Praeventra continuously collects forensic evidence from endpoints while incidents are unfolding, turning raw activity into actionable intelligence through predefined IoCs, graph-based correlation, and automated response workflows.
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Detect suspicious behavior, known attack patterns, and policy-relevant activity faster
70+
Broad endpoint visibility across forensic and security-relevant activity
100+
Flexible workflow-based response from notifications to controlled containment
Praeventra is built to transform endpoint activity into meaningful forensic context. The platform currently includes more than 1,800 predefined Indicators of Compromise, helping security teams detect suspicious behavior, known attack patterns, and policy-relevant activity faster. In addition to IoC coverage, Praeventra collects a wide range of endpoint forensic data points, including process activity, system behavior, file-related events, network indicators, user activity, and other security-relevant signals.
More than 1,800 predefined Indicators of Compromise that help detect known suspicious patterns, malicious indicators, and policy-relevant activity. The IoC library strengthens detection capability and can be expanded with customer-specific intelligence.
70+ client-side forensic data points, including process activity, system behavior, file-related events, network indicators, and user activity, provide the foundation for detection, investigation, correlation, and response.
More than 100 response actions enable flexible, policy-driven response workflows, from notifications and investigation steps to controlled containment actions that reduce incident spread.
Praeventra delivers value before an incident, during an incident, and after detection, giving security teams the tools they need at every stage of the forensic lifecycle.
Continuously collect endpoint evidence before critical information is lost, modified, or deleted. Security teams gain richer investigation context, stronger evidence quality, and a clearer understanding of suspicious activity as it develops.
Predefined IoCs, advanced rule logic, and customer-specific detection policies identify suspicious behavior faster. When detected, Praeventra generates enriched alarms and triggers investigation, notification, containment, or automated response workflows.
With near real-time visibility, graph-based correlation, and workflow-driven response, security teams detect incidents earlier, contain affected systems faster, and reduce the potential impact on business continuity.
Praeventra uses a graph database to connect endpoints, users, processes, files, events, and alarms, revealing relationships, attack paths, and wider incident patterns rather than treating every alert as an isolated signal.
Standardize and automate response processes so analysts can reduce repetitive manual work, focus on high-priority incidents, and use workflow-based actions to respond more consistently and with greater confidence.
Praeventra brings AI into the investigation process, combining forensic data and graph-based relationships to help analysts understand incidents faster and with less complexity, summarizing incidents, surfacing critical relationships, and highlighting attack paths.
Praeventra brings digital forensics into the live security operation, combining capabilities that are often handled separately in one unified DFIR platform.
While conventional forensic tools are often used after an incident has already happened, Praeventra is designed to run continuously, supporting investigation before, during, and after suspicious activity occurs. It collects and preserves forensic evidence while endpoint activity is still happening, reducing the risk of missing critical context.
Praeventra combines continuous endpoint collection, IoC-based detection, advanced rule processing, graph-powered correlation, workflow automation, and controlled response actions. This allows security teams to move faster from signal to investigation, from investigation to understanding, and from understanding to action.
Unlike tools that focus only on alerts or only on post-incident analysis, Praeventra connects the full incident story. The platform links users, machines, processes, files, events, alarms, and response actions through a graph database, helping analysts understand not just what happened, but how each activity is connected.
With more than 100 response actions, Praeventra can trigger notifications, support investigation workflows, provide structured data to AI agents, isolate machines, terminate suspicious processes, shut down systems, or control network interfaces, manual, approval-based, or fully automated based on operational requirements.
Praeventra is built from purpose-designed components that work together to provide continuous forensic readiness, intelligent detection, graph-based correlation, and workflow-driven response.
Runs continuously on client machines and collects forensic and security-relevant information. Provides the foundation for continuous visibility by capturing endpoint activity that may be important for detection, investigation, and evidence preservation.
Processes collected endpoint data using advanced rule logic. Evaluates incoming events against predefined IoCs, detection rules, and customer-specific policies. When suspicious activity is detected, the event engine creates alarms and enriches them with useful context.
More than 1,800 predefined Indicators of Compromise that help identify suspicious activity and known threat patterns. The IoC library strengthens detection capability and can be expanded over time with new intelligence and customer-specific indicators.
Stores and connects forensic entities such as endpoints, users, processes, files, events, alarms, and relationships. Allows Praeventra to analyze security activity as a connected structure instead of isolated records, revealing attack paths and related incidents.
Uses graph relationships and correlation rules to identify links between events, alarms, systems, users, and processes. Helps analysts understand whether an event is isolated or part of a broader incident chain.
Turns detection and correlation results into action. Can trigger notifications, investigation tasks, AI-agent support, containment steps, or controlled response actions based on predefined policies and customer configuration.
Praeventra brings AI into the investigation process by combining forensic data, graph-based relationships, and workflow-driven intelligence. The platform uses the graph database to navigate connected security context across users, endpoints, processes, files, events, and alarms, helping analysts understand incidents faster and with less complexity.
With AI-supported analysis, Praeventra can summarize incidents, surface critical relationships, highlight possible attack paths, and guide analysts toward the evidence that matters most. Through workflow integration, Praeventra can also provide structured forensic context to AI agents for deeper analysis, reporting, and response recommendations.
This creates a practical and intuitive investigation experience that helps security teams move from data overload to clear, actionable insight.
Learn how Praeventra can improve your forensic readiness, accelerate investigation, and strengthen your incident response capability.
