Uncover malicious API activity to decrease the potential of a major security breach
There is no way around it – study after study shows that security breaches cost millions. And with APIs being the most frequent attack vector for application attacks according to Gartner, it simply makes financial sense to do everything you can to protect your production APIs during runtime.
Unlike when they launch more traditional attacks, bad actors targeting APIs use far more subtle methods to uncover and exploit vulnerabilities. They’re looking for business logic flaws they can exploit to access data they should not be able to get. For example, attackers often obtain access to an API – in many cases using valid credentials they’ve established – and then manipulate elements of an API request to find a logic gap and exploit it to abuse an API or gain unauthorized access to systems or data.
Hackers have to do a lot of experimentation to find these business logic flaws, so this reconnaissance activity can take days and weeks. And the API manipulations used during recon are often subtle, so you need sophisticated – and accurate – anomaly detection to spot them. Combining big data with AI and ML will enable you to capture and baseline all API traffic and spot these deviations. Given the duration of API attacks, you need to apply cloud-scale big data to this problem, so that you have enough context over time to find these attackers.
