Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The Impact of AI and Machine Learning on Cloud Data Protection

The momentous rise of AI continues, and more and more customers are demanding concrete results from these early implementations. The time has come for tech companies to prove what AI can do beyond adding conversational chat agents to website sidebars. Fortunately, it’s easy to see how cloud data protection has already benefited from advancements in AI and ML. Headline-grabbing large-language models are also making protecting data in the cloud easier to manage across organizations. ‍

"Better context in a world that's changing quickly": Leading CISOs discuss AI's role in SecOps

Earlier this month, I was thrilled to join forces with the team at Dark Reading for a webinar on the future of AI in security operations. Titled CISO Perspectives: How to make AI an accelerator, not a blocker, the webinar allowed me to take a deep dive into the future role of AI in security with some of the most knowledgeable CISOs on the subject, Mandy Andress of Elastic and Matt Hillary of Drata.

Navigating the AI-powered development era in financial services

Australian and New Zealand financial service institutions (FSIs) are facing pressure to innovate quickly while maintaining robust security and regulatory compliance. Many, like ANZ Bank and Commonwealth Bank, are exploring Generative AI to accelerate software development, but is it a silver bullet?

A developer's best friend: Lessons learned from our canine companions about AI code security

Happy International Dog Day! This official holiday celebrates our furry friends and the joy they bring to our lives! Today is particularly special for all of us at Snyk because of our four-legged mascot, Patch the Doberman. But what exactly does a dog have to do with application security? Here at Snyk, we see the idea of a “guard dog” protecting someone’s home as similar to how AppSec solutions can protect today’s development practices.

AI in API Security: How Artificial Intelligence Enhances API Protection"

Explore how artificial intelligence is revolutionizing API security by detecting and mitigating threats in real-time. In this video, we discuss the growing importance of AI in safeguarding APIs against malicious attacks and how it helps organizations stay ahead of evolving cyber threats.

Response Accuracy Retention Index (RARI) - Evaluating Impact of Data Masking on LLM Response

As language models (LLMs) in enterprise applications continue to grow, ensuring data privacy while maintaining response accuracy becomes crucial. One of the primary methods for protecting sensitive information is data masking. However, this process can lead to significant information loss, potentially rendering responses from LLMs less accurate. How can this loss be measured?

Deceptive AI: A New Wave of Cyber Threats

As artificial intelligence (AI) technology advances, its influence on social media has become more and more pervasive and riddled with challenges. In particular, the ability for humans to discern genuine content from AI-generated material. Our recent survey conducted with OnePoll on over 2,000 UK workers found that a substantial portion of social media users are struggling to navigate this new digital frontier.

Keeping Financial Services Organizations Secure in an AI World

When we talk about financial services and technology, security and regulatory compliance are always top of mind. And now, Generative AI has entered the chat - one of the most talked-about technologies of recent years. And Financial Services institutions have only begun to scratch the surface of what generative AI can do. The problem is, so have cyber threat actors. In this session from Splunk, and IDC, you’ll hear key insights into how financial services companies are improving their security posture in an AI World, and how those practices can benefit your organizations.

Sysdig's AI Workload Security: The risks of rapid AI adoption

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.