FlowHawk

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          🦅 eBPF-POWERED NETWORK SECURITY MONITOR 🦅

Modern Network Security Platform

FlowHawk is a modern open-source eBPF-powered Network Security Monitoring Platform engineered for mission-critical infrastructure protection. Leveraging advanced kernel-space packet processing and machine learning threat detection, FlowHawk delivers unparalleled visibility into network traffic patterns and security anomalies.

"Strike fast, see everything. FlowHawk soars above your network, detecting threats with the precision of a hunting raptor."

Core Technology Stack

• 🔥 eBPF Kernel Integration: Zero-copy packet processing at wire speed
• ⚡ XDP High-Performance Path: Sub-microsecond latency packet analysis
• 🧠 Machine Learning Engine: Adaptive behavioral anomaly detection
• 🌐 Cross-Platform Compatibility: Universal Unix deployment via containerization

What Makes FlowHawk Special

FlowHawk combines the keen eyesight of a hunting hawk with eBPF's lightning-fast packet processing to deliver unparalleled network security monitoring.

Lightning Speed

• 10M+ packets per second processing capability
• Sub-microsecond latency with XDP (eXpress Data Path)
• Zero-copy packet analysis directly in kernel space

Eagle-Eyed Detection

• Multi-engine threat detection (rule-based + ML)
• Real-time anomaly scoring with adaptive thresholds
• Custom rule engine with flexible pattern matching

Precision Hunting

• Port scan detection (rapid, stealth, horizontal)
• DDoS attack identification (volumetric + amplification)
• Botnet activity tracking (C2 beaconing patterns)
• Data exfiltration monitoring (traffic anomalies)

Quick Start

Prerequisites

• Unix-based Operating System: Linux, macOS, FreeBSD, or other Unix variants
• Containerization: Docker or compatible container runtime
• Go 1.23+ (for source builds)
• eBPF Support: Modern kernel with eBPF capabilities (Linux 4.15+, or containerized deployment)

Hunt Begins

Build FlowHawk

docker build -t flowhawk:latest .

Security Modes

FlowHawk operates in two distinct hunting modes:

🟢 Training Mode (Recommended)

Safe for development and demonstrations

Launch in training mode (safe, simulated data) and access the eyrie (dashboard)

docker run -d \
  --name flowhawk \
  -p 8080:8080 \
  -e SKIP_ROOT_CHECK=1 \
  flowhawk:latest

open http://localhost:8080

Training Mode Features:

• ✅ Safe: No system privileges required
• ✅ Isolated: Cannot affect host system
• ✅ Functional: Complete UI/API testing
• ✅ Realistic: Dynamic simulated data
• ⚠️ Limited: No real network monitoring

---

🔴 Hunt Mode - ⚠️ SECURITY RISKS

🚨 WARNING: Hunt mode enables real eBPF with significant security implications!

Before unleashing the hawk, understand these risks:

1. 🔥 Kernel-Level Access: Direct kernel memory access
   • Risk: System crashes or kernel panics
   • Risk: Access to sensitive kernel data
2. 👁️ Total Network Visibility: Sees ALL host traffic
   • Risk: Exposure to passwords, API keys, private data
   • Risk: Privacy violations and data interception
3. 🔓 Container Escape: Privileged mode = near-root access
   • Risk: Host filesystem access and kernel module loading
   • Risk: Breaking container isolation barriers
4. 💥 Resource Exhaustion: Unlimited consumption potential
   • Risk: Memory exhaustion from BPF map growth
   • Risk: CPU spikes from processing loops

Only unleash hunt mode if:

• You fully understand and accept these security risks
• You have implemented appropriate security mitigations
• You need real network monitoring (not just testing)
• You're running in a controlled, isolated environment

⚠️ SECURITY WARNING: Unleash the hawk responsibly! ⚠️

docker run -d \
  --name flowhawk \
  --privileged \
  --user root \
  -p 8080:8080 \
  flowhawk:latest

Hunt Mode Features:

• ✅ Real Monitoring: Actual network traffic analysis
• ✅ Full eBPF: Complete high-performance capabilities
• ⚠️ High Risk: Significant security implications
• ⚠️ Privileged: Requires root and privileged container

🔐 Security Mitigations

If you must use hunt mode, implement these hawk-training measures:

Minimal Privileges

Use specific capabilities instead of --privileged

docker run -d \
  --name flowhawk \
  --cap-add=BPF \
  --cap-add=NET_ADMIN \
  --cap-add=SYS_ADMIN \
  --cap-drop=ALL \
  --read-only \
  --tmpfs /tmp \
  --device=/dev/bpf \
  -p 8080:8080 \
  flowhawk:latest

Resource Constraints

Limit the hawk's appetite

docker run -d \
  --name flowhawk \
  --memory=512m \
  --cpus=1.0 \
  --pids-limit=100 \
  # ... other security flags

⚙️ Configuration

Basic Hunt Configuration

# Network interface and eBPF settings
ebpf:
  xdp:
    interface: "eth0"
    mode: "native"  # native, skb, hw
    enable: true
  tc:
    direction: "both"  # ingress, egress, both
    enable: true

# Monitoring parameters
monitoring:
  sampling_rate: 1000      # 1 in N packets
  flow_timeout: 300s       # Flow expiration
  max_flows: 1000000       # Memory limit

# Threat detection configuration
threats:
  enable: true
  port_scan:
    enable: true
    threshold: 100         # connections per minute
  ddos:
    enable: true
    pps_threshold: 100000  # packets per second
    bps_threshold: 1000000000  # 1 Gbps

# Alert configuration
alerts:
  enable: true
  webhook_url: "https://hooks.slack.com/..."
  severity_threshold: "medium"

# Dashboard settings
dashboard:
  listen_addr: ":8080"
  enable_auth: false
  retention_days: 7

🎯 Real-World Hunt Examples

Port Scan Detection

# FlowHawk spots scanning patterns instantly:

2024-01-15 10:30:15 THREAT: Port Scan from 192.168.1.100
- Pattern: Rapid scanning (127 ports in 30s)
- Severity: High
- Targets: 192.168.1.10

DDoS Attack Detection

# Volumetric attack spotted:
2024-01-15 11:15:33 THREAT: DDoS Attack targeting 192.168.1.10
- Type: Distributed attack (1.2M PPS from 500 sources)
- Severity: Critical
- Protocol: UDP (DNS amplification)

ML Anomaly Detection

# Behavioral anomaly detected:
2024-01-15 12:20:45 THREAT: ML Anomaly from 10.0.1.25
- Anomaly score: 4.7 (threshold: 2.5)
- Pattern: Unusual packet sizes and timing
- Confidence: 89%

📊 Performance Metrics

Hunt Statistics

• XDP Native Mode: 10M+ PPS on modern hardware
• Memory Usage: <100MB userspace footprint
• CPU Overhead: <5% at 1Gbps sustained traffic
• Latency: <1μs packet processing time

Scalability

• Flow Tracking: 1M+ concurrent flows
• Threat Detection: Real-time analysis up to 10Gbps
• Dashboard: 1000+ concurrent WebSocket connections

🛠️ Development

Developer Setup

FlowHawk includes comprehensive CI/CD workflows and development tools:

Set up development environment (includes git hooks)

make dev-setup

Run tests

make test

Run all tests including integration

make test-all

Run tests with coverage

make test-coverage

Run linting

make lint

Format code

make format

Git Hooks

FlowHawk includes pre-commit hooks that automatically:

• Format Go code with gofmt
• Run go vet for static analysis
• Execute linting with golangci-lint
• Run the full test suite
• Check for common issues (debug statements, large files)

To set up git hooks: Initialize git repository (if not done)

git init

Set up git hooks

./scripts/setup-git-hooks.sh

Or use make target

make dev-setup

CI/CD Workflows

FlowHawk includes GitHub Actions workflows for:

• Continuous Integration (.github/workflows/ci.yml)

  • Multi-version Go testing (1.23+)
  • Linting with golangci-lint
  • Security scanning with Gosec and Trivy
  • Code coverage reporting to Codecov
  • Docker build verification

• Release Management (.github/workflows/release.yml)

  • Automated binary builds for multiple platforms
  • Docker image publishing to GitHub Container Registry
  • GitHub Releases with checksums

• Dependency Management (.github/workflows/dependabot-automerge.yml)

  • Automated dependency updates via Dependabot
  • Auto-merge for minor/patch updates after testing

Testing Strategy

FlowHawk follows a comprehensive testing approach:

• Unit Tests: Located in tests/unit/ with package-specific subdirectories
• Integration Tests: End-to-end testing of major components
• Benchmark Tests: Performance validation for critical paths
• Security Tests: Vulnerability scanning and secure coding validation

Coverage targets:

• Overall: 80%+ statement coverage
• Core packages: 90%+ statement coverage
• Critical security components: 95%+ statement coverage

Building from Source

Prepare the env

go mod download

Build the image

go build -o flowhawk ./cmd/flowhawk

Release the hawk

sudo ./flowhawk -config ./configs/development.yaml

Hunt Commands

Show version

flowhawk -version

Custom interface

flowhawk -interface eth1

Custom config

flowha