AI security.
Most organizations are adopting AI faster than they are securing it. We help you do both at the same pace: ship the productivity, hold the line on data, identity, and governance.
One signature program, three focused engagements.
Rapid AI Security Adoption Framework.
A structured eight-week program that moves an organization from "we want to use AI but it scares legal" to "we have an approved AI program, technical guardrails, and monitoring." Aligned to the NIST AI Risk Management Framework, MITRE ATLAS, the OWASP Top 10 for LLM applications, and ISO/IEC 42001 where applicable.
Discovery and risk landscape.
Inventory the AI already in use (sanctioned and shadow), surface intended use cases, classify the data those use cases touch, and map regulatory exposure. The output is a one-page risk landscape that drives every subsequent decision.
Governance and policy.
Acceptable use policy, AI inventory and intake process, model risk tiering, human-in-the-loop requirements by tier, and an approval workflow that does not collapse under volume. Designed to be defensible to auditors and usable by builders.
Technical guardrails.
Identity-bound AI access through Entra ID, data loss prevention applied to AI tools and prompts, output redaction patterns, an approved enterprise model catalog, and a sanctioned path for builders so they do not route around the program.
Monitoring and detection.
MITRE ATLAS-aligned detections for prompt injection, model abuse, data exfiltration through AI channels, and unauthorized model access. AI-specific incident response playbooks integrated into your existing SOC tooling. Model drift and prompt-log review cadence established.
Adoption enablement.
Builder training on secure prompting and secure-by-default templates, business-user training on what the policy actually means in practice, and handover documentation. The program continues running after we leave because the people running it know how.
- AI risk landscape, acceptable use policy, and intake workflow
- AI inventory and model risk tiering, ready for board reporting
- Technical guardrails: identity, DLP, model catalog, sanctioned path
- MITRE ATLAS-aligned detections and AI-specific IR playbooks
- Training materials for builders and business users
- Handover so the program runs without us
LLM and generative AI security review.
A focused security assessment of a specific AI feature, application, or vendor integration. Useful before launch, before procurement, or after an incident in a peer organization.
- Architecture review with threat model mapped to OWASP LLM Top 10 and MITRE ATLAS
- Prompt injection, data leakage, and authorization boundary testing
- Supply chain analysis: model provenance, third-party API risk, data residency
- Written findings report with prioritized remediation guidance
AI risk assessment, NIST AI RMF.
A formal AI risk assessment producing artifacts that satisfy the Govern, Map, Measure, and Manage functions of the NIST AI Risk Management Framework. Suited to organizations preparing for ISO/IEC 42001, contractual AI risk obligations, or board-level AI oversight.
- AI use case inventory with tiered risk classification
- Govern, Map, Measure, Manage artifacts per NIST AI RMF 1.0
- Integration with existing enterprise risk management cadence
- Board-readable summary and roadmap
AI governance program operation.
Run the AI governance function on retainer once the program is stood up. Useful for organizations that have completed the Rapid Adoption Framework and need ongoing operation without hiring a full-time AI risk officer.
- AI intake review and approval workflow operation
- Quarterly inventory review and risk re-tiering
- Model and vendor change reviews
- Continuous alignment as NIST, MITRE ATLAS, and federal guidance evolve
Adopting AI faster than you are securing it?
Most organizations are. Reach out for a scoping conversation about the Rapid AI Security Adoption Framework or a more targeted engagement.
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