Yes, AI chatbots can write code very fast, but you still need human oversight and security testing in your AppSec program. Chatbots are taking the tech world and the rest of the world by storm—for good reason. Artificial intelligence (AI) large language model (LLM) tools can write things in seconds that would take humans hours or days—everything from research papers to poems to press releases, and yes, to computer code in multiple programming languages.

Advancements in AI have led to the creation of generative AI systems like ChatGPT, which can generate human-like responses to text-based inputs. However, these inputs are at the discretion of the user and they aren’t automatically filtered for sensitive data. This means that these systems can also be used to generate content from sensitive data, such as medical records, financial information, or personal details.

The nature of an advanced artificial intelligence (AI) engine such as ChatGPT provides its users with an ability to use and misuse, potentially empowering both security teams and threat actors alike. I’ve previously covered examples of how ChatGPT and other AI engines like it can be used to craft believable business-related phishing emails, malicious code, and more for the threat actor.

We’re pleased to share that Salt has extended the capabilities of our powerful AI algorithms, further strengthening the threat detection and API discovery abilities of the Salt Security API Protection Platform. (Check out today’s announcement.) Here at Salt, we always look forward to the RSA Conference, but this year we are doubly excited to attend and showcase these new advanced capabilities! Salt invests significant resources into the continued innovation of our API security platform.

The Verge came out with an article that got my attention. As artificial intelligence continues to advance at an unprecedented pace, the potential for its misuse in the realm of information security grows in parallel. A recent experiment by data scientist Izzy Miller shows another angle. Miller managed to clone his best friends' group chat using AI, downloading 500,000 messages from a seven-year-long group chat, and training an AI language model to replicate his friends' conversations.

Not long after impressing Microsoft 365 customers with the recent Microsoft 365 Copilot announcement, Microsoft have launched another AI-powered Copilot product. This time with a whole new set of possibilities – introducing Microsoft Security Copilot.

ChatGPT may not be used by all organizations and may even be banned. But that doesn't mean you don't have exposure to the security risks it contains. This post looks at why ChatGPT should be part of your threat landscape.

Remember The Sims? Well Stanford created a small virtual world with 25 ChatGPT-powered "people". The simulation ran for 2 days and showed that AI-powered bots can interact in a very human-like way. They planned a party, coordinated the event, and attended the party within the sim. A summary of it can be found on the Cornell University website. That page also has a download link for a PDF of the entire paper (via Reddit).

The use of Large Language Models (LLMs) is the fine tuning AI engines like ChatGPT need to focus the scam email output to only effective content that results in a wave of new email scams.

AI coding is here, and it’s transforming the way we create software. The use of AI in coding is actively revolutionizing the industry and increasing developer productivity by 55%. However, just because we can use AI in coding doesn't mean we should adopt it blindly without considering the potential risks and unintended consequences.