Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Since the widespread launch of GPT-3.5 in November of last year, we’ve seen a meteoric rise in generative AI (GenAI) tools, along with an onslaught of security concerns from both countries and companies around the globe. Tech leaders like Apple have warned employees against using ChatGPT and GitHub Copilot, while other major players like Samsung have even go so far as to completely ban GenAI tools. Why are companies taking such drastic measures to prevent data leaks to LLMs, you may ask?

San Francisco, CA, August 4, 2023—Nightfall AI, the leader in cloud data leak prevention (DLP), announces the launch of the industry’s first complete data security platform designed specifically for Generative AI (GenAI).

The landscape of cybercrime continues to evolve, and cybercriminals are constantly seeking new methods to compromise software projects and systems. In a disconcerting development, cybercriminals are now capitalizing on AI-generated unpublished package names also known as “AI-Hallucinated packages” to publish malicious packages under commonly hallucinated package names.

Artificial intelligence (AI) has generated significant hype in recent years, and separating the promise from reality can be challenging. However, at Torq, AI is not just a concept. It is a reality that is revolutionizing the SOC field, specifically in the area of Tier-1 security analysis, especially as cybercriminals become more sophisticated in their tactics and techniques. Traditional security tools continue to fall short in detecting and mitigating these attacks effectively, particularly at scale.

The life sciences industry is at the forefront of data-intensive research and innovation. Scientists and researchers rely heavily on the collection, processing, and analysis of vast amounts of data generated by lab instruments. And they are often challenged by errors or confusion in managing data flows that in turn, have a direct impact on the quality of data and corresponding compliance with regulatory requirements.

If you had to choose a security measure that would make the most difference to your cyber program right now, what would it be? Maybe you’d like to get another person on your team? Someone who is a skilled analyst, happy to do routine work and incredibly reliable. Or perhaps you’d prefer an investment that would give your existing team members back more of their time without compromising your ability to find and fix threats? What about human intelligence without human limitations?

‍ This month's release rollup includes Egnyte's AI-driven document summarization, project dashboard for Android, and Smart Cache file download improvements. Below is an overview of these and other new releases. Visit the linked articles for more details.

Researchers from Carnegie Mellon University and the Center for A.I. Safety have discovered a new prompt injection method to override the guardrails of large language models (LLMs). These guardrails are safety measures designed to prevent AI from generating harmful content. This discovery poses a significant risk to the deployment of LLMs in public-facing applications, as it could potentially allow these models to be used for malicious purposes.

Five worthy reads is a regular column on five noteworthy items we have discovered while researching trending and timeless topics. This week we are exploring the significant role of AI in the field of cybersecurity and why it’s the next biggest thing in cybersecurity.