Agentic AI Security Assessment: Validate and Secure Your AI Agents
As organizations deploy autonomous AI agents, security must also be ensured. Our Agentic AI Security Assessment provides a deep technical evaluation of your real-world AI environment, including AI agents, identity flows, and security controls to ensure your environment is secure, governed, and scalable.
Designed for:
- Security and IAM Teams
- Cloud and Platform Engineers
- AI and Application Owners
Ideal for organizations that are:
- Deploying or scaling AI agents and autonomous systems
- Integrating AI into business-critical workflows
- Needing validation of identity, access, and security controls
- Looking to align AI deployments with Zero Trust principles
What You Get from the Assessment
Technical Validation of AI Security Controls
Assess whether your identity and access controls effectively govern AI agents and their actions.
Deep Visibility into Identity Flows
Understand how AI agents authenticate, request access, and interact across systems.
Risk Identification Across Agent Behavior
Identify risks related to delegation, autonomy, and access patterns.
Security Gap Analysis
Detect weaknesses across architecture, identity, and implementation.
Actionable Remediation Plan
Receive prioritized recommendations to strengthen your AI security posture.
What We Assess
- Agent Identity Lifecycle
How agent identities are created, managed, rotated, and decommissioned - Delegation & Consent
OAuth, token exchange, and agent-to-agent authorization flows - Least Privilege & Dynamic Authorization
Policy-based access and runtime enforcement
- Observability & Audit
Logging, tracing, and visibility into agent decisions - Threat Model
Prompt injection, misuse, privilege escalation, data exposure - Multi-Cloud & Tool Access
Security across Azure, AWS, GCP, and AI tool ecosystems
Assessment Approach
1
Threat Model Workshop
Define agent types, data flows, and trust boundaries
2
Identity & Cloud Analysis
Evaluate identity providers, platforms, and standards
3
Zero Trust Architecture Design
Define enforcement points, delegation models, and controls
4
IAM Integration Roadmap
Embed AI security into your existing identity architecture
Looking to Get Transparency First?
If you are in an earlier stage of your AI journey and need to understand risks and define a strategy, explore our AI Security Workshops.
Why iC Consult for Agentic AI Security Assessment
Validating AI agent security requires hands-on technical depth across identity, cloud, and AI architecture. iC Consult brings 25 years of identity engineering, real-world experience with agentic deployments, and a vendor-independent stance — so our findings are concrete, actionable, and free of product-vendor bias.
Identity engineering, not just consulting
our experts work in the same architectures they assess.
Multi-cloud reach
we operate across Azure, AWS, GCP, and the major AI tool ecosystems.
Vendor-independent
our recommendations integrate the right combination of tools, not a single vendor’s portfolio.
Operational maturity
from rapid validation to long-term architectural transformation, the assessment scales to the engagement we are asked to deliver.
FAQ
What is an Agentic AI Security Assessment?
An Agentic AI Security Assessment is a hands-on technical evaluation of an organization’s AI agents, identity flows, and access controls. It validates that controls effectively govern AI agents and their actions, identifies risks across delegation and access patterns, and delivers prioritized, concrete remediation guidance to strengthen the AI security posture.
Who should run an Agentic AI Security Assessment?
The assessment is designed for organizations already deploying or scaling AI agents, integrating AI into business-critical workflows, or seeking validation of identity, access, and security controls for AI. The natural participants are security and IAM teams, cloud and platform engineers, and AI and application owners.
What does the assessment cover?
Six core domains: agent identity lifecycle (creation, management, rotation, decommissioning); delegation and consent (OAuth, token exchange, agent-to-agent authorization); least privilege and dynamic authorization (policy-based access, runtime enforcement); observability and audit (logging, tracing, visibility); threat model (prompt injection, misuse, privilege escalation, data exposure); and multi-cloud and tool access (security across Azure, AWS, GCP, and AI tool ecosystems).
How is the assessment delivered?
In four structured phases: (1) a Threat Model Workshop to define agent types, data flows, and trust boundaries; (2) an Identity and Cloud Analysis evaluating identity providers, platforms, and standards; (3) a Zero Trust Architecture Design defining enforcement points, delegation models, and controls; and (4) an IAM Integration Roadmap that embeds AI security into the existing identity architecture.
When should I run an Assessment versus a Workshop?
Run an AI Security Workshop first if you are still mapping AI risk and need a strategic roadmap. Run an Agentic AI Security Assessment when you are already deploying AI agents and need rigorous technical validation of your identity controls and architecture. Many organizations sequence the two: Workshop sets direction; Assessment validates and hardens specific deployments.
Secure your AI Agents Today
Get a clear view of your risks and define the controls needed to secure your AI environment.