What is a bot and how does it work?

A bot is an automated software program that in­de­pend­ently performs digital tasks and, for example, crawls websites, answers chat messages, compares prices or automates login attempts. Bots can work on a rules-based basis or use ar­ti­fi­cial in­tel­li­gence. This means their areas of ap­plic­a­tion range from search engine crawlers, chatbots and AI agents to spam bots, phishing bots and botnets.

What is a bot?

The term ‘bot’ comes from the word ‘robot’. Much like mech­an­ic­al robots, internet bots are pro­grammed to carry out specific, re­pet­it­ive tasks. They follow clearly defined commands in the form of al­gorithms and scripts, allowing them to complete these tasks much faster than a human could. Bots are therefore computer programs that operate in­de­pend­ently and auto­mat­ic­ally, without requiring ongoing human in­volve­ment or su­per­vi­sion.

The first known internet bot was the World Wide Web Wanderer, which began measuring the growth of the internet in 1993 and stored the data it collected in an index known as Wandex. Today, bots have a much wider range of uses. They support customer service as chatbots, operate on social networks as social bots, analyse websites as web crawlers and can also be used in botnets to carry out spam and phishing attacks.

How does a bot work?

The easiest way to un­der­stand how bots work is to compare them with physical robots. Unlike robots, they are not made up of material machine parts such as screws, threads, plastic and wires, but of code. The code contains the necessary commands and in­struc­tions that tell the bot how it should com­mu­nic­ate actively or re­act­ively with human users, systems or other bots.

Bots can range from very simple programs to soph­ist­ic­ated systems that use complex code and ar­ti­fi­cial in­tel­li­gence. On social networks, advanced bots can sometimes be difficult to dis­tin­guish from human users. Today, even people without pro­gram­ming expertise can create bots using the many tools and in­ter­faces available online, from basic automated programs to more complex ap­plic­a­tions.

Based on the al­gorithms defined in the code, bots can perform a range of simple or complex tasks. Com­mu­nic­a­tion usually takes place via internet-based platforms and services, such as instant messaging (IM) or Internet Relay Chat (IRC).

What functions can a bot have?

Bots can perform a wide range of functions depending on how and where they are used online. Some of the most common include:

• Sup­port­ing com­mu­nic­a­tion services on instant messaging platforms such as Facebook, X and WhatsApp.
• Auto­mat­ic­ally col­lect­ing data through web scraping by searching, analysing and indexing in­form­a­tion on websites using keywords, pattern matching or hashtags.
• Sim­u­lat­ing and auto­mat­ing pre­defined com­mu­nic­a­tion based on specific keywords, al­gorithms or hashtags, for example in chats, on websites or in customer service.
• Con­nect­ing to other ap­plic­a­tions and bots through in­ter­faces to perform ad­di­tion­al functions, such as col­lect­ing and dis­play­ing data from weather or traffic apps.
• Providing automated services such as trans­la­tions, per­son­al­ised ad­vert­ising or order pro­cessing.
• Per­form­ing gaming functions, such as playing chess.
• Forming botnets that use networks of computers to carry out data theft, scams and DDoS attacks.

What is a bot made up of? How bot ar­chi­tec­ture works

A bot es­sen­tially consists of three main com­pon­ents:

1. Ap­plic­a­tion or workflow logic: This is the ex­ecut­able, machine-readable code written by pro­gram­mers to define the bot’s functions, tasks and processes.
2. Database: The database stores the data and in­form­a­tion the program needs to perform its tasks. It can also be con­tinu­ously expanded, as is the case with search engine bots such as web crawlers.
3. APIs: APIs (Ap­plic­a­tion Pro­gram­ming In­ter­faces) allow bots to access functions and data from other ap­plic­a­tions without pro­gram­mers having to develop these features from scratch. These in­ter­faces integrate external software commands into the bot’s code and extend its func­tion­al­ity.

Rule-based and self-learning AI bots

Simple bots use rule-based ‘if-then-else’ logic to carry out clearly defined, pre-pro­grammed commands and tasks. Modern bots can also use ar­ti­fi­cial in­tel­li­gence to adapt over time, expand the data available to them and learn new functions and terms. Bots can therefore be dis­tin­guished not only by their area of use, but also by their technical basis.

Rule-based bots follow fixed decision trees, keywords or ‘if-then-else’ rules. Self-learning, AI-powered bots, by contrast, use ar­ti­fi­cial in­tel­li­gence to analyse inputs more flexibly and generate responses dy­nam­ic­ally. One in­creas­ingly important type is the AI agent. AI agents can process natural-language queries, take context into account and, depending on the system, retrieve in­form­a­tion from connected tools, databases or APIs.

Based on their main functions, rule-based and self-learning bots can be divided into several groups:

1. En­ter­tain­ment bots
2. Com­mer­cial bots
3. Service bots
4. News bots
5. Malware bots

What types of benign bots are there?

Bots can be used in a wide range of areas on the internet and are all similar in that they provide a service that can be used for both legal and illegal purposes. One of the most important types of bot are chatbots. Simple, rule-based chatbots follow fixed decision trees, keywords or pre­defined response patterns. They are par­tic­u­larly suitable for stand­ard­ised requests such as FAQs, ap­point­ment bookings or simple support processes. However, they quickly reach their limits when it comes to more complex issues.

Modern LLM-based chatbots use large language models to un­der­stand natural-language queries, consider the context of a con­ver­sa­tion and generate responses dy­nam­ic­ally. This makes them useful not only for customer service, but also for lead gen­er­a­tion, sales, internal knowledge searches and the initial as­sess­ment of support requests. Combined with live chat support, they can respond to queries around the clock and transfer con­ver­sa­tions to human staff when necessary.

If LLM-based chatbots are ad­di­tion­ally connected to tools, databases, APIs, memory functions or workflows, con­ver­sa­tion­al AI agents or AI chatbots can emerge from them. Such systems not only answer questions, but depending on the con­nec­tion can also retrieve in­form­a­tion, prepare tasks or carry out in­di­vidu­al actions. This sets them apart from classic chatbots, which usually only react to inputs. One example of a ready-to-use AI assistant is the IONOS AI Chat Assistant. It can help busi­nesses collect and analyse customer feedback, identify trends and use these insights to uncover potential areas for im­prove­ment.

Other common benign bots (often referred to as ‘good bots’) are:

• Social bots: Umbrella term for all bots that operate on social media and take over automated tasks in the areas of help, FAQs, direct messaging, com­ment­ing on posts, or likes, shares, retweets and following.
• Web crawlers: These bots collect and evaluate data and in­form­a­tion from websites in order to extend the func­tion­al­ity of search engines and com­par­is­on portals, register and index new web content, create links and optimise search queries.
• Gaming bots: These are bots that appear in video games as ar­ti­fi­cial fellow players (NPCs).
• Shop bots: Bots that compare prices in online shops and look for the cheapest offers or select the most popular shopping sites for users.
• Mon­it­or­ing bots: They monitor the status of a website or a system.

What malware bots are there and how do they work?

Although bots have many positive functions and numerous services such as search engines, instant messaging or com­par­is­on portals would be un­think­able without them, bots have a largely bad repu­ta­tion because of malware and hacker attacks. This is because many types of bots are developed spe­cific­ally for illegal and harmful purposes.

The following types belong to malware or malicious bots:

• Pro­pa­ganda bots or ma­nip­u­lat­ive bots: Social bots that simulate user profiles, influence digital opinion formation and spread political state­ments, fake news and con­spir­acy theories, or react to comments and posts based on keywords.
• Scam/phishing bots: These bots steal data using pseudo-links, fake emails and fake websites.
• Key­log­ging bots: Bots that log message traffic or record, store and forward all activ­it­ies on a PC.
• File-sharing bots: Bots that respond to targeted search queries and offer users a link to the desired search term. When this link is clicked, the bot can infect the PC used by the person.
• Spam bots: They send large quant­it­ies of spam emails and use the address books and contacts of un­sus­pect­ing users to de­lib­er­ately expand their spam radius.
• Zombie bots: So-called zombie bots are computers that have been infected with malware by bots or made part of a botnet and provide computing power for large botnet attacks. Com­prom­ised PCs are often not easily re­cog­nis­able as part of a botnet.
• Botnet: Refers to the entirety of infected PCs that are linked together into a network and serve, for example, as a basis for DDoS attacks.

What types of attacks can botnets carry out?

Botnets can be used for a range of illegal activ­it­ies, including:

• Data and identity theft through scraping, phishing and key­log­ging to obtain sensitive in­form­a­tion such as passwords, bank details and addresses.
• Dis­trib­uted denial-of-service attacks (DDoS), in which large volumes of traffic are used to overload and po­ten­tially paralyse servers.
• Backdoor attacks, which exploit vul­ner­ab­il­it­ies in a computer’s security system to infect it with malware.
• Spam dis­tri­bu­tion and traffic re­dir­ec­tion, in which com­prom­ised devices are used to relay unwanted messages or redirect data packets.

Five of the most common large-scale bot attacks are:

• DDoS attacks: De­lib­er­ately over­whelm­ing servers with large volumes of traffic.
• Spam and traffic mon­it­or­ing: Over­load­ing email servers, dis­trib­ut­ing spam or in­ter­cept­ing large amounts of data.
• Denial-of-inventory attacks: Reserving products in online shops so that they appear to be un­avail­able to genuine customers.
• Scraping attacks: Auto­mat­ic­ally col­lect­ing data for un­au­thor­ised use or resale.
• Cre­den­tial stuffing attacks: Using stolen login details to carry out automated login attempts across a large number of accounts.

How can busi­nesses use bots safely and ef­fect­ively?

If you work in online marketing, benign bots can help you stream­line and automate routine tasks. At the same time, bot man­age­ment should form an essential part of your company’s cyber security strategy. It helps you identify malicious bots and protect your website or online shop from attacks while con­tinu­ing to allow access to le­git­im­ate bots.