Codex CLI • Secure Remediation • Threat Modeling • Patch Validation • Audit-Ready Evidence
I build public, sanitized cybersecurity labs that demonstrate how AI-assisted security workflows can remain scoped, reviewed, validated, and safe for publication.
- Defensive AI Workflows
- Secure Remediation
- Threat Modeling
- Dependency Risk Review
- Patch Validation
- Human-in-the-Loop Validation
- Audit-Ready Documentation
- Sanitized Public Security Labs
AI generates.
Humans review.
Evidence validates.
Security decisions remain accountable.
Demonstrates:
- defensive code review
- remediation workflow
- patch validation
- public evidence generation
Demonstrates:
- threat modeling
- dependency analysis
- remediation planning
- validation workflow
Demonstrates:
- safe AI operation
- controlled execution
- evidence generation
- human approval checkpoints
- Local-first validation
- No unsupported security claims
- No offensive activity
- Human approval required
- Reproducible evidence
- Auditability over hype
Building defensive AI workflows that help security teams move from:
Discovery → Review → Remediation → Validation → Evidence
without sacrificing traceability, accountability, or human oversight.
