KavachRT

Vulnerability Assessment & Penetration Testing

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KavachRT is an open-source AI red-team framework designed to autonomously identify, exploit, and evaluate vulnerabilities within large language models (LLMs) and artificial intelligence systems through adaptive, agent-driven attack strategies. It features automated reconnaissance, multi-category vulnerability assessments, dynamic attack orchestration, reproducible security scoring, and standards-based reporting, targeting AI developers, security researchers, and organizations seeking proactive, thorough AI security testing to prevent exploitation and improve robustness.

KavachRT can be found in Vulnerability Assessment & Penetration Testing categories.

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Details

KavachRT Main Features

• Decision making
  It provides a yes or no security decision before shipping the AI system.
• Agentic approach
  The framework plans attacks, changes strategies, and re-attacks automatically based on results.
• Autonomous attacker
  It automatically finds weaknesses in AI systems and tests for security problems.
• Open-source framework
  KavachRT is a free and open-source AI red-team framework that anyone can use.
• Standards-mapped results
  All findings are linked to well-known security standards like OWASP and MITRE ATLAS.
• Built-in security controls
  Features like authorization, budget limits, redaction, and sandboxing are included for safe testing.
• Reproducible security score
  It gives a clear security score that can be repeated and used to decide if the system is safe.
• Simulates human red-teaming
  It behaves like a human red-team by reasoning, escalating, and analyzing vulnerabilities.
• Supports different AI models
  You can test any LLM or AI system, including hosted APIs and self-hosted models.
• Open core with advanced features
  It offers free basic tools and additional paid features for more power, teamwork, and compliance.

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