Exabeam, a leader in behavior intelligence for the agentic enterprise, has announced the launch of Agent Behavior Verification (ABV). This pioneering security discipline is designed to help organizations evaluate whether AI agents are properly configured, authorized, and governed prior to their deployment in production environments. Alongside this framework, Exabeam has introduced Praxen, an open-source reference implementation of ABV, enabling enterprises to proactively audit digital workers before they go live.
Addressing the Pre-Deployment Security Gap in Enterprise AI
With the development of AI within organizations moving from assistants to full-fledged autonomous systems, companies are now facing new security risks. Contemporary AI-based systems regularly connect with confidential internal systems, perform advanced automation processes, and independently make decisions. While conventional security tools such as run-time monitoring, vulnerability scans, and red-teaming focus on ongoing threats, there has never been any established methodology for checking whether an agent is safe prior to its deployment.
Agent Behavior Verification fills this critical operational void. Instead of scanning individual code artifacts or hunting exclusively for known software vulnerabilities, ABV treats AI agents as holistic systems. It establishes a structured framework to map out an agent’s authorized capabilities and evaluates whether its underlying configurations, access permissions, and boundaries match its intended corporate role.
“Organizations are rapidly moving from AI experimentation to operational deployment,” said Steve Wilson, Chief AI Officer at Exabeam and Founder and Co-Chair of the OWASP Gen AI Security Project. “As agents become digital workers, security teams need more than runtime visibility. They need confidence that agents have the right permissions, the right controls, and the right boundaries before they enter production. Agent Behavior Verification helps answer a fundamental question: will this agent do its job, and only its job?”
How Praxen Operationalizes Agent Safety
Praxen serves as a practical tool to implement ABV guidelines. It utilizes an ABV “remit”—essentially a policy contract specifying exactly what resources an agent can access and what operational guardrails it must obey. Developers and security operations teams can leverage Praxen to verify that an agent’s integrations, memory, tools, and environment align seamlessly with its designated responsibilities.
By flagging discrepancies between intended and actual implementation, Praxen delivers prescriptive recommendations to resolve behavioral risks during the development phase. The resulting automated reports include granular engineering feedback, mitigation strategies, and an objective security maturity score for the agent.
“Traditional security tools help identify vulnerabilities in software,” continued Wilson. “Praxen evaluates something different: whether an agent’s capabilities, permissions, tools, and controls align with the role it was authorized to perform. This addresses one of the most critical risks introduced by highly autonomous agents and establishes a stronger foundation for ongoing governance throughout the agent lifecycle.”
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ABV provides the essential pre-deployment groundwork for Exabeam’s end-to-end AI security portfolio. It works in tandem with Agent Behavior Analytics (ABA), which monitors live environments to identify anomalies or risky autonomous actions after deployment.
Developed as an extensible skill for agentic coding and distributed under the Apache 2.0 license, Praxen offers full transparency for security practitioners, developers, and researchers.
“Most security tools tell you what’s vulnerable. Praxen asked a different question entirely: Does this agent’s actual behavior match the governance or work remit it was built to enforce?” said Sherri Douville, CEO of Medigram. “The code-level remediation path it produced didn’t give us a risk report to file away. It gave us a precise engineering roadmap we could act on immediately. In enterprise AI deployment, the gap between what an agent is authorized to do and what it is actually capable of doing is where operational risk lives.”
Fostering Transparency and Trust in Autonomous AI Systems
Through its open-source nature, Exabeam is seeking to make use of Praxen in order to promote the adoption of ABV methods throughout the industry. Due to the fact that AI governance strategies for enterprises are not stable at all, opening up the project enables developers and security experts from around the globe to examine and improve it.
