agentic-top-10

Evaluate autonomous AI system architecture and code for security vulnerabilities.

Updated Apr 19, 2026

Search Tags:#OWASP #multi-agent #architecture review #security assessment #AI vulnerabilities #agent security

Ready to run

npx skills add https://github.com/do360now/security-agents --skill agentic-top-10

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agentic-top-10
Source: https://github.com/do360now/security-agents/tree/main/.claude/skills/agentic-top-10
Command: npx skills add https://github.com/do360now/security-agents --skill agentic-top-10

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill assesses agentic AI systems to identify vulnerabilities related to permissions, tool misuse, memory poisoning, and trust boundaries, helping organizations prevent exploitation and ensure secure deployment.

Core Features & Use Cases

Threat Identification: Detects issues like excessive permissions, privilege escalation, and memory attacks in multi-agent setups.
Architectural Analysis: Reviews system architecture diagrams and code to highlight security gaps.
Risk Recommendations: Provides mitigation strategies tailored to agent permissions, communication, and resource management.
Use Case: Ideal for security engineers and developers evaluating AI-powered multi-agent systems in production for compliance and robustness.

Quick Start

Provide system architecture diagrams and code snippets for an agent deployed with tool permissions and credential handling to evaluate security risks.

Frequently Asked Questions about agentic-top-10

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I perform a security assessment of a multi-agent AI system architecture?▼

To perform a security assessment of a multi-agent AI system, evaluate the architecture and code to identify vulnerabilities like privilege escalation, trust boundary violations, and resource exhaustion. This process detects excessive permissions and memory poisoning.

What are common AI vulnerabilities in autonomous multi-agent deployments?▼

Common AI vulnerabilities in autonomous multi-agent deployments include excessive permissions, privilege escalation, memory poisoning, and tool misuse. These issues often arise from inadequate trust boundaries and improper resource management within the system architecture.

How do I check my autonomous AI agents for OWASP Top 10 compliance?▼

To check autonomous AI agents for OWASP Top 10 compliance, review system architecture diagrams and code snippets focusing on tool permissions and credential handling. This identifies security gaps and ensures robust multi-agent deployment against known threats.

Can I detect trust boundary violations in multi-agent setups using architecture review?▼

Yes, you can detect trust boundary violations in multi-agent setups through architecture review. Analyzing system diagrams and code highlights security gaps in agent communication and resource management, preventing exploitation across different trust levels.

Does AI agent security review require specific code snippets or architecture diagrams?▼

AI agent security review requires both architecture diagrams and code snippets to be effective. Providing context on tool permissions and credential handling enables accurate evaluation of security risks and identification of deployment vulnerabilities.

What is the best way to mitigate resource exhaustion risks in autonomous AI systems?▼

The best way to mitigate resource exhaustion risks in autonomous AI systems is through architectural analysis and tailored risk recommendations. This approach addresses agent permissions and resource management to prevent exploitation and ensure robust deployment.