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Overview
Flowmon is an extensive Cybersecurity Software that detects ransomware, insider and unknown threats with AI and ‘ML’ anomaly detection and encrypted-traffic analysis. While the platform documentation about methods of ADS may require some improvements for some users, it delivers automated on-event packet capture and ‘SIEM’ export for fast forensic investigations.
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Starting Price
Custom
Flowmon Specifications
Threat Intelligence
Intrusion Detection
Security Information and Event Management (SIEM)
Cloud Security
What Is Flowmon?
Flowmon software is a cloud-based Cybersecurity Software that detects and provides alerts on network anomalies, ransomware, insider, and unknown threats using AI and machine-learning analysis of flow and telemetry. It ingests ‘NetFlow’ and ‘IPFIX’, cloud ‘FlowLogs’, and enriched ‘L2–L7’ data to provide continuous visibility across on-prem, cloud and hybrid environments. The platform also correlates context-rich evidence, timelines, and ‘MITRE ATT&CK’ mappings to prioritize incidents.
Flowmon Pricing
Flowmon Integrations
Flowmon software integrates with a wide range of apps, including:
- Splunk Enterprise
- Microsoft Azure
- Google Cloud
- WhatsUp Gold
Who Is Flowmon For?
Flowmon is suitable for small and midsize enterprises along with the following sectors:
- Educational institutes
- Public firms
- Data center operations departments
- Industrial control systems
- Telco, ISP, and carrier services
Is Flowmon Right For You?
Flowmon software is a comprehensive Cybersecurity Software suitable for businesses aiming to strengthen network-centric detection, reduce dwell time, and accelerate forensic investigations across hybrid estates. It offers SIEMs, IDS probes, and orchestration tools to enable prioritized incident response, threat hunting, and compliance reporting at scale across environments globally.
Still not sure if Flowmon is right for you? Contact our customer helpline at (661) 384-7070 for further guidance.
Flowmon Features
Flowmon understands every suspicious network event in its complexity and provide context-rich evidence and visualizations. It correlates flow metadata, network data and full-packet traces to build timelines and protocol-level detail for forensic analysis.
The software leverages entropy modelling, behavioural analytics, and machine-learning engines to detect suspicious anomalies in network traffic. It applies dozens of AI methods and hundreds of algorithms to reduce noise and surface high-confidence indicators of unknown and insider threats.
The system ingests commercial and community threat intel feeds to enrich network detections with known indicators of compromise. It correlates external indicators with local flow and packet evidence to validate alerts and lower false positives.
The platform triggers full packet capture automatically upon detection events and preserves pre-event data using a rolling memory buffer. It stores and retrieves complete packet evidence for deep forensic analysis and timeline reconstruction.
