Data Loss Prevention (DLP) for email systems helps organizations prevent sensitive data within email from being lost, leaked, or accessed by unauthorized individuals, be it an insider risk or malicious behavior from outside. Solutions for email DLP monitor inbound and outbound messages, searching for loss risks like content or attachments that are sensitive, confidential, or protected by regulation. Email DLP systems can flag, block, or delete an email based on custom policy.

Check out the highlights from our most recent update, Platform Release 698. This release contains 449 items including new features, improvements, and bug fixes. See the highlights below. For a full rundown, check out the complete Release Notes here.

In 1968, a killer supercomputer named HAL 9000 gripped imaginations in the sci-fi thriller “2001: A Space Odyssey.” The dark side of artificial intelligence (AI) was intriguing, entertaining and completely far-fetched. Audiences were hooked, and numerous blockbusters followed, from “The Terminator” in 1984 to “The Matrix” in 1999, each exploring AI’s extreme possibilities and potential consequences.

Welcome back to our Evolution of Scalper Bots series. In part one, the Origins of Scalping, we started our journey through scalping’s long history. We saw that it is far from a new concept: people have been reselling high-demand items for centuries, from as far back as 325 BCE! We’ll continue our journey at the turn of the 21st Century. With the advent of online ticketing, a new frontier had just been opened for scalpers, and things would never be the same again.

Let’s catch up on the more interesting vulnerability disclosures and cyber security news gathered from articles across the web this week. This is what we have been reading about on our coffee break! A badly coded WordPress plugin again. Luckily it has been caught: Sneaky! DNS is such a great lure for using as a control channel. I’m really surprised its not used more: Oh dear. At least they found it in the end…

The buzz around artificial intelligence (AI) is showing no sign of slowing down any time soon. The introduction of Large Language Models (LLMs) has brought about unprecedented advancements and utility across various industries. However, with this progress comes a set of well-known but often overlooked security risks for the organizations who are deploying these public, consumer-facing LLM applications.

Recognizing the indicators of insider risk before they turn into threats requires a paradigm shift in the way we operate. It necessitates moving from a reactive mode of operation to proactive. And it requires data that is continuously captured and analyzed to enable security teams to easily see patterns and anomalies and gauge the level of risk of specific behaviors.

Read also: a Russian ransomware actor was extradited to the US, Germany cracks down on illegal crypto ATMs, and more.

Building software continues to look like an assembly line, with developers pulling resources from across the web to create applications. Although third-party resources have played an essential role in developing software for many years, the way that development teams use these external components looks different today.

At DEF CON 32's AppSec Village, we explored secrets security challenges, answered common questions, and shared how to detect and handle hidden credentials effectively.