AI Security Assessment

Know Your AI Security Risk Before Attackers Do.

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

AI Has Created a New Attack Surface

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.

We Help Answer:

  • What can an attacker access?
  • What can our AI agents do?
  • What systems can our AI interact with?
  • Can sensitive information be exposed?
  • Are AI agents operating with excessive permissions?
  • Where are our highest-priority AI security gaps?

What We Evaluate

What We Evaluate

Our assessment examines the security of your AI environment across applications, agents, infrastructure, identity, data, and supply-chain components.

01. AI Governance

Policies, responsibilities, risk management, security requirements, and AI controls.

02. AI Architecture

Applications, models, agents, APIs, data flows, cloud services, integrations, and trust boundaries.

03. Identity & Access

Authentication, authorization, service accounts, agent identities, secrets, and least privilege.

04. AI Application Security

Prompt handling, RAG, APIs, input and output security, data access, and application workflows.

05. AI-Specific Threats

Prompt injection, data exposure, unsafe outputs, model abuse, and other AI-specific attack scenarios.

06. AI Agent Security

Agent identity, permissions, tools, memory, workflows, autonomous actions, and human approval.

07. MCP Security

MCP servers, tools, authentication, authorization, data access, secrets, and trust boundaries.

08. AI Supply Chain

Models, packages, dependencies, datasets, containers, repositories, and third-party AI services.

09. Monitoring & Response

Logging, monitoring, detection, alerting, and incident response.

AI Threat Modeling

AI Threat Modeling

Every assessment includes AI-specific threat modeling appropriate to the scope of the engagement.

We identify:

Assets

What needs to be protected?

Trust Boundaries

Where does trust change between users, applications, AI systems, agents, tools, and infrastructure?

Threats

What could an attacker manipulate, access, modify, or abuse?

Attack Paths

How could an attacker move from an initial compromise to meaningful impact?

Abuse Cases

How could legitimate AI functionality be misused?

What You Receive

What You Receive

Executive Risk Assessment

A concise view of your most important AI security risks and business impact.

AI Architecture Review

Documentation and analysis of the AI environment, applications, integrations, data flows, and trust boundaries.

AI Threat Model

Documented threats, abuse cases, trust boundaries, and attack paths.

Security Findings & Risk Ratings

Individual findings prioritized according to severity, exploitability, exposure, and business impact.

AI Security Risk Assessment

A high-level view of your organization's overall AI security posture.

Remediation Recommendations

Specific recommendations for security, engineering, cloud, and AI teams.

30/60/90-Day Roadmap

A prioritized remediation plan designed to help your organization address the most important risks first.

Executive Presentation

A walkthrough of key findings, business impact, priorities, and recommended next steps.

How the Assessment Works

How the Assessment Works

01 — Discover

Understand your AI use cases, architecture, technology stack, data, and business objectives.

02 — Map

Map applications, models, agents, APIs, identities, tools, data flows, and trust boundaries.

03 — Threat Model

Identify realistic threats, abuse cases, and potential attack paths.

04 — Assess

Evaluate security controls and identify vulnerabilities and gaps.

05 — Prioritize

Rank findings based on severity, exploitability, exposure, and business impact.

06 — Report

Deliver technical findings, evidence, risk ratings, and executive-level insights.

07 — Remediate

Provide a practical 30/60/90-day roadmap for addressing the highest-priority risks.

Who Should Get an AI Security Assessment?

Who Should Get an AI Security Assessment?

An assessment is particularly valuable if your organization:

  • Is deploying AI into production
  • Builds AI-powered applications
  • Deploys autonomous AI agents
  • Uses RAG or vector databases
  • Implements MCP
  • Gives AI access to internal systems or sensitive data
  • Uses third-party AI services or open-source AI components
  • Is expanding an existing AppSec program into AI
  • Needs an independent security review

Why Arapearly

What Makes Arapearly Different?

AI-Native

We assess security risks specific to AI applications, agents, MCP, RAG, and AI-enabled workflows.

AppSec-Driven

We apply established application security, API, identity, cloud, and supply-chain principles to AI systems.

Risk-Based

We prioritize findings according to technical severity, exposure, exploitability, and business impact.

Actionable

Every assessment produces practical remediation recommendations and a prioritized roadmap.

When Should You Assess?

When Should You Perform an AI Security Assessment?

Before Production

Identify security gaps before an AI application reaches users.

Before Granting Agent Access

Evaluate permissions before autonomous systems can interact with critical systems.

Before Connecting MCP Tools

Understand the security implications of giving AI access to enterprise tools and data.

After Major Changes

Reassess when models, agents, infrastructure, integrations, or AI capabilities change.