5 Most Ignored Signs of a Malicious Bot ATTACK!
According to a 2017 survey, bot traffic has surpassed human traffic on the Internet.
What is Modern botnet and why they are dangerous?
The modern botnet is one of the sophisticated cybercrime techniques. A botnet is a collection of internet-connected devices infected by malware that lets cybercriminals control them. The botnet attack is commonly used to get unauthorized access, data theft, DDoS attacks, and credentials leak.
Because of their complicated size and the challenges involved in detecting them, botnets can be operated secretly so that victims can’t sense them. Some software updates are also bots. Simply put, our digital technologies are surrounded by unavoidable bots.
But that doesn’t mean your network is destined to be attacked by bots. You can protect your network by identifying these malicious robots and you don’t have to be a skilled data scientist.
So How to Identify Malicious bots on your network?
All you need to do is follow the steps given below.
- Keep an Eye on the Uniformity of Communications:
First, try to distinguish between bots (both bad and good) and humans. You can do this by identifying those machines that continuously communicates with a victim.
Bots communicate with their targets because they require commands, signals, and data. You need to find out the hosts that stay in touch with their targets periodically and continuously. Weekly traffic is sufficient to figure out client-target communication. Uniform communications are likely to be generated by a bot.
- The Rate of Failed Login Attempts is Quite High:
One of the popular uses of bots is to steal passwords—a practice that is also known as ATO attack. A botnet will try to take control of user accounts by testing user-password combinations obtained from other sites. This way, botnets might attempt to legalize millions of accounts per day. If you’re struggling with your passwords, it might be the sign of a bot attack. You can use analytic tools like Google Analytics and your access logs to track those failed login attempts over time.
- Identify Malicious Bots within Browsers:
Another way to identify malicious bots is to look at particular information contained in HTTP headers. Internet browsers generally have clear headers’ image. In normal browsing, the link within a browser will generate a “referrer” header that will be included in the next request for that URL.
However, traffic generated by a bot might not have a “referrer” header or it will look “fake”. The bots that look the same in every traffic flow are likely to be highly malicious.
- Failing of Gift Card Numbers:
Botnets are also used to steal the value from genuine gift cards. It is easy to target gift card accounts with bots.
This is because companies don’t ask for a billing address, account name or personal info when attackers get their hand on gift cards account. That’s why attackers can use several combinations to get valid pairs of card numbers and pin codes. When an invalid pair is made, it generates a failed validation notification. If your gift card validation fails several times, consider it a solid signal that bots are attempting to steal your customer’s gift card balances to resell them on the dark web.
- Increase in Irregular Page Viewing Patterns:
A human customer is likely to check the things that appeal to them. They look for their desired items and check out. What if they check every single product page on your website—or even half of those pages?
Scraper bots are used for this purpose as they are only aimed at the product pages. Those bots also visit the search page numerous times during a session. Unusual sessions generally include ridiculous searches and can be a sign of a bot attack. Besides, those sessions could be longer as it takes bot time to copy content in large volumes.
So these are the things to look for in your network to keep the risk of malicious bots at a bay. Plus, you can install effective anti-malware software to add extra layers to your cybersecurity.
What do you think? Let us know by commenting below.