Agentic AI security | LLM/RAG security | MCP and tool security | IAM and least privilege | Model supply-chain security
AI becomes a different security problem when it can act. My work focuses on securing the boundaries between AI agents, tools, identities, data, and model artifacts. I build and evaluate open-source security tooling across agentic AI security, MCP and tool access, IAM, model supply-chain security, adversarial ML, and model privacy.
Recent work includes an inline MCP security gateway, an AWS IAM policy analyzer for agent roles, and a pre-load security scanner for Hugging Face model artifacts. Broader research includes adversarial robustness, membership inference, model extraction, differential privacy, prompt-injection testing, and RAG security evaluation.
I care about security engineering that is testable, reproducible, and honest about its limitations.
- Agentic AI security: MCP/tool-call inspection, policy enforcement, audit trails, tool access boundaries, and data-exposure controls.
- IAM and least privilege for AI agents: trust relationships, delegated access, risky permissions, and cloud identity review.
- Model supply-chain security: Hugging Face artifact scanning, unsafe deserialization signals, metadata/provenance review, and pre-load risk checks.
- LLM/RAG security: prompt-injection testing, leakage checks, RAG/tool misuse scenarios, and detector evaluation.
- ML security research: adversarial robustness, dataset poisoning, membership inference, model extraction, differential privacy, and model privacy evaluation.
- Engineering stack: Python, FastAPI, PyTorch, scikit-learn, Docker, GitHub Actions, AWS IAM, SARIF, JSON evidence, and technical documentation.
| Project | Security boundary | What it demonstrates |
|---|---|---|
| mcp-agent-security-gateway | Agent to tool | Inline MCP/tool-call inspection for prompt injection, PII leakage, shadow servers, exfiltration patterns, policy decisions, and audit logging. |
| aws-agent-identity-guard | Agent to cloud identity | Static IAM analysis for agent roles, risky permissions, trust relationships, and least-privilege violations. |
| hf-model-provenance-scanner | ML system to model artifact | Pre-load Hugging Face scanner for provenance, impersonation, pickle risk, suspicious metadata, and model supply-chain signals. |
| llm-redteam-framework | LLM to untrusted input | Adversarial prompt generation and offline detector evaluation for LLM red-team experiments. |
| model-privacy-attacks | Model output to privacy risk | Membership-inference and model-privacy attack evaluation for ML classifiers. |
| adversarial-ml-lab | Model robustness | FGSM, PGD, and C&W adversarial robustness benchmark harness for CIFAR-10 research experiments. |
| dataset-poisoning-detector | Training data to model behavior | Dataset poisoning and anomalous-sample detection with reproducible ML security checks. |
| unified-ml-security-platform | Security services to platform | Integration workspace for ML security services with CI, compose validation, scans, and health checks. |
| ml-security-command-center | Portfolio evidence | Static inventory of sibling repository revisions, source observations, and evidence availability. |
| mlsec-dashboards | Evidence to dashboard | Dashboard hub with authenticated API endpoints that aggregate JSON evidence from sibling ML security repositories. |
| mlsec-benchmark-suite | Tools to fixtures | Smoke-test and evidence infrastructure using small, versioned fixtures and structured JSON results. |
| attack-v19-core | ATT&CK data to application logic | Importable Python package for MITRE ATT&CK v19 Enterprise, Mobile, and ICS data models with migration-aware lookups. |
| PulseNet-RUL-Forecasting | Telemetry to ML pipeline | NASA C-MAPSS remaining-useful-life forecasting work with adversarial sensor-input checks and secure MLOps controls. |
- Independent AI Security Researcher & Engineer, Self-Directed Research, Tempe, AZ, Aug 2024 - Present.
- Business Compliance Lead & Market/Cost Analyst, AEROSEC, Arizona State University Technology Innovation Lab, Aug 2025 - Dec 2025.
- Graduate Teaching Assistant / IT Grader, Ira A. Fulton Schools of Engineering at Arizona State University, Jan 2025 - Oct 2025.
- M.S. Information Technology, Arizona State University, Aug 2024 - May 2026.
- B.Tech Computer Science and Engineering, M. S. Ramaiah University of Applied Sciences, Aug 2019 - Aug 2023.
A Personalized E-Learning System Using Reinforcement Learning Through Satellite
IEEE INDICON 2023 / IEEE Xplore document 10440852
https://ieeexplore.ieee.org/document/10440852
- AWS Academy Graduate - Cloud Security Foundations training badge.
- Technology Innovation Lab - Honeywell Aerospace & ASU.
- KSCST 46th Series Student Project Programme Research Grant.
I am currently open to full-time opportunities in AI Security, AI/ML Security, Product Security for AI, Security Research Engineering, and AI Systems Security, particularly roles involving agentic AI, LLM applications, MCP/tool security, identity and access control, model supply-chain security, adversarial testing, and secure AI infrastructure.
Location: Greater Phoenix Area, Arizona, USA
Availability: Available now; open to relocation
Work authorization: F-1 OPT; H-1B sponsorship required for longer-term employment
Contact: [email protected]
Security claims here are limited to public repositories, committed artifacts, documented limitations, and reproducible checks. Research prototypes are not described as production deployments.