Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

APIs are now the most attacked layer in the application stack— APIs are being hit 68% more often per host than traditional web apps with APIs facing 1600% more DDoS traffic than web apps. This was found in the state of application security 2024 report where we analyzed 2 billion API attacks blocked on AppTrana WAAP. This isn’t surprising. APIs are inherently automation-friendly, often underprotected, and expose direct access to data and logic.

Imagine waking up to news that your company’s data has been leaked, your customers' trust is shattered, and your brand’s reputation is in tatters. Cybercriminals don’t wait for you to react—they exploit vulnerabilities the moment they find them. You're already playing a dangerous game if your security measures are outdated or reactive.

In this blog post we'll walk you through the essential steps of getting started with LimaCharlie's SecOps Cloud Platform. This guide is designed for technical security professionals who want to leverage LimaCharlie's capabilities to enhance their organization's security posture. By the end of this guide you will have configured your organization in LimaCharlie, deployed sensors, and enabled detection and response rules.

Over the past few weeks, the topic of tariffs has dominated headlines internationally. These trade measures have triggered global economic volatility, with the European Union (EU) pausing its retaliatory tariffs to allow room for negotiation. While the immediate focus is on economic ramifications, it's crucial to recognize the less visible, yet significant, impact these tariffs can have on cybersecurity infrastructures, especially in the realm of API security.

MCP, short for Message Communication Protocol, refers to a category of protocols used for exchanging structured messages between systems or applications. It was developed primarily to meet the communication needs of early enterprise systems that required: MCP protocols are often seen in banking, insurance, healthcare, and telecom industries—sectors where many systems were developed before APIs became mainstream.

The rapid adoption of generative AI (GenAI) in the enterprise is introducing a new category of unmanaged risk known as shadow AI. Organizations frequently lack insight into which employees are using GenAI tools and how they are being accessed, resulting in visibility limitations, policy enforcement challenges, and increased risk of data exposure. Security teams face potential data leaks and compliance violations, while IT teams struggle to integrate GenAI usage into existing governance models.