AI agents are rapidly becoming part of everyday business operations. They automate workflows, assist employees, interact with enterprise systems, and increasingly make decisions and take actions on behalf of users.
While organizations focus on accelerating AI adoption, many are discovering a growing challenge: securing and governing an expanding ecosystem of autonomous agents operating across multiple environments. As agent usage grows, visibility, accountability, and compliance have become just as important as innovation.
That challenge is driving the next evolution of Radware Agentic AI Protection. Designed to help organizations secure, govern, and gain visibility into their AI ecosystems, the latest release introduces enhanced compliance reporting, protection for developer-hosted agents, and a more powerful Agent Graph experience.
The New Challenges of Managing Centralized and Developer-Hosted AI Agents
Enterprises are no longer relying on a single model of AI adoption. Today, most organizations operate a combination of centrally managed AI platforms—such as Microsoft Copilot, Google Gemini, ChatGPT Enterprise, and AWS Bedrock—alongside developer-hosted agents like Claude Code, OpenClaw, and N8N that are used by individual teams and developers.
This dual adoption model delivers enormous business value, enabling organizations to scale AI innovation across both enterprise-wide and team-specific use cases. However, it also creates new visibility, governance, and security challenges. Different types of agents operate in different environments, interact with different tools and resources, and often fall under different operational controls. As a result, security teams must find ways to govern and protect an increasingly distributed agent ecosystem without slowing innovation.
While these tools unlock significant productivity gains, they also introduce an expanded attack surface.
Developer-hosted agents often operate closer to sensitive data, local resources, source code repositories, cloud credentials, and internal business systems. Security teams may have limited visibility into how these agents are used, what tools they invoke, which resources they access, and what actions they perform. At the same time, centralized agents may interact with enterprise applications, SaaS platforms, and business-critical workflows, creating their own governance and oversight requirements.
Compounding these challenges is the growing pressure organizations face from governments, regulators, auditors, customers, and executive stakeholders. Enterprises are increasingly expected to demonstrate that their AI systems operate according to established governance and risk management frameworks. Standards and regulations such as ISO 42001, the European Union AI Act, and the NIST AI Risk Management Framework (RMF) are raising expectations for transparency, accountability, traceability, and risk management across AI environments.
The reality is that many organizations are deploying AI agents faster than they can effectively secure and govern them. CISOs, security teams, and compliance stakeholders need comprehensive visibility into their AI ecosystem, audit-ready governance capabilities, and consistent security controls that span both centralized and developer-hosted AI agents.
Introducing the Next Evolution of Radware Agentic AI Protection
To help organizations address these challenges, Radware has introduced significant enhancements to its Agentic AI Protection solution. The latest release expands visibility, governance, and protection capabilities across both centralized and developer-hosted agent environments, helping organizations securely scale AI adoption while maintaining control, accountability, and compliance.
1. Compliance Reporting Aligned with Global AI Standards
As AI governance moves from a best practice to a business requirement, organizations need practical mechanisms for demonstrating accountability and regulatory alignment.
The latest release introduces new audit-ready reporting capabilities aligned with three major global AI governance frameworks:
- ISO 42001
- EU AI Act
- NIST AI Risk Management Framework (RMF)
These reports provide detailed visibility into agent behavior, prompts, interactions, tools, resources, anomalies, and security events. Security, compliance, and governance teams can generate structured reports that help demonstrate traceability, risk mitigation efforts, and alignment with industry-recognized standards.
By automating the collection and presentation of governance information, organizations can simplify audit preparation, support regulatory requirements, and strengthen AI governance programs without relying on time-consuming manual reporting processes.
2. Protection for Developer-Hosted AI Agents
One of the most significant additions in this release is expanded support for developer-hosted AI agents.
Radware Agentic AI Protection now supports Claude Code, OpenClaw, and N8N, extending visibility, governance, and protection beyond centralized AI deployments. Organizations can now apply enterprise-grade security controls to AI agents running directly on developer workstations and client-side environments.
With this capability, organizations can:
- Secure locally installed AI agents and workflows.
- Monitor interactions between agents, tools, APIs, environments, and external services.
- Detect and prevent attacks targeting locally executed agent workflows.
- Extend governance and security controls to client-side AI deployments.
- Close visibility gaps across developer-hosted and homegrown agents.
This enhancement provides organizations with a more complete approach to AI security, protecting both enterprise-wide agent deployments and the rapidly growing ecosystem of developer-hosted agents used throughout the organization.
3. Enhanced Agent Graph and Interactive Connection Map
Visibility is the foundation of effective AI governance and security.
The latest release significantly enhances Radware's Agent Graph and Interactive Connection Map, providing a more comprehensive and intuitive view of the entire agent ecosystem. The enhanced experience transforms raw telemetry into structured, human-readable context while delivering deeper visibility into the relationships between agents, tools, services, resources, and workflows.
Organizations can more easily understand:
- Which agents exist across the environment.
- Which tools and resources they use.
- How agents interact with enterprise systems.
- Dependencies and relationships between agents and tools.
- Potential governance gaps and areas of risk.
By making complex agent interactions easier to visualize and understand, the enhanced Agent Graph helps security and governance teams gain better oversight of their growing AI environments and make more informed decisions about risk management and policy enforcement.
Secure AI Innovation Without Sacrificing Governance
The future of enterprise AI will be increasingly agent-driven. As organizations deploy more autonomous systems across centralized platforms, developer environments, and business workflows, maintaining visibility, governance, and security becomes essential.
With new compliance reporting for ISO 42001, EU AI Act, and NIST RMF, expanded protection for developer-hosted agents such as Claude Code, OpenClaw, and N8N, and a significantly enhanced Agent Graph experience, the latest release of Radware Agentic AI Protection helps organizations gain the visibility, governance, and protection needed to safely scale Agentic AI adoption.
Because securing AI is no longer just about protecting models and prompts. It's about understanding, governing, and protecting every agent across the enterprise—wherever it runs.