# dreadl0ck/netcap

A framework for secure and scalable network traffic analysis - https://netcap.io

Repository: https://github.com/dreadl0ck/netcap
Canonical: https://ross.abutalabs.com/products/netcap
Language: Go
License: GPL-3.0
License Family: copyleft
Topics: network, security, monitoring, detection, analysis
Last push: 2026-08-26T13:59:17+00:00

## Health v2 (maintenance only)
Score: 92/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 78, longevity 100
- inputs: {"age_days": 2835, "days_push": 7, "days_rel": 146, "gap_med": 0, "n_releases_24m": 8}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1805, forks 168 (observed 2026-08-28T04:05:39.004411+00:00)

## What it is
Netcap is a Go framework that converts network packets into structured, type-safe Protocol Buffer audit records for security monitoring, forensics, and machine learning. It ships as a single binary with 83 packet decoders, 40+ stream decoders, 141+ audit record types, and a built-in web UI for visualization and analysis.

## Use cases
- analyze pcap files and extract structured audit records
- monitor network traffic for security threats
- fingerprint TLS, HTTP, and SSH clients with JA4
- detect malware in transferred files with YARA rules
- reconstruct TCP and UDP streams from captures
- feed network features into machine learning models
- inspect industrial control system protocols like Modbus and S7Comm
- visualize protocol hierarchy and host communication

## When to choose
- you need scalable, concurrent full-packet analysis on Linux, macOS, or Windows
- you want structured, machine-readable output instead of ad-hoc pcap parsing
- you need broad protocol coverage including industrial protocols
- you are building security monitoring, forensics, or ML pipelines on network data

## When to avoid
- you only need simple packet capture without structured analysis
- you require a lightweight passive sniffer with minimal resource usage
- you need a GUI-first tool rather than a CLI/service framework
- your license requirements are incompatible with GPL-3.0

## Facets
- artifact type: framework
- maturity: active
- function: networking, security, monitoring, analytics, machine-learning, data-science
- domain: security, networking, monitoring, analytics, machine-learning
- platform: windows, cross-platform, cli, go
- tags: network-traffic-analysis, packet-capture, audit-records, protocol-buffers, pcap, forensics, intrusion-detection, ja4-fingerprinting, yara, stream-reassembly, linux, macos

## Member repositories
- dreadl0ck/netcap (main) score 92

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:39.004411+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:21:33.475421+00:00, confidence not recorded.
  - readme: https://github.com/dreadl0ck/netcap (fetched 2026-08-28T04:05:39.004411+00:00, sha 1d2f4d883a7a)
- Data as of 2026-08-30T08:39:29.467469+00:00.