Traffic Bot Types: Good Bots vs Bad Bots in 2023

In this article, we will explore the different types of bot traffic and differentiate between good bots and bad bots.

‍Good Bots

Good bots are software applications designed to perform useful and beneficial tasks on the internet. They are generally created by companies, organizations, or search engines to perform specific tasks such as web indexing, content curation, and website optimization.

‍Here are some examples of good bots:

• ‍Search engine bots. Search engine bots, also known as crawlers or spiders, are used by search engines like Google, Bing, and Yahoo to crawl and index web pages. These bots are responsible for finding new content on the internet and making it available to search engine users. Without search engine bots, it would be impossible for websites to rank in search engine results pages (SERPs), which would severely impact the visibility and traffic of websites.
• Content aggregation bots. Content aggregation bots, also known as news bots, are designed to collect and curate content from various sources on the internet. These bots are often used by news organizations to find and share the latest news stories with their readers. Content aggregation bots help to save time and resources by automating the process of finding and curating content.
• Monitoring bots. Monitoring bots are used to track and monitor the performance of websites and web applications. These bots check websites for uptime, response time, and other performance metrics. They are also used to monitor social media accounts, online reviews, and other online channels for mentions of a brand or company.

Bad Bots (Malicious Bots)

Bad bots are software applications designed to perform malicious or harmful tasks on the internet. They are created by cybercriminals to steal data, conduct fraud, and disrupt online services. Bad bots can be used for a variety of nefarious purposes, including:

• Web scraping. Web scraping is the process of extracting data from websites. While some web scraping bots are good, many are bad because they are used to steal data for malicious purposes. Bad bots can scrape sensitive information like credit card numbers, social security numbers, and login credentials.
• Credential stuffing. Credential stuffing is a type of cyberattack where a bot tries to log into user accounts using stolen login credentials. Cybercriminals use this technique to gain access to sensitive information and steal personal data. Credential stuffing bots can try thousands of login combinations in a matter of seconds, making it difficult for users to protect their accounts.
• DDoS attacks. Distributed denial-of-service (DDoS) attacks are a type of cyberattack that overwhelms a website with traffic, making it unavailable to users. Bad bots can be used to launch DDoS attacks by sending a large amount of traffic to a website, causing it to crash.

Ad fraud bots

Bad bots can cause various forms of harm, from stealing personal data to performing distributed denial of service (DDoS) attacks. However, one of the most common ways that bad bots cause harm is through ad fraud. 

Ad fraud is a widespread problem that costs the digital advertising industry billions of dollars every year, and bots are a primary tool used by fraudsters to generate fake traffic and inflate ad metrics. 

Here are some of the different types of bots that commit ad fraud:

• Click bots. Click bots are bots that mimic human clicks on ads. They are designed to click on ads repeatedly, generating revenue for the ad fraudster or inflating the click-through rate (CTR) of the ad. Click bots can be difficult to detect because they can mimic human behavior and use different IP addresses and user-agent strings to evade detection.
• Impression bots. Impression bots are bots that mimic human impressions on ads. They are designed to load and view ads repeatedly, generating revenue for the ad fraudster or inflating the impression count of the ad. Impression bots can be difficult to detect because they can mimic human behavior and use different IP addresses and user-agent strings to evade detection.
• Conversion bots. Conversion bots are bots that mimic human conversions on ads. They are designed to complete actions like filling out a form or making a purchase, generating revenue for the ad fraudster or inflating the conversion rate of the ad. Conversion bots can be difficult to detect because they can mimic human behavior and use different IP addresses and user-agent strings to evade detection.
• Ad stacking bots. Ad stacking bots are bots that stack multiple ads on top of each other in a single ad slot. Ad stacking can inflate the impression count of the ad and generate revenue for the ad fraudster. Ad stacking bots can be difficult to detect because they can use different ad sizes and placements to evade detection.
• Domain spoofing bots. Domain spoofing bots are bots that impersonate legitimate websites to generate traffic and revenue. The bot will create a fake website that looks like a legitimate website and then direct traffic to that fake website, generating revenue for the ad fraudster. Domain spoofing bots can be difficult to detect because they can use legitimate-looking domain names and URLs to evade detection.

How To Differentiate Between Good Bots And Bad Bots

Differentiating between good bots and bad bots can be challenging because bots can impersonate humans and evade detection. However, there are a few ways to distinguish between the two:

• User-agent strings. User-agent strings are pieces of text that identify the software application making a request to a server. User-agent strings can be used to identify whether a bot is good or bad. Good bots often have well-known user-agent strings, while bad bots can use fake or obscure user-agent strings.
• Traffic patterns. Traffic patterns can also be used to differentiate between good and bad bots. Good bots typically follow a regular traffic pattern, while bad bots can generate irregular traffic patterns that are difficult to distinguish from human traffic.
• IP addresses. IP addresses can be used to identify the source of bot traffic. Some bad bots use IP addresses from known botnets or VPNs, while good bots often use IP addresses from known and trusted sources.
• Behavioral analysis. Behavioral analysis involves analyzing the behavior of a bot to determine whether it is good or bad. Good bots typically follow predictable patterns and adhere to industry standards and best practices. Bad bots, on the other hand, can exhibit erratic behavior and deviate from industry standards.

Say Goodbye To Bot Attacks With Spider AF

Distinguishing between good bots and bad bots is crucial for ensuring the security and integrity of online services and personal data. 

Among bad bots, ad fraud is one of the most common ways that they cause harm, and it is a serious problem for the digital advertising industry. However, with the right tools and strategies, it is possible to detect and prevent ad fraud. 

Spider AF offers a powerful AI-driven solution that can help you protect your campaigns from every type of invalid traffic. With increased visibility into your ideal customer data, you can achieve high-quality protection that helps you maximize the value of your digital advertising investment. 

Don't wait to see the difference that Spider AF can make. Sign up now for a free Spider AF account and start protecting your ad campaigns.

Frequently Asked Questions about Good Bot vs Bad Bot

What are good bots and can they affect search engine rankings?

Good bots are computer programs designed to perform useful or helpful tasks on the internet, such as indexing websites for search engines, content curation, and website optimization. They are crucial for search engine rankings as they help index websites and make website content available in search results, which affects the visibility and traffic of websites positively.

How do bad bots participate in phishing attacks and credit card fraud?

Bad bots are programmed to engage in malicious activities such as stealing sensitive data and personal information. They can be used in phishing attacks to deceive individuals into providing personal data and in credit card fraud by scraping website content to obtain credit card numbers and other financial information.

Why is it important to block bot traffic and how does it relate to malicious traffic?

It's essential to block bot traffic that is malicious to protect your online presence from cyber threats. Malicious traffic can include a range of harmful activities, such as data theft, DDoS attacks, and ad fraud. Blocking these bad bots helps ensure that only legitimate traffic from real users and good bots, like search engine crawlers, can access your site.

What strategies can be employed to identify bad bots and detect bad bots effectively?

To identify bad bots and detect bad bots, website owners can use tools that analyze web traffic patterns, inspect user agents, and monitor IP addresses. Implementing a bot management strategy that includes behavioral analysis and the use of machine learning can help detect and differentiate between bad bots and legitimate users.

What is the role of personal assistant bots on social media platforms?

Personal assistant bots on social media platforms are designed to help with automated tasks such as scheduling, customer service, and user engagement. They can improve efficiency and user experience when they follow the platforms' guidelines and perform useful or helpful tasks without engaging in spamming or other disruptive behaviors.

Can DDoS bots affect multiple sites at once and how does this impact web traffic?

Yes, DDoS bots can target a targeted server that hosts multiple sites, causing a surge in web traffic that can slow down or even crash all the sites on that server. This type of malicious intent disrupts service for legitimate users and can cause significant downtime and loss of revenue.

How do site monitoring bots contribute to maintaining website health?

Site monitoring bots are used to continuously check the health and performance of websites. They can alert website owners to issues like downtime, slow response times, or other technical problems, which helps in maintaining optimal site performance and availability for real users.

What is the difference between commercial bots and social network bots, and how do they operate on social media platforms?

Commercial bots are typically used by businesses for advertising, customer service, and data analysis, while social network bots may run automated tasks like posting content or interacting with users on social media platforms. Both types of bots should aim to add value without contributing to spam or other malicious activities.

How do scraper bots affect the website content and what can be done to mitigate their impact?

Scraper bots can negatively impact website content by copying it without permission, which may lead to issues like content duplication that can affect search engine rankings. To mitigate this, website owners can implement measures to block bad bots, such as setting up firewalls that filter incoming traffic and using CAPTCHAs.

What measures can be taken to prevent account takeover bots from accessing multiple accounts?

To prevent account takeover bots from accessing multiple accounts, implement strong password policies, use multi-factor authentication, and monitor for suspicious activities. These steps help to secure user accounts from being compromised by bots attempting account takeover and other forms of unauthorized access.

How does bot management play a role in protecting against data breaches on online businesses?

Bot management involves a set of practices and technologies designed to block bad bots while allowing good bots to access a web server. This is critical for online businesses, as effective bot management can prevent malicious actors from using bots for data breaches. By distinguishing and controlling bot traffic, businesses can safeguard sensitive customer data and protect their reputations.

What techniques can be used to detect bots that attempt to submit junk data on websites?

To detect bots that submit junk data, website owners can implement machine learning algorithms that analyze incoming traffic and identify patterns indicative of automated tasks. By setting up advanced filters and monitoring for unusual behavior, such as rapid submission of data, websites can prevent bots from overwhelming systems with junk data, which can be a precursor to more severe attacks like DDoS or account takeover.

Can web crawlers from search engines be mistaken for spam bots on social media platforms?

Web crawlers from search engines are generally designed to index website content and are considered good bots, but if they start accessing social media platforms with the frequency and patterns similar to spam bots, they could be mistakenly blocked. To prevent this, social media platforms and website owners must accurately detect bots, possibly by analyzing the user agents and IP addresses, to ensure that legitimate search engine crawlers are not impeded.