This research proposes a structured approach to managing Chain-of-Thought (CoT) disclosure in large language models, addressing the tension between transparency and security concerns.

• CoT reasoning improves LLM performance but creates risks when fully disclosed
• Current disclosure policies lack consistency across model providers
• The proposed tiered-access framework balances needs of different stakeholders
• Implementation requires thoughtful guardrails against misuse while enabling trust and innovation

For security professionals, this framework offers practical guidance on managing AI transparency without compromising system integrity or enabling adversarial attacks, while still fostering responsible innovation.

Policy Frameworks for Transparent Chain-of-Thought Reasoning in Large Language Models