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Achievement: Pull Shark

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themayursinha/README.md

Mayur Sinha

Staff Security Engineer | AI Security Architecture & Systems Engineering

I engineer secure, resilient systems from first principles. With 15 years of industry experience in cybersecurity, my focus bridges the gap between low-level machine execution and high-level autonomous AI governance. I build architectures designed to withstand adversarial realities and endure as robust legacy systems.

Current Focus

  • AI Security Architecture: Designing secure inference pipelines, governing autonomous agents, and researching adversarial attacks on Large Language Models (LLMs).
  • Systems & Reverse Engineering: Deep-dive analysis and runtime protection at the machine level utilizing C, C++, Assembly, and CUDA.
  • Agentic SOC Development: Architecting AI-driven security automation platforms that transform raw investigation data into structured, actionable intelligence.

Engineering Philosophy

  • First Principles: Breaking down complex security vulnerabilities and system architectures to their fundamental components.
  • Zero Trust & Security by Design: Prioritizing rigorous runtime protection and identity governance over superficial static analysis.
  • Interdisciplinary Rigor: Applying analytical frameworks from physics and philosophy to solve asymmetrical challenges in cyberspace.

Technical Arsenal

  • Languages: C, C++, Assembly, Python, Go, CUDA
  • Domains: Malware Research, Edge Security, Autonomous Agent Governance, Model Context Protocol (MCP)
  • Paradigms: Zero Trust Architecture, Adversarial Machine Learning, Reverse Engineering

Pinned Loading

  1. security-assessments-scripts security-assessments-scripts Public

    This is a collection of various python scripts to get through security assessments.

    Python

  2. mcp-llm-security-evaluator mcp-llm-security-evaluator Public

    Security focused tooling for testing how an LLM behaves when it is exposed to sensitive text, repository content, and MCP-style tool access. The project can run local smoke tests with a determinist…

    Python

  3. adversarial-ml-lab adversarial-ml-lab Public

    Interactive demonstrations of adversarial ML attacks & defenses. Prompt injection, context tampering, inference evasion

    Python

  4. ctem-leader-lab ctem-leader-lab Public

    An interactive implementation workbench for security leaders moving from vulnerability management to Continuous Threat Exposure Management

    Python

  5. verity-trust-copilot verity-trust-copilot Public

    Self-hosted compliance automation with AI-powered questionnaire answering, public Trust Center, and continuous AWS/GitHub monitoring. BYOK — supports OpenAI, Anthropic, Gemini, Groq, DeepSeek, Mist…

    Python

  6. mcp-visor mcp-visor Public

    Runtime policy enforcement and audit control plane for MCP tool execution. Deterministic, non-AI policy engine that intercepts MCP tools/call requests before execution.

    Go