Wanting to maintain a traditional traffic monitoring model, based on packet analysis, anomaly detection, and border inspection, is wasting precious time of IT teams. This happens because advanced techniques are increasingly being developed to evade detection by classical systems, using loopholes that remain invisible to security tools based solely on network traffic.
Indeed,72% of respondents in a global survey by the World Economic Forum 2025, reported an increase in organizational cyber risks, reflecting how threats evolve to hide from traditional defenses. Furthermore, fileless attacks have10 times more chances of success compared to traditional file-based malware attacks.
Cybercriminals no longer act through trial and error. Today, they act in a precise way that leaves no traces. They heavily utilize fileless attacks, exploit legitimate system tools such as PowerShell and WMI to execute malicious commands without raising suspicion, and move laterally across the network silently, as if they were already part of the environment.
This type of attack is intentionally designed to appear legitimate, the traffic does not raise suspicion, the tools are not unknown, and the events do not follow common threat patterns. In this scenario,According to the World Economic Forum 2025 report, 66% of organizations believe that artificial intelligence will have the most significant impact on cybersecurityboth for defense and for attacks, reflecting a paradigm shift.
Traditional solutions, such as firewalls, IDS, and simple correlation systems, no longer provide the necessary protection, especially since 47% of organizations cite adversarial advances powered by generative AI as their main concern. In addition, 54% of large organizations identify supply chain vulnerabilities as the biggest barrier to cyber resilience, increasing the complexity of the challenge.
The role of granular visibility
In this scenario, granular visibility emerges as a fundamental requirement for an effective cybersecurity strategy. It is the ability to observe, in detail, the behavior of endpoints, users, processes, internal flows, and activities between systems, in a contextualized and continuous manner.
This approach requires the use of more advanced technologies, such as EDR (Endpoint Detection and Response), XDR (Extended Detection and Response), and NDR (Network Detection and Response). These tools collect telemetry across various layers, from the network to the endpoint, and apply behavioral analysis, artificial intelligence, and event correlation to detect threats that would go unnoticed in environments monitored solely by traffic volume.
Techniques that explore invisibility
Among the most common tactics used in stealth attacks are:
- DNS tunneling, data encapsulation in seemingly normal DNS queries;
- Digital steganography, hiding malicious commands in image, audio, or video files;
- Encrypted command and control (C2) channels, secure communication between malware and their controllers, making interception difficult;
- These techniques not only bypass traditional systems but also exploit flaws in the correlation between security layers. The traffic may appear clean, but the actual activity is hidden behind legitimate operations or encrypted patterns.
Intelligent and contextual monitoring
To deal with this type of threat, it is essential that the analysis goes beyond Indicators of Compromise (IoCs) and begins to consider Indicators of Behavior (IoBs). This means monitoring not only "what" was accessed or transmitted, but also "how," "when," "by whom," and "in what context" a particular action occurred.
Furthermore, the integration between different data sources, such as authentication logs, command executions, lateral movements, and API calls, allows for the detection of subtle deviations and a faster and more accurate response to incidents.
What does all of this mean
The increasing sophistication of cyberattacks demands an urgent reevaluation of digital defense practices. Traffic monitoring is still necessary, but it can no longer be the only pillar of protection. Granular visibility, with continuous, contextual, and correlated analysis, becomes essential to detect and mitigate invisible threats.
Investing in advanced detection technology and strategies that consider the actual behavior of systems is, today, the only effective way to face adversaries who know how to hide in plain sight.
