Mate Security has been named the winner of the “Security Response Solution of the Year” award by CyberSecurity Breakthrough as part of the 10th annual CyberSecurity Breakthrough Awards program, recognizing the company’s approach to building an AI-driven foundation for security response. The recognition comes as enterprises increasingly explore how AI agents can move beyond assisting security teams and begin taking action across complex environments.
Mate is building what it calls the open foundation for agentic cyberdefense, centered on a context layer designed to help AI agents understand how an organization operates. Rather than treating security alerts as isolated events, the platform gives agents access to organizational knowledge that can inform investigation, decision-making and response.
The Next Stage of Security Automation
Cybersecurity automation has traditionally focused on reducing repetitive work. Security platforms can correlate alerts, enrich events and recommend actions, but critical response decisions often remain with human analysts.
The reason is straightforward: the cost of an incorrect action can be significant.
An automated system that isolates the wrong host, disables the wrong account or blocks too much of an organization’s infrastructure can create disruption while attempting to contain a threat. As AI agents become more capable, security teams therefore face a new question: how much autonomy can safely be given to an AI system?
Mate’s approach is to make organizational context a prerequisite for autonomous action.
Its Security Context Graph creates a living model of an organization’s security knowledge and relationships. The graph incorporates information such as asset ownership, dependencies, business criticality, privileged identities and applicable policy.
That allows agents to consider the environment surrounding an alert before determining how to respond.
Context Before Action
Mate’s Reason Mining engine populates the Security Context Graph, turning organizational data into knowledge that AI agents can use.
The goal is not simply to provide agents with more information. It is to give them the information needed to understand consequences.
A suspicious event involving a production host can carry very different implications from an identical event involving a non-critical system. Likewise, an anomalous session associated with a privileged identity may require a different response from one involving a standard account.
This organizational context becomes particularly important when an agent is authorized to act rather than simply recommend an action.
“Precision and reversibility require organizational context. That means for agents to act with precision, alerts need to be evaluated in relation to the specific business environment rather than in isolation. “When we started Mate, we knew we had to build context and trust into our product,” said Asaf Wiener, co-founder and CEO of Mate Security. “Enterprises need security platforms that can not only act faster, but also make the right decisions with enough context at scale. We are answering that need and are grateful to CyberSecurity Breakthrough for this award. We will continue moving fast and stay laser-focused on our customers, as we proudly build the foundation for agentic cyberdefense in the AI era.״
Putting Guardrails Around Agents
Mate combines its organizational context with a framework called Confidence, Precision, and Reversibility, or CPR.
The framework evaluates proposed actions based on how certain the agent is about its conclusion, how narrowly the action can be applied and whether it can be reversed.
That can mean revoking a single session instead of an entire account, blocking one URL instead of an entire domain or isolating one host rather than a broader network segment.
“CPR weighs the risk of acting against the risk of not acting. A human can decide fast, and an agent acts on its own only when acting is the safer choice,” said Inbal Argov, VP Product Strategy at Mate Security, who created the CPR framework.
The approach effectively makes autonomy conditional. An agent does not need to act simply because it can. Instead, it can weigh the potential risk of taking action against the risk of waiting for a human decision.
A Recognition of the Changing Security Model
The CyberSecurity Breakthrough Awards marked their 10th anniversary in 2026 and received thousands of nominations from organizations across more than 20 countries.
Steve Johansson, managing director at CyberSecurity Breakthrough, highlighted the difficulty of automating response safely.
“Mate compresses multi-day MTTR to minutes with real organizational context. Response is the hardest part to automate because a wrong action can damage the entire business. From isolating a production host to revoking a shared credential, this can cost more than the incident. So most actions are routed through human approval, and that delay is costly in the age of AI-related attacks,” said Steve Johansson, managing director, CyberSecurity Breakthrough.
For Mate, the award reflects a broader thesis about the future of security operations: AI agents may eventually handle much more of the response process, but their ability to act safely will depend on how well they understand the organizations they protect.