What is a bot? Types of bots and their cybersecurity impact

According to recent research, bots now generate over 40% of all internet traffic. Some are helpful assistants indexing pages for search engines. Others are malicious programs stealing data, conducting DDoS attacks, or spreading disinformation. Understanding the difference between them is fundamental to effective online protection.

What is a Bot?

Definition

A bot (short for “robot”) is a computer program that performs automated tasks on the internet. Bots work much faster than humans and can operate 24/7 without breaks, executing repetitive operations at massive scale.

Bot Characteristics

Common characteristics of all bots:
├── Automation - operate without human intervention
├── Speed - execute thousands of operations per second
├── Scalability - can run on many machines
├── Programmability - execute defined tasks
└── Persistence - operate continuously, 24/7

📚 Read the complete guide: Cloud Security / AWS: Bezpieczeństwo chmury publicznej - AWS, Azure, best practices

Good Bots (Legitimate Bots)

Search Engine Bots (Web Crawlers)

The most well-known and useful internet bots:

Bot	Owner	Purpose
Googlebot	Google	Indexing pages for Google Search
Bingbot	Microsoft	Indexing for Bing
Yandexbot	Yandex	Indexing for Yandex
Baiduspider	Baidu	Indexing for Baidu
DuckDuckBot	DuckDuckGo	Indexing for DuckDuckGo

How they work:

Fetch the homepage
Analyze links on the page
Follow links to subsequent pages
Index content in search engine databases
Repeat the process cyclically

Monitoring Bots

Check service availability and performance:

Uptime monitoring - Pingdom, UptimeRobot
Performance monitoring - GTmetrix, PageSpeed
Security scanning - Qualys, Nessus
SEO crawlers - Screaming Frog, Ahrefs

Chatbots and Assistants

Communication automation with users:

Customer service chatbots - answer FAQs
Voice assistants - Siri, Alexa, Google Assistant
Messenger bots - Slack bots, Telegram bots

Aggregator Bots

Collect data from various sources:

Price comparison sites - PriceGrabber, Google Shopping
News aggregators - Google News, Feedly
Job aggregators - Indeed, LinkedIn

Malicious Bots

Botnets

A botnet is a network of infected computers controlled by an attacker:

Botnet architecture:
                    ┌─────────────┐
                    │   C&C       │  ← Command & Control Server
                    │   Server    │
                    └──────┬──────┘
                           │
         ┌─────────────────┼─────────────────┐
         │                 │                 │
    ┌────▼────┐       ┌────▼────┐       ┌────▼────┐
    │   Bot   │       │   Bot   │       │   Bot   │
    │  Zombie │       │  Zombie │       │  Zombie │
    └─────────┘       └─────────┘       └─────────┘
         │                 │                 │
    Infected          Infected          Infected
    computer          computer          computer

Known botnets:

Botnet	Peak Activity	Size	Main Activities
Mirai	2016	600,000 IoT	DDoS on Dyn DNS
Emotet	2014-2021	Millions	Malware, spam
TrickBot	2016-2022	Hundreds of thousands	Credential theft
Necurs	2012-2020	9 million	Spam, ransomware

DDoS Bots

Conduct denial of service attacks:

Attack types:

Volumetric - bandwidth flooding (UDP flood)
Protocol - exploiting protocol weaknesses (SYN flood)
Application - application layer attacks (HTTP flood)

Attack scale:

Record DDoS attacks:
├── 2024: 5.6 Tbps (Cloudflare)
├── 2023: 3.47 Tbps (Microsoft)
├── 2022: 2.5 Tbps (Cloudflare)
└── 2020: 2.3 Tbps (AWS)

Credential Stuffing Bots

Automated testing of stolen logins and passwords:

Credential stuffing process:
1. Attacker buys login database from breach (e.g., 1M records)
2. Bot tests each combination on various services
3. With password reuse - success in 0.1-2% of cases
4. Compromised accounts are sold or exploited

Problem scale:

193 billion credential stuffing attempts in 2020
Average account takeover cost: $150
80% of breaches use stolen passwords

Web Scraping Bots

Malicious data collection from websites:

Price scraping - copying competitor prices
Content scraping - content theft
Data harvesting - collecting personal data

Click Fraud Bots

Advertising fraud:

Fake clicks on PPC ads
Bot ad impressions
Advertiser losses: $100 billion annually (estimated)

Spam and Disinformation Bots

Automated content distribution:

Email spam - 85% of emails are spam
Comment spam - spam in comments
Social bots - fake social media accounts
Disinformation - spreading fake news

How Bots Infect Devices

Infection Vectors

Phishing - malicious attachments and links
Drive-by download - automatic download from infected sites
Exploits - vulnerability exploitation
Social engineering - user manipulation
Malvertising - malicious advertisements
IoT default credentials - default device passwords

Vulnerable Devices

Device	Risk	Reason
Home routers	High	Rarely updated
IP cameras	High	Default passwords
Smart TVs	Medium	Lack of updates
Smartwatches	Medium	Limited security
Network printers	Medium	Ignored by IT
Smart bulbs	Low-Medium	No security

Bot Detection

Bot Traffic Indicators

Traffic anomalies:

Sudden request spike
Traffic at unusual hours
Repeating request patterns
High bounce rate
Short session time

Technical indicators:

No cookies/JavaScript
Suspicious User-Agents
Unusual HTTP headers
Request rate
Sequential IPs or from cloud providers

Detection Techniques

1. CAPTCHA and reCAPTCHA

Traditional CAPTCHA → Broken by AI
reCAPTCHA v2 → Checkbox + challenge
reCAPTCHA v3 → Behavioral analysis (no interaction)
hCaptcha → Privacy-focused alternative

2. Device Fingerprinting

Screen resolution
Installed fonts
Browser plugins
Canvas fingerprint
WebGL fingerprint

3. Behavioral Analysis

Mouse movements
Click patterns
Typing speed
Page scrolling

4. Rate Limiting

# Example nginx rate limiting
limit_req_zone $binary_remote_addr zone=api:10m rate=10r/s;

location /api/ {
    limit_req zone=api burst=20 nodelay;
}

Bot Protection Tools

Solution	Type	Use Case
Cloudflare Bot Management	Cloud	Comprehensive protection
Akamai Bot Manager	Cloud	Enterprise
Imperva	Cloud/On-prem	WAF + bot protection
DataDome	Cloud	Real-time detection
PerimeterX	Cloud	Behavioral analysis

Protection Against Malicious Bots

Multi-Layer Strategy

┌─────────────────────────────────────────────┐
│         LAYER 1: EDGE (CDN/WAF)             │
│  Rate limiting, geoblocking, reputation     │
├─────────────────────────────────────────────┤
│         LAYER 2: APPLICATION                │
│  CAPTCHA, fingerprinting, challenges        │
├─────────────────────────────────────────────┤
│         LAYER 3: BEHAVIORAL                 │
│  Pattern analysis, ML detection             │
├─────────────────────────────────────────────┤
│         LAYER 4: BUSINESS LOGIC             │
│  Transaction limits, verification           │
└─────────────────────────────────────────────┘

robots.txt Configuration

Controlling good bots:

# Allow all bots
User-agent: *
Allow: /

# Block specific bot
User-agent: BadBot
Disallow: /

# Limit crawl rate
User-agent: Googlebot
Crawl-delay: 10

Note: robots.txt won’t stop malicious bots - it’s only a suggestion for good bots.

Best Practices

For websites:

Deploy WAF with bot protection
Use CAPTCHA strategically (not everywhere)
Implement rate limiting
Monitor logs for anomalies
Update software

For users:

Use unique passwords (password manager)
Enable MFA wherever possible
Update IoT devices
Don’t click suspicious links
Install only trusted software

For organizations:

Inventory IoT devices
Segment network
Monitor outbound traffic
Educate employees
Plan response to botnet incidents

Future of Bots

Trends

AI-powered bots:

Bots using GPT for content generation
Advanced chatbots indistinguishable from humans
Automatic CAPTCHA bypassing by AI

Bots in IoT:

Growing number of vulnerable devices
Botnets using 5G
Attacks on smart cities

Regulations:

Bot Disclosure Laws (California)
Digital Services Act (EU)
Transparency requirements

Arms Race

Attackers: New detection bypass techniques
     ↓
Defenders: Better ML algorithms
     ↓
Attackers: Adversarial ML attacks
     ↓
Defenders: Behavioral biometrics
     ↓
Attackers: Realistic bot behavior
     ↓
... cycle continues

Bots in 2025-2026 — Latest Trends

AI-Powered Bots

2025 brought a fundamental shift in the bot landscape. Generative AI (LLMs) combined with automation created a new generation of threats:

Next-generation conversational bots:

Malicious chatbots leveraging GPT-4 and Claude to conduct realistic phishing conversations
Deepfake bots generating real-time video and audio during calls
Social engineering bots capable of multi-stage victim manipulation

AI-powered credential attacks:

Bots combining credential stuffing with victim profiling based on social media data
Automated generation of personalized phishing messages at massive scale
Adaptive bots bypassing CAPTCHA using vision models

Software supply chain bots:

Automated creation of malicious npm/PyPI packages mimicking popular libraries (typosquatting)
Bots generating fake pull requests with backdoors in open-source projects
Supply chain bots targeting CI/CD pipelines

Enterprise Chatbots — A New Attack Surface

Organizations are deploying AI chatbots en masse for customer service, sales, and IT support. This creates new attack vectors:

Prompt injection — attackers manipulate enterprise chatbots to reveal internal data
Data exfiltration — bots with access to customer databases become attack targets
Impersonation — fake chatbots impersonating official company channels

Securing chatbots requires: input validation, LLM sandboxing, interaction monitoring, and data access restrictions (principle of least privilege).

IoT Bots and 5G Botnets

By the end of 2026, there will be over 18 billion IoT devices worldwide. 5G networks provide them with low latency and high bandwidth — ideal conditions for next-generation botnets:

Botnets leveraging edge computing devices — cameras, industrial sensors, IoT gateways
DDoS attacks exceeding 10 Tbps — through aggregation of thousands of 5G-connected devices
Bots targeting smart cities — transportation systems, lighting, energy management
Botnets in OT (Operational Technology) — threats to industrial SCADA and ICS systems

Regulations and Compliance

Legal frameworks around bots are tightening:

EU AI Act (2025) — mandatory labeling of AI bot interactions, risk classification of AI systems
Digital Services Act — platform liability for malicious bot activity
NIS2 Directive — requirements to report botnet-related incidents within 24 hours
Bot Disclosure Laws (California) — obligation to disclose that a user is interacting with a bot

How nFlo Protects Against Malicious Bots

Bot protection demands a multi-layered approach combining technology, processes, and people. nFlo delivers comprehensive solutions tailored to the scale and specifics of the threat landscape:

SOC 24/7 — Continuous Bot Activity Monitoring

nFlo’s Security Operations Center monitors network traffic 24/7/365, detecting:

Anomalies indicating botnet activity (unusual outbound traffic, beaconing to C&C servers)
Credential stuffing and brute force attempts
DDoS patterns and volumetric bot attacks
Communication with known C&C servers (threat intelligence feeds)

nFlo SOC response time to detected threats is under 15 minutes.

Managed EDR/XDR — Endpoint Protection Against Bots

EDR/XDR solutions managed by nFlo detect and block infection attempts by botnet-forming malware:

Behavioral detection — identifying processes attempting to establish C&C connections
Automatic isolation of infected endpoints
Forensic analysis to determine the infection vector and scope of compromise
Threat hunting — proactive search for bot activity indicators across the infrastructure

Firewall Deployment — Blocking Bot Traffic at the Network Edge

Next-Generation Firewalls (NGFW) deployed by nFlo provide:

Bot traffic filtering based on IP reputation, geolocation, and behavioral signatures
SSL/TLS inspection enabling analysis of encrypted bot traffic
Application control blocking C&C protocol communications
Integration with real-time threat intelligence feeds

Summary

Bots are an integral part of the internet - both useful and malicious ones. Effective protection requires:

Understanding - distinguishing good bots from bad
Multi-layering - different detection and protection methods
Adaptation - continuous adjustment to new threats
Monitoring - constant observation of traffic and anomalies

In an era when bots account for nearly half of internet traffic, ignoring this threat is asking for trouble. Proper bot traffic management is a balance between blocking malicious actors and allowing those who help with visibility and online business functioning.

Need help protecting against malicious bots? Contact us - nFlo will implement effective bot management solutions for your organization. Over 500 completed projects, 200+ clients, and response time under 15 minutes.

Frequently Asked Questions

What is an internet bot?

An internet bot is a computer program that performs automated tasks online. It can be a beneficial search engine crawler (e.g., Googlebot indexing pages for search results), a customer service chatbot, or a malicious program conducting DDoS attacks, credential stuffing, or data scraping. Bots generate over 40% of all internet traffic — identifying and managing them is a critical component of every organization’s cybersecurity strategy.

What are the most dangerous types of malicious bots?

The most dangerous categories of malicious bots include:

DDoS bots — flood servers with network traffic; modern attacks reach 5.6 Tbps
Credential stuffing bots — automatically test stolen login credentials across multiple services (193 billion attempts annually)
Web scraping bots — steal content, pricing data, and personal information from websites
Click fraud bots — generate fake ad clicks, causing estimated losses of $100 billion per year
Spam and disinformation bots — spread unwanted content and fake news across social media platforms

What is a botnet and how does it work?

A botnet is a network of infected devices (computers, routers, IoT cameras) remotely controlled by an attacker through a C&C (Command & Control) server. Infected devices — known as “zombies” — execute commands without their owners’ knowledge. The largest botnets in history, such as Necurs, comprised 9 million devices. Botnets are used for DDoS attacks, spam distribution, data theft, and ransomware delivery.

How can I tell if my device is part of a botnet?

Common signs of bot infection include:

Unexplained device slowdown without an apparent cause
Unusual outbound network traffic — especially to unknown IP addresses
Increased bandwidth usage without corresponding user activity
Unexpected reboots and system instability
Inability to update antivirus software
Unknown processes in the task manager consuming CPU or network resources

If you suspect an infection, consider commissioning a security audit and deploying EDR/XDR solutions to detect and isolate the threat.

How can businesses protect against bot attacks?

Effective protection requires a multi-layered strategy encompassing:

WAF with bot protection at the network edge — filtering malicious traffic
CAPTCHA and device fingerprinting at the application layer
Behavioral analysis with ML at the detection layer — recognizing bot patterns
Rate limiting — restricting the number of requests from a single source
Network segmentation — isolating critical assets
24/7 SOC monitoring — continuous traffic observation and rapid incident response
IoT device updates — eliminating default passwords and known vulnerabilities
Employee training — building resilience against phishing and social engineering

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Solutions mentioned in this article that can help protect your organization:

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