Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

In the evolving landscape of digital threats, two growing concerns are proving costly for organizations worldwide: insecure APIs and bot attacks. A recent report highlights that these vulnerabilities have escalated dramatically, with global firms suffering financial losses between $94 billion to $186 billion annually. The exponential rise in API adoption, combined with AI-powered bot attacks, has created a perfect storm for cybercriminals to exploit.

Earlier this week we had the pleasure of hosting a regional API Security Summit in Chicago (well, actually in Lombard). These summits bring together the local cybersecurity community for half-day of API Security-focused content, including expert speakers and panelists. While this isn’t the first time we’ve organized an event like this, it was memorable for the quality of content and participants.

In a groundbreaking move, some of the world’s largest telecom operators—América Móvil, AT&T, Bharti Airtel, Deutsche Telekom, Orange, Reliance Jio, Singtel, Telefonica, Telstra, T-Mobile, Verizon, and Vodafone—are partnering with Ericsson to launch a new venture aimed at transforming how network Application Programming Interfaces (APIs) are accessed and used.

Developers are constantly exploring new technologies that can improve the performance, flexibility, and usability of applications. GraphQL is one such technology that has gained significant attention for its ability to fetch data efficiently. Unlike the traditional REST API, which requires multiple round trips to the server to gather various pieces of data, GraphQL allows developers to retrieve all the needed data in a single request.

Consider the case of a malicious actor attempting to inject, scrape, harvest, or exfiltrate data via an API. Such malicious activities are often characterized by the particular order in which the actor initiates requests to API endpoints. Moreover, the malicious activity is often not readily detectable using volumetric techniques alone, because the actor may intentionally execute API requests slowly, in an attempt to thwart volumetric abuse protection.

We are excited to share the tremendous response to our Large Language Model (LLM) attacker summary feature. Since its launch, usage has increased by an amazing 800%, demonstrating its significant impact on our customers' daily operations.