01. AI Governance
Policies, responsibilities, risk management, security requirements, and AI controls.
AI Security Assessment
An independent security assessment designed to identify vulnerabilities, attack paths, excessive permissions, data exposure, and security gaps across your AI environment.
Arapearly AI Security evaluates the applications, models, agents, APIs, data, infrastructure, integrations, and supply-chain components that support your AI systems.
Why This Matters
Traditional application security controls are important, but AI introduces additional attack surfaces.
An AI system can interpret untrusted instructions, retrieve sensitive information, invoke tools, interact with APIs, make decisions, and perform actions.
An AI Security Assessment helps you understand what could go wrong before an attacker discovers it.
What We Evaluate
Our assessment examines the security of your AI environment across applications, agents, infrastructure, identity, data, and supply-chain components.
Policies, responsibilities, risk management, security requirements, and AI controls.
Applications, models, agents, APIs, data flows, cloud services, integrations, and trust boundaries.
Authentication, authorization, service accounts, agent identities, secrets, and least privilege.
Prompt handling, RAG, APIs, input and output security, data access, and application workflows.
Prompt injection, data exposure, unsafe outputs, model abuse, and other AI-specific attack scenarios.
Agent identity, permissions, tools, memory, workflows, autonomous actions, and human approval.
MCP servers, tools, authentication, authorization, data access, secrets, and trust boundaries.
Models, packages, dependencies, datasets, containers, repositories, and third-party AI services.
Logging, monitoring, detection, alerting, and incident response.
AI Threat Modeling
Every assessment includes AI-specific threat modeling appropriate to the scope of the engagement.
We identify:
What needs to be protected?
Where does trust change between users, applications, AI systems, agents, tools, and infrastructure?
What could an attacker manipulate, access, modify, or abuse?
How could an attacker move from an initial compromise to meaningful impact?
How could legitimate AI functionality be misused?
What You Receive
A concise view of your most important AI security risks and business impact.
Documentation and analysis of the AI environment, applications, integrations, data flows, and trust boundaries.
Documented threats, abuse cases, trust boundaries, and attack paths.
Individual findings prioritized according to severity, exploitability, exposure, and business impact.
A high-level view of your organization's overall AI security posture.
Specific recommendations for security, engineering, cloud, and AI teams.
A prioritized remediation plan designed to help your organization address the most important risks first.
A walkthrough of key findings, business impact, priorities, and recommended next steps.
How the Assessment Works
Understand your AI use cases, architecture, technology stack, data, and business objectives.
Map applications, models, agents, APIs, identities, tools, data flows, and trust boundaries.
Identify realistic threats, abuse cases, and potential attack paths.
Evaluate security controls and identify vulnerabilities and gaps.
Rank findings based on severity, exploitability, exposure, and business impact.
Deliver technical findings, evidence, risk ratings, and executive-level insights.
Provide a practical 30/60/90-day roadmap for addressing the highest-priority risks.
Who Should Get an AI Security Assessment?
An assessment is particularly valuable if your organization:
Why Arapearly
We assess security risks specific to AI applications, agents, MCP, RAG, and AI-enabled workflows.
We apply established application security, API, identity, cloud, and supply-chain principles to AI systems.
We prioritize findings according to technical severity, exposure, exploitability, and business impact.
Every assessment produces practical remediation recommendations and a prioritized roadmap.
When Should You Assess?
Identify security gaps before an AI application reaches users.
Evaluate permissions before autonomous systems can interact with critical systems.
Understand the security implications of giving AI access to enterprise tools and data.
Reassess when models, agents, infrastructure, integrations, or AI capabilities change.
Next Step
Don't wait for an AI security incident to discover the gaps.
Understand your exposure. Prioritize your risks. Build a stronger AI security program.
Request an AI Security Assessment Schedule a Confidential Consultation