A lightweight personal AI assistant framework
Project description
ShibaClaw 🐕
Security-first AI agent with built-in WebUI, native provider support, and hardened tools.
ShibaClaw is a security-first AI agent that runs in your terminal or in a browser-based WebUI. Instead of assuming the surrounding app will handle safety, it builds it into the core: install-time CVE auditing, randomized tool-output wrapping against prompt injection, SSRF and DNS rebinding protection, shell hardening, workspace sandboxing, and token auth. You still get the practical pieces you need for daily use: WebUI & onboarding, 22 LLM providers, built-in file tools, long-term memory, 11 chat channels, cron, heartbeat, skills, and MCP support.
Security, Built In
These are the defenses that are often left to app glue code or external proxies. In ShibaClaw they are part of the framework itself.
| Layer | Built in by default | Why it matters |
|---|---|---|
| Distributed Engine | Decoupled UI (128MB RAM) from Brain (256MB+ RAM) | High performance even on low-spec hardware or VPS |
| Install-time audit | Audits pip and npm installs before execution; blocks critical/high CVEs |
Catches risky dependencies before they land in the environment |
| Prompt-injection wrapping | Wraps every tool result in a randomized <tool_output_...> boundary and sanitizes closing tags |
Untrusted pages and files stay data, not instructions |
| Shell hardening | 20+ deny patterns, escape normalization (\x.., \u....), internal URL detection |
Blocks common destructive or obfuscated commands |
| Network guard | SSRF filtering, redirect revalidation, DNS-rebinding-safe resolution | Prevents web tools from pivoting into localhost or private networks |
| Workspace sandbox | File tools and the WebUI file browser stay inside the configured workspace | Reduces traversal and accidental host-wide access |
| Access control | Bearer token auth, constant-time token checks, channel allowlists, optional sender rate limiting | Safer when the agent is exposed beyond a local shell |
Quick Start
Docker
git clone https://github.com/RikyZ90/ShibaClaw.git && cd ShibaClaw
docker compose up -d --build
docker exec -it shibaclaw-gateway shibaclaw print-token
Open http://localhost:3000 — paste the token if auth is enabled, then complete the onboard wizard in the browser.
pip
pip install shibaclaw
# Simple start (default localhost:3000)
shibaclaw web --with-gateway
# Custom local port
shibaclaw web --host 127.0.0.1 --port 3000 --with-gateway
Open http://localhost:3000 and complete the onboard wizard.
The --with-gateway flag automatically starts the agent engine in the background for you.
Prefer the terminal? shibaclaw onboard runs the same guided setup from the CLI.
WebUI
The WebUI is built-in — no separate frontend or Node.js required.
- Chat — multi-session conversations with live streaming of tool calls, thinking blocks, and elapsed time
- Agent Profiles — switch personas per session (Hacker, Builder, Planner, Reviewer) with dynamic avatars
- File browser — browse, view, and edit workspace files in-browser (sandboxed to workspace)
- Voice — speech-to-text via OpenAI-compatible audio APIs and browser-native TTS
- Settings — configure agent, provider, tools, MCP servers, channels, skills, and OAuth from a single panel
- Onboard wizard — guided first-time setup: pick a provider, enter API key or start OAuth, choose a model
- Context viewer — inspect the full system prompt and token usage breakdown
- Gateway monitor — health check and one-click restart
- Auto-update — checks GitHub releases every 12h, notifies in the UI and on all active channels
- Responsive — works on desktop and mobile
Agent Profiles
Switch the agent's personality on-the-fly without losing context. Each profile overrides the system prompt (SOUL.md) while keeping model, memory, and tools shared. Profiles are per-session — run a security audit in one tab and plan architecture in another.
Built-in profiles: Default · Builder · Planner · Reviewer · Hacker (elite security expert with 50+ tool recommendations, OWASP/MITRE/NIST methodologies, CVSS scoring, and a custom cyber-shiba avatar).
Create your own profiles interactively — the agent walks you through defining the persona and saves everything automatically.
Features
Memory & Workflow
- Three-level memory —
USER.md(personal profile),MEMORY.md(operational facts),HISTORY.md(timestamped session archive with TF-IDF + recency search) - Proactive learning — every N messages the agent silently consolidates new learnings into memory, without interrupting the conversation
- Focused background delegation — the
spawntool can offload a specific task and report back into the same session when done - Advanced reasoning — supports extended thinking (Anthropic), reasoning effort (OpenAI o-series), and DeepSeek-R1 chains
Tools
| Tool | What it does |
|---|---|
exec |
Shell commands with 20+ deny-pattern guards, encoding normalization, and CVE scanning |
read_file / write_file / edit_file |
Paginated reads, fuzzy find-and-replace, auto-created parent dirs |
web_search |
Brave, Tavily, SearXNG, Jina, or DuckDuckGo (fallback, no key needed) |
web_fetch |
HTTP fetch with SSRF protection, DNS rebinding defense, and redirect validation |
memory_search |
Ranked search over session history (TF-IDF + recency + importance scoring) |
message |
Cross-channel messaging with media attachments |
cron |
Schedule one-time or recurring jobs (cron expressions, intervals, ISO dates, timezone-aware) |
spawn |
Optional background worker for a focused task; reports back to the main session when done |
| MCP | Connect any MCP server (stdio, SSE, or streamable HTTP) — tools auto-registered as mcp_<server>_<tool> |
Channels
Telegram · Discord · Slack · WhatsApp · Matrix · Email · DingTalk · Feishu · QQ · WeCom · MoChat
All channels route through the same message bus. WhatsApp uses a Node.js bridge (Baileys) for QR-based linking.
Skills
8 built-in skills (GitHub, weather, summarize, tmux, cron reference, memory guide, skill-creator, ClawHub browser). Skills are Markdown files with YAML frontmatter and optional scripts — create your own or install from ClawHub. Pin frequently-used skills to load them on every conversation.
Automation
- Cron service — persistent, timezone-aware scheduled jobs stored in
jobs.json. Supportsevery,cron, andatschedules. Overdue jobs fire on startup. - Heartbeat — periodic wake-up reads
HEARTBEAT.md, uses its frontmatter for session/profile/targets, keeps enable/interval in global settings, skips the LLM entirely whenActive Tasksis empty, and only asks the model to decide when real active work exists.
If you are upgrading from an older release, it is recommended to reset your workspace HEARTBEAT.md once so you get the new frontmatter-based base template. Existing files still work, but they will not gain the new editable settings block automatically.
Security Policy
The table above is the operational summary. The full disclosure process, supported versions, and defense-in-depth notes live in SECURITY.md.
Supported Providers
ShibaClaw uses native SDKs (no LiteLLM proxy) and auto-detects the right provider from the model name.
API Key
| Provider | Env Variable |
|---|---|
| OpenAI | OPENAI_API_KEY |
| Anthropic | ANTHROPIC_API_KEY |
| DeepSeek | DEEPSEEK_API_KEY |
| Google Gemini | GEMINI_API_KEY |
| Groq | GROQ_API_KEY |
| Moonshot | MOONSHOT_API_KEY |
| MiniMax | MINIMAX_API_KEY |
| Zhipu AI | ZAI_API_KEY |
| DashScope | DASHSCOPE_API_KEY |
Gateway / Proxy
OpenRouter · AiHubMix · SiliconFlow · VolcEngine · BytePlus — auto-detected by key prefix or api_base.
Local
Ollama (http://localhost:11434) · vLLM · any OpenAI-compatible endpoint.
OAuth
| Provider | Flow | Setup |
|---|---|---|
| GitHub Copilot | Device flow, auto token refresh | shibaclaw provider login github-copilot or WebUI Settings |
| OpenAI Codex | PKCE browser flow | shibaclaw provider login openai-codex or WebUI Settings |
Architecture
Docker Compose
| Service | Role | Default Port |
|---|---|---|
shibaclaw-gateway |
Core agent loop, message bus, channel integrations | 19999 |
shibaclaw-web |
WebUI (Starlette + Socket.IO), cron service | 3000 |
Both share the ~/.shibaclaw/ volume (config, workspace, memory, cron jobs, media cache).
Single-process mode
shibaclaw web runs agent + WebUI + cron in a single process — no gateway container needed.
Stack
| Layer | Technology |
|---|---|
| Server | Uvicorn → Starlette (ASGI) + python-socketio |
| Real-time | Socket.IO (WebSocket primary, polling fallback) |
| Frontend | Vanilla JS · Marked.js · Highlight.js |
| Sessions | JSONL append-only per session (cache-friendly for LLM prompt prefixes) |
Resource usage
| Component | Idle | Peak (install/compile) |
|---|---|---|
| Gateway | ~120 MB | ~350 MB |
| WebUI | ~120 MB | ~350 MB |
Docker Compose sets a 512 MB limit / 256 MB reservation per container. Tool output is streamed with bounded buffers, so long-running commands (apt, npm install) can't blow up memory.
CLI Reference
shibaclaw web # Start WebUI (agent + cron in-process)
shibaclaw gateway # Start gateway only (for Docker split)
shibaclaw onboard # CLI-based first-time setup wizard
shibaclaw agent -m "Hello" # One-shot message via terminal
shibaclaw agent # Interactive REPL with history
shibaclaw status # Provider, workspace, OAuth health check
shibaclaw print-token # Show WebUI auth token
shibaclaw channels status # List enabled channels
shibaclaw provider login <p> # OAuth login (github-copilot, openai-codex)
Latest — v0.0.28
- Heartbeat frontmatter config — configure session, profile, interval, and output targets directly in
HEARTBEAT.md - No-op heartbeat optimization — no LLM call when
Active Tasksis empty - Cron blank-job guard — empty scheduled agent jobs are skipped instead of waking the model
→ v0.0.28: full details and upgrade notes, including the recommended HEARTBEAT.md reset
→ Full history in CHANGELOG.md
Troubleshooting
| Problem | Try |
|---|---|
| General status check | shibaclaw status |
| Container logs | docker logs shibaclaw-gateway / docker logs shibaclaw-web |
| WebUI won't connect | Check token with shibaclaw print-token, verify port binding |
| Provider errors | shibaclaw status shows API key and OAuth state |
| Security policy | SECURITY.md |
Contributing
See CONTRIBUTING.md — PRs welcome.
Channels are extensible via Python entry points (shibaclaw.integrations). Skill creation is documented in docs/CHANNEL_PLUGIN_GUIDE.md and the built-in skill-creator skill.
Credits
Inspired by NanoBot by HKUDS — MIT License.
If you like ShibaClaw and want to help it grow:
⭐ Drop a star —
🐛 Open an issue —
🔧 Send a PR
contributions of any size are welcome
💬 Join the Discord — questions, feedback, and show & tell
We're new — come help shape what ShibaClaw becomes.
Join us on Discord and let's build something together.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file shibaclaw-0.0.37.tar.gz.
File metadata
- Download URL: shibaclaw-0.0.37.tar.gz
- Upload date:
- Size: 1.9 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
dc637a4a26ef067dcba9a5a50c57cf62cd0eb6aa36778f6f1840713ce496e766
|
|
| MD5 |
185a4a6325a1f3ffd8c350f6802f159b
|
|
| BLAKE2b-256 |
1651fef89ea0b59f33f1312d57889cd8e79bda98142f668259aa3da46ae3a224
|
Provenance
The following attestation bundles were made for shibaclaw-0.0.37.tar.gz:
Publisher:
publish.yml on RikyZ90/ShibaClaw
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
shibaclaw-0.0.37.tar.gz -
Subject digest:
dc637a4a26ef067dcba9a5a50c57cf62cd0eb6aa36778f6f1840713ce496e766 - Sigstore transparency entry: 1327965528
- Sigstore integration time:
-
Permalink:
RikyZ90/ShibaClaw@aeaa731602a95ec204b085a93da4f1c5584b34fd -
Branch / Tag:
refs/tags/v0.0.37 - Owner: https://github.com/RikyZ90
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@aeaa731602a95ec204b085a93da4f1c5584b34fd -
Trigger Event:
push
-
Statement type:
File details
Details for the file shibaclaw-0.0.37-py3-none-any.whl.
File metadata
- Download URL: shibaclaw-0.0.37-py3-none-any.whl
- Upload date:
- Size: 2.0 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8a72de4dec765df3fd5721f9f6e6ec5ee697be6f6b1aec7cb8c4f39f9cd7b0da
|
|
| MD5 |
b91df53aaf3b720dc115618628e454e3
|
|
| BLAKE2b-256 |
6d913d5aaf9920cf54bd9603f8cfaa74018da9a1a69b17dca133b490652b6692
|
Provenance
The following attestation bundles were made for shibaclaw-0.0.37-py3-none-any.whl:
Publisher:
publish.yml on RikyZ90/ShibaClaw
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
shibaclaw-0.0.37-py3-none-any.whl -
Subject digest:
8a72de4dec765df3fd5721f9f6e6ec5ee697be6f6b1aec7cb8c4f39f9cd7b0da - Sigstore transparency entry: 1327965618
- Sigstore integration time:
-
Permalink:
RikyZ90/ShibaClaw@aeaa731602a95ec204b085a93da4f1c5584b34fd -
Branch / Tag:
refs/tags/v0.0.37 - Owner: https://github.com/RikyZ90
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@aeaa731602a95ec204b085a93da4f1c5584b34fd -
Trigger Event:
push
-
Statement type: