Trace3, Senior Solutions Architect, Offensive Security and AI Security
- Lead offensive and AI security engagements for more than twenty enterprise clients across healthcare, insurance, pharmaceuticals, manufacturing, and financial services: agentic platform penetration tests, AI threat models, cloud posture assessments, web application and external tests, and threat hunts.
- Run Azure and Entra ID engagements end to end: tenant and identity enumeration, conditional access and token abuse paths, attack-path analysis, posture and benchmark assessment against CIS and CISA baselines, and threat hunts across Azure and Microsoft 365 telemetry. Microsoft Copilot Studio is the pilot platform for the insurer's review capability.
- Advise on Azure cloud security beyond the test: best-practice assessments against Microsoft and CIS baselines, and cloud security framework work that gives a client a standing basis for its own architecture decisions instead of a one-time finding list.
- Designed the practice's agentic threat-modeling method: a falsifiable claims ledger over a data-flow diagram, anchored on CSA MAESTRO with OWASP LLM Top 10, AISVS, and MITRE ATLAS mapped onto it, delivered as a review process clients run themselves after the engagement ends.
- Delivered an agentic AI penetration test of a production enterprise agent: validated exposure at the agent-to-tool, agent-to-agent, and user-content-to-instruction boundaries, with findings the engineering team could reproduce and close.
- Conduct MCP (Model Context Protocol) security assessments: credentialed tool-surface enumeration, prompt-injection and jailbreak execution, confused-deputy and token-passthrough testing, SSRF via tool, tool-schema poisoning, and human-in-the-loop bypass, each finding tied to a documented claim and its evidence.
- Co-authored and operationalized an enterprise AI safety and security standard for a global pharmaceutical company: risk classification, lifecycle controls, threat modeling, secure deployment, incident readiness, and emergency shutdown protocols for high-risk systems. Ran the AI-specific tabletop exercises and red-versus-blue scenarios that put it into practice.
- Built HackbotHarness, an agent-assisted penetration testing platform adopted into the practice's engineering organization: a deterministic scope gate on every tool call, human approval before any exploitation, and a severity-scaled evidence bar before a finding reaches a client report. Roughly 80,000 lines of TypeScript across 379 commits since April 2026, built to cover more attack surface per engagement without loosening the safety gates.
- Authored a vendor-agnostic MCP and agent-identity security reference and a library of seventeen engagement skill packages that turn methodology into repeatable, reviewable tooling across Azure, AWS, internal, external, web application, and agentic assessments, so a second consultant runs the same method at the same depth without retraining.
- Built the Azure infrastructure the offensive practice tests from: idempotent provisioning and cloud-init images for scanning and range roles, a dedicated egress identity, and a subscription guard that refuses to build outside the offensive security subscription, so engagements run from reproducible infrastructure instead of a consultant's laptop.
- Automated the path from scan output to client report: orchestration and parsing for network and vulnerability scanners, a finding importer that pushes reviewed markdown findings into the reporting platform, and evidence capture wired into the same pipeline, removing the hand copying that used to sit between testing and reporting.
- Turn assessment output into risk decisions rather than finding lists: every claim scored and sequenced by likelihood and business impact against the client's own architecture, with remediation owners, control gaps, and a register the client keeps running after the engagement ends.
- Led penetration tests across Azure, AWS, GCP, and OCI, plus external, web application, and OSINT engagements. Architected data security programs on DSPM tooling and cloud-native controls with remediation patterns clients could repeat without us.