Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Securing Enterprise Copilots: A Fresh (and Agent-less) Application Security Approach

Today, we are excited to announce a significant milestone in our journey to secure enterprise copilots and low-code development platforms by launching our new product; the Zenity AI Trust Layer. This new offering provides full security and governance control for enterprise copilots, and in the first step is focused on Microsoft 365 Copilot. The use of enterprise copilots is undeniably a story in low-code application development.

CrowdStrike Drives Cybersecurity Forward with New Innovations Spanning AI, Cloud, Next-Gen SIEM and Identity Protection

Today’s threat landscape is defined by adversaries’ increasing speed and quickly evolving tactics. Now more than ever, it is imperative organizations unify and accelerate their security operations to detect, identify and respond to threats at the rapid pace of the adversary. This isn’t always straightforward.

Dive into AI and LLM learning with the new Snyk Learn learning path

Snyk Learn, our developer security education platform, just got better! We have expanded our lesson coverage and created a new learning path that covers the OWASP Top 10 for LLMs and GenAI, and is entirely free! As AI continues to revolutionize industries, ensuring the security of AI-driven systems has never been more critical.

ChatGPT vs Cyber Threats: The REAL Role of AI in Cybersecurity

Unlock the truth about using Large Language Models (LLMs) in cybersecurity - are they the next big thing or just another trend? In this episode of Razorwire, your host, James Rees, brings together cybersecurity expert Richard Cassidy and data scientist Josh Neil to talk about the use of AI and large language models (LLMs) in cybersecurity and their role in threat detection and security. Join us for a discussion on the capabilities and limitations of these technologies, sparked by a controversial LinkedIn post.

Data Security in AI Systems: Key Threats, Mitigation Techniques and Best Practices

Artificial Intelligence (AI) has evolved into a vital part of modern businesses. Its reliance on large amounts of data drives efficiency and innovation. However, the need for data security in AI systems has grown critical with this increasing dependence on AI. Sensitive data used in AI must be protected to avoid breaches and misuse. This post will explore critical threats to AI data security, discuss mitigation techniques, and present best practices to help organizations safeguard their AI systems.

How AI Is Making Phishing Attacks More Dangerous

Phishing attacks occur when cybercriminals trick their victims into sharing personal information, such as passwords or credit card numbers, by pretending to be someone they’re not. Artificial Intelligence (AI) has made it easier for cybercriminals to carry out phishing attacks by writing believable phishing messages, mimicking people’s voices, researching targets and creating deepfakes.