The cyber kill chain framework is used to understand and describe various stages of cyberattacks, such as ransomware, from initial reconnaissance to data exfiltration. Hackers use AI to scale up their attacks through automation, improve targeting, and hide lateral movement across the network.

Preparation

AI will automate the collection and analysis of data to identify potential targets and vulnerabilities, craft emails, and generate malware designed to evade detection.

Outsmart AI with AI

AI techniques make phishing and social engineering attacks easier to detect, and logs with credential access can be analyzed faster for anomalies. Sifting through network-level traffic data can be done more efficiently with natural language processing. Detection of lateral movement, suspicious files, folders or system activities is easier. Security teams can use AI to detect threats earlier in the cyber kill chain, making their defenses and responses more effective than traditional security measures.

Improved threat detection and intelligence

Machine learning algorithms analyze email traffic and network activity to establish a company’s baseline behavior and then identify anomalies related to potential attacks, such as unusual traffic, emails, or unexpected user behavior. AI’s pattern recognition capabilities excel in identifying complex attack patterns, recognizing evolving techniques, and using predictive analysis to anticipate future threats.