pavel-odintsov/fastnetmon

Very fast DDoS sensor with sFlow/Netflow/IPFIX/SPAN support

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Summary Information

Updated 1 hour ago
Added to GitGenius on September 18th, 2026
Created on October 18th, 2013
Open Issues & Pull Requests: 60 (+0)
GitHub issues: Enabled
Number of forks: 590
Total Stargazers: 3,703 (+0)
Total Subscribers: 190 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 20.4 hours
Mean response time: 34.1 days
90th percentile: 74.2 days
Tracked items: 24

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Issue Activity (beta)

Open issues: 7
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 882 days
Stale 30+ days: 7
Stale 90+ days: 4

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • dependencies (2)
  • enhancement (2)

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Detailed Description

FastNetMon is a high-performance DDoS detector and sensor built to identify hosts sending or receiving abnormally large traffic volumes across a network.

The tool ingests traffic data from multiple sources—NetFlow, IPFIX, sFlow, PCAP, AF_PACKET port mirrors, AF_XDP, and Netmap—and analyzes packet rates, byte rates, and flow counts per second to detect anomalous activity. When it identifies a host exceeding configured thresholds, it triggers configurable responses: notifications, custom script execution, or BGP announcements for traffic diversion.

Organizations running networks where DDoS detection is a core operational need should evaluate this tool. It suits deployments with existing flow collection infrastructure or the ability to mirror traffic, particularly those already using Cisco, Juniper, or MikroTik equipment that can export NetFlow or sFlow. The community edition provides the core detection engine; a commercial advanced edition exists with additional capabilities.

Development activity shows consistent maintenance of the packet capture backend integrations, with support for multiple competing technologies (NetFlow v5 and v9, IPFIX, sFlow v5, PCAP, AF_PACKET, AF_XDP, and legacy Netmap and PF_RING options) kept functional across Linux, macOS, and FreeBSD platforms. The project maintains detailed documentation including a reference guide and comparison tables for capture backends and feature editions. The codebase is written in C++ and carries trademark and licensing terms that users must accept before installation.