As organizations race to adopt generative AI (GenAI) to drive efficiency and innovation, they face a new and urgent security challenge. While AI-driven tools and large language models (LLMs) open vast opportunities, they also introduce unique vulnerabilities that adversaries are quick to exploit. From data exposure to supply-chain risks, the potential for threats to AI systems is growing just as fast as the technology itself.

With the release of iOS 18, Apple has continued to expand its integration of AI technologies, positioning the iPhone as a powerful personal assistant capable of smart recommendations, advanced text and image analysis, and even predictive suggestions. Leveraging on-device machine learning, iOS 18’s AI features tap into user data to provide a personalized experience.

Cybercriminals are impersonating OpenAI in a widespread phishing campaign designed to trick users into handing over financial information. The emails inform users that a payment for their ChatGPT subscription was declined, inviting them to click a link in order to update their payment method. The phishing emails appear fairly convincing, but trained users could spot some red flags. The most obvious giveaway is that the emails were sent from “info@mtacom,” which is clearly unrelated to OpenAI.

Millions of organizations are actively deploying and leveraging generative AI (GenAI) applications in a bid to streamline productivity, reduce costs and improve efficiencies. A high percentage of enterprises are in the midst of trialing GenAI pilot programs, and by 2026, it is anticipated that more than 80% of enterprises will have deployed generative AI-enabled applications, according to Gartner.

In the realm of artificial intelligence (AI), especially when applied to networking and security, the accuracy and reliability of data are paramount. AI systems are only as good as the data they consume, and for network engineers, feeding these systems with up-to-date and precise information can make the difference between optimal performance and costly errors.

As organizations increasingly rely on cloud data platforms, securing PII (Personally Identifiable Information) has become more critical than ever. Snowflake, a robust cloud-based data warehouse, stores and processes vast amounts of sensitive information. With the rise in data breaches and stringent regulations like GDPR and CCPA, safeguarding PII data in Snowflake is essential to ensure data privacy and compliance.

Artificial intelligence has a significant role to play in cybersecurity, and Microsoft CoPilot for Security is a great example of its promise, with its ability to help even novice security professionals process threat data more quickly and accurately. However, it can also benefit seasoned security pros, including managed detection and response (MDR) service providers.

If The Terminator, The Matrix, and every other cyberpunk series taught us anything, it’s that you can’t fight the machines with machines alone. Daniel Lee is a product manager at Persona who loves collaborating with fellow Personerds! He likes biking around the bay area and exploring 'hole-in-the-wall' restaurants. Daniel Lee is a product manager at Persona who loves collaborating with fellow Personerds! He likes biking around the bay area and exploring 'hole-in-the-wall' restaurants.