Cyber Risk Advisory, DFIR Evidence & CMMC/GRC
I translate security evidence, control gaps, DFIR readiness, and compliance requirements into decision-ready narratives for leaders who need more than a dashboard.
Security Decisions Need Evidence
Cyber risk work gets stronger when it is connected to what the environment can actually prove. A control assertion is only useful if the organization can show which telemetry supports it, which incidents would test it, and which business decision it informs.
My advisory work sits between technical investigation and executive translation. That includes DFIR-ready evidence strategy, CMMC/GRC control narratives, detection validation, risk prioritization, and plain-language artifacts that help leadership understand what is known, what is missing, and what should happen next.
What I Help Translate
- DFIR evidence readiness. Which logs, approvals, identities, tool actions, cloud events, and data-access records would matter when an incident has to be reconstructed quickly.
- CMMC/GRC control stories. How control expectations connect to real evidence, operational ownership, validation cadence, and executive risk language.
- Detection and response gaps. Where current alerts, telemetry, and procedures leave unanswered questions during an incident or audit.
- Board-ready cyber risk framing. Clear narratives that show what a security issue means, why it matters, and what decision is being requested.
Proof Of Work
Detection Engineering Starter
Operating-model patterns for detection work that needs to survive audits, incidents, and executive tradeoff conversations.
Open artifact ->AI Agent Telemetry Contract
Control and telemetry requirements that translate AI-agent behavior into evidence security teams can review, validate, and govern.
Open artifact ->DFIR Evidence Model
A plain-language research note on reconstructing AI-related incidents when traditional logs only tell part of the story.
Open artifact ->Security R&D Toolkit
A deployed portfolio of threat modeling, ATT&CK, cloud, red-team, investigation, and AI security workflows.
Open artifact ->Useful For
This lane is useful for organizations trying to make cyber risk decisions without losing the technical evidence underneath them. It is especially relevant for teams preparing for CMMC/GRC conversations, improving DFIR readiness, validating detection coverage, or translating AI and cloud security risks for executives, boards, and cross-functional stakeholders.
Start Here
Start with the detection engineering starter and the DFIR evidence model. For the AI security side of this work, move into the AI Security & Detection Validation page.