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ai-security-verification

Verify AI/LLM security findings through direct prompt and variation testing.

Updated Apr 21, 2026
Search Tags:#jailbreak#ai-security#prompt-injection#ai-verification#llm-security
One-click install
npx skills add https://github.com/jayjpatel9717/kurukshetra --skill ai-security-verification-jayjpatel9717
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-security-verification
Source: https://github.com/jayjpatel9717/kurukshetra/tree/main/_universal/agents/dharmaraj/skills/ai-security-verification
Command: npx skills add https://github.com/jayjpatel9717/kurukshetra --skill ai-security-verification-jayjpatel9717

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill provides independent verification for AI/LLM security assessment findings, ensuring accuracy and thoroughness in identifying vulnerabilities.

Core Features & Use Cases

  • Prompt Injection Verification: Validates the effectiveness of prompt injection attacks.
  • Jailbreak Verification: Confirms the actual bypass of safety filters.
  • Data Leakage Verification: Checks for actual data leakage from the model.
  • Model Extraction Verification: Validates the ability to extract model weights and architecture.
  • Denial of Service Verification: Assesses the impact of claimed denial of service attacks.
  • System Prompt Extraction Verification: Ensures system prompts are not leaked.
  • Tool Misuse Verification: Checks for the model's misuse of tools.
  • Use Case: Before deploying an AI model in a production environment, use this Skill to verify that all security findings are accurate and actionable.

Quick Start

Verify the security of an AI model by providing the model and the prompt for verification.

Frequently Asked Questions about ai-security-verification

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

FAQPage Schema
How do I verify prompt injection vulnerabilities in an LLM?▼

Verify jailbreak effectiveness by confirming the actual bypass of safety filters through direct prompt testing and behavioral verification. This ensures the model does not merely acknowledge harmful actions without actual execution, providing reproducible security checks.

What is the best way to check for actual data leakage from an AI model?▼

Verify LLM security findings before production deployment by providing the model and the prompt for verification. This independent validation assesses the impact of denial of service, tool misuse, and data leakage claims to ensure all findings are accurate and actionable.

Why does an AI model grade itself as secure during security assessments?▼

Model extraction verification checks for actual data leakage by validating the ability to extract model weights and architecture. It uses variation testing and baseline comparison to ensure the claimed extraction is reproducible and truly impacts the model's security posture.

Can I use automated scripts to test LLM security vulnerabilities?▼

Denial of service verification for LLMs assesses the impact of claimed attacks through behavioral verification and reproducibility checks. It confirms whether the model's availability is genuinely compromised or if the finding is a false positive.

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