Generally speaking, in marketing a bot refers to a software or application that is designed to automate certain tasks such as interacting with users. Bots can be used for various purposes to streamline marketing activities, but they are also exploited for malicious activities that interrupt marketers and damage brands.

Fraud bots in mobile marketing 

Fraud bots, also known as malicious bots, are a type of bot software program specifically programmed to attack mobile apps with fraudulent activities. These bots are created with the intention of manipulating data and generating false user activities for financial gain.

The malware programs are able to impersonate a real user and simulate certain activities like installations or in-app engagement. These impressions are then logged on as legitimate data and distort the overall marketing performance metrics. 

How do bots work? 

Fraudsters typically use emulation software to design bots that can perfectly mimic real user behavior like installation activities, ad interactions, and even in-app purchases. They are able to perform a number of tasks including install frauds, click frauds, and ad stacking frauds. 

Mobile fraud bots are constantly evolving, and fraudsters continue to employ sophisticated techniques to evade fraud detection solutions and stay up-to-date with user behavior trends. They also consistently refresh their database and replace it with new ones to minimize their chances of getting caught.

Different types of fraud bots 

As mentioned before, mobile fraud bots are capable of performing a variety of fraudulent activities, and below are several types of bot fraud marketers experience: 

  • Click fraud bots: These bots learn how real users interact with ads and mimic the behavior to generate fake clicks on mobile ads. Click spamming, click injections, and click hijacking are all potential click frauds bots may perform. 
  • Install fraud bots: These bots simulate app installation activities on mobile devices to generate fake installs and take credit for leading conversions. 
  • App engagement fraud bots: These fraud bots study in-app behaviors to generate fake app engagement metrics. Activities such as viewing and interacting with an in-app ad, creating fake accounts, or even completing an in-app purchase are examples of app engagement fraud. 
  • SDK spoofing bots: While limited to device-based bots, SDK spoofing bots are able to mimic an app as a whole by hacking the app’s SDK. The bot can impersonate the app and perform false activities and send in-app activity reports pertaining to the fraud. 

Overall, there are variations in what fraud bots can perform, depending on the fraudster’s intention and abilities. Yet, all four fraud types listed above have a common goal of tainting the app’s marketing activities and performance. It can affect marketers by exhausting their marketing budget, tricking them into giving false attribution / false commissions to fraudsters, and providing them with misleading marketing performance metrics. 

How to protect yourself from bot frauds 

Use closed source SDKs

Apps should use a closed source SDK to avoid giving public access to their SDK code and fraudsters exploiting it for malicious purposes. This minimizes the chances of fraudsters simulating and decoding it. 

Challenge-based detection

This is a commonly used bot detection method where users are required to solve a challenge before gaining access to the desired destination. The challenge is designed so that human users can very easily solve it but bots cannot. CAPTCHA is a commonly used challenge-based detection. 

Keeping track of bot signatures 

Marketers can collect the signatures of bots to blacklist their IPs and keep track of malicious accounts. All known signatures that have a history of malicious activity can be detected and automatically blocked. 

Monitor suspicious activities or anomalies  

With ad fraud incidents skyrocketing in today’s mobile marketing landscape, it is the marketer’s responsibility to constantly monitor user activities and detect any suspicious behavior or anomalies. For instance, click reports could show an unusual amount of clicks within a short amount of time, which would most likely indicate a click spamming fraud.

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