Multi-tenant enterprise security operations background across 60+ clients. Currently building at the intersection of detection engineering, AI security, and autonomous agent infrastructure.
AgentLedger — Trust & Discovery Infrastructure for the Autonomous Agent Web
104,000+ AI agents registered across 15+ incompatible registries. No shared trust layer exists. AgentLedger fills that gap: a universal capability ontology, blockchain-anchored Trust Ledger, and tamper-proof Audit Chain for autonomous agent commerce.
Targeting: Cybersecurity Analyst · Detection Engineer · Threat Hunter · SOC Engineer (L2/L3)
My core foundation. Multi-tenant SOC operations across 60+ enterprise clients — building detection logic, running hunts, and automating investigation pipelines at scale.
| Project | What It Proves |
|---|---|
| MultiAgent_SOC | Multi-agent architecture applied to SOC workflows — automated triage, investigation routing, and response orchestration |
| High-Recall_Malware_Detector | Supervised + unsupervised ML for malware classification — precision/recall tradeoffs in detection engineering |
| ThreatPrism | API-driven SOC investigation and threat hunt automation pipeline — built for analyst velocity |
Skills in this space: SIEM rule development · Behavioral analytics · Alert fidelity optimization · Hypothesis-driven threat hunting · IOC development · Adversary emulation · Sigma · YARA · KQL · Splunk SPL
Targeting: AI Security Engineer · AI Red Team · Adversarial ML · DevSecOps Engineer
Where my detection background meets the AI threat surface. I build tools that attack, evaluate, and harden AI systems — mapped to real frameworks, not theoretical exercises.
| Project | What It Proves |
|---|---|
| LLM-Red-Teaming-Audit-Demo | Structured LLM red team evaluation with audit trail — adversarial prompt testing mapped to OWASP LLM Top 10 |
| Trust-Bench-SecureEval-Ops | Benchmarking framework for AI trust and security evaluation — behavioral consistency testing at scale |
| ai-guardrails | Production guardrail implementations for LLM-based systems — input/output validation and policy enforcement |
| SecureCLI-Tuner | QLoRA fine-tuning pipeline for hardened NL → CLI translation — reduces command injection surface in agentic workflows |
| AI DevSecOps Platform | End-to-end adversarial testing framework for AI systems — OWASP LLM Top 10 and MITRE ATLAS alignment |
Skills in this space: LLM threat modeling · Prompt injection defense · Agentic attack surface analysis · Adversarial ML · OWASP LLM Top 10 · MITRE ATLAS · NIST AI RMF · Fine-tuning pipelines · AI governance
Targeting: Customer Success Engineer · Solutions Engineer · Security Architect · Technical Advisor
I translate complex security and AI infrastructure into actionable guidance — for clients, collaborators, and technical audiences. Demonstrated through 60+ enterprise client engagements and public technical writing.
| Project | What It Proves |
|---|---|
| AgentLedger | Whitepaper authorship, full technical docs site, architecture spec — communicating complex infrastructure clearly to multiple audiences |
| SageVault | Secure data architecture and vault implementation — translating security requirements into working systems |
| Trust-Bench-SecureEval-Ops | Evaluation framework designed to surface security posture clearly — built for decision-making, not just testing |
Skills in this space: Client-facing security advisory · Technical documentation · Architecture specification · Stakeholder communication · Security posture translation · Whitepaper authorship · Enterprise onboarding
| Domain | Frameworks & Standards |
|---|---|
| Threat Modeling | MITRE ATT&CK · MITRE ATLAS · STRIDE |
| AI Security | OWASP LLM Top 10 · CoSAI MCP Security Taxonomy · NIST AI RMF |
| Agent Protocols | MCP · A2A · agents.txt · AgentLedger Manifest Spec |
| Compliance | EU AI Act · SOC 2 · GDPR · CCPA |
| Detection | Sigma · YARA · KQL · Splunk SPL |
