AI Security Assessment
Find every AI tool. Assess every risk.
We inventory every AI tool in your environment -- chatbots, copilots, agents, embedded SaaS AI -- and assess governance, access, and data handling against current frameworks.
Overview
AI adoption outpaced security programs. Most organizations have more AI running than they realize -- embedded features in approved SaaS tools, personal accounts connected to corporate email, coding assistants with access to production repos, agents with API keys nobody tracks. We inventory everything, assess governance and access controls, evaluate data handling practices, and map the results against the NIST AI Risk Management Framework and its Generative AI Profile (NIST AI 600-1), plus the OWASP Top 10 for LLM Applications (2025) and Agentic Applications (2026). This is a gap assessment adapted to the specific risks AI creates in your environment.
What We Test
We evaluate six areas where AI creates risk that traditional security programs miss.
AI Tool Inventory
Network traffic analysis, SaaS logs, OAuth grant audits, and team interviews to find every AI tool -- sanctioned and shadow -- running in your environment.
Data Handling & Privacy
How data flows to and from AI systems. What gets sent to external models, what's stored, what's logged, and whether your data handling meets regulatory requirements.
Access & Permissions
What each AI tool can access and whether those permissions follow least privilege. Service accounts, API keys, OAuth scopes, and agent credentials reviewed.
Governance & Policy
Whether your organization has AI-specific policies covering acceptable use, procurement, data classification, and incident response for AI-related events, aligned to the NIST AI RMF, ISO/IEC 42001, and EU AI Act obligations where they apply.
Agent Controls
For AI agents with system access: scope limits, human oversight gates, action logging, and rollback capabilities. What the agent can do versus what it should be allowed to do.
Monitoring & Detection
Whether your security monitoring covers AI activity -- model queries, agent actions, data transfers to AI services, and anomalous usage patterns.
Our Approach
Our AI security assessment follows the same structured approach as our other gap assessments, adapted to discover and evaluate AI-specific risk.
AI Discovery
We find what's running. Network analysis, SaaS inventories, OAuth grants, browser extensions, and structured interviews across departments.
Risk Mapping
Each discovered AI tool is evaluated against the NIST AI RMF functions (Govern, Map, Measure, Manage) and OWASP AI security categories based on its access level and function.
Control Assessment
We evaluate existing controls -- access management, data classification, monitoring, incident response -- for coverage of AI-specific risks.
Roadmap Development
Prioritized recommendations organized by effort and impact: policy gaps, technical controls, governance fixes, and quick wins.
Common Findings
These are issues we frequently discover during ai security assessment engagements:
Undetected Shadow AI
HighAI tools running in the environment that security and IT teams don't know about -- personal accounts, browser extensions, embedded SaaS features.
Excessive AI Permissions
HighAI tools and agents with broader access than their function requires. OAuth scopes granting full mailbox access for a summarization tool.
No AI-Specific Policies
MediumAcceptable use policies that don't address AI, leaving employees without guidance on what's allowed and what isn't.
Missing AI Monitoring
MediumSecurity monitoring that doesn't cover AI activity -- no visibility into model queries, agent actions, or data transfers to AI services.
Agent Scope Creep
HighAI agents deployed with initial constraints that expanded over time without security review. Agents making API calls or accessing systems beyond their original mandate.
Ungoverned Data Flows
CriticalSensitive data -- customer PII, financial records, source code -- flowing to AI services with no classification controls, retention policies, or audit trail.
Common Questions
How is this different from a regular gap assessment?
Do we need this if we already have an AI usage policy?
What if we don't think we have much AI in our environment?
Other AI Security Options
AI & LLM Penetration Testing
We test your deployed AI systems adversarially (prompt injection, jailbreaking, agent manipulation, data extraction) using the same attacker mindset we bring to every engagement.
AI Agent Security Testing
AI agents don't just answer, they act. We test the tools, permissions, and autonomy behind your agents: MCP servers, over-permissioned coding agents, and the injection paths that turn an agent against your own systems.
AI Application Security Review
We review how your applications integrate AI -- data flows to models, output handling, agent connections, RAG pipelines -- finding the vulnerabilities that live at integration points.
Ready to Strengthen Your Defenses?
Schedule a free consultation with our security experts to discuss your organization's needs.
Or call us directly at (445) 273-2873