You can usually identify how much of an attack you can withstand. To make things worse, DDoS malware is typically very sophisticated and employs techniques to overload your server as efficiently as possible, for example by sending incomplete connection requests that cause wait states on your system, during which the attacking system can send new requests. The number of machines at the attacker’s disposal depends on the number of machines infected, but it can be in the tens of thousands. The attacker uses a centralized system that then tells these malware-infected machines to send traffic to the site.

DDoS attackers infect user systems (that can mean computers but also embedded systems or IoT devices) with software that allows them to control them around the globe. During the attack, there isn’t one source, so you can’t just filter one IP to stop it. As you can probably guess, this means a crash in your service and loss in revenue for as long as the attack continues.ĭDoS attacks can be devastating to an online business, which is why understanding how they work and how to mitigate them quickly is important. The server crashes, or there just isn’t enough bandwidth to allow true customers to access your web service. With enough traffic, an attacker can eat away at your bandwidth and server resources until one (or both) are so inundated that they can no longer function. In short, a DDoS attack is a flood of traffic to your web host or server. Automated DDoS monitoring gives your security team more bandwidth to focus on other important tasks and still get notifications should anomalies happen as a result of a DDoS event. A while back, we covered how you can check your Windows IIS and Loggly logs to view the source of a DDoS attack, but how do you know when your network is under attack? It is not efficient to have humans monitoring logs every day and every hour, so you must rely on automated resources.

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