Cybersecurity Automation Counters AIPowered Attacks and FortiGate Exploits 

Cybersecurity automation is becoming the mainstay of the defense against AI-enabled threats, which are changing the attack landscape quickly and radically. Being first on the scene, the malicious use of AI by the hackers who analyze and exploit vulnerabilities of Fortinet FortiGate is the case point. The online retail and telecommunications sectors, which have been recently compromised, are a case in point of how automated reconnaissance leads to compromises by stealing credentials and further abuse of VPNs in a matter of minutes after bypassing traditional defenders.  

Businesses are responding by investing in AI-assisted Security Orchestration, Automation, and Response (SOAR) platforms, Extended Detection, and Response (XDR), as well as Managed Detection, and Response (MDR) services that are built around machine learning to perform real-time threat hunting and automated isolation. First of all, these solutions fight against the overload of security alerts by ranking anomalies with the use of User and Entity Behavior Analytics (UEBA) and carrying out measures such as blocking IPs or isolating endpoints independently of humans. Secondly, AI-based predictive models are at present capable of predicting the methods used in attacks by learning from the past data, thus preparing schedules of work that may help to reduce the time taken for incident response significantly.  

In addition, organizations are also turning to micro-segmentation and behavioral analysis with which they are restricting the movement in their environment of the attacker, taking a view that in fact some systems will be compromised but damage will be kept to the minimum level through automation. This trend is further driven by regulatory requirements since the frameworks are outlining the need for lead time to recovery, continuous testing, and the like due to the increasing risks of ransomware and supply chains.