What is an AI security assessment?
An AI security assessment is a passive, authorized review of the platforms and AI systems a business runs on, surfacing real exposure and a prioritized remediation plan.
Definition
An AI security assessment is a structured, authorized evaluation of an organization's real attack surface — cloud platforms (AWS, Azure, GCP), SaaS like Salesforce, and any deployed LLM/AI systems — to identify exposure, misconfiguration, and excessive access. Done ethically, it is passive and read-only by default: it assesses, it does not exploit or disrupt.
What it covers
A modern assessment goes beyond the network perimeter. It reviews external exposure (headers, TLS, exposed services), identity and access (over-permissioned roles, guest and profile access), storage exposure and misconfiguration, and — increasingly — AI-specific risks like prompt injection and agent permissions. The point is to cover every layer the business actually runs on.
The process
A typical engagement runs in four steps. First, a free Quick Scan gives a passive external snapshot. Second, scope is agreed and authorized in writing. Third, an AI-augmented assessment covers the agreed surface, with a senior practitioner validating each finding. Fourth, you receive a prioritized findings report and a remediation roadmap.
What you receive
The deliverable is a clear report ranked by real risk — not a raw scanner dump — with each finding explained in context and paired with a concrete remediation step. For compliance-driven organizations, findings can be mapped to SOC 2 or ISO 27001 controls and tracked to closure with fractional CISO support.
Frequently asked
Is an AI security assessment safe to run on production systems?
How is this different from a penetration test?
How do I start?
Want this checked on your own systems? Start with a free, passive Quick Scan.