Bot detection is the process of analyzing all the traffic to a website, mobile application, or API, in order to detect and block malicious bots, while allowing access to legitimate visitors and authorized partner bots.
Detecting and blocking bad bots is crucial in preventing crime, fraud, website slowdowns and outages, protecting confidential data, and stopping bot activities such as content scraping, account takeover, financial fraud, denial of service attacks, API abuse, scalping, ad fraud, and other malicious activities.
How to Detect Bots
Detecting bots requires considerable analysis and sophistication, as it is crucial to have minimal false positives (i.e., humans being mistaken for bots) as well as false negatives (when bad bots are mistaken for humans). It is crucial to ascertain the intent of every visitor to a website, app and API for effective bot detection and management. Some basic ways to detect bot traffic are:
-
If you see any irregular spikes in traffic, take a closer look at it.
-
Check if a channel is contributing to most new sessions and users.
-
Multiple bot hits can slow down your server performance.
-
An increase in activity on your site from a remote location could be from bots.
-
A large number of hits from a single IP within a very short period of time points to bot traffic.
The growing sophistication of bots today requires specialized techniques. In the next section, we discuss which techniques or tools you can use to detect bots.
Why Organizations are Failing to Manage Rising Bot Attacks
Bot Detection Tools
Older methods of blocking bots generally relied on rule-based measures such as blocking IP ranges, countries, and data centers known to host bots. Web Application Firewalls (WAF) and Access Control Lists (ACL) have also been used to detect and block bad bots, but they are generally not as effective as a specialized bot management solution when it comes to detecting advanced bots that can mimic human behavior and rotate through thousands of IP addresses and device IDs.
In-house bot detection measures that some organizations initially deployed have several disadvantages compared to a specialized solution, and are thus ineffective in detecting the most advanced bad bots.
An anti-bot solution like Radware Bot Manager combines cutting edge technology and robust algorithms to detect, analyze and categorize bot patterns and signatures. Bot Manager leverages a combination of methodologies including unique device fingerprinting, dynamic Turing tests, user behavior analysis, and JavaScript challenges.
Our detection engine deploys various forms of machine learning (ML) to train algorithms based on known patterns and historical data to detect new types of bots and stop their attacks. Radware’s patented semi-supervised ML techniques help us detect the intent of every visitor to recognize malicious activities even in the absence of definitive bot signatures.
Free Bot Analysis: Radware Bad Bot Analyzer
JavaScript Bot Detection
Radware Bot Manager's API call and embedded JavaScript tag collect and share several parameters about the visitor for processing by bot detection engine. Bot Manager’s detection engine works in real time to analyze every visitor to a website, mobile application, and API, and develops a unique fingerprint for each visitor and bot.
If a visitor is a human or search engine or partner bot, Bot Manager allows access in a few milliseconds without slowing down the user experience. However, when a bad bot is detected, Bot Manager can block it, show a CAPTCHA, feed it with fake data, and other types of responses based on your organization’s needs.
To read how JavaScript injection helps in building a comprehensive bot detection solution for web applications, read this article.
Five Benefits of Integrating Bot Management with Your CDN
Essentials of a Bot Detection Solution
A bot detection and management solution should detect and manage every kind of bot ─ good as well as bad ─ based on an organization’s specific needs. It should work in real-time to identify bot traffic and take measures such as blocking, showing a CAPTCHA to solve, feeding it with fake data, or dropping the connection, among other measures. Bot management tools should also be able to easily integrate with a wide range of Web and application infrastructure architectures to suit the unique needs of their users.