Introduction

Bot management is a strategy that is based on what does a bot do understanding. It employs detecting activity, the source and nature of the activity of bots before one allows the filtered bot to access web assets. Let’s learn about bot management, bot systems, bot activity, bot control, bot strategy, manager bot, what does a bot do in this article.

  1. What is Bot Management?
  2. How Does Bot Management Work?
  3. Why is Bot Management Important?

1) What is Bot Management?

Bot management tools use machine learning, security tools and web-development technology to assess and block malicious activity while allowing the legitimate bots to operate unhindered. They include UBA (User Behavioral Analytics) (UBA), bot pattern databases and WAF (Web Application Firewalls) operating to block, after interception any unwanted network traffic not based on business rules and real-time analysis.

2) How Does Bot Management Work?

When malicious bot systems access assets, they overload servers and cause DoS or denial of service and slowing of the system. Some malicious bots are deployed to scrape content and steal assets like system files, proprietary and credential-based assets etc., which are used when phishing, planning cyber attacks and to send spam content. Thus bot management is essential to prevent security and performance parameters from impacting the site.

When bot management systems are overstrict and falsely recognize bot activity, it could disrupt the organization’s business. For example, blocking the Google server search engine bots could lead to loss of legitimate traffic, poor conversions, and hence loss of revenues. Blocking the home-grown bots used for automation and testing can similarly cause disruptions in important business activities. Thus, the main tasks for bot management techniques are to distinguish malicious from legitimate bots and identify sophisticated attacker bots emulating human users. There are 3 approaches to bot management.

  • Static approach tools use static information analysis to identify web requests and header information correlated with malicious bot control and can contain active/ known bots.
  • Challenge-based approach tools pose active tests/challenges to identify bots. Ex: CAPTCHA verification, acceptance of cookies or the ability to run JavaScript.
  • Behavioural approach tools evaluate and match the activity of potential users with known patterns to verify user-identity and make a distinction between human users, bad and good bots.

3) Why is Bot Management Important? 

Bot management is a must for the operational security of all organizations as poor bot strategy can cause mild to severe implications and revenue loss. 

Some of its uses are

  • It can block Distributed Denial-of-Service (DDoS) attacks, where a network is used to spam servers with packets of requests and overwhelm the processing resources and bandwidth causing internet disruptions.
  • Prevents credential stuffing where bots automatically try lists of stolen credentials until one is accepted, providing criminals access to user accounts and systems.
  • Avoid credit/ gift card fraud accounts being broken into and create counterfeit cards used for cash value exchange, allowing the stolen information to be used for large purchases.
  • Check intelligence harvesting attacks using bots to scan and crawl social media, web sites, forums etc., for user’s personal information and perform phishing attacks mimicking the authorities to gain confidential information like passwords and OTPs.
  • Stop web scraping protected content attacks using bots on storage resources and sites to extract proprietary information/assets like logos, pricing data, branding materials, hidden files or product information from vulnerable eCommerce, online gaming, ticketing and airline booking sites.

Some benefits of a modern bot management solution are

  • Sifts spam mail attacks that can corrupt the database and leads to extra costs on data cleansing. Thus the lead data and brand is protected from illegitimate spam content.
  • Fast and easy solution deployment requiring no maintenance, complex configurations, or third party JS instrumentation wherein auto-suggestions recommend rules.
  • Configurability and control through in-house rules using the technique of defining the scope of rules with different attributes like specific paths, the request method, score sensitivity etc. and use methods like captcha, accept cookies etc.
  • Rich logs and analytics are provided on a dashboard providing bot traffic details, rich request metadata for every request and bot scores allowing one to analyze and correct the solution through drill-downs, time-series graphs, 3rd party SIEMS solutions or even BI applications.

Conclusion

Effective bot management uses all 3 techniques to ensure the identification of the largest number of bots, recently created ones and those with dynamic behaviour. Manager bot services use automated tools to apply the strategies and monitor the API traffic while implementing rate-limitations to prevent abuse of API abuse by using the landscape of bots and not a single IP. A successful bot management solution investigates all site visitors, has DDoS protection in real-time, use CDN to reduce bandwidth costs, accelerate dynamic websites/ APIs and cache static resources at the edge. The enterprise-class cloud WAF permits only legitimate traffic while ensuring the applications and APIs work within the Gateway WAF of the network while RASP is used to protect against zero‑day and known attacks.

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