SuperClaw: Open-Source Framework for Red-Teaming AI Agents
3 min. read 
Published on
Superagentic AI released SuperClaw, an open-source framework for security testing autonomous AI coding agents before deployment. This tool helps teams find weaknesses in AI agents that handle tools and make decisions on their own. It focuses on real-world behavior under attack, unlike old static scanners.
Many companies deploy AI agents with high privileges and tool access. Few run proper security checks first. SuperClaw fills this gap by simulating attacks in safe setups. Developers can now test agents locally or in pipelines without risking production systems.
Access content across the globe at the highest speed rate.
70% of our readers choose Private Internet Access
70% of our readers choose ExpressVPN
Browse the web from multiple devices with industry-standard security protocols.
Faster dedicated servers for specific actions (currently at summer discounts)
Autonomous AI agents think over time and adapt based on context. Traditional tools miss this dynamic nature. SuperClaw checks how agents act when faced with tricks like hidden commands or step-by-step escalations.
Core Workflow
SuperClaw runs scenario-based tests on live or mock AI agents. Its Bloom engine creates attack scenarios. The tool records tool calls, outputs, and decisions. Results get scored against clear security rules that outline what safe behavior looks like.
Teams get detailed evidence from each test. Reports come in formats ready for review or automation. This setup lets security pros verify issues manually every time.
The framework links with CodeOptiX from Superagentic AI. This combo checks both security and code quality in one flow.
Attack Techniques Supported
SuperClaw handles five main attack types right away. Each targets common AI agent risks.
| Attack Technique | Description | What It Tests |
|---|---|---|
| Prompt Injection | Malicious inputs try to override core instructions. | Agent rejection of untrusted prompts over developer rules. |
| Encoding Obfuscation | Hides attacks in Base64, hex, Unicode, or jumbled text. | Detection of decoded payloads before action. |
| Jailbreaks | Uses role-play or “ignore rules” prompts to bypass limits. | Strength against safety filter tricks. |
| Tool-Policy Bypass | Tricks via tool name confusion or weak rules. | Enforcement of allow/deny lists for tools. |
| Multi-Turn Escalation | Builds from safe queries to harmful ones over chats. | Long-term memory and safety in extended talks. |
These cover prompt resistance, tool controls, and session safety. Medium risks like config changes also get checked.
Safety Features
SuperClaw starts in local mode only. It blocks remote tests to avoid accidents. Users need a SUPERCLAW_AUTH_TOKEN for outside access, set by admins.
Every test requires written okay first. Findings flag issues for human checks, not auto-exploits. The GitHub repo warns: “Use responsibly as a testing tool.”
Installation and Ecosystem
Install via pip install superclaw. The Apache 2.0 license allows free use and tweaks. It joins SuperQE and CodeOptiX in Superagentic AI’s toolkit for agent builders.
Superagentic AI states: “Red-team your agents before they face real threats.”
FAQ
SuperClaw tests AI agents for security flaws before live use. It runs attacks to spot bad behaviors.
Yes, it’s open-source under Apache 2.0. Install with pip.
Prompt injection, encoding tricks, jailbreaks, tool bypass, and multi-turn attacks.
Only with auth token and permission. Defaults to local for safety.
HTML for review, JSON for pipes, SARIF for GitHub CI/CD.
Read our disclosure page to find out how can you help VPNCentral sustain the editorial team Read more
Improve this guide
User forum
0 messages