Be Future Proof Against the Full Range of Bot Attacks
The optimal solution should protect against not just basic bots, but even advanced, or so called “intelligent” bots. It should be “future proof” and continuously evolve in order to stay ahead of the increasing sophistication of today’s bots. Investing in such a solution can save you money in the long run and yield a great return on investment while protecting your business against powerful bots.
Robust Detection Engine
By investing in increasingly sophisticated bots that can accurately mimic human users with a high degree of accuracy, businesses can save money while gaining increased protection. By having a solution that can accurately identify bots, differentiate between good and bad bots, identify the type of bot attack, and detect even the most complex attacks, businesses can protect their systems and data while also reducing costs associated with manual monitoring. Incorporating data points like global telltales (common or known bad signatures) makes the solution even more effective, helping businesses ensure their systems remain secure while realizing cost savings and increasing their ROI.
Machine Learning Usage and Training
The ideal solution should deploy machine learning to identify new attacks. The vendor should ensure its data sets are sufficient and up to date for training the model, and frequently retrain the model to account for new threats, changing signatures, or customer-specific requirements. In addition, the solution should natively enable feedback loops to its client’s security teams to notify them of attacks, responses, and the results of the response, and be able to push new rules to customers based on discovered threats, allowing for cost savings and a better ROI.
Explainability and Transparency
The ideal solution should deploy machine learning to identify new attacks, providing businesses with a risk score, bot classification, and detailed session telemetry with reason codes. Session flow diagrams should present explanations in an easy-to-consume way, with insight into bot traffic identification accuracy. This solution not only streamlines processes, but can also help businesses save costs and maximize ROI.
End-user Experience
Ultimately, the effectiveness of a solution in preventing malicious bots is moot if it also blocks too many genuine user interactions. The solution should leverage real-time signals (such as device, network, behavior), advanced ML models, and historical insights to accurately differentiate good traffic from bad, while also providing cost savings and a strong ROI.
Efficacy of Response Types
Businesses that are the target of frequent bot-powered attacks need to consider how the solution natively responds to attacks, such as by alerting, blocking, delaying, challenging, misdirecting, or creating honeypots. Even more importantly, does it have a native challenge option to stop bad bots, or would you have to invest in another solution to provide that as well?
Response Configuration & Exception Handling
A bot prevention solution should not hinder or cause much friction to good users. The product should enable its customers to set exceptions for false positives or good bots. This can be done effectively by leveraging global rules, signatures, and learnings to define a custom attack response configuration to, and if needed, surgically override the set global response.
Privacy
Data privacy has never been more important than it is now. Consumer data privacy laws grow in number seemingly by the day, and any bot prevention vendor should make sure it is not violating data privacy regulations. Legacy captcha solutions like reCAPTCHA use cookies to determine whether a user is a bot or human. Consumers who are not Google users must share their data, which leads to data privacy concerns.
Set Up & Implementation
Clients should not have to spend a lot of time and effort in order to get a bot prevention solution up and running and configured to their specific needs and the customer should be able to quickly begin to see value from the bot management solution after implementation.
Level of Performance
The vendor should be able to ensure its product enables good performance for its customers, including low latency, high availability, and scalability across all types of endpoints. The vendor should also offer SLAs or other types of commercial assurances that its solution works as advertised. That means they stand behind their product.