All industries are grappling with a major problem which is bad bot activities which lead to many complex attacks on networks and infrastructure.
Every industry that uses the Internet to maintain its business has a common problem: the Big Bad Bot problem. So what is this problem? These are the bad bots that roam the entire web application to gather the information which can then be used by the attackers to exploit the web application. And the solution brings anti-bot protection techniques to block and mitigate the activity of bad bots.
According to research done by R&D department of Haltdos.com, it was found that bad bot traffic increased by 19.2% YoY for APAC region from 2020 to 2021, while for Global region, the increase was limited to 3.8% YoY from 2020 to 2021. As the increase in bad bot activity for the PAC region has caused a lot of concern in the cybersecurity industry, the The good bot activity that is important for businesses in terms of ranking on the SERP page has not seen as much growth.
So what are bad bots? These are software applications that perform automated tasks over the Internet. And when they start reconnaissance activity for potential attackers and start mutating into many advanced robots. They mainly pretend to be search engine crawlers, easily hiding behind known anonymous proxies and keeping changing IP addresses.
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Depending on their activity, bad bots can now be classified into four categories. Starting with very simple bots, whose sole purpose is exploit recognition and testing. After that, they evolve into headless robots, which usually take the form of a script that is either run on a schedule or triggered by an external system event. The primary goals of a headless bot can be defined as credential stuffing, scraping, and spamming. Next comes a much more sophisticated category of bad bot, capable of mimicking real human behavior. Under sophisticated bad bots we have interactive bots and behavioral bots which are capable of API abuse, account takeover, carding, scraping, spamming.
According to research done by the department haltdos.com, the traffic distribution of the different categories of advanced bots is as follows: the simpler bots take the least traffic distribution with only 10%, while the majority of the traffic distribution was seen by headless bots with around 45%%, as they are mostly deployed in activities such as recognition and scratching. Sophisticated bots like interactive bots and behavioral bots have a traffic split of 30% and 15% respectively.
If we look at the breakdown of bot activity by industry, we see that bad bots are wreaking havoc in the financial sector, followed closely by the education and SaaS sectors. The lease industry impacted by bad bot activity is the e-commerce and healthcare industries, followed closely by the gaming and digital content and advertising industry. Good bot activity mainly plays a role in the digital content and advertising industry while there is almost zero good bot activity in the gaming industry, according to research by the R&D department of haltdos .com, although we look at bot activity on specific pages, we find bad bots mostly on login and product pages, while good bots can be seen crawling on the homepage, category and product pages.
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Along with simpler bot protection techniques that can be implemented to detect and mitigate bad bots, the most common and trusted technique in the industry is to implement captcha and JS challenge, which can be run to the user trying to login, fill out a form or even on the very first visit to the web application. Have a good Intel anti-bot threat with known malicious user agent data set, anonymous proxy list and IP reputation to strengthen anti-bot protection. Also, industry experts believe that checking the search engine‘s crawler with a reverse DNS lookup can help identify whether the request is coming from a real human user or a bot agent. Bot protection can also be further enhanced by continuously monitoring the user session and blocking unsolicited POST requests. But there are also some hiccups when it comes to simpler bot protection techniques such as IP address blocking, geo-fencing, and bad user agent blocking.
Overcoming the challenges faced by simpler anti-bot protection techniques can be solved by advanced anti-bot protection techniques that industry experts can implement in their solution to provide much tighter anti-bot protection. Have advanced fingerprinting techniques with advanced detection of human versus automated traffic. HTML elements with dynamic names and IDs, browser fingerprinting and TLS fingerprinting are some of the advanced bot protection techniques. In addition, customer interaction fingerprinting and server-side user behavior analysis can help identify and analyze activity on web applications. Implemented mobile SDK and third-party SDK for API to provide additional anti-bot protection for mobile devices and mobile applications.
Preemptive anti-bot protection can be achieved by simply tricking bad bots into a tar pit or providing misinformation via decoys to disrupt the evolutionary chain of bad bots that allows them to produce data and helps them evolve from simpler bots to headless bots and finally too many sophisticated bad bots like interactive bots and behavioral bots. Therefore, preventive defense can be strategic in three phases. First, deploy, embed decoy links and forms, create decoy pages and advertise as something you are not. This deployment will act as the first sugar coated candy for the bad bots (flies), they will see it as a real source of information and pounce on it. Second, Monitor, where you need to detect bad bot activity on deployed decoy forms, links and pages. Engaging with bad bots and learning their behavior will help the security professional understand the bot’s intentions. And finally, Block, where you dynamically blacklist sources of malicious bots, improves bot ratings and creates application-specific bot behavior.
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