Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

As Large Language Models (LLMs) continue to advance and integrate into various applications, ensuring LLM data privacy remains a critical priority. Organizations and developers must adopt privacy-focused best practices to mitigate LLM privacy concerns, enhance LLM data security, and comply with evolving data privacy laws. Below are key strategies for preserving data privacy in LLMs.

Each year, Data Protection Day marks an opportunity to assess the state of privacy and security in the midst of technological innovation. This year’s inflection point follows a robust dialogue on AI from last week’s World Economic Forum Annual Meeting in Davos. As CrowdStrike participated in these discussions, we emphasized the importance of leveraging AI to defend against ever-evolving cyber threats and protect the very data and workloads used to power AI.

If you’re looking for a quick way to block bots with robots.txt, you may be disappointed to learn that it’s not as effective as many people think. Robots.txt is often discussed as a simple solution for controlling crawler traffic, but in reality, it provides very limited protection.

With the 12.3 release of the Veeam Data Platform, integrating 11:11 Systems’ low-cost, Veeam-optimized Cloud Object Storage just got a whole lot easier. Now directly built into the Veeam UIs for both Backup & Replication and Veeam ONE, this integration gives you the best of both worlds—a seamless, streamlined setup and the unmatched efficiency of 11:11 Systems’ partnership with AWS S3.

In 2025, fuzz testing has become an essential practice for ensuring software security and reliability. By identifying vulnerabilities through randomized input testing, fuzzing helps development teams uncover bugs that traditional testing methods—such as static analysis and penetration testing—often miss. With rapid advancements in security tools, let’s explore the top fuzz testing tools of 2025, their key features, benefits, and how they compare.

In Part 1 of our cloud security research and guide roundup, we looked at our contributions to helping you manage cloud infrastructure, data, identities, and access. In Part 2, we share our research, insights, and guides from Datadog Security Labs and The Monitor that support the NSA’s cloud mitigation strategies in the following areas: We’ll also go beyond these common strategies to look at how security plays a role in working with LLMs.

Developing in the cloud introduces unique challenges for protecting applications, resources, and data. These challenges include but are not limited to detecting legitimate threats to your environment and managing complex cloud permissions and access controls.