Salt Security API Protection Platform

The Salt Security API Protection Platform manages securing rapidly expanding API ecosystems, which are increasingly targeted by sophisticated threats. This platform leverages a robust technical architecture that combines cloud-scale big data, machine learning (ML), and artificial intelligence (AI) to provide comprehensive API security.

At its core, the Salt platform employs an AI-based runtime engine that correlates activities across millions of APIs and users, delivering adaptive intelligence with real-time analysis and continuous insights. This engine is fueled by the largest data lake in the API security domain, allowing it to continuously train and improve its threat detection capabilities. The platform includes an industry-first API posture governance engine, which enables organizations to author, assess, and enforce corporate standards for API posture, aligning with industry best practices and regulatory requirements.

Operationally, the platform integrates with existing security infrastructure, including SIEM/SOAR systems, ticketing systems, CMDB, and application security testing tools. This holistic approach ensures that API security is not isolated but rather an integral part of the broader security ecosystem. The platform also features enhanced role-based access control, improved integrations with corporate identity systems, and advanced data collection and protection mechanisms to minimize operational friction during onboarding and ongoing management.

Key technical details include the platform's ability to handle billions of API calls, determine intent behind API interactions, and provide real-time threat analysis with end-to-end encryption. The platform supports extensive customization through a Policy Hub, allowing organizations to deploy, track, and manage policies quickly, including dozens of pre-built policies based on real-world usage across various industries.

However, it's important to note that managing such a comprehensive platform can come with operational challenges, such as the need for significant data storage and processing capabilities to support the large data lake and AI-driven analytics. Additionally, the cost of retaining and analyzing large volumes of API data can be substantial, particularly in multi-tenant or large-scale deployments.