You bought the cloud security platform. We make it do what the sales deck promised. We stand it up, tune the noise out, close the findings that are actually exploitable, and wire the alerts into the channels engineering already lives in. Day-one red dashboard, day-thirty working program.

• Stand up the platform you boughtCNAPP/CSPM configured, scoped, and tuned — not left in default-policy purgatory
• Close the findings backlogWe work the queue with engineering — fix, suppress with justification, or ship a guardrail so it never comes back
• Wire it into how you shipTriage, ticketing, CI/CD, and on-call paths — security shows up in the tools engineers already use
• Audit evidence captured as a byproduct — not a Q4 scramble
• Stack rationalization — kill the overlapping tools you stopped opening

Compliance is the deal blocker — SOC 2 and ISO 27001 for the SMB enterprise contract, FedRAMP 20x for the public-sector deal. We've built these programs from the inside, including first-generation FedRAMP 20x with machine-readable controls and continuous validation. We know what auditors actually accept, not just what the documentation says.

• SOC 2 & ISO 27001 readinessGap close-out, policies that match how you actually operate, and evidence pulled straight from your CNAPP and cloud accounts
• Auditor & 3PAO liaisonWe sit in the audit calls — translate between auditors, engineering, and agency sponsors so you ship answers, not delays
• FedRAMP 20x compliance readinessMachine-readable controls, automated evidence pipelines, and continuous validation infrastructure
• SSP, POA&M, and artifact library development
• C-SCRM and software supply chain security controls

Embedded practitioner, not advisory — a fractional CISO who stays on the keyboard. For SMBs that need security ownership without a full-time hire, and scaling teams bridging to their first security exec. Available exclusively to clients who have completed an engagement with CyberMuse — so the relationship, environment, and trust are already in place before the retainer begins.

• Monthly strategy sessions with IT/OT and leadership teams
• Quarterly board-ready risk and posture review
• Security program oversight — priorities, KPIs, vendor governance
• Incident response — hands on the keyboard during active events
• Compliance posture tracking and audit readiness
• Policy, procurement, and third-party risk review

Secure what your AI stack actually does in production. We threat-model the agent loop, lock down the MCP surface, and close the prompt-injection, over-permissioned-tool, and data-exfiltration paths before they ship.

• Agentic & MCP security reviewThreat model the agent loop, tool permissions, and MCP server surface — not just the model
• Model supply chain controlsProvenance, integrity, and access across model weights, fine-tuning data, vector stores, and inference endpoints
• Guardrail engineering — input/output filtering, tool allow-lists, evaluator pipelines
• Red-team and adversarial evaluation of the agent, model, and tool surface

Stand up the governance evidence your enterprise customers — and soon your auditors — will ask for. Inventory, risk classification, policy, oversight, and reporting — built to map cleanly onto whichever AI framework your buyers eventually ask for.

• AI & agent inventory + risk classificationDiscover what’s shipping, classify by risk, and assign ownership
• Policy, oversight, and lifecycle controlsRisk-tiered guardrails, human review gates, and lifecycle accountability across AI systems
• Framework-ready evidenceStructured so it maps cleanly onto formal AI assurance frameworks as your customers and auditors start asking for them
• Board- and customer-ready AI risk reporting

• Know what's runningEvery AI system, agent, and vendor tool inventoried and classified by risk before it goes near production.
• Humans stay accountableDecisions that affect customers, money, or safety have a named human owner — not a model and not a committee.
• Tier oversight to riskLow-risk experiments move fast. High-risk systems get review gates, evaluation, and rollback paths proportional to blast radius.
• Evidence as you goDecisions, approvals, and changes are logged when they happen — not reconstructed the week before an audit.
• Frameworks last, not firstWe build on durable controls, then map onto whichever AI assurance framework your buyers ask for.

• Executive sponsorOwns the risk appetite, signs off on high-risk deployments, and answers to the board. Usually a founder, CEO, or COO at SMB scale.
• AI governance leadRuns the program day-to-day — inventory, policy, reviews, reporting. Often a fractional role early on; CyberMuse can hold this seat.
• System ownerNamed human for each AI system or agent. Accountable for its scope, controls, and lifecycle decisions.
• Security & engineeringImplement guardrails, monitoring, and incident response for AI-specific failure modes alongside the rest of the stack.
• Independent reviewerA second set of eyes for high-risk systems — internal, fractional, or external. Never the same person who built it.

• Pre-deployment reviewBefore a new AI system or material change ships — risk classification, controls check, sign-off by the system owner and (for high-risk) the executive sponsor.
• Monthly operational reviewInventory drift, incidents, evaluation results, and open actions. Lightweight. 30 minutes.
• Quarterly governance reviewPolicy updates, risk-tier changes, vendor reassessments, and metrics for the executive sponsor.
• Annual program reviewEnd-to-end review of the program, refresh of principles and roles, and a clean evidence pack for customers and (when needed) auditors.
• Event-driven reviewTriggered by an incident, a new regulation, or a material model or vendor change. Standing process — not a fire drill.