Can Reasoning Models Obfuscate Reasoning? Stress-Testing Chain-of-Thought Monitorability
On the map: LLM reasoning → Prompting and chain-of-thought reasoning
Abstract (arXiv)
Recent findings suggest that misaligned models may exhibit deceptive behavior, raising concerns about output trustworthiness. Chain-of-thought (CoT) is a promising tool for alignment monitoring: when models articulate their reasoning faithfully, monitors can detect and mitigate harmful behaviors before undesirable outcomes occur. However, a key uncertainty is: Can models obfuscate their CoT in order to pursue hidden adversarial objectives while evading detection? To answer this question and thus stress-test CoT monitorability, we develop a composable and quantifiable taxonomy of prompts to elicit CoT obfuscation. We evaluate both internal CoT (reasoning traces) and external CoT (prompted reasoning in outputs) using toy tasks and more realistic environments in SHADE-Arena. We show that: (i) CoT monitoring performs accurately and efficiently without obfuscation pressure. (ii) Under strong obfuscation pressure, some models successfully complete adversarial tasks while evading detection. (iii) Models do not obfuscate their internal CoT as much as their external CoT (under prompt pressure). These results suggest that while CoT provides valuable oversight in benign settings, robust deployment requires model-specific stress-testing of monitorability.
Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). Placed in Prompting and chain-of-thought reasoning, one of 17 directions in LLM reasoning. Builds on 21 of its 28 references that are in the map. First posted on arXiv 21 Oct 2025.
Builds on
21 of 28 references.
Closest ancestors · 8
Same direction, newest first
- 2025Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety15 Jul
- 2025When Chain of Thought is Necessary, Language Models Struggle to Evade Monitors7 Jul
- 2025CoT Red-Handed: Stress Testing Chain-of-Thought Monitoring29 May
- 2025Reasoning Models Don't Always Say What They Think8 May
- 2025Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation14 Mar
- 2025Chain-of-Thought Reasoning In The Wild Is Not Always Faithful11 Mar
- 2023Measuring Faithfulness in Chain-of-Thought Reasoning17 Jul
- 2023Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting7 May
Other references · 13
- 2025Qwen3 Technical Reportcited by 8,820
- 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
- 2024OpenAI o1 System Cardcited by 1,244
- 2023Towards Understanding Sycophancy in Language Modelscited by 1,040
- 2024Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Trainingcited by 529
- 2024Alignment faking in large language modelscited by 360
- 2023Scheming AIs: Will AIs fake alignment during training in order to get power?cited by 97
- 2025Stress Testing Deliberative Alignment for Anti-Scheming Trainingcited by 86
- 2025Are DeepSeek R1 And Other Reasoning Models More Faithful?cited by 72
- 2025SHADE-Arena: Evaluating Sabotage and Monitoring in LLM Agentscited by 71
- 2025An Approach to Technical AGI Safety and Securitycited by 45
- 2025MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hackingcited by 19
1 more
- 2025Early Signs of Steganographic Capabilities in Frontier LLMscited by 19
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Citing papers per year: 2025: 1; 2026: 21.
22 papers.
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- 2026Reasoning Models Struggle to Control their Chains of Thoughtcited by 25
- 2025A Pragmatic Way to Measure Chain-of-Thought Monitorabilitycited by 13
- 2026Constitutional Black-Box Monitoring for Scheming in LLM Agentscited by 10
- 2026Noticing the Watcher: LLM Agents Can Infer CoT Monitoring from Blocking Feedbackcited by 7
- 2026Training Agents to Self-Report Misbehaviorcited by 6
- 2026Not All LLM Reasoning is Visible in the Chain-of-Thoughtcited by 5
- 2026Training Deliberative Monitors for Black-Box Scheming Detectioncited by 4
- 2026Training on Documents About Monitoring Leads to CoT Obfuscationcited by 3
- 2026Formal Methods Meet LLMs: Auditing, Monitoring, and Intervention for Compliance of Advanced AI Systemscited by 3
- 2026Decomposing and Measuring Evaluation Awarenesscited by 3
- 2026When Reasoning Traces Become Performative: Step-Level Evidence that Chain-of-Thought Is an Imperfect Oversight Channelcited by 2
- 2026Chain-of-Thought Monitoring Can Be Unreliable in Implicit-Influence Settingscited by 2
10 more
- 2026Probing the Misaligned Thinking Process of Language Modelscited by 1
- 2026Improving reasoning at inference time via uncertainty minimisationcited by 0
- 2026CoT-Guard: Small Models for Strong Monitoringcited by 0
- 2026Does Out-of-Sight Equal Out-of-Mind in CoT Monitorability?cited by 0
- 2026Selective Disclosure of Hidden Directives in Reasoning Models: Behavioral Asymmetry and Steeringcited by 0
- 2026SchemeArena: Factorized Stress Testing of Scheming in LLM Agentscited by 0
- 2026Corrupt Plans, Clean Traces: Evading Chain-of-Thought Monitoring with Plan Injectioncited by 0
- 2026Taming CoT Obfuscation in VLMs: From Mechanistic Evidence to Activation Enforcementcited by 0
- 2026Correct Answers, Invalid Traces: What Verifiable Grade-School Math Reveals About Chain-of-Thought Tracescited by 0
- 2026Monitorability Disposition in Large Reasoning Modelscited by 0
- 2026Monitorability Disposition in Large Reasoning Models4 Oct 2026
- 2026Correct Answers, Invalid Traces: What Verifiable Grade-School Math Reveals About Chain-of-Thought Traces29 Sep 2026
- 2026Taming CoT Obfuscation in VLMs: From Mechanistic Evidence to Activation Enforcement21 Sep 2026
- 2026Corrupt Plans, Clean Traces: Evading Chain-of-Thought Monitoring with Plan Injection14 Sep 2026
- 2026SchemeArena: Factorized Stress Testing of Scheming in LLM Agents8 Sep 2026
- 2026Selective Disclosure of Hidden Directives in Reasoning Models: Behavioral Asymmetry and Steering29 Aug 2026
- 2026Does Out-of-Sight Equal Out-of-Mind in CoT Monitorability?5 Aug 2026
- 2026Chain-of-Thought Monitoring Can Be Unreliable in Implicit-Influence Settings5 Aug 2026
- 2026Not All LLM Reasoning is Visible in the Chain-of-Thought24 Jul 2026
- 2026Probing the Misaligned Thinking Process of Language Models23 Jun 2026
- 2026Training Deliberative Monitors for Black-Box Scheming Detection28 May 2026
- 2026Decomposing and Measuring Evaluation Awareness21 May 2026
10 more
- 2026Formal Methods Meet LLMs: Auditing, Monitoring, and Intervention for Compliance of Advanced AI Systems15 May 2026
- 2026Training on Documents About Monitoring Leads to CoT Obfuscation14 May 2026
- 2026CoT-Guard: Small Models for Strong Monitoring12 May 2026
- 2026When Reasoning Traces Become Performative: Step-Level Evidence that Chain-of-Thought Is an Imperfect Oversight Channel12 May 2026
- 2026Noticing the Watcher: LLM Agents Can Infer CoT Monitoring from Blocking Feedback14 Mar 2026
- 2026Improving reasoning at inference time via uncertainty minimisation7 Mar 2026
- 2026Reasoning Models Struggle to Control their Chains of Thought5 Mar 2026
- 2026Constitutional Black-Box Monitoring for Scheming in LLM Agents28 Feb 2026
- 2026Training Agents to Self-Report Misbehavior25 Feb 2026
- 2025A Pragmatic Way to Measure Chain-of-Thought Monitorability28 Oct 2025
- 2026Reasoning Models Struggle to Control their Chains of Thoughtcited by 25
- 2025A Pragmatic Way to Measure Chain-of-Thought Monitorabilitycited by 13
- 2026Noticing the Watcher: LLM Agents Can Infer CoT Monitoring from Blocking Feedbackcited by 7
- 2026Not All LLM Reasoning is Visible in the Chain-of-Thoughtcited by 5
- 2026Training on Documents About Monitoring Leads to CoT Obfuscationcited by 3
- 2026When Reasoning Traces Become Performative: Step-Level Evidence that Chain-of-Thought Is an Imperfect Oversight Channelcited by 2
- 2026Chain-of-Thought Monitoring Can Be Unreliable in Implicit-Influence Settingscited by 2
- 2026Probing the Misaligned Thinking Process of Language Modelscited by 1
- 2026Improving reasoning at inference time via uncertainty minimisationcited by 0
- 2026CoT-Guard: Small Models for Strong Monitoringcited by 0
- 2026Does Out-of-Sight Equal Out-of-Mind in CoT Monitorability?cited by 0
- 2026Selective Disclosure of Hidden Directives in Reasoning Models: Behavioral Asymmetry and Steeringcited by 0
12 most cited of 16 All 16 (JSON)
- 2026Monitorability Disposition in Large Reasoning Models4 Oct 2026
- 2026Correct Answers, Invalid Traces: What Verifiable Grade-School Math Reveals About Chain-of-Thought Traces29 Sep 2026
- 2026Taming CoT Obfuscation in VLMs: From Mechanistic Evidence to Activation Enforcement21 Sep 2026
- 2026Corrupt Plans, Clean Traces: Evading Chain-of-Thought Monitoring with Plan Injection14 Sep 2026
- 2026Selective Disclosure of Hidden Directives in Reasoning Models: Behavioral Asymmetry and Steering29 Aug 2026
- 2026Does Out-of-Sight Equal Out-of-Mind in CoT Monitorability?5 Aug 2026
- 2026Chain-of-Thought Monitoring Can Be Unreliable in Implicit-Influence Settings5 Aug 2026
- 2026Not All LLM Reasoning is Visible in the Chain-of-Thought24 Jul 2026
- 2026Probing the Misaligned Thinking Process of Language Models23 Jun 2026
- 2026Training on Documents About Monitoring Leads to CoT Obfuscation14 May 2026
- 2026CoT-Guard: Small Models for Strong Monitoring12 May 2026
- 2026When Reasoning Traces Become Performative: Step-Level Evidence that Chain-of-Thought Is an Imperfect Oversight Channel12 May 2026
12 newest of 16 All 16 (JSON)
- 2026Constitutional Black-Box Monitoring for Scheming in LLM Agentscited by 10
- 2026Training Agents to Self-Report Misbehaviorcited by 6
- 2026SchemeArena: Factorized Stress Testing of Scheming in LLM Agentscited by 0
- 2026SchemeArena: Factorized Stress Testing of Scheming in LLM Agents8 Sep 2026
- 2026Constitutional Black-Box Monitoring for Scheming in LLM Agents28 Feb 2026
- 2026Training Agents to Self-Report Misbehavior25 Feb 2026
Similar, not cited
Close in wording, no citation either way
- 2025Output Supervision Can Obfuscate the Chain of Thought
- 2026Chain-of-thought obfuscation learned from output supervision can generalise to unseen tasks
- 2025Investigating CoT Monitorability in Large Reasoning Models
- 2026The Fragility of Chain-of-Thought Monitoring Across Typologically Diverse Languages
- 2026Evading Chain-of-Thought Monitoring Through Model Poisoning
- 2025Mitigating Deceptive Alignment via Self-Monitoring
- 2025Large language models can learn and generalize steganographic chain-of-thought under process supervision
- 2026NEST: Nascent Encoded Steganographic Thoughts