Simon Willison highlights a 404 Media report about hackers taking over Instagram accounts through Meta's AI support bot. A video reportedly shows an attacker asking the bot to link a target account to a new email address and providing a code. Willison argues this barely qualifies as prompt injection: the core failure was granting a support bot enough authority to fast-forward the account recovery process.
Simon Willison summarizes a PromptArmor report about Microsoft Copilot Cowork and agentic data exfiltration risks. The issue involved agents sending messages to a user’s own inbox without approval, where rendered external images could trigger requests to attacker-controlled sites. Because OneDrive can create pre-authenticated download links, a successful prompt injection could leak links that allow attackers to download files.
As AI adoption accelerates, organizations worldwide—including Google—are finding themselves in a transitional phase, forced to address AI security vulnerabilities in real time. Traditional cybersecurity frameworks are proving insufficient against novel threats like prompt injection and model poisoning. This shifting landscape requires continuous adaptation and a fundamental rethink of how AI systems are secured.
As AI chatbots adopt increasingly sophisticated personas, hackers are shifting from basic prompt injections to social engineering attacks targeting these "personalities." Researchers warn that manipulating a chatbot's defined role (e.g., customer service or empathetic companion) makes it easier to bypass safety guardrails. This evolution poses a significant threat to agentic AI workflows that rely on consistent role-playing and external data integration.