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KnowBe4 Introduces Agent Risk Manager to Address Emerging AI Agent Security Risks

by تكنو فن
أبريل 16, 2026
Reading Time: 6 mins read
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KnowBe4

KnowBe4, the globally recognized platform specializing in human risk management and AI-driven risk mitigation, has announced the launch of Agent Risk Manager. The solution is positioned as the industry’s first defensive system designed to secure, monitor, and govern the behavior of autonomous AI agents.

The new capability is introduced as a core component of the KnowBe4 HRM+ platform, marking a significant shift in how organizations assess and mitigate risks associated with both human workforces and AI-augmented operations.

Addressing a New Security Gap in Agentic AI Environments

As enterprise workflows increasingly transition from AI-assisted systems to fully agent-driven models, a new security gap has emerged. While many existing solutions focus on static code analysis or API-level protection, KnowBe4 targets the behavioral risks associated with autonomous AI agents.

Agent Risk Manager is designed to prevent unauthorized actions such as sensitive data exposure, detect indirect prompt injection attacks, and enforce strict agent containment policies across enterprise environments.

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Real-Time Behavioral Governance for AI Agents

The solution provides a real-time operational security layer that governs how AI agents behave after deployment. It focuses not only on access control but also on action-level monitoring and enforcement.

Greg Kras, Chief Product Officer at KnowBe4, emphasized the evolving nature of workplace risk:

“The industry has spent years securing the human element, but today AI agents have become new members of the workforce. Securing instructions is only half the battle. Agent Risk Manager focuses on outputs and actions, ensuring agents do not become an invisible IT layer or an entry point for advanced prompt injection attacks.”

Key Features of Agent Risk Manager

Agent Risk Manager introduces several core capabilities designed to strengthen enterprise AI governance, including:

  • Behavioral Guardrails: Real-time monitoring of agent actions to prevent unauthorized data leaks and unrestricted execution due to jailbreak attempts.
  • AI Agent Identity Governance: Defines access rights and tools available to each AI agent.
  • Agent Attack Simulation: Stress-tests AI agents against advanced prompt injection and social engineering techniques used by attackers.
  • Data-Driven Intelligence: Built on 15 years of behavioral data to predict deviations from safe operational standards.

The platform operates as a dynamic enforcement layer, controlling agent behavior continuously after deployment.

Advanced Detection and Compliance Capabilities

The system also includes a broad set of monitoring and governance tools:

  • Prompt Injection Detection: Machine learning models identify jailbreak attempts, logic bypassing, and indirect prompt injection across inputs and outputs.
  • Sensitive Data Detection: More than 20 classifiers detect and block exposure of personal and credential data before it reaches audit logs.
  • Resource Abuse Monitoring: Tracks excessive API calls, data queries, and compute usage to prevent uncontrolled agent activity and cost overruns.
  • Agent Containment: Automatically maps and indexes agents and tools across multi-tenant environments without manual configuration.
  • Audit Logging: Fully compliant, filterable audit trails for incident response and forensic investigations.
  • Lifecycle Integration Management: Centralized control of agent integrations with automated connectivity and access verification.
  • Guided Onboarding: Simplified setup enabling organizations to detect and deploy their first AI agent within minutes.

Industry Context and Market Perspective

The launch coincides with Identity Management Day, underscoring the growing importance of securing not only human identities but also machine identities within AI-driven systems.

Greg Kras highlighted that the cybersecurity landscape is rapidly evolving from human-centric risks to a broader threat environment that includes AI-driven actors capable of executing autonomous actions within enterprise networks.

Customer Perspective on AI-Driven Security

A KnowBe4 customer review on TrustRadius highlighted the company’s AI capabilities, noting that AI-driven personalization helps reduce user fatigue while improving targeted security awareness and risk reduction across organizational environments.

A Shift Toward AI-Native Risk Governance

With the introduction of Agent Risk Manager, KnowBe4 positions itself at the forefront of AI-native security governance, addressing emerging risks associated with autonomous agents, prompt-based attacks, and hybrid human-AI workforces.

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مرتبط

Tags: Agentic AIAI governanceAI securitycyber risk managementKnowBe4

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