Bot Management Technology Landscape: A 360-degree view (Part 2)

CAPTCHAs

While CAPTCHAs are designed to distinguish between human users and automated bots, they are not foolproof. Bots equipped with optical character recognition (OCR) technology can bypass basic CAPTCHAs, rendering them less effective in preventing automated attacks. Additionally, CAPTCHA Solving services can be found in abundance in the online market today which solely focuses on resolving CAPTCHA puzzles.

Firewalls

While firewalls can offer protection against basic bot attacks, they lack the specificity and advanced detection mechanisms required to identify and mitigate the diverse range of bot activities. They often rely on known attack signatures, leaving them vulnerable to novel and evolving bot tactics which is what is more commonly observed in the internet ecosystem today.

IP Blocking

Blocking specific IP addresses associated with malicious activities was a common practice. However, this method would block not only bots but also genuine users. Moreover, bots can easily switch IP addresses or use distributed networks, making it challenging to maintain an updated and comprehensive blacklist.

Rate Limiting

Rate limiting involves restricting the number of requests from a particular IP address within a specified time frame. While it can help mitigate the impact of bot attacks, it often leads to false positives, inconveniencing legitimate users who may be mistakenly identified as bots, thus affecting user experience.

1. With the advancement in AI and bot development tools, malicious actors have been successful in bridging the gap between the behaviour observed in bots and that of a human. Therefore, customers need a specialized tool that analyses clusters of incoming requests to find distinct patterns in their behaviour and judge them for malice. Traditional security modules only process a single incoming request instead of a sample of requests from the source which only helps eradicate basic bots.

2. As bots attack in volumes, they have the capability to choke the traffic of a digital asset. A bot manager solution has the capability to filter these.
3. Bot management solutions maintain a history of data from bot attacks identified in the past. This is leveraged to ensure cross-customer safety which similar type of attacks are identified in multiple customers.

Pros:

Efficient: Quick processing of known malicious actors.

Low False Positives: The bot repository only contains known bad bots therefore there is little chance of legitimate users getting blocked.

Cons:

Adaptability: Sophisticated evolving bots cannot be caught.

High False Negatives: As the repository contains only known bad bots, new unknown threats are not identified instantaneously.

Pros:

Effective: Deters automated bots.

Customizable: Challenges can be tailored as required.

Cons:

User Experience: Legitimate users also need to solve challenges to prove that they are not bots. This hampers user experience.

Resource Intensive: Requires additional client-side data processing.

Pros:

Adaptive: Can detect new and sophisticated bot behavior.

Positive User Experience: Only provide challenges to suspected bad actors.

Lower False Positives: Fewer legitimate users mistakenly blocked.

Cons:

Learning Period: Requires an initial training phase as platform is AI based.

Complex Implementation: Requires robust data collection and analysis.

Behavorial Analysis:

Bots can wreak havoc on online assets and Radware Bot Manager with its strong and robust layered approach towards bot detection provides acts as a line of defence against them. The solution does behavioral analysis on the source by executing advanced bot and anomaly detection algorithms on a cluster of requests to identify malicious patterns. Good requests (humans and good bots) are allowed to access the customer asset while bad ones are mitigated.

Safeguarding User Experience:

Radware Bot Manager has a very strong focus towards ensuring a positive user experience for genuine users accessing applications protected by us. Mitigation challenges are only to malicious bots and unwanted traffic, thereby hot hampering the user experience of legitimate users and good bots. Good user experience is maintained due to the accuracy and effectiveness of the solution.

Real-time Monitoring and Reporting:

Radware Bot Manager provides real-time monitoring and detailed reporting on bot activities. This not only aids in understanding the threat landscape of the protected digital asset but also enables organizations to fine-tune their security measures based on evolving patterns of bot behavior.

Self Service:

Radware Bot Manager provides multiple self-service capabilities like choosing the mitigation options which should show to the bots after they are caught, enabling / disabling of security modules, create custom policies, creating your own allow / block list etc.

Advanced Bot Detection Capabilities:

Radware Bot Manager leverages AI / ML capability to detect and bot attacks. It continues to add these new capabilities for each customer and provide the necessary control for them to enable / disable as and when required.

Multiple newer AI capabilities have been recently introduced. Some of the recent new capabilities include ability to detect sophisticated bots that attack by rotating their identities, advanced machine learning security modules that detect bad bots based on analysing and finding anomalies based on HTTP headers, CAPTCHA farm detection module that can accurately detect 3rd parties and effectively mitigate them.

Bot Intelligence:

Radware Bot Manager maintains a history of behaviorial data of all bad bots that were caught in the past from customer applications. This data is leveraged as intelligence to mitigate bots in all digital assets of all customers.