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IntelliFend Bot Types

The bot types are based on the list of the latest bot types at New Bot Types.

Bot Types

Understanding the various types of bots that may pose risks to your application is crucial. To help you better understand bots, we have systematically categorized them by their unique behaviors and characteristics.

Good Bot​

A good bot is a software program that performs useful or helpful tasks that are tasks without being experienced on the Internet. Good bots are often used to automate tasks that would be tedious or time-consuming for humans, such as searching for information, providing customer service, or crawling websites.

There are several types of good bots, each serving a specific purpose. Here are a few examples:

  • Search engine bots: These bots crawl content on websites on the Internet, then index that content to make it easier for users to find information. Search engines like Google and Bing operate them.

  • Social media bots: These bots automate tasks on social media, such as posting updates, responding to comments, or sending messages.

  • Customer service bots: These bots provide customer service support, such as answering questions, resolving issues, or enhancing the customer service experience.

  • Crawling bots: These bots crawl websites and collect data, like product listings or user profiles. This data can be used for various purposes, such as price comparison or marketing.

Good bots play a crucial role on the Internet, contributing to a more efficient and user-friendly environment.

Account Takeover Bot​

An account takeover bot is a type of software program that is used to automate the process of taking over online accounts. Account takeover bots are typically used by cybercriminals to gain access to accounts that they do not own, such as bank accounts, email accounts, and social media accounts.

Account takeover bots work by using a variety of techniques, such as:

  • Brute force attacks: This involves trying different combinations of usernames and passwords until the correct combination is found.

  • Password spraying: This involves trying a small number of common passwords against a large number of accounts.

  • Phishing: This involves sending emails or text messages that appear to be from a legitimate source, such as a bank or a social media platform. The emails or text messages will often contain a link that, when clicked, will take the victim to a fake website that looks like the real website. Once the victim enters their login credentials on the fake website, the cybercriminal will be able to steal them.

Account takeover bots are a serious threat to online security. It is important to be aware of the risks and to take steps to protect accounts from attack.

Scraper Bot​

A scraper bot, also known as a web scraper or data scraper, is a software program that is used to extract data from websites. Scraper bots are typically used to automate the process of collecting data from websites, and they can be used for a variety of purposes, such as:

  • Creating product feeds for online retailers

  • Generating reports on market trends

  • Tracking competitor pricing

  • Collecting customer reviews

  • Scraping social media data

Scraper bots work by sending HTTP requests to websites, parsing the HTML code that is returned, and extracting the data needed. The HTML code contains the structure of the website, as well as the text, images, and other elements that are displayed on the page.

The legality of using scraper bots to extract data from websites depends on the terms of service of the website in question. Some websites explicitly prohibit the use of scraper bots, while others allow it with certain restrictions.

Some of the risks of using scraper bots:

  • They can be used to violate the terms of service of websites, which could result in legal action.

  • They can be used to collect data that is not intended to be public, such as personal information or financial data.

  • They can overload websites with requests, which can slow down the performance of the website or even cause it to crash.

Scalper Bot​

Scalping is a frequent challenge faced by e-commerce and ticketing industries, often leading to inventory denial. Online scalping is carried out by using scalper bots; these bots are deployed to outpace genuine consumers in securing fast-moving goods such as event tickets, gaming consoles, and limited-edition items. Because bots quickly add sought-after items to their carts, normal users often miss out on good deals and discounts. Scalper bots enable fraudsters to complete purchases rapidly, allowing them to stockpile these items in bulk. These items can then be resold at a premium. Alternatively, attackers may later abandon the items in their carts, leading to potential losses for the business.

API Abuse Bot​

As APIs become more frequently targeted by cyber attackers, API abuse bots have been created to exploit these crucial components of digital infrastructure. They send an unusually high number of requests within a short period, far exceeding normal user behavior, and they usually target some valuable endpoints.

API abuse bots can be used to carry out a variety of attacks, including:

  • Denial of service (DoS) attacks: These attacks flood an API with requests, causing it to crash or become unresponsive.

  • Data scraping: These attacks collect sensitive data from an API, such as user credentials or financial information.

AI Training Bot​

An AI Training bot is a specialized type of web scraper bot designed to automatically extract and collect large volumes of data from websites for the purpose of training artificial intelligence (AI) and machine learning (ML) models. These bots systematically crawl websites, extract text, images, code, and other content, then aggregate the collected data into datasets used to train large language models (LLMs), computer vision systems, and other AI applications.

AI Training bots operate similarly to general web scrapers but are distinguished by their scale, intensity, and purpose. They send an unusually high volume of requests to target websites over extended periods, consuming significant bandwidth and computational resources. Unlike legitimate search engine crawlers that respect robots.txt and rate limiting, many AI Training bots operate without proper authorization or adherence to website terms of service.

The risks and impacts of AI Training bots include:

  • Bandwidth and resource consumption: These bots generate large volumes of traffic that compete directly with legitimate user traffic, potentially degrading website performance, increasing server costs, and causing service disruptions for normal visitors;

  • Intellectual property violations: AI Training bots often collect copyrighted content, proprietary information, and trade secrets without authorization or attribution, resulting in the unauthorized use of creators' work in AI models;

  • Terms of service violations: Most websites explicitly prohibit automated scraping and data extraction in their Terms of Service. AI Training bots frequently violate these agreements;

  • Economic harm: Website operators may incur increased infrastructure costs to handle bot traffic, while content creators receive no compensation when their work is used to train commercial AI systems;

  • Data privacy concerns: These bots may inadvertently or intentionally collect personal data, user information, or sensitive content that should not be used for AI training;

  • Legal exposure: Website owners and AI companies using data collected by these bots may face potential legal liability for copyright infringement, unauthorized data use, and violations of computer fraud or cybersecurity laws.

As AI development continues to accelerate, AI Training bots have become increasingly prevalent and represent a significant threat to website owners, content creators, and internet users.

AI Agent Bot​

An AI Agent bot is a sophisticated type of bot autonomously operated by browser automation systems or related AI services. These bots are engineered to perform complex actions on behalf of human users to accomplish specific objectives that would otherwise require significant manual intervention and time investment.

AI Agent bots are programmed to execute a wide range of tasks, including:

  • Data retrieval: These bots systematically gather information from websites and online services, aggregating data for analysis, research, or competitive intelligence purposes;

  • Price comparison: These bots monitor and compare prices across multiple e-commerce platforms and retailers, helping users identify the best deals and market trends;

  • Ticket purchasing: These bots automate the process of searching for and purchasing tickets to events, concerts, shows, and other time-sensitive offerings;

  • Travel planning: These bots assist in itinerary creation, flight bookings, hotel reservations, and travel logistics by accessing multiple travel platforms simultaneously;

  • Research and analysis: These bots can perform automated research tasks, collect competitive intelligence, and synthesize information from various online sources;

AI Agent bots operate by leveraging artificial intelligence (AI) and natural language processing (NLP) to understand user intent, navigate complex web interfaces, make decisions based on specified criteria, and execute actions autonomously. Unlike simple automation scripts, AI Agent bots can adapt to changing website layouts, handle dynamic content, and make contextual decisions based on real-time data.

The risks and concerns associated with AI Agent bots include:

  • Unauthorized automation: Many websites prohibit automated access through their Terms of Service, and AI Agent bots may violate these agreements by automating interactions without explicit permission;

  • Resource consumption: These bots can generate significant traffic and server load, potentially degrading performance for legitimate users and increasing operational costs for website operators;

  • Unfair competition: When used for activities like ticket purchasing or price monitoring at scale, AI Agent bots can create unfair advantages and disadvantage human users competing for the same resources;

  • Data privacy violations: AI Agent bots may inadvertently or intentionally collect personal information or sensitive data during their operations, raising privacy and security concerns;

  • Market manipulation: In certain contexts, such as ticket resale markets, AI Agent bots can be used to artificially inflate prices or monopolize inventory;

  • Legal and compliance issues: The use of AI Agent bots for certain purposes may violate computer fraud laws, terms of service agreements, and other applicable regulations, depending on the jurisdiction and specific use case;

As AI technology becomes more sophisticated and accessible, AI Agent bots represent an evolving challenge for website operators and service providers, who must balance automation innovation with the need to maintain fair access and protect their platforms from automated abuse.

Fraud Bot​

A fraud bot is a malicious software program designed to automate fraudulent activities and generate unauthorized revenue. Fraud bots are typically deployed by cybercriminals to exploit online systems and deceive users for financial gain.

Fraud bots are programmed to execute a variety of deceptive activities, including:

  • Click fraud: These bots automatically click on advertisements and affiliate links to generate false impressions and artificially inflate traffic metrics, deceiving advertisers and generating fraudulent revenue for the bot operator;

  • Ad fraud: These bots simulate legitimate user interactions with online advertisements, leading advertisers to pay for fake clicks or impressions that provide no genuine marketing value;

  • Affiliate fraud: These bots exploit affiliate marketing programs by falsely attributing conversions and sales to affiliate links, allowing fraudsters to earn commissions on transactions they did not legitimately generate;

  • Credit card fraud: These bots can be used in conjunction with stolen payment information to perform unauthorized purchases and transactions;

  • Fake account creation: These bots automate the large-scale creation of fraudulent accounts, enabling attackers to bypass security measures and establish multiple identities for fraudulent activities;

Fraud bots pose a significant threat to online businesses, advertisers, and consumers. They distort marketing analytics, waste advertising budgets, compromise the integrity of affiliate programs, and erode trust in digital platforms and online ecosystems.

The risks and impacts of fraud bots include:

  • Financial losses: Businesses and advertisers may suffer substantial financial losses due to fraudulent transactions, fake clicks, and artificial impressions generated by fraud bots;

  • Skewed analytics: Fraud bots distort performance metrics and analytics data, making it difficult for businesses to analyze genuine user behavior and make data-driven decisions;

  • Reputational damage: Websites and platforms affected by fraud bot activity may experience reputational harm when users associate the platform with fraudulent behavior;

  • Regulatory compliance issues: Fraud bots may cause websites and platforms to violate regulations such as the CAN-SPAM Act, FTC advertising guidelines, or other consumer protection laws;

  • System resource drain: Fraud bots consume significant bandwidth and computational resources, potentially degrading service quality for legitimate users;

Scan/Security Bot​

A security scanning bot, also known as a vulnerability scanner or security assessment bot, is a software program designed to automatically identify and map potential security vulnerabilities and attack surfaces on websites and web applications. Security scanning bots systematically probe target systems to discover hidden endpoints, exposed APIs, misconfigured resources, and other security weaknesses that could potentially be exploited by malicious actors.

Security scanning bots operate by sending automated requests to websites, analyzing responses, and mapping the application structure to identify:

  • Hidden or undiscovered endpoints: Endpoints that are not publicly documented or linked but remain accessible through direct requests;

  • Exposed administrative interfaces: Unprotected or improper secured admin panels, configuration pages, or debug endpoints;

  • Misconfigured resources: Improperly secured API endpoints, databases, or file storage systems;

  • Information disclosure vulnerabilities: Endpoints that expose sensitive information such as API keys, credentials, or internal system details;

  • Suspicious or sensitive paths: URLs and routes intended for administrative or debugging purposes that should not be publicly accessible;

Security scanning bots can serve legitimate purposes when used by authorized security researchers, or organizations to identify vulnerabilities in their own systems before they can be exploited by attackers. However, unauthorized use of these bots constitutes a significant security threat and may violate computer fraud or cybersecurity laws.

The risks and impacts of unauthorized security scanning bots include:

  • Reconnaissance for attacks: Attackers use security scanning bots to map application architecture and identify vulnerabilities prior to launching targeted cyberattacks;

  • Denial-of-service: Automated scanning activity may generate large volumes of requests, consuming server resources and degrading performance for legitimate users;

  • Unauthorized access: Discovered vulnerabilities may be exploited to gain unauthorized access to sensitive data or system infrastructure;

  • Legal consequences: Unauthorized security scanning may violate computer fraud, cybersecurity, or anti-hacking laws in most jurisdictions;

  • Compliance violations: Organizations conducting unauthorized scanning activities may breach industry regulations, contractual obligations or data protection standards.