Which one will shape your future in cybersecurity?

04 Tem 16:57

The biggest advantage of AI-assisted analysis is its ability to instantly detect and respond to real-time threats. Last year, while working at a financial institution, I saw an AI-based tool uncover a vulnerability that had taken us weeks to find during a traditional penetration test—all in just a few hours. Machine learning is so fast in log analysis and anomaly detection that manual checks are nearly impossible. Of course, these tools have limitations—human oversight is still needed to filter out false positives—but they’re so efficient that you can focus on more strategic testing afterward. On the other hand, I believe manual pentesting is unmatched when it comes to deep-dive analysis. Once, I spent a week manually examining a system to uncover a backdoor vulnerability that AI tools missed—one that could only be detected at the code level. Protocol-level errors or flaws hidden in business logic often slip past automated tools. That’s why the ideal approach is to combine both: use AI for large-scale scanning, followed by manual deep inspection. Instead of choosing one over the other, synchronizing their workflows will be the foundation of future cybersecurity strategies.