2024 was a monumental year for cybersecurity, with both defense triumphs and unfortunate breaches throughout the year. From the pervasive MOVEit vulnerability to successful government disruption of notorious cybergangs, lessons were learned about cyberattack strategies and the best practices to deploy against them. Like the threats cybersecurity stands against, the industry itself is ever-changing, continuously adapting to meet the next challenge. Given what we saw in 2024, here’s what we expect to see in 2025.
Generative AI has leveled the playing field for threat actors, as premium hacking skills are no longer required to wreak havoc. Malware as a Service (MaaS) powered by AI has made heavy-hitting attacks more approachable than ever by offering turn-key systems to anyone willing to pay. AI has also played a part in making newer variants of malware, yet another frontier for security analysts to defend. SOCs already deal with an influx of threats daily, so having technology that excels at identifying zero-day, multipart and custom threats helps organizations to take a proactive approach to security. Leveraging proactive behavioral learnings and feeding that data back into a security tech stack enables security teams to respond to alerts more efficiently and effectively.
Over 60 countries held elections in 2024. As a result, the world will have a number of power transitions throughout the course of 2025. CodeHunter’s Chris O’Ferrell notes that these transitory times are common targets for cyberattacks. Security leadership faces unique challenges, as political changes can introduce risks related to shifts in policies, personnel, priorities, and public trust. Learn more about this threat from our Administration Change blog series.
Malware often relies on multiple components working together, which can help hide its malicious behavior from existing solutions that rely solely upon signature matching to identify known malware. Overly strict identification rules will result in an overwhelm of alerts, especially false positives, that could reduce the urgency with which security analysts respond. However, identification patterns that are too loose will result in a delay in malware identification that can cost companies thousands in lost customer trust and regulatory fees. The identification of not only a known malicious sequence but its behavioral dependencies will be critical to protecting against more sophisticated attacks. Behavioral analysis looks beyond signature matching to analyze the code’s behaviors, providing deeper insight into its potential for harm.
The ongoing battle between legitimate AI used for cybersecurity defense and malicious AI used by cybercriminals to create more sophisticated and evasive malware is going to become a top security priority. Devising a plan for dealing with these tactics is key, so we expect a trial-and-error period to occur. We’ve already seen how AI can make workflows more efficient and complete routine tasks to free up human talent for more mission-critical efforts. However, not every AI addition boosts productivity or eliminates the need for human involvement. The cybersecurity industry will have to experiment with AI implementations to find the sweet spot that builds upon existing cybersecurity capabilities to defend against cybercriminals’ use of AI. At the same time as this unfolds, malicious actors will be taking advantage of AI’s possibilities as well, further expanding what malware is capable of.
The common use of dynamic analysis, maybe backed by static analysis, isn’t going to cut it as threats develop in 2025. The combination of static, dynamic, and AI analyses will be crucial for complete threat visibility to better identify malware. This robust analysis will provide more actionable insights, enabling the threat containment and triage processes to be executed with greater confidence. Modern cybercriminals attack quickly, building malware to target zero-day vulnerabilities that have yet to be detected or even those announced that are yet to be patched. Accordingly, security teams will have to respond to threats swiftly and accurately. Automation will empower SOCs to move quickly between the steps of the threat mitigation process, reducing mean time to detect (MTTD), contain (MTTC), and respond (MTTR) to minimize malware’s impact.