Cybersecurity investigators using artificial intelligence tools to generate incident response reports face a significant risk of cross-contamination between separate breach details. When drafting reports for multiple incidents in the same session with the same AI tool, information from one incident can inadvertently bleed into another, potentially compromising the accuracy and integrity of the reports. This phenomenon can have serious consequences, particularly in high-stakes breach response situations where precise documentation is crucial. Researchers caution that the use of AI tools in incident response must be carefully managed to prevent such contamination, highlighting the need for robust validation and verification protocols. The potential for cross-contamination undermines the reliability of AI-generated reports, so practitioners must be vigilant in ensuring the integrity of their incident response processes1. This oversight is critical to maintaining the trustworthiness of breach response efforts and preventing further complications.