Product Positioning
Wiz connects code, cloud, and runtime into a single agentic cybersecurity platform, covering various cloud and AI layers, for preventing risk, detecting threats, and achieving secure start. Its proposition is: AI itself does not directly make security faster; context is the key. By connecting code, cloud, and runtime into a unified security graph, the platform provides end-to-end context for automated risk reduction and threat response, enabling security teams to operate at AI speed.
Main Capabilities
- Secure development: Provides security protection from the first line of code in the IDE to CI/CD and deployment.
- Cloud and AI risk prevention: Protects every application built in the cloud, covering infrastructure to data.
- Runtime protection: Runtime protection and threat detection for the cloud and AI era.
Security Agents
- Wiz Green agent: Automatically turns risk into code remediation, opens PRs to fix issues at the source, and helps write secure code from the start.
- AI-driven attacker (Red Agent): Continuously simulates real attack paths across the cloud and AI stack, validates actual exploitability, filters theoretical noise, and surfaces high-priority risks.
- Autonomous investigator (Blue Agent): Autonomously investigates alerts across cloud and code, provides defensible conclusions and orchestrates response, and quickly exposes the full scope of impact by correlating evidence end to end.
- Precise remediation: Connects discovery and remediation through context-aware source remediation, automatically generates action plans, assigns ownership, and executes remediation.
Usage and Workflow
The workflow described in the materials includes:
- Attack surface scanning: Maps externally reachable assets and models initial access paths, including internet exposure of endpoints and services as well as Wiz threat research intelligence.
- Deep internal analysis: Connects code, cloud, identity, network, and runtime to model lateral movement, privilege escalation, and data access chains.
- Remediation at scale in code: Uses graph context and ownership mapping to identify the right place to fix, assign the right ownership (team, repository, service), and generate direct code and infrastructure fixes.
- Detection and blocking: Uses Wiz eBPF runtime sensors, combined with deep analysis of cloud and SaaS logs and rich application and code context, to detect real exploitation attempts, block ongoing lateral movement, and conduct investigations with full context lineage.
Applicable Scenarios
- Protect cloud environments, AI workloads, and the data supporting next-generation innovation.
- Continuously discover AI models, agents, MCP servers, and services across cloud and SaaS, identifying AI-specific risks (sensitive data exposure, guardrails, exposed endpoints, etc.).
- Understand real AI risks through contextual understanding that connects infrastructure, identity, data, and AI.
- Detect and respond to AI runtime threats, including data exposure and malicious agent behavior.
Customers and Reviews
The material states that more than 65% of Fortune 100 companies trust Wiz; customers rate it first in cloud security. In the Forrester Wave Q1 2026 CNAPP report, Wiz was named a Leader and received the highest current offering score; it was recognized as a Leader in the IDC MarketScape 2025 Worldwide CNAPP; and was named a Customers' Choice in the 2026 CSPM. The material also cites reviews from several security and product leaders, saying that Red Agent discovered critical authorization flaws missed by traditional testing and bug bounty programs, Blue Agent can quickly help understand why an alert occurred, and Green Agent automatically creates Jira tickets that include a complete description, attack path analysis, and remediation steps.
Limitations and Missing Information
Regarding pricing, charging model, specific installation commands, the list of supported platforms, and deployment requirements, the material does not currently provide them.