Top 20 Considerations When Looking for a Bot Prevention Vendor

The key to effectively safeguarding business platforms and keeping customers safe today is by stopping malicious bots. Bots allow bad actors to launch attacks at a massive scale so that only a small percentage need to be successful for the attacker to turn a profit. Automated scripts are cheap to acquire and easy to deploy, making the barrier to entry for any enterprising cyberattacker low. 

That’s why having robust bot defense systems in place is so critical for businesses today. In this blog, we will examine the top 20 features that businesses need to consider when in the market for a new bot prevention solution. 

• Protects Against the Full Range of Bot Attacks

This goes without saying, but the optimal solution should protect against not just basic bots, but even advanced bots that are able to obfuscate their true identity, both those emulating remote clients and those trying to impersonate true users. It should protect all customer touch points from automated attacks, as well as all mobile apps, web applications, APIs, and IoT devices. 

• Robust Detection Engine

As noted, increasingly sophisticated bots are able to mimic human users with a high degree of accuracy. The ideal solution should be able accurately to identify bots, differentiate between good and bad bots, identify the type of bot attack (for example, credential stuffing, inventory hoarding, web scraping, ad fraud), and be able to detect even the most complex attacks. This should be done using tools such as real-time signals, historical experience, anomaly detection, spoofing & obfuscating detection, and risk classification validation via a challenge feedback loop.

• 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. Machine learning in areas such as device spoofing, risk scoring, behavioral biometrics, identifying patterns, anomaly detection, and traffic shaping are vital to stopping advanced automated attacks. 

• Explainability and Transparency

Businesses using a bot prevention solution need to know why a certain conclusion was reached. How well does the product explain why a particular request was identified as a bot? And how well does it tailor the explanation to the customers’ applications? The answers to these questions are vital to know as they help reduce false positives and further refine defenses. Bot defense platforms should present their clients 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  

• 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

Not only does the solution need to have an effective response to stopping attacks, but it should not hinder or cause much friction to good users. The product needs to 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. 

• End-user Experience

Ultimately, how effective a solution is at stopping bad bots is meaningless if it also stops too many good users. 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. It should also provide its clients with the false positive rate and the reasons behind false positives as well as SLAs minimizing false positives and false negatives.

• 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. The vendor should be clear on changes required to individual applications, pages, or infrastructure configurations for the bot management solution to work on different application types. And the customer should be able to quickly begin to see value from the bot management solution after implementation. 

• Good Bot Configuration

Of course, not all bots on the web are bad. Some, like search engine bots, are not malicious. The optimal bot prevention solution should be able to accurately identify, track, and configure good bots. The vendor should work with its clients to assess legitimate bot traffic, and tune its configuration to classify it as legitimate.

• UI Management

A bot prevention tool is of little use if businesses have trouble managing it. It’s imperative that the solution has a robust user interface that enables centralized management for the application and modification of attack detection and response. It should provide its users with specific tools such as managing rules and models that use real-time signals, the ability to configure detection methods, the ability to configure attack response as well as provide a dashboard with data insights and allowing the client to create custom reports. 

• Accessibility

Businesses using a challenge-response mechanism to test potentially bad traffic need to ensure that it is accessible to all potentially good users. If a good user gets caught in its snare, you want them to be able to easily self-remediate. That means the solution should provide audio challenges for the hearing impaired, have full keyboard and machine-readable text support as well as other considerations for those with cognitive and motor impairments. 

• Threat Research

Bad guys never stand still, and attacks are always evolving and increasing in sophistication. That’s why businesses should work with a bot prevention vendor that employs a threat research team that is tasked with discovering and addressing new threats and bot patterns. It should use this research to push new rules to customers based on discovered threats as well as share the research on evolving bot threats with customers. 

• Out of the Box Reports

The ideal bot prevention solution should provide robust out-of-the-box reports. It should include options to report current and trending data as well as reports against different bot types, across single applications, and across a portfolio of applications. Furthermore, analysts want to know the ‘why’ behind metrics. Reports should be available that give transparency into how risk classifications and decisions were arrived at

• Custom Reports

Besides out-of-the-box reports, the platform should also have the ability to deliver bespoke reporting. The solution should natively provide tools for creating and modifying reports and dashboards while allowing the client to apply different metrics and visualizations. It should also easily allow reports and dashboards to be shared with different internal stakeholders. Users should also be able to create and modify reports through integrations with other BI and reporting tools. 

• 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. That’s why the solution should collect as little PII from users as possible. 

• Level of Performance

The vendor should be able to ensure its bot management 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.

• Security Feedback Loops

In order to achieve maximum effectiveness, 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. This is critical for defending against evolving attacks and keeping the platform safe long term. Clients should also be free to discuss any unusual results seen in these feedback loops with the vendor.  

• Marketing Feedback Loops

Besides the importance of notifying security teams of potential threats, the solution should natively enable feedback loops to marketing and e-commerce teams to notify them of the impact of bots on marketing campaigns, promotional events, and the like. Monitoring activity on these endpoints helps marketing teams measure campaign or marketing event success. This also enables marketing teams to do a quantitative and qualitative analysis of the visitors to their site.

• Product Vision and Roadmap

If a bot detection vendor is not continually innovating, its product will soon become obsolete. The vendor must have a product vision that aligns with the current and future needs of customers. Its roadmap should have clearly defined objectives in place along with realistic timelines to achieve them. Above all, there must be an environment of continual innovation, so the solution is always able to stand up to ever-evolving bot attacks. 

• Planned Enhancements

The vendor should be responsive to client requests and suggested enhancements to the product. It is important they listen to customer feedback and make ongoing changes as speedily as possible. They should also be transparent about planned enhancements and clients should be involved as advisors, as they are the ultimate end user of the product. 

This is a fairly exhaustive list, but businesses need to make the right decision when choosing a bot prevention solution today. If they don’t, they risk losing customers, draining revenue and potentially facing legal and compliance repercussions. With the right solution, however, they can be assured their platform is safe against even the most sophisticated attacks.

*** This is a Security Bloggers Network syndicated blog from Arkose Labs authored by Ashish Jain. Read the original post at: https://www.arkoselabs.com/blog/top-20-considerations-when-looking-for-a-bot-prevention-vendor/