For years, I have been focused on finding the optimal way to detect threats. However, this is a highly complex task, as there is no absolute method to definitively determine whether an activity is malicious, unless you only rely on low-level indicators. It is true that certain behaviors can be considered malicious in most cases, such as a process loaded from AppData using a TrustedInstaller token, but this is not something that occurs frequently. In other scenarios, such as the use of anti-debugging techniques in BOF (Beacon Object File) through NtDelayExecution, identifying the optimal detection point can range from simply searching for the sleep import in an executable to inspecting thread call stacks. While both approaches are effective, thread stack analysis is significantly more precise, though at a higher cost than analyzing an executable’s import table. This reality highlights the need to establish a strategy that enables defensive teams to do more with less, which is why I will discuss the concept of Resilient Detection, not only from a technical standpoint but also from a broader, strategic perspective.
First and foremost, it is necessary to understand the current ecosystem. Today, and particularly in this part of the hemisphere, the digital ecosystem is composed of Windows and Unix systems, major public cloud environments (Azure, GCP, and AWS), the global supply chain, Artificial Intelligence and essential services such as email, identity, and application platforms. The dynamic nature of this ecosystem introduces new needs, opportunities, and challenges for adversaries and, in parallel, new detection strategies.
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