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
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 Bad Bots 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.
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