Model Security | Breaking Cybersecurity News | The Hacker News

Cybersecurity researchers have disclosed a new set of vulnerabilities impacting OpenAI's ChatGPT artificial intelligence (AI) chatbot that could be exploited by an attacker to steal personal information from users' memories and chat histories without their knowledge. The seven vulnerabilities and attack techniques, according to Tenable, were found in OpenAI's GPT-4o and GPT-5 models. OpenAI has since addressed some of them .  These issues expose the AI system to indirect prompt injection attacks , allowing an attacker to manipulate the expected behavior of a large language model (LLM) and trick it into performing unintended or malicious actions, security researchers Moshe Bernstein and Liv Matan said in a report shared with The Hacker News. The identified shortcomings are listed below - Indirect prompt injection vulnerability via trusted sites in Browsing Context, which involves asking ChatGPT to summarize the contents of web pages with malicious instructions added...

Cybersecurity researchers have found that it's possible to use large language models (LLMs) to generate new variants of malicious JavaScript code at scale in a manner that can better evade detection. "Although LLMs struggle to create malware from scratch, criminals can easily use them to rewrite or obfuscate existing malware, making it harder to detect," Palo Alto Networks Unit 42 researchers said in a new analysis. "Criminals can prompt LLMs to perform transformations that are much more natural-looking, which makes detecting this malware more challenging." With enough transformations over time, the approach could have the advantage of degrading the performance of malware classification systems, tricking them into believing that a piece of nefarious code is actually benign. While LLM providers have increasingly enforced security guardrails to prevent them from going off the rails and producing unintended output, bad actors have advertised tools like WormGPT...