Threat X Labs - Blog

We need to face reality - web application protection is incredibly challenging in the agile, cloud-based world in which businesses operate. Many organizations focus their security strategy on the applications themselves - a never-ending pattern of "patch and pray." Trying to successfully guide applications through the barrage of attacks, multiple technologies, and growing sophistication of attackers is like trying to follow an obscure map. You can see your final destination, but there are new obstacles to face every hour. This fact, coupled with the frustration with the limited intelligence of legacy WAFs, has created overburdened security teams and "firewall fatigue."

In the first two parts of this series we discussed methods to identify and block a few different types of botnet traffic, namely commodity comment/form spam and slightly more targeted attacks like distributed password guessing. This final part covers a slightly different way of analyzing malicious web traffic: grouping attackers based on their behavioral characteristics.

The previous post in this series discussed comment spam, one of the most pervasive forms of 'botnet' web traffic and accordingly, one of the least targeted varieties of attack. Part II will discuss a more serious form of botnet traffic: Targeted attacks that are coordinated centrally and distributed across multiple actors in an attempt to avoid security controls.

Microservices and containers are a hot topic right now - and for various reasons. They are making the news because of their ease of use, but also for the challenges associated with protecting them. We'll start with the positives...In the realm of organizational growth and flexibility, microservices have various advantages. One such advantage is their ability to enable continuous refactoring of small parts of an application, which prevents developers from dealing with large product releases that tend to be more prone to bugs, backward compatibility issues, etc. Other key advantages of microservices include: 

• Independent scaling. Scaling can be limited to the parts of the application that require more resources

• Services can be implemented using different technology stacks

• More fine-grained testing of individual components

• Makes workflow failures easy to handle and recover from

• Easier to distribute development tasks across different developers or teams

We recently co-hosted a webinar with SANS Institute, Your Current Approaches to Threat Detection and Neutralization are Broken. During that webcast, experts from Threat X and SANS addressed the current challenges inherent in protecting your web applications in today's complex hybrid cloud environments, and the common inefficiencies of some legacy WAF approaches.

This discussion sparked various questions, some of which we receive quite often. In case you missed it, we compiled the answers to the mosts frequently asked questions.

The following is the first post in a three-part series surrounding bot detection and neutralization based on botnet analysis. The series will begin by addressing commodity form/comment spam. 

One of the unfortunate realities of running a site on the Internet is the amount of "background noise" -- the automated, unsophisticated, poorly targeted attacks, which make up the bulk of malicious web traffic. For the sake of this series, we're calling this 'botnet' traffic. 

In today’s complex cybersecurity landscape, it is very apparent that threats can and will originate from virtually anywhere and hardly ever follow predictable patterns. We consistently share this knowledge with our customers and use these insights to drive our product updates and roadmap.

This fact alone makes the task of properly securing your applications even more challenging. To effectively secure your applications, it is critical to implement security controls using the zero-trust model. That means you should not rely solely on external reputation sources, threat feeds, or patches. In fact, we have found that many of the threats we identify using behavioral analysis methods go undetected when using the more traditional methods. More accurate and reliable detection is critical to effective application security, especially when attacks come from the most unsuspecting of sources.