AI agents are rapidly becoming a new channel for customers to interact with businesses online. They can navigate applications, research services, purchase products, and complete multi-step tasks on behalf of users. For businesses, this creates significant opportunities for customer engagement, but it also introduces new security, fraud, and business risks. The question now for organizations is: How can they enable trusted agent activity, and agent-driven business, while maintaining control over malicious, compromised, or otherwise risky agentic interactions?
Today, Radware is introducing Agent Trust Management, a new solution that enables organizations to identify all AI agents in real-time, continuously assess their trustworthiness with conversational intent capture and AI-based trust assessment, and govern the actions they are permitted to perform. With the visibility and control to enable trusted agent interactions while containing risk, organizations can confidently participate in the emerging agentic economy and embrace its benefits.
Gain Deeper Visibility into Agent Activity
Establishing trust starts with understanding the agentic activity on applications and having sufficient context to evaluate their activity. Radware provides prompt-aware, session-level visibility through a dedicated, purpose-built console. It brings together information about agent interactions at the session-level with prompt-level context that can help security teams better understand agent behavior, investigate potential risks, and make informed policy decisions.
Built-in analytics reveal evolving agent behaviors, traffic patterns, and security events across the agent ecosystem. By combining trend-level insights with session-level detail, Radware gives organizations deeper visibility into agent activity and the context needed to assess it.
Identify AI Agents Across the Ecosystem
Not every AI agent identifies itself in the same way. Some comply with emerging authentication standards such as Web Bot Auth, while others do not. As a result, relying on standards compliance alone can leave gaps in identifying the agents interacting with the organization’s applications.
Radware identifies and classifies all AI agents in real-time, including agents that comply with Web Bot Auth and those that do not, using multiple signals across request headers, client-side behavior, and direct agent responses. For standards-compliant agents, Radware supports cryptographic verification through Web Bot Auth.
Continuously Assess Agent Trustworthiness
Knowing an agent’s identity provides important context, but identity alone does not establish trust. An identifiable or legitimate agent may be misdirected, compromised, or attempt actions that do not align with its stated intent.
Radware Agent Trust Management captures intent directly from AI agents through active conversation, providing context beyond agent identity and observed behavior alone. Declared intent is not treated as proof of trustworthiness. Radware continuously evaluates trust through multiple AI-based assessments, including whether the agent’s behavior remains consistent with the captured intent, to identify deviations, manipulation, or potentially malicious activity as they emerge.
The trust levels assigned based on this continuous assessment is dynamic in nature, evolving with agent behavior across sessions. These dynamic trust levels provide the basis for applying appropriate agent-level policies and permissions.
Govern What Each Agent is Allowed to Do
Managing AI agent traffic should not require organizations to choose between binary allow-or-block decisions. An agent may be trusted to perform certain activities, while other workflows may require greater control.
Radware enables granular, permission-based governance, allowing organizations to control the specific actions an agent can perform such as logging in, creating an account, or completing a checkout. Policies and permissions can be aligned with the agent’s trust level and the context of the interaction.
For example, an organization could allow an agent to browse products and log in while preventing it from completing a purchase. This allows organizations to enable valuable agent interactions while maintaining control over sensitive workflows or higher-risk actions.
Engage Confidently in The Agentic Economy
With the growing adoption of AI agents by consumers, they are becoming an important part of digital customer journeys. Capturing the value from these transactions and the broader agentic economy require businesses to distinguish trusted interactions from those that introduce risk and apply the appropriate level of control.
Radware Agent Trust Management combines prompt-aware visibility, real-time agent identification, continuous trust assessment, and permission-based governance - empowering organizations to enable trusted agent interactions, restrict actions that require greater control, and stop high-risk activity.
Contact us to learn more about Radware’s Agent Trust Management solution and how it can help your organization participate confidently in the agentic economy.