Artificial Intelligence is transforming how organizations operate — and intelligent agents are leading the charge. From copilots and remediation bots to data-driven assistants, these agents now automate decisions across the cloud and continue to take on more complex tasks. But with new capability comes new exposure.
Security teams everywhere are asking:
Where are these agents running?
What access do they have? Who can access them?
What capabilities do they have?
Where did they originate from?
What risks do they introduce?
How do we stay compliant as AI evolves?
Wiz AI Security Posture Management (AI-SPM) extends Wiz’s agentless CNAPP foundation to secure this new layer of automation — giving teams the visibility, context, and automation to manage AI agents confidently.The model below shows how Wiz AI-SPM secures AI agents end-to-end — from visibility to continuous defense.
Stage 1: Visibility — Discover Your AI Footprint
Security starts with knowing what’s running. Wiz brings agentless discovery to your AI footprint, identifying AI services, models, and integrations — including Model Context Protocol (MCP) connections- with broad coverage across major clouds.
Wiz brings agentless discovery to your AI footprint, identifying AI services, models, and integrations — including MCP connections — with broad coverage across major clouds.
AI Bill of Materials (AI BOM): inventories all AI software, SDKs, libraries, and dependencies across your environment.
Agent Inventory View: visualizes your agents, models, tools, MCP technology ,data (training and knowledge base) - allowing you to contextualize the access, capabilities and potential blast radius of each agent.
Attack Surface Mapping: uncovers external-facing AI endpoints, validated with our dynamic scanner, evaluates their exposure, and connects them to workloads and owners via the Wiz Security Graph.
Outcome: full visibility into AI agents and its connections, across cloud providers, SaaS platforms, and self hosted architectures — without deploying new agents.
Stage 2: AI Misconfigurations — Secure the Foundations
With your AI landscape mapped, the next step is securing how those agents are configured and controlled. Many early AI risks come from weak defaults or missing guardrails that expose sensitive data or grant unintended permissions to agents.
Baseline Enforcement: continuously validates that AI platforms like Bedrock, Vertex AI, and OpenAI follow secure configuration baselines, such identity/CIEM/access and logging for monitoring.
Guardrail Verification: confirms provider-native protections (e.g., AWS Bedrock Guardrails) are enabled and properly configured for both input and output
Sensitive Data Controls: detects and prevents inadvertent access to PII or regulated datasets through misconfigured prompts, storage, or APIs.
Outcome: eliminate preventable exposures and ensure agents operate within secure, approved boundaries.
Stage 3: AI Posture — Understand Context and Prioritize Risk
Visibility and configuration checks only go so far without context. Wiz connects every AI-related finding — from agents to data to workloads — through the Security Graph, revealing how risks propagate and where they truly matter.
Contextual Correlation: maps agents to the identities, workloads, and data they touch, showing the real attack paths an exploited agent could follow.
DSPM for AI: extends data discovery and classification into AI training and inference pipelines, surfacing unprotected datasets or over-permissive access.
OWASP LLM Alignment: addresses leading AI risks like prompt injection, data poisoning, and insecure output handling with built-in policies.
Outcome: move from static posture to context-driven insight — understanding which agent risks are exploitable and how to fix them fast. Visibility shows you what exists. Context shows you what matters.
Stage 4: Response & Runtime — Defend Continuously, Evolve Securely
As AI agents become part of everyday operations, protection can’t stop at prevention. Wiz brings runtime visibility and automated response to keep agents secure in motion — and ready for what’s next.
Runtime Monitoring: detects new AI activity in production, watching for drift from established baselines or suspicious behavior — such as an AI workload hosting a rogue agent or attempting to communicate with a suspicious DNS destination.
Threat Correlation: links live agent behavior to underlying cloud resources, identities, and sensitive data to trace potential exploitation paths.
Automated Response: triggers contextual fixes or tickets through Jira, ServiceNow, or CI/CD pipelines, turning alerts into action.
Outcome: continuous defense for agents in action — securing innovation today and preparing for what’s next.
Building Trust in Intelligent Automation
Securing AI agents isn’t a one-time project — it’s a continuous journey built on visibility, context, and response. Wiz AI-SPM gives organizations the framework to mature confidently through each stage, ensuring innovation moves as securely as it scales.
As AI reshapes the enterprise, Wiz keeps every agent — and every connection — operating with the same trust and protection that power the modern cloud. And this is only the beginning: Wiz continues to expand AI-SPM with deeper runtime insight, richer context for AI-driven workflows, and new capabilities that strengthen defense as AI evolves.
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