Machine Learning-Powered API Abuse Detection Dashboard
Abuse detection API service is when someone uses your service to do something that goes against its intended purpose or harms it in some way. This can include things like data scraping, or an attacker using your API to perform actions that suck up all the resources needed for other users. Variation abuse API attacks, such as rate limit evasion, are difficult to detect because attackers exploit lawful functionality and manipulate it to achieve their malicious goals without triggering any static security alerts.
With a machine learning-powered API abuse detection dashboard, businesses and organizations can detect these attacks before they cause significant damage. The abuse detection dashboard in Advanced API Security monitors API traffic and uses machine learning algorithms to identify suspicious patterns of behavior that may indicate an attack. These ML models have been trained and tuned by Google’s internal teams to help protect their public-facing APIs.
Top Abuse Detection API Services to Protect Your Platform
The dashboard shows a list of incidents in your environment and information about those incidents. You can also view detected traffic related to the incidents. To archive an incident, select Archive at the top of the Incident details view. The button label then changes to Unarchive.
In addition to detecting abnormal patterns, the ML model looks at many other factors to determine if an incident is suspicious. For example, it analyzes time intervals between requests to see if they lack randomness, and compares query behavior to determine whether an attacker is trying to exploit a vulnerability (such as outdated browsers or platforms). You can enable or disable the use of your data for training the ML model on the Abuse detection page.