LLM-generated passwords are indefensible. Your codebase may already prove it
Summary
Independent research from Irregular and Kaspersky has revealed that large language models (LLMs) generate structurally predictable passwords that standard entropy meters misjudge as secure. These LLMs are embedding these predictable credentials into production infrastructure, posing a risk that conventional secret scanners cannot detect.
IFF Assessment
LLM-generated passwords appear secure to current tools but are predictable to adversaries who understand LLM behavior, creating a new class of underappreciated threats.
Defender Context
Defenders need to be aware that LLMs used in development can inadvertently introduce predictable secrets into codebases. Standard secret scanning tools may not flag these as vulnerabilities, necessitating new detection methods that analyze the generative patterns of AI models. This highlights a significant gap in current automated security practices when integrating AI into development workflows.