What’s changed: The evolution of traditional guidance (the threat landscape)
Traditional cybersecurity guidance emphasized antivirus protection (AV), network firewalls, and periodic vulnerability scanning. Today, these measures are part of baseline cyber hygiene rather than comprehensive defense.
Traditional antivirus vs. novel attacks
Traditional antivirus tools (AV) compare files against a database of known malware, which is efficient for blocking off-the-shelf threats but struggles with polymorphic or custom malware that constantly changes its signature. With new malware being created every second, traditional AV may also miss unknown signatures.
Visibility gaps
Organizations’ ever-expanding attack surfaces of cloud environments, SaaS applications, and OT and IoT devices have increased the risk of visibility gaps due to unmonitored assets or unlogged data flows (network traffic that passes through an environment without being recorded or analyzed). This lack of visibility is significantly more dangerous than security tools that don’t have all of the latest features.
For example, “Shadow AI,” employees using unauthorized AI tools, has become a major visibility gap, as has the increasing number of cloud environments businesses employ. Many organizations don’t monitor internal "East-West" cloud traffic flows, allowing attackers to move laterally between cloud environments.
Persistence over speed
Ransomware-as-a-service (RaaS) has accelerated many ransomware attacks (some payloads deploy in under 15 minutes); however, more sophisticated threat actors have increasingly been avoiding “loud” attacks (e.g., immediate, widespread file encryption) in favor of “low-and-slow” techniques. This approach is about attackers maintaining a silent, authorized lifeline into the network while they find high-value data to exfiltrate and encrypt for double or triple extortion.
Increasingly, attackers use techniques like command and control (C2) and living-off-the-land (LotL), hijacking legitimate administrative tools, such as PowerShell, to conceal their activity. As actors silently map networks, escalate privileges, move laterally, and steal data, they also deploy survival mechanisms (e.g., registry run keys, malicious services) to maintain access even after reboots or credential changes.
Identity is the new perimeter
The shift toward cloud infrastructure and SaaS has put identity credentials on the front lines of defense. A rapidly increasing number of machine identities (e.g., APIs, microservices) has further broadened the attack surface. With their often high-level permissions and historically limited oversight or MFA protection, these accounts are prime targets.
From brute force and credential stuffing to sophisticated spear phishing, OAuth attacks, and MFA fatigue, attackers have a deep playbook of credential abuse techniques. These tactics allow them to simply log in, rather than trying to hack through a firewall.
The AI arms race: offense and defense
AI is a double-edged sword in cybersecurity. Threat actors use agentic AI to automate reconnaissance and vulnerability discovery. Generative AI allows them to craft highly convincing, targeted spear-phishing emails, as well as deepfake audio and video.
Meanwhile, security teams use AI for predictive detection, identifying anomalous behavior that deviates from baseline activity patterns. Automation can also assist with risk-based prioritization and filter out false-positive alerts, reducing alert fatigue.