Consider companies that are under threat from AI-assisted attacks. Hackers used generation tools and LLMS to write code designed to be difficult to target a particular dataset. At first glance, this scenario may seem overwhelming.
Simple: Start with the basics.
First, identify important data. Given the vast amount of information generated and collected by businesses now, it is impossible to protect all data at the same time. Identifying key digital assets such as financial, intellectual property, and HR data allows businesses to focus their protection efforts.
Next is to track the IOA. By implementing processes that help identify common attack characteristics, teams are better prepared to respond when threats appear. A typical IOAS can include a sudden increase in certain data access requests, no identifiable cause of performance issues in widely used applications, or an increase in the number of failed login attempts. Armed with this information, teams can better predict the likelihood of attacking passes.
Finally, the Zero Trust model can help provide a protective breakwater if an attacker compromises login and password data. By always using a verify approach that uses a strong authentication process and paired combination of behavioral and geography data, your business will irritate your attackers at the ultimate hurdle.
