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Red-team challenges have been a fun activity for PZ team members in the past, so we recently conducted a small challenge at our fortnightly brown-bag session, focusing on the burgeoning topic of prompt injection. Injection vulnerabilities all follow the same basic pattern – un-trusted input is inadvertently treated as executable code, causing the security of the system to be compromised. SQL injection (SQLi) and cross-site scripting (XSS) are probably two of the best-known variants, but other technologies are also susceptible. Does anyone remember XPath injection? As generative models get incorporated into more products, user input can be used to subvert the model. This can lead to the model revealing its system prompt or other trade secrets, reveal information about the model itself which may be commercially valuable, subvert or waste computation resources, perform unintended actions if the model is hooked up to APIs, or cause reputational damage to the company if the model can be coerced into doing amusing or inappropriate things. As an example, entrepreneur and technologist Chris Bakke was recently able to trick a Chevy dealership’s ChatGPT-powered bot into agreeing to sell him a Chevy Tahoe for $1 . Although the U.S. supreme court has yet to rule on the legal validity of a “no takesies backsies” contract (as an employee of X Chris is probably legally obligated to drive a Tesla anyway) it is not hard to imagine a future scenario with steeper financial consequences.