Security Executive · Dallas–Fort Worth

I build security functions where none exist.

Former CISO. Fifteen years across federal healthcare, defense, financial services and telecommunications — and a working practice of governing AI as enforced controls rather than policy.

Ketrica R. Green
223,596Vulnerability findings inherited with no remediation process — dispositioned to zero
$2.08BFederal services contract portfolio secured as CISO, leading a team of seven
150+VA healthcare systems accredited under NIST RMF, with ATOs achieved
01

Case studies

Three engagements, written out properly. Clients are anonymized; the numbers are not.

Enterprise vulnerability management · 2026

A 223,596-finding backlog and no process at all

An enterprise cloud estate was generating findings that landed nowhere. No intake, no triage, no risk tiering, no verification, no defined ownership. Cluster resources carried no ownership tags, so a large share of container findings were structurally orphaned — nobody could be assigned them even in principle. There was no governed path to accept risk on findings with no available fix, so those aged in place and inflated the count indefinitely.

The practical consequence for leadership was that posture was unreportable. You could produce a count. You could not answer whether risk was going down, who owned what, or what needed deciding.

I built the process from zero and versioned the baseline, made exploitation rather than CVSS the governing prioritization rule, designed a remediation RACI and secured formal adoption across three teams, and implemented the ownership tagging that made orphaned findings routable at all. The load-bearing move was relocating accountability for unremediated risk from the security team onto the asset owner — which converted remediation from a security request into a business obligation.

100%Baseline dispositioned
129,825Findings remediated
55,532Governed risk acceptances
AI governance in a regulated environment

Letting clinicians use language models without creating a breach

Enterprises were adopting AI faster than they could govern it, and healthcare posed a specific question: how do you let clinicians use large language models against protected health information without creating a HIPAA breach or pulling cardholder data into scope?

Self-hosted models keep data inside the environment but introduce new leak paths — poisoned model weights, prompt and response logs full of PHI, vector stores that bypass record-level access control, and agentic systems that can be steered into unauthorized actions.

Rather than a policy of general principles, I built a hard control: no local model processes PHI until an approval gate is passed and signed. Five mandatory controls, any one of which fails the gate — endpoint authentication, attributable audit, no PHI in logs, retrieval authorization, and model weight provenance. Agentic deployments carry further controls before go-live. Every approved deployment is registered, re-attested annually, and reflected in the HIPAA Security Risk Analysis. Cardholder data never enters the model path at all, enforced through tokenization and a broker pattern.

100%Of models under governance
25%Improvement in threat detection
StablePCI scope, while AI capability expanded
Incident command · PCI environment

The ransomware that arrived through a trusted vendor identity

A user clicked a document link shared from an internal collaboration site. Ransomware followed. The vector is the part worth dwelling on, because it defeats two layers of defense simultaneously: it defeats the user, since every awareness program trains people to scrutinize external mail and this was an internal platform on a domain they used daily; and it defeats the email security stack, because URL reputation and sandbox detonation are calibrated against inbound external mail, not a link to a trusted internal tenant.

Which reframes the investigation. The click was not the incident — it was stage two. The real question was how a malicious document reached an internal library and whose access put it there. The answer was an external vendor identity holding upload and sharing rights far exceeding what the collaboration required, provisioned for a legitimate reason and then never reviewed, scoped down, or expired.

In a cardholder data environment the first question governs everything downstream, so segmentation validation came before anything else. Containment was surgical rather than broad — taking the collaboration platform offline halts the business and creates pressure to rush every subsequent decision. The lessons-learned review targeted the class of problem rather than the symptom: external identity governance, default expiry on guest access, and least-privilege scoping of upload rights.

UnaffectedCardholder data environment
600+Privileged accounts isolated
15Endpoints infected, contained
02

Writing

Where I work through the problems that don't have settled answers yet.

Essay

An approval gate is a control. An AI policy is not.

Most AI governance programs fail at the same place: the moment someone has to be told no. What an enforceable gate looks like when the data in question is protected health information.

Analysis

The phishing vector your awareness training cannot fix

An internal link, on a trusted domain, through the normal channel. Why blaming the user guarantees recurrence — and why the only control that addresses this is third-party access governance.

Field note

What to do when you inherit 223,596 findings

Volume is the symptom, not the problem. On versioned baselines, exploitation-based prioritization, and why the first real fix is asset ownership tagging.

03

Systems I've built

I don't only govern AI — I build it. These are systems I designed and wrote to solve problems I hit in practice, developed and validated under formal software quality discipline.

Python

Sentinel — remediation tooling where none existed

Engineers were receiving raw scan exports and expected to work out prioritization, remediation approach and compensating controls independently, per finding. At enterprise volume that is not a workload problem, it is an arithmetic impossibility. Sentinel generates structured remediation playbooks from finding data, applies exploitation-based prioritization automatically, and surfaces candidate compensating controls for findings with no available fix. The design intent was to encode judgment into the tool so a less experienced engineer starts from correct prioritization rather than a blank page.

Product

CyberPulse — CMMC Level 2 compliance console

Controls management, POA&M, evidence, SSP, risk assessment, CMMC readiness and SPRS scoring, with role-based access. Taken through a formal 94-case user acceptance test across 14 modules against defined exit criteria: 100% executed, zero open Critical or High defects, and every scoring-accuracy and access-control case passing before launch.

Product

Sentinel Care — healthcare governance and compliance automation

Continuous control monitoring and evidence collection across SOC 2, ISO 27001, HIPAA and PCI DSS, built for healthcare organizations carrying several frameworks at once and duplicating effort across each.

Architecture

Multi-agent security systems

Three systems with non-overlapping authority boundaries, defined handoff contracts and explicit framework citations per agent: a 17-agent vulnerability management system, a 14-agent threat research system anchored to MITRE ATT&CK and ATLAS, OWASP and NIST SP 800-115, and a 13-agent AI governance system covering ethics, policy, model validation, red-teaming, data lineage and privacy — validated end to end against a 41-test acceptance suite at a 100% pass rate.

04

Advisory

Keatrin Technology Solutions — a small number of engagements a year, in the areas where I have done the work rather than only studied it.

Most security advisory is sold on frameworks. Mine is sold on having stood in the environment — having run the remediation program, commanded the incident, held the CISO seat, and signed the risk acceptance. I take on engagements where that difference is the point.

Vulnerability program build

Intake through verification, with the RACI, risk tiering and governed exception path that make posture reportable. Built from zero against a 223,596-finding baseline.

AI governance stand-up

Enforceable control gates rather than principles documents, folded into existing HIPAA, HITRUST, SOX and CMMC obligations instead of running as a parallel program.

CMMC & NIST 800-171 readiness

Gap assessment, SSP and POA&M, SPRS scoring and evidence discipline. Certified CMMC Professional and CMMC-AB Registered Practitioner.

Third-party & vendor risk

Due diligence frameworks, risk scoring and assessment automation. Built a program evaluating 500+ financial services suppliers annually.

PCI-DSS scope & assessment readiness

Scope reduction, segmentation validation and evidence preparation, from a Qualified Security Assessor.

Transaction security

Cyber due diligence, integration and separation planning. Seven transactions across four enterprises, including IAM workstream ownership on a $4.4B acquisition.

How I work. Engagements are scoped to a deliverable, not to a retainer of indefinite length. I would rather build something your team can run after I leave than become a dependency — the tooling and the RACI outlast the engagement, or the engagement did not work.

05

Get in touch

Open to Deputy CISO, Head of Security and CISO roles in regulated, federal and defense-adjacent environments — and to a small number of advisory engagements.

Let's talk

Whether it's a security function that needs building, an AI program that needs governing, or a leadership seat that needs filling — I'd rather have the specific conversation than the general one.

C|CISO · CISM · CISA · CDPSE · PMP · PCI-QSA · ISO/IEC 27001:2022 Lead Implementer · CMMC-CCP · CMMC-AB Registered Practitioner · AWS Certified Security – Specialty · Microsoft Azure AI Engineer · CompTIA Security+ · U.S. Army Veteran