Tonic Security Unveils AI Agents to Automate Cyber Remediation

TEL AVIV, Israel – February 24, 2026 – As organizations grapple with an ever-expanding digital attack surface and a flood of security alerts, Israeli-based Tonic Security today announced a new approach that aims to shift the paradigm from manual intervention to autonomous action. The company has launched its Tonic Mobilization Coordinator, a system it describes as the industry’s first “agentic workflow” designed to autonomously manage and verify cybersecurity remediation from start to finish.

This new technology is the centerpiece of Tonic’s Agentic Exposure Management Platform, which seeks to address a critical and persistent challenge in cybersecurity: the gap between identifying a vulnerability and actually fixing it. While traditional tools have become adept at finding flaws, security teams remain overwhelmed, struggling to prioritize and coordinate fixes across sprawling IT environments. This delay creates a window of opportunity that attackers are quick to exploit.

“Most breaches don’t happen because vulnerabilities weren’t found - they happen because teams couldn’t decide and act fast enough,” said Sharon Isaaci, CEO of Tonic Security, in the company's announcement. “Tonic closes the gap between knowing and doing. Our Mobilization Coordinator continuously determines what actually matters to the business, orchestrates remediation across teams and tools, and validates that risk is truly reduced.”

From Automation to Autonomy: What is Agentic AI?

The term “agentic” signals a significant evolution from the automation currently prevalent in cybersecurity. While Security Orchestration, Automation, and Response (SOAR) platforms have been instrumental in automating repetitive tasks by following pre-defined playbooks, they largely rely on human-scripted logic. If a situation deviates from the playbook, human intervention is typically required.

Agentic AI, in contrast, introduces a layer of cognitive capability. An agentic system is designed to perceive its environment, reason about the context, and dynamically generate multi-step plans to achieve a goal. Instead of merely executing a script to patch a server, an agentic workflow can understand the vulnerability, identify the system owner, assess the potential business impact of a patch, schedule the remediation, apply the fix, and then independently verify that the vulnerability has been closed and no new operational issues have been created.

This move from rules-based execution to goal-oriented reasoning is what sets Tonic's platform apart. It's designed not just to follow orders, but to understand intent—the intent being the continuous reduction of business risk. The platform ingests and reconciles vast amounts of data from security tools, IT systems, and even internal knowledge bases to create what Tonic calls a “Security Data Fabric.” This unified data layer provides the rich context necessary for the AI agents to make intelligent, autonomous decisions.

Closing the Action Gap in Exposure Management

Tonic’s platform is built on a four-part framework designed to manage the entire exposure lifecycle: Collect, Contextualize, Prioritize, and Act.

First, agents Collect and reconcile data from a wide array of sources, creating a dynamic, self-maintaining map of the organization's operational reality. Next, they Contextualize this data, inferring factors like business criticality, asset ownership, and exploitability to understand not just what exists, but what truly matters.

This leads to the Prioritize phase, where the system moves beyond generic severity scores. Instead of presenting teams with a list of thousands of “critical” vulnerabilities, the platform transforms the data into a short, explainable queue of business-aligned risks. Finally, the Mobilization Coordinator steps in to Act. It orchestrates the end-to-end remediation campaign, routing tasks, providing context to human teams when needed, and validating that the risk is eliminated. If a direct fix isn't feasible, the agent can propose alternative mitigating controls or formal risk acceptance, aligning its suggestions with the organization's established policies.

The business impact, according to the company's data from early customers, is substantial. Tonic reports a 90% reduction in the volume of exposures requiring manual remediation, a 50% faster remediation time for business-critical risks, and that 80% of remediation work is orchestrated automatically, freeing up significant security team capacity.

A New Partnership: Governable AI and Human Oversight

Handing over the keys to an autonomous system is a source of significant anxiety in the cybersecurity world, where a single misconfiguration can lead to a major outage or security incident. Tonic Security addresses this head-on with a design philosophy it calls “Governable Agentic Execution.”

The goal is not to replace human experts but to augment them, creating a human-machine partnership. Every recommendation and action within the platform is designed to be fully explainable, evidence-backed, and controlled by human-defined policies. Human teams retain ultimate oversight and can set the “rules of the road” for the AI agents.

This is achieved through principles of Explainable AI (XAI), where the system must be able to justify its decisions. For example, it can articulate why a specific vulnerability was prioritized by citing its reachability from the internet, the availability of an exploit, and the business-critical nature of the affected asset. Furthermore, the platform incorporates human-in-the-loop workflows, allowing for approval gates on high-impact changes and providing a clear audit trail for every action taken. The system then closes the loop by automatically validating the remediation, providing executives with measurable, evidence-backed reports on actual risk reduction, not just activity metrics.

Navigating a Crowded and Evolving Market

Tonic Security enters a market populated by established giants in vulnerability management like Tenable and Qualys, as well as powerful SOAR platforms from companies like Palo Alto Networks and Splunk. However, its approach carves out a distinct niche. Traditional vulnerability management platforms excel at identifying and prioritizing risks, but often leave the complex task of orchestration and remediation to other teams and tools. SOAR platforms provide the automation engine but require security teams to build and maintain the playbooks for them to execute.

Tonic aims to bridge the gap between these two worlds. It differentiates itself by offering a system that doesn't just prioritize a list or execute a static playbook, but autonomously plans and manages the entire remediation campaign. By embedding the orchestration and action phase directly into the exposure management lifecycle and powering it with agentic AI, the company is betting that it can deliver a more holistic and effective solution to the core problem of turning security data into decisive action. This positions the platform as a next-generation operating layer for security, one where intelligent agents handle the relentless work of coordination and follow-through, allowing human experts to focus on strategic risk management.