At BSides Orlando 2024, security experts and students explored the future of cybersecurity, from AI failures to security assessments to efficient log management.

In today’s fast-evolving cybersecurity landscape, organizations face an increasing barrage of sophisticated threats targeting endpoints, networks and every layer in between. CrowdStrike and Fortinet have formed a powerful partnership to deliver industry-leading protection from endpoint to firewall.

We’ve just released the 2024 State of Cloud Security study, where we analyzed the security posture of thousands of organizations using AWS, Azure, and Google Cloud. In particular, we found that: In this post, we provide key recommendations based on these findings, and we explain how you can use Datadog Cloud Security Management (CSM) to improve your security posture.

These days, your organization's data is its most valuable asset. But what happens when that data slips through your fingers? Picture this: It's Friday afternoon, and your security team receives an alert about an unusual number of downloads from your cloud storage app, Google Drive. As you investigate, you realize it's corporate IP that's being downloaded en masse by a departing employee. This type of exfiltration incident isn't just hypothetical; it's a reality that organizations face on the daily.

With 16+ billion mobile devices in use worldwide, new data sheds light on how cyber attackers are shifting focus and tactics to put attacks into the victim’s hands. There’s an interesting story woven throughout mobile security provider Zimperium’s 2024 Global Mobile Threat Report that demands the attention of organizations intent on securing every attack vector – which includes personal mobile devices.

Deploying large language models (LLMs) securely and accurately is crucial in today’s AI deployment landscape. As generative AI technologies evolve, ensuring their safe use is more important than ever. LLM guardrails are essential mechanisms designed to maintain the safety, accuracy, and ethical integrity of these models. They prevent issues like misinformation, bias, and unintended outputs.