What are Bots? How to Prevent Bad Bots Attack on your Websites?

What are Bots?

A bot is simply a computer program designed for automatic operation over the Internet. It can include a very simple and repetitive type of activity, such as collecting information from sites; or more complicated functions can be implemented directly, in live interaction with users.

Its speed in processing data could take place on bots faster than a human, allowing them to penetrate every single area, such as in search engines and to offer support to customers.

What is Bot Traffic?

Bot traffic is just the number of visitors to the site who happen to be generated by automated programs or “bots” other than humans.

The bots do things like index web pages for search engines, scrape content, and test websites for security among other things. The bots can be broadly classified into two types, good bots and bad bots.

Also Read: Data Encryption: Protecting Privacy and Preventing Breaches

The good bots include search engine crawlers such as Googlebot, which are used to improve the visibility of a website by crawling the pages so they could find their information in fewer time steps for bettering search results. The others include monitoring bots that observe the uptime and performance of the website.

Bad bots are mainly used for malicious stuff like data scraping, DDoS attacks, spamming form submissions, unauthorized logins, and content theft.

These can have real bites on resources, cause the site to become extremely slow, produce false analytics impressions, and in a serious manner compromise your data breach.

So, with the presence of bad bot traffic, web sites would be going slower than before, or miscalculations of analytics, or compromised security due to the attackers.

How to Detect Bot Traffic?

Analyzing Traffic Patterns and Anomalies

Method: The traffic patterns by bots are quite odd given spiky behaviors suddenly happen and requests at high rates in one IP address or sometime in odd time during off peak hours. All of those things are miles away from normal human behavior.

Implementation: One can make use of analytics tools such as Google Analytics or Adobe Analytics, among others, in order to track the trends of traffic.

This helps set up alerts regarding abnormal spikes or unusual patterns in traffic behavior such as page views per session with higher values than normal and unexpected rates of requests.

Track User Activities

Method: These bots tend to be acting in a deterministic and repeating pattern. Most of them don’t pretend to be humans and many click-through at a consistent speed and rapid rate, short session time, and avoid events that would generate interaction like scrolling, clicking, or submitting forms.

Implementation: Using Hotjar and Mixpanel for session tracking would trace the behaviors of a user on pages.

The average session duration and scroll depth and even the rate of interaction would be measurable to look into sessions with no interaction at all. In particular, these might probably be marked as bot activity.

Identification of Some of the Sources with Very High Bounce Rates

Method: The site-visit bots exit the web page within a second causing a high bounce rate particularly from a given set of referrers or even geographical locations.

Implementation: Monitor the analytics tool for a bounce rate. Apply a filter based on source/region/referral URLs to gain insight into the pattern of high bounce traffic Identify high suspicious bounce rates coming from some IP ranges or geolocations where your audience isn’t located.

Identification of Pages with Heavy Volume, but Low Engagement

Method: Bots load pages but do not interact with content. This is an example of how high page views combined with low engagement rates, say no form submissions or no downloads of content, are indicators of bot traffic.

Implementation: Track engagement metrics-per page or session-through your analytics tool, such as click-through rate and download rate. Lots of page views with no conversion or interaction might indicate the presence of bots.

IP addresses and User Agent Monitoring

Method: The same IP address is reused multiple times, or there is a cycling of a set of known IP addresses. Both user-agent strings may look unusual or be generic, such as “Mozilla/5.0” with no specifics included.

Implementation: Use web server logs or security tools such as AWS WAF to log and analyze incoming traffic’s IP addresses and user agents. Cross-check with known bot IP databases and use tools such as Bot Manager by Akamai to detect bots based on user-agent patterns.

Scanning to High Frequency of Requests

Method: Multiple hundreds of requests in extremely short time scales far, far exceed normal user behavior. This is manifested with numerous successive requests to essentially the same pages, at least in the space of a few seconds.

Implementation: Log every request that comes from any IP address over time. Set rate limits so that any IPs that send too many requests would be caught by most security tools like SiteLock or Content Delivery Networks, like Cloudflare.

Inclusion of CAPTCHA Challenges

Method: CAPTCHA or reCAPTCHA tests are designed to determine the difference between human and bot behavior by presenting them with tests that most bots cannot satisfactorily complete.

Implementation: CAPTCHAs should be deployed across forms, login pages and high-value actions like registration of accounts. It would deploy a tool such as Google reCAPTCHA whereby it ensures that the legit user can perform the desired action but blocks or filters most of the bot activity.

Implement honeypot fields in Forms

Method: The hidden form fields are the honeypots, and the bots tend to fill up honeypots. The bots fill up all form fields, including the honeypots, hence it captures the bots.

Implementation: Adding hidden form fields via CSS or JavaScript and tracking of submissions, on which when a hidden field is filled, flag that session as bot traffic.

Install Bot Detection Tools and Services

Method: Leverage dedicated bot detection and management services that operate on the basis of machine learning and behavioral analysis to identify bots.

Implementation: It deploys advanced algorithms on such platforms as Distil Networks, PerimeterX, Cloudflare Bot Management, and Imperva where the services analyze behavioral patterns as well as fingerprinting of the devices or other signals for proper filtering and identification of the bot.

Sporadic Pattern of Geographical Distribution of Traffic

Method: If your average user base is coming from particular regions, a sudden rise in traffic coming from unknown locations or regions known to have bot farms may indicate the presence of bots.

Implementation: Geolocation tracking using analytics tools will enable traffic source tracking. Mass traffic coming from a new location can be analyzed for checking if it is actually a good traffic source or bot.

How to Prevent Bad Bots Attack?

Block or CAPTCHA Outdated User Agents/Browsers

Explanation: Most bots utilize outdated user agents or browsers since they do not have the newest security protocols and are easy to manipulate on the part of an attacker. Filtering requests with user-agent strings outdated can prevent or challenge suspicious traffic at a site.

Implementation: This is achieved through configuring server rules or settings of the Content Delivery Network to deny or challenge outdated browsers or prompt them to solve a CAPTCHA. In this way, the website denies access to the users using outdated browsers and the bots using old generic user agents are blocked out.

Block Known Hosting Providers and Proxy Services

Explanation: Most bots come from IP addresses of cloud hosting services like AWS, Google Cloud, or Azure and proxy servers. Blocking the known sources would certainly curtail the bot traffic that’s coming from these automated scripts.

Also Read: What is Website Security? 10 Ways to Make Your Website Secure

Implementation: Keep a dynamic list of major hosts and proxy service providers, filter these ranges on your server using their firewall or WAF and include an IP intelligence service that dynamically adds all of those IPs known to start from malicious activity in your block list.

Protect Every Bad Bot Access Point

Explanation: Bots can hit any number of endpoints on your site-from login pages and forms to search bars and APIs. Each of these points of access is an open invitation for bots to abuse your site in ways that are unintended.

Implementation: Lock all the access points with CAPTCHAs, rate limiting, and bot detection algorithms. The APIs need to be tokenized along with sensitive endpoints such as login pages or registering pages that must be monitored for anomalies.

Carefully Evaluate Traffic Sources

Explanation: Sometimes, the sources of traffic may seem suspicious or unknown. For example, an unknown referrer URL may be from places known to be unusual for one’s geographic location, either in high-risk networks and other places.

So, traffic sources can be watched as bot traffic can now easily be detected and filtered well before it hits crucial portions of your site.

Implementation: Analytics tools can identify the referring URL, source region, or traffic pattern.

CAPTCHAs or more restrictions can be implemented at the IP layer if it is coming from a specific unknown or high-risk geography. The higher bounce rate or engagement on a given source traffic is the primary indicator of bots.

Investigate Traffic Spikes

Explanation: Traffic spikes, often unidentified, are generally the case of bot attacks when traffic surges at unusual times or from unusual IP addresses.

Bots directed toward a website may trigger spikes in traffic, and may overwhelm servers to create congestion for legitimate users.

Implementation: Be monitoring for sudden surges of traffic and analyze them to know whether they are real or not.

Tools for monitoring will be helpful in ascertaining what type of traffic is, and these include IP ranges, user agent strings, and behavior patterns which ought to point out the bots.

Monitor for Failed login attempts

Explanation: The bots often combine credential stuffing and brute-force attacks by using a username and password combination for login attempts. A lot of failed login attempts within a short period of time may indicate bot activity to gain unauthorized access.

Implementation: It incorporates the rate limiting on the attempts for login and also alerts ability if the failed logins exceed the specified levels.

CAPTCHA challenge after several failed logins is meant to prove whether the user is a real one as well as gives the users multi-factor authentication which goes a long way to secure the user accounts.

Monitor increases in Failed Validation of Gift Card Numbers

Explanation: Bots often key in stolen gift card numbers hoping to find active gift cards. An increase in denied gift card validations most of the times is an indicator of the presence of bots to verify valid card numbers.

Implementation: Monitor and track the gift card validation requests, marking IP addresses or sessions that have a failure rate higher than the set threshold.

Set rate limits on validation requests and challenge some of the requests with CAPTCHA to prevent automated access against your system. Regular review and monitoring of gift card validation logs for suspicious activities.

Pay Close Attention to Public Data Breaches

Explanation: Public credential breaches encourage attacks from credential stuffing as other sites use the stolen credentials. Industry news and breach alerts will keep you up to date on new security threats that may adversely affect your site.

Implementation: Check publicly known data breaches against your user database to detect which accounts are compromised. Alert users whose accounts could be compromised to change passwords.

Use proactive security techniques such as account lockout and enhanced monitoring to keep your website from being exposed to credential-stuffing attacks.

Evaluate a Bot Mitigation Solution

Explanation: Bot-specific mitigation solutions would provide advanced detection and response capabilities for bot management.

These include machine learning and behavioral analysis so they are actually able to differentiate between human-originated traffic and one from bots. They learn over time what new behaviors the bots assume.

Implementation: You can implement a bot management solution, such as Cloudflare Bot Management, Distil Networks, or Akamai Bot Manager.

All these have features like device fingerprinting, behavior-based detection, and automated blocking of bots so you can focus on actual traffic while protecting your website from ever-evolving bot threats.

Conclusion

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