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DDoS Mitigation

Thomas Mangin edited this page Nov 10, 2025 · 13 revisions

DDoS Mitigation with ExaBGP

Automated DDoS protection using BGP FlowSpec

🛡️ ExaBGP pioneered open-source FlowSpec - enabling network-wide DDoS mitigation in seconds


Table of Contents


Overview

DDoS mitigation with ExaBGP enables automated, network-wide traffic filtering using BGP FlowSpec.

The Problem

Traditional DDoS response is slow:

  1. ⏱️ Detection: Minutes to identify attack
  2. 🔧 Manual intervention: SSH to routers, configure ACLs
  3. 📝 Error-prone: Manual configuration mistakes
  4. 🐌 Slow deployment: Can't update hundreds of routers quickly
  5. 💰 Damage: Attack causes disruption before mitigation

The ExaBGP Solution

Automated FlowSpec-based mitigation:

  1. Instant detection: Automated systems detect attack patterns
  2. 🤖 Automated response: ExaBGP generates FlowSpec rules via API
  3. 🌐 Network-wide: Rules propagate to all edge routers via BGP
  4. 🚀 Fast: Attack blocked in seconds (not minutes)
  5. Reliable: No manual intervention required

Why FlowSpec for DDoS Mitigation?

Advantages Over Traditional Methods

vs. RTBH (Remote Triggered Black Hole):

  • Granular filtering: Match on ports, protocols, packet size, TCP flags
  • Surgical mitigation: Rate-limit instead of complete blackhole
  • Reduced collateral damage: Single rule vs. thousands of /32 prefixes
  • Flexible actions: Discard, rate-limit, redirect, or mark traffic

vs. On-Premises Scrubbing:

  • Upstream filtering: Traffic blocked at provider edge (before reaching your network)
  • Bandwidth savings: Attack traffic never consumes your bandwidth
  • Scalability: Leverage provider infrastructure
  • Fast convergence: BGP propagation in seconds

vs. Cloud Scrubbing Services:

  • No third-party dependency: On-premises control
  • Lower cost: No per-GB scrubbing fees
  • Lower latency: No traffic redirection
  • Privacy: Traffic stays in your network

Architecture Patterns

Pattern 1: Centralized FlowSpec Controller

Most common deployment:

┌─────────────────────┐
│  DDoS Detection     │  FastNetMon, custom detection
│  System             │
└──────────┬──────────┘
           │ Attack detected
           ▼
┌─────────────────────┐
│  ExaBGP             │  FlowSpec controller
│  (Central)          │  Generates rules via API
└──────────┬──────────┘
           │ BGP FlowSpec UPDATE
           ▼
┌─────────────────────┐
│  Edge Routers       │  Cisco, Juniper, Arista, etc.
│  (100s-1000s)       │  Apply filters in hardware
└──────────┬──────────┘
           │ Filtered traffic
           ▼
     Attack blocked ✅

Characteristics:

  • Single ExaBGP instance as FlowSpec controller
  • Peers with route reflectors or edge routers
  • Rules propagate network-wide via BGP
  • Centralized logging and management

Pattern 2: Distributed FlowSpec with Route Reflectors

For large-scale networks:

┌────────────────┐         ┌────────────────┐
│ ExaBGP         │◄───────►│ Route          │
│ FlowSpec       │   iBGP  │ Reflectors     │
│ Controller     │         │                │
└────────────────┘         └────────┬───────┘
                                    │
                    ┌───────────────┼───────────────┐
                    ▼               ▼               ▼
            ┌──────────────┐ ┌──────────────┐ ┌──────────────┐
            │ Edge Router  │ │ Edge Router  │ │ Edge Router  │
            │ (Region A)   │ │ (Region B)   │ │ (Region C)   │
            └──────────────┘ └──────────────┘ └──────────────┘

Benefits:

  • Scalable to thousands of edge routers
  • Reduced BGP session overhead
  • Regional route reflectors for redundancy
  • Standard BGP topology

Pattern 3: Hybrid (FlowSpec + Scrubbing)

Combine FlowSpec with scrubbing centers:

┌─────────────────┐
│ Detection       │
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│ ExaBGP          │
│ Decision Logic  │
└────────┬────────┘
         │
    ┌────┴──────────┐
    ▼               ▼
Small Attack    Large Attack
(< 1 Gbps)     (> 1 Gbps)
    │               │
    ▼               ▼
FlowSpec        FlowSpec
discard         redirect to VRF
                    │
                    ▼
             ┌──────────────┐
             │ Scrubbing    │
             │ Center       │
             └──────┬───────┘
                    │
                    ▼
             Clean traffic back

Use cases:

  • Small attacks: Block at edge with FlowSpec
  • Large volumetric attacks: Redirect to scrubbing
  • Graduated response based on attack size

Detection Integration

ExaBGP can integrate with various DDoS detection systems:

Open-Source Options:

  • FastNetMon - High-performance DDoS detection (native ExaBGP support)
  • Custom detection - Build your own using flow analysis tools

Flow Analysis Tools (for custom detection):

  • Akvorado - Flow collector and visualizer (can feed custom detection logic)
  • pmacct - Flow accounting and analysis
  • nfdump/nfsen - NetFlow analysis toolkit

Option 1: FastNetMon

FastNetMon is an open-source DDoS detection system with native ExaBGP integration.

Architecture

FastNetMon → sFlow/NetFlow → Analysis → ExaBGP API → FlowSpec

Configuration

FastNetMon config (/etc/fastnetmon.conf):

# Enable ExaBGP integration
enable_ban_for_tcp_syn_flood = on
enable_ban_for_udp_flood = on
enable_ban_for_icmp_flood = on

# ExaBGP FlowSpec
exabgp = on
exabgp_flow_spec_announces = on
exabgp_command_pipe = /var/run/exabgp.cmd

# Thresholds
ban_for_pps = on
threshold_pps = 20000
ban_for_bandwidth = on
threshold_mbps = 1000

ExaBGP config (/etc/exabgp/exabgp.conf):

neighbor 192.168.1.1 {
    router-id 192.168.1.2;
    local-address 192.168.1.2;
    local-as 65001;
    peer-as 65000;

    family {
        ipv4 flowspec;
    }

    api {
        processes [ fastnetmon ];
    }
}

process fastnetmon {
    run /etc/exabgp/api/fastnetmon.py;
    encoder text;
}

Integration script (/etc/exabgp/api/fastnetmon.py):

#!/usr/bin/env python3
"""
FastNetMon integration for ExaBGP FlowSpec
Reads attack notifications and generates FlowSpec rules
"""
import sys
import time
import os

# Named pipe from FastNetMon
PIPE_PATH = "/var/run/exabgp.cmd"

def read_fastnetmon_commands():
    """Read FlowSpec commands from FastNetMon pipe"""
    if not os.path.exists(PIPE_PATH):
        os.mkfifo(PIPE_PATH)

    while True:
        with open(PIPE_PATH, 'r') as pipe:
            for line in pipe:
                command = line.strip()
                if command:
                    # Forward to ExaBGP
                    sys.stdout.write(command + "\n")
                    sys.stdout.flush()
                    sys.stderr.write(f"[FASTNETMON] {command}\n")

time.sleep(2)
read_fastnetmon_commands()

Option 2: Custom Detection

Build your own detection system:

#!/usr/bin/env python3
"""
Custom DDoS detection and mitigation
Analyzes traffic patterns and generates FlowSpec rules
"""
import sys
import time
import collections
from datetime import datetime

# Attack detection state
traffic_stats = collections.defaultdict(lambda: {'pps': 0, 'bps': 0})
blocked_sources = set()

# Thresholds
SYN_FLOOD_THRESHOLD = 10000  # SYN packets per second
UDP_FLOOD_THRESHOLD = 50000  # UDP packets per second
BANDWIDTH_THRESHOLD = 1000000000  # 1 Gbps

def analyze_traffic():
    """
    Analyze traffic patterns (placeholder - integrate with your monitoring)
    Returns: list of detected attacks
    """
    # TODO: Integrate with your traffic analysis system
    # Examples: sFlow collector, SNMP polling, pcap analysis

    attacks = []

    for source_ip, stats in traffic_stats.items():
        # SYN flood detection
        if stats['syn_pps'] > SYN_FLOOD_THRESHOLD:
            attacks.append({
                'type': 'syn_flood',
                'source': source_ip,
                'metric': stats['syn_pps'],
                'dest_port': stats.get('dest_port', 80)
            })

        # UDP flood detection
        if stats['udp_pps'] > UDP_FLOOD_THRESHOLD:
            attacks.append({
                'type': 'udp_flood',
                'source': source_ip,
                'metric': stats['udp_pps']
            })

        # Bandwidth-based detection
        if stats['bps'] > BANDWIDTH_THRESHOLD:
            attacks.append({
                'type': 'bandwidth_flood',
                'source': source_ip,
                'metric': stats['bps']
            })

    return attacks

def mitigate_attack(attack):
    """Generate and announce FlowSpec rule"""
    attack_type = attack['type']
    source = attack['source']

    if source in blocked_sources:
        return  # Already blocked

    if attack_type == 'syn_flood':
        dest_port = attack.get('dest_port', 80)
        rule = (
            f"announce flow route {{ "
            f"match {{ source {source}/32; destination-port ={dest_port}; "
            f"protocol =tcp; tcp-flags [ syn ]; }} "
            f"then {{ rate-limit 10000000; }} "
            f"}}"
        )

    elif attack_type == 'udp_flood':
        rule = (
            f"announce flow route {{ "
            f"match {{ source {source}/32; protocol =udp; }} "
            f"then {{ rate-limit 5000000; }} "
            f"}}"
        )

    elif attack_type == 'bandwidth_flood':
        rule = (
            f"announce flow route {{ "
            f"match {{ source {source}/32; }} "
            f"then {{ rate-limit 1000000; }} "
            f"}}"
        )

    else:
        rule = (
            f"announce flow route {{ "
            f"match {{ source {source}/32; }} "
            f"then {{ discard; }} "
            f"}}"
        )

    sys.stdout.write(rule + "\n")
    sys.stdout.flush()

    blocked_sources.add(source)

    timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
    sys.stderr.write(
        f"[{timestamp}] Blocked {attack_type} from {source} "
        f"(metric: {attack['metric']})\n"
    )

    # Schedule auto-withdrawal after 300 seconds
    schedule_withdrawal(rule, 300)

def schedule_withdrawal(rule, timeout):
    """Auto-withdraw rule after timeout"""
    import threading

    def withdraw_after_timeout():
        time.sleep(timeout)
        withdraw = rule.replace('announce', 'withdraw')
        # Remove 'then' clause for withdrawal
        withdraw = withdraw.split('then')[0].rstrip() + '}'
        sys.stdout.write(withdraw + "\n")
        sys.stdout.flush()
        sys.stderr.write(f"[AUTO-WITHDRAW] {withdraw}\n")

    thread = threading.Thread(target=withdraw_after_timeout, daemon=True)
    thread.start()

# Main detection loop
time.sleep(2)

sys.stderr.write("[DETECTION] Custom DDoS detection started\n")

while True:
    attacks = analyze_traffic()

    for attack in attacks:
        mitigate_attack(attack)

    time.sleep(5)  # Check every 5 seconds

Complete Workflow

End-to-End DDoS Mitigation

Step 1: Detection

Attack traffic → Edge routers → NetFlow/sFlow → Detection system

Detection triggers when:

  • Packets per second > threshold
  • Bandwidth > threshold
  • Anomaly detected by ML model
  • Specific attack patterns identified

Step 2: Rule Generation

# Detection system generates FlowSpec rule
rule = (
    "announce flow route { "
    "match { source 203.0.113.0/24; destination-port =80; protocol =tcp; } "
    "then { discard; } "
    "}"
)

Step 3: ExaBGP Announcement

# Send to ExaBGP via API
sys.stdout.write(rule + "\n")
sys.stdout.flush()

Step 4: BGP Propagation

ExaBGP → BGP UPDATE (FlowSpec) → Route Reflectors → Edge Routers

Convergence time: 1-5 seconds network-wide


Step 5: Traffic Filtering

Edge routers install FlowSpec rule in hardware (TCAM)
→ Matching traffic dropped/rate-limited at wire speed
→ Attack blocked ✅

Step 6: Auto-Withdrawal

# After attack ends (e.g., 5 minutes)
time.sleep(300)
withdraw = "withdraw flow route { match { source 203.0.113.0/24; ... } }"
sys.stdout.write(withdraw + "\n")
sys.stdout.flush()

Attack Types and Mitigation

1. SYN Flood

Attack: TCP SYN packets without completing handshake

Detection:

  • High SYN rate to specific port
  • SYN packets without corresponding ACK

Mitigation:

announce flow route {
    match {
        destination 100.10.0.100/32;  # Target server
        destination-port =80|=443;     # HTTP/HTTPS
        protocol =tcp;
        tcp-flags [ syn ];             # SYN flag only
    }
    then {
        rate-limit 10000000;           # 10 Mbps
    }
}

2. UDP Amplification

Attack: Spoofed UDP requests to amplification servers (DNS, NTP, SSDP, etc.)

Detection:

  • Large UDP responses (> 512 bytes)
  • High volume from specific source ports (53, 123, 1900)

Mitigation:

# DNS amplification
announce flow route {
    match {
        source-port =53;               # DNS responses
        protocol =udp;
        packet-length >512;            # Large responses
    }
    then {
        discard;
    }
}

# NTP amplification
announce flow route {
    match {
        source-port =123;              # NTP responses
        protocol =udp;
        packet-length >100;
    }
    then {
        discard;
    }
}

# SSDP amplification
announce flow route {
    match {
        source-port =1900;             # SSDP
        protocol =udp;
    }
    then {
        discard;
    }
}

3. HTTP Flood

Attack: High volume of HTTP requests

Detection:

  • High connection rate to web servers
  • Unusual HTTP request patterns

Mitigation:

# Rate-limit HTTP traffic from attack source
announce flow route {
    match {
        source 10.0.0.0/8;             # Attack network
        destination-port =80|=443;
        protocol =tcp;
    }
    then {
        rate-limit 5000000;            # 5 Mbps per source
    }
}

4. ICMP Flood

Attack: High volume of ICMP packets (ping flood, smurf attack)

Detection:

  • High ICMP packet rate
  • Large ICMP packet sizes

Mitigation:

# Block all ICMP during attack
announce flow route {
    match {
        protocol =icmp;
    }
    then {
        discard;
    }
}

# Or rate-limit ICMP
announce flow route {
    match {
        protocol =icmp;
        icmp-type =8;                  # Echo request
    }
    then {
        rate-limit 1000000;            # 1 Mbps
    }
}

5. Fragmentation Attack

Attack: Malformed or excessive fragmented packets

Detection:

  • High rate of fragmented packets
  • Invalid fragment patterns

Mitigation:

# Block all fragmented packets
announce flow route {
    match {
        fragment [ is-fragment ];
    }
    then {
        discard;
    }
}

6. Volumetric Attack

Attack: High bandwidth consumption (> line capacity)

Detection:

  • Total bandwidth exceeds threshold
  • Traffic from specific sources/networks

Mitigation:

# Aggressive rate-limiting for attack sources
announce flow route {
    match {
        source 203.0.113.0/24;
    }
    then {
        rate-limit 1000000;            # 1 Mbps total
    }
}

# Or redirect to scrubbing VRF
announce flow route {
    match {
        destination 100.10.0.0/24;     # Attacked network
    }
    then {
        redirect 65001:999;            # Scrubbing VRF
    }
}

Implementation Guide

Step 1: Install ExaBGP

# Using pip
pip3 install exabgp

# Verify installation
exabgp --version

See Installation Guide for details.


Step 2: Configure ExaBGP

Create config (/etc/exabgp/ddos-mitigation.conf):

neighbor 192.168.1.1 {
    router-id 192.168.1.2;
    local-address 192.168.1.2;
    local-as 65001;
    peer-as 65000;

    family {
        ipv4 flowspec;
    }

    api {
        processes [ ddos-controller ];
    }
}

process ddos-controller {
    run /etc/exabgp/api/ddos_controller.py;
    encoder text;
}

Step 3: Create Detection Script

Basic template (/etc/exabgp/api/ddos_controller.py):

#!/usr/bin/env python3
import sys
import time

time.sleep(2)
sys.stderr.write("[DDOS] Controller started\n")

# Your detection logic here
# When attack detected, generate FlowSpec rule:

def block_attack(source_ip, attack_type):
    rule = (
        f"announce flow route {{ "
        f"match {{ source {source_ip}/32; }} "
        f"then {{ discard; }} "
        f"}}"
    )
    sys.stdout.write(rule + "\n")
    sys.stdout.flush()
    sys.stderr.write(f"[DDOS] Blocked {attack_type} from {source_ip}\n")

# Main loop
while True:
    # TODO: Integrate with your detection system
    time.sleep(10)

Step 4: Configure Edge Routers

Cisco IOS-XR:

router bgp 65000
 neighbor 192.168.1.2 remote-as 65001
 !
 address-family ipv4 flowspec
  neighbor 192.168.1.2 activate
 !
!
flowspec
 local-install interface-all
!

Juniper Junos:

protocols {
    bgp {
        group exabgp {
            type external;
            peer-as 65001;
            neighbor 192.168.1.2 {
                family inet {
                    flow;
                }
            }
        }
    }
}

routing-options {
    flow {
        validation {
            local {
                enabled;
            }
        }
    }
}

Step 5: Test FlowSpec Rules

Manual test:

# Start ExaBGP
exabgp /etc/exabgp/ddos-mitigation.conf

# In another terminal, inject test rule
echo "announce flow route { match { source 10.0.0.1/32; } then { discard; } }" > /tmp/exabgp.cmd

Verify on router:

# Cisco
show flowspec ipv4 summary
show flowspec ipv4 detail

# Juniper
show firewall filter __flowspec_default_inet__

Production Deployment

High Availability

Deploy redundant ExaBGP instances:

┌────────────────┐         ┌────────────────┐
│ ExaBGP         │         │ ExaBGP         │
│ Primary        │         │ Secondary      │
│ 192.168.1.2    │         │ 192.168.1.3    │
└────────┬───────┘         └───────┬────────┘
         │                         │
         └────────────┬────────────┘
                      │
                      ▼
              ┌───────────────┐
              │ Route         │
              │ Reflectors    │
              └───────────────┘

Both instances:

  • Run same detection logic
  • Announce same FlowSpec rules
  • BGP handles deduplication

Logging and Auditing

Log all FlowSpec announcements:

import logging

logging.basicConfig(
    filename='/var/log/exabgp-ddos.log',
    level=logging.INFO,
    format='%(asctime)s [%(levelname)s] %(message)s'
)

def announce_flowspec(rule, reason):
    sys.stdout.write(rule + "\n")
    sys.stdout.flush()
    logging.info(f"ANNOUNCE: {rule} - Reason: {reason}")

Alerting Integration

Send alerts to NOC:

import requests

def send_alert(message, severity='high'):
    """Send alert to Slack/PagerDuty/email"""
    # Slack webhook
    requests.post(
        "https://hooks.slack.com/services/YOUR/WEBHOOK/URL",
        json={
            "text": f":warning: DDoS Alert: {message}",
            "username": "ExaBGP DDoS Controller"
        }
    )

    # PagerDuty
    requests.post(
        "https://events.pagerduty.com/v2/enqueue",
        json={
            "routing_key": "YOUR_ROUTING_KEY",
            "event_action": "trigger",
            "payload": {
                "summary": message,
                "severity": severity,
                "source": "ExaBGP"
            }
        }
    )

# When blocking attack
send_alert(f"Blocking SYN flood from {source_ip} to port {port}")

Monitoring and Alerting

Metrics to Track

1. Attack Metrics:

  • Number of active FlowSpec rules
  • Attacks detected per hour
  • Attack types distribution
  • Top attack sources

2. Mitigation Metrics:

  • Time to mitigation (detection → blocking)
  • Bandwidth saved
  • False positive rate
  • Rule withdrawal time

3. System Metrics:

  • ExaBGP process health
  • BGP session state
  • API response time
  • Rule announcement latency

Monitoring Script

#!/usr/bin/env python3
"""
Monitor ExaBGP DDoS mitigation metrics
"""
import time
import subprocess
import requests

# Metrics
active_rules = 0
attacks_detected = 0
attacks_blocked = 0

def check_exabgp_health():
    """Check if ExaBGP process is running"""
    try:
        result = subprocess.run(
            ['pgrep', '-f', 'exabgp'],
            capture_output=True,
            timeout=5
        )
        return result.returncode == 0
    except:
        return False

def check_bgp_session():
    """Check BGP session state (example for Cisco via SNMP)"""
    # TODO: Implement SNMP check or router API
    pass

def export_metrics_to_prometheus():
    """Export metrics to Prometheus"""
    # Expose metrics endpoint
    metrics = f"""
# HELP exabgp_ddos_active_rules Number of active FlowSpec rules
# TYPE exabgp_ddos_active_rules gauge
exabgp_ddos_active_rules {active_rules}

# HELP exabgp_ddos_attacks_detected Total attacks detected
# TYPE exabgp_ddos_attacks_detected counter
exabgp_ddos_attacks_detected {attacks_detected}

# HELP exabgp_ddos_attacks_blocked Total attacks blocked
# TYPE exabgp_ddos_attacks_blocked counter
exabgp_ddos_attacks_blocked {attacks_blocked}
"""
    # Write to textfile collector or push to Pushgateway
    with open('/var/lib/prometheus/node-exporter/exabgp_ddos.prom', 'w') as f:
        f.write(metrics)

while True:
    if not check_exabgp_health():
        send_alert("ExaBGP process not running!", severity='critical')

    export_metrics_to_prometheus()
    time.sleep(60)

Best Practices

1. Graduated Response

Start conservative, escalate if needed:

# Level 1: Rate-limit (warning)
rate_limit_1 = 50000000  # 50 Mbps

# Level 2: Tighter rate-limit
rate_limit_2 = 10000000  # 10 Mbps

# Level 3: Very tight rate-limit
rate_limit_3 = 1000000   # 1 Mbps

# Level 4: Block completely
# discard

2. Whitelist Critical Services

Never block critical infrastructure:

WHITELIST = [
    '8.8.8.8',      # Google DNS
    '1.1.1.1',      # Cloudflare DNS
    # Add your critical IPs
]

def should_block(ip):
    return ip not in WHITELIST

3. Auto-Expiration

Always set TTL on rules:

def announce_with_ttl(rule, ttl=300):
    """Announce rule with auto-withdrawal"""
    sys.stdout.write(rule + "\n")
    sys.stdout.flush()

    # Schedule withdrawal
    threading.Timer(ttl, withdraw_rule, args=[rule]).start()

4. Rate-Limit Before Blocking

Try rate-limiting first:

if attack_severity < 5:
    action = f"rate-limit {bandwidth}"
else:
    action = "discard"

5. Validate Rules Before Announcement

Prevent misconfigurations:

def validate_flowspec_rule(rule):
    """Validate FlowSpec syntax"""
    required_keywords = ['announce', 'flow', 'route', 'match', 'then']

    for keyword in required_keywords:
        if keyword not in rule:
            raise ValueError(f"Missing keyword: {keyword}")

    # Additional validation
    if 'source 0.0.0.0/0' in rule and 'discard' in rule:
        raise ValueError("Refusing to blackhole entire internet!")

    return True

Troubleshooting

Issue 1: Rules Not Applied on Routers

Symptoms: FlowSpec rules announced but not filtering traffic

Diagnosis:

# Cisco
show flowspec ipv4
show flowspec ipv4 summary

# Juniper
show firewall filter __flowspec_default_inet__

Common causes:

  • FlowSpec not enabled on router
  • BGP session down
  • FlowSpec validation failing
  • Hardware limitations (TCAM full)

Solutions:

# Enable FlowSpec
router bgp 65000
 address-family ipv4 flowspec
  neighbor 192.168.1.2 activate

# Enable local installation
flowspec
 local-install interface-all

Issue 2: ExaBGP Not Announcing Rules

Symptoms: No BGP UPDATEs sent

Diagnosis:

# Check ExaBGP logs
exabgp -d /etc/exabgp/ddos.conf 2>&1 | tee exabgp.log

# Look for errors
grep ERROR exabgp.log

Common causes:

  • API process not running
  • Syntax error in FlowSpec rule
  • stdout not flushed

Solutions:

# Always flush stdout
sys.stdout.write(rule + "\n")
sys.stdout.flush()  # Critical!

# Check process is running
ps aux | grep ddos_controller

Issue 3: False Positives

Symptoms: Legitimate traffic blocked

Diagnosis:

  • Monitor user complaints
  • Analyze blocked traffic patterns
  • Review FlowSpec match conditions

Solutions:

  • Make rules more specific
  • Use rate-limiting instead of discard
  • Implement whitelisting
  • Adjust detection thresholds

Issue 4: High Latency

Symptoms: Slow rule propagation (> 10 seconds)

Diagnosis:

# Measure BGP convergence time
time exabgp announce-rule.py

# Check BGP timers
show bgp neighbor 192.168.1.2

Solutions:

  • Reduce BGP timers (keepalive, hold-time)
  • Use route reflectors for scalability
  • Optimize detection script performance

Real-World Examples

Example 1: ISP DDoS Mitigation

Scenario: Regional ISP with 100 edge routers

Architecture:

  • Central ExaBGP FlowSpec controller
  • FastNetMon for detection (analyzing sFlow)
  • Route reflectors for BGP scalability

Results:

  • Detection to mitigation: 3 seconds average
  • 50+ attacks blocked per day
  • 99.9% uptime maintained
  • Bandwidth savings: ~500 Gbps/month

Example 2: Enterprise Network Protection

Scenario: Enterprise with multiple data centers

Architecture:

  • ExaBGP + custom Python detection
  • Integration with SIEM (Splunk)
  • Hybrid approach (FlowSpec + cloud scrubbing)

Attack handling:

  • Small attacks (< 1 Gbps): FlowSpec at edge
  • Large attacks (> 1 Gbps): Redirect to cloud scrubbing
  • Auto-escalation based on attack size

Results:

  • 95% of attacks handled at edge
  • Scrubbing costs reduced by 70%
  • No service outages in 12 months

Example 3: Hosting Provider

Scenario: Hosting provider protecting customer VMs

Architecture:

  • ExaBGP per customer (multi-tenant)
  • Custom detection with sFlow/NetFlow analysis
  • Per-customer FlowSpec rules

Features:

  • Customer portal for rule visibility
  • Automatic protection for all customers
  • Granular per-VM filtering

Results:

  • 1000+ customers protected
  • Sub-second mitigation
  • Customer satisfaction: 98%

Next Steps

Learn More

API Documentation

Operations


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👻 Ghost written by Claude (Anthropic AI)

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