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RavindraAnnam/README.md

Hi there 👋 I'm Ravindra Annam

AI & Cyber Security Architect | Researcher | Speaker | Author | Judge

I am an AI & Cyber Security Architect with 20+ years of experience designing and securing enterprise platforms across telecommunications, finance, healthcare, retail, and cloud-native environments.

My work focuses on securing Agentic AI systems, Large Language Models (LLMs), Product Security, Application Security, Cloud Security, and Zero Trust architectures. I actively contribute to the cybersecurity community through research, technical speaking, mentoring, judging, and open-source initiatives.


🔬 Current Research

  • ANNAM™ – Zero Trust Runtime Framework for Agentic AI
  • AGENTSCOPE™ – AI Agent Governance & Observability
  • Runtime Security for Autonomous AI Agents
  • Secure MCP (Model Context Protocol)
  • AI Threat Modeling Framework
  • Enterprise AI Security Architecture
  • AI Runtime Policy Enforcement
  • Multi-Agent Security Controls

💼 Areas of Expertise

  • Agentic AI Security
  • LLM Security
  • AI Threat Modeling
  • Product Security
  • Application Security
  • Secure SDLC
  • DevSecOps
  • Cloud Security
  • Zero Trust Architecture
  • AI Governance
  • AI Red Teaming
  • Runtime Security
  • Prompt Injection Defense
  • RAG Security
  • API Security
  • Secure Software Architecture

🛠 Technologies

AI • Python • GitHub Advanced Security • CodeQL • Azure • AWS • Kubernetes • Docker • LangGraph • OpenAI • OWASP • MITRE ATLAS • NIST AI RMF • Splunk • SIEM • Terraform • CI/CD


📚 Publications & Technical Writing

I regularly publish technical content covering:

  • AI Security
  • Agentic AI
  • Application Security
  • Product Security
  • Secure AI Development
  • Zero Trust for AI
  • Cloud Security
  • Runtime Protection

🎤 Community Contributions

  • Conference Speaker
  • Technical Reviewer
  • Security Judge
  • Mentor
  • Technical Author
  • AI Security Researcher

🚀 Featured Projects

Project Description
ANNAM™ Zero Trust Runtime Framework for Agentic AI
AGENTSCOPE™ Runtime Governance for Autonomous AI
AI Threat Modeling Practical threat modeling for AI systems
AI Security Reference Architecture Enterprise architecture patterns
Secure MCP Security controls for Model Context Protocol

🌱 Current Focus

  • Enterprise AI Security
  • Autonomous Agent Security
  • Runtime Governance
  • AI Supply Chain Security
  • AI Observability
  • Secure AI Platforms

📫 Connect With Me


"Building secure AI systems that enterprises can trust."

📈 GitHub Stats

GitHub Stats

Top Languages

Popular repositories Loading

  1. Ravi Ravi Public

    Java 1

  2. aiagent-threatmodeling aiagent-threatmodeling Public

    This open-source tool is designed to test AI agent and LLM threat modeling scenarios, enabling the identification of risks aligned with industry-recognized frameworks such as STRIDE, PASTA, and MITRE.

    Python 1

  3. ai-security-agent-platform ai-security-agent-platform Public

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  4. ai-security-agent-platform-enterpraise ai-security-agent-platform-enterpraise Public

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  5. raai-runtime-security-model raai-runtime-security-model Public

    The RAAI Runtime Security Model™ provides a structured framework for securing Agentic AI systems during runtime operations. Traditional AI security focuses on protecting models.

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  6. agentic-ai-runtime-security-raai agentic-ai-runtime-security-raai Public

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