helpers module Co-Authored-By: Sanjeev-S <[email protected]> Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]> * fix: address PR review feedback on OpenAI Codex provider (#1461) - Login command now resolves OPENAI_CODEX_* env overrides even when LLM_BACKEND isn't set to openai_codex (Copilot review) - Setup wizard "Keep current provider?" for codex no longer re-triggers device code login — mirrors Bedrock's keep-and-return pattern (Copilot) - Revert provider init log from info back to debug (Copilot) - Add warning log when token expires_in=0, before defaulting to 3600s (Gemini review) Co-Authored-By: Sanjeev-S <[email protected]> Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]> --------- Co-authored-by: Sanjeev Suresh <[email protected]> Co-authored-by: Claude Opus 4.6 <[email protected]>
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 1.85+
- 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, 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/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
# First-time setup (configures database, auth, etc.)
ironclaw onboard
# Start interactive REPL
cargo run
# With debug logging
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
- Telegram channel: See docs/TELEGRAM_SETUP.md for setup and DM pairing.
- 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.
