RedThread is a CLI-first framework for testing Large Language Model (LLM) systems, validating failures, and generating evidence-backed defense candidates. It conducts adversarial campaigns using various attack strategies, including PAIR, TAP, and Crescendo, and scores the results to synthesize potential defenses. RedThread's closed evidence loop involves attack generation, target execution, judge scoring, defense synthesis, replay validation, and promotion evidence. This system is useful for local campaigns, replay evidence, deterministic security checks, and operator review, but is not intended for universal production enforcement. It addresses the limitations of existing AI red-team tools by asking additional questions about the nature and causes of failures, and providing a more comprehensive approach to AI security.