AI Agent Wave: Chaitin ShouYuan Solves Enterprise Security Concerns AI Agent 风潮已至，长亭「守元」破解企业”不敢用”困境

Originally published on Chaitin Technology’s WeChat account. Read original

The AI Agent wave triggered by OpenClaw is shifting from “who can use it first” to “who can use it more safely.” Enterprises are deploying agents and building platforms, but security concerns remain the biggest hurdle.

Chaitin Technology’s “ShouYuan” LLM Security Guardrail has upgraded again, officially launching Agent protection capabilities — a systematic solution targeting AI Agent ecosystem threats.

Three core functions precisely address malicious Skill injection, agent execution chain failures, covering black-box assessment, white-box Skills analysis, and real-time protection across the full pipeline.

Why Can’t Conventional Tools Stop Agent Risks?

Challenge 1: Diverse agent architectures defy universal analysis

Dify, LangChain, Claude Code, OpenClaw — each has different input channels, runtime logic, and call chains. Fixed-architecture tools simply can’t achieve full coverage.

Challenge 2: LLM Guard models can’t handle agent risk analysis

Qwen3Guard achieves only 55.3% accuracy on the ATBench agent attack dataset. LLM Guards focus on generated content safety, while agent risks hide in execution chains, script calls, external interactions, and privilege escalation — fundamentally different from text content safety.

Challenge 3: Agent risks require multi-dimensional fine-grained classification

Agent security spans unsafe requests, task intent hijacking, unsafe execution, credential abuse, and more. Single-dimension tools can’t form complete protection.

ShouYuan’s Three Core Functions

Function 1: Proactive Security Assessment

ShouYuan employs a closed-loop automated red team mechanism:

1. Knowledge acquisition to understand target Agent architecture and capabilities
2. “Malicious user” construction to probe functional boundaries in real interactions
3. Dynamic attack strategy and payload generation based on gathered intelligence
4. Real-time feedback driving strategy iteration for adaptive assessment

Function 2: SKILLS White-box Penetration Testing

For malicious Skill injection (no-code document lures, binary backdoors, nested malicious scripts), ShouYuan deploys a proprietary penetration testing agent for professional-grade scanning. It features a unique white-box vulnerability verification mechanism that actively validates every finding to eliminate false positives.

ShouYuan has scanned 9,000+ skills across public ClawhHub and skills.rest platforms, discovering 100+ malicious skills.

Function 3: Real-time Traffic Detection with Semantic-driven Intent Blocking

The most dangerous agent attacks aren’t explicit malicious code — they’re intent manipulation, task deviation, and stealth instruction injection. ShouYuan constructs complete dialog context from agent traffic, performing real-time intent recognition and task alignment verification around two core principles: intent invariance and task alignment.

Use Cases

Enterprise users: R&D agents, ops agents, third-party Skill plugin management — defending against supply chain attacks and intranet infection.

Security professionals: Penetration testing, threat analysis, Skill sample auditing — efficient malicious sample triage.

Individual developers: Personal agent tools, third-party script protection — preventing backdoor implantation and data theft.

Conclusion

AI Agent adoption is here, but security must remain the bottom line. An AI Agent without security guarantees is like a high-speed engine without brakes — the faster it runs, the greater the risk.