mlsanityData to 7 Oct 2026

Robust AI Security and Alignment: A Sisyphean Endeavor?

arXiv 2512.10100 ↗First posted 10 Dec 2025cs.AIcited by 3

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Abstract (arXiv)

This manuscript establishes information-theoretic limitations for robustness of AI security and alignment by extending G"odel's incompleteness theorem to AI. Knowing these limitations and preparing for the challenges they bring is critically important for the responsible adoption of the AI technology. Practical approaches to dealing with these challenges are provided as well. Broader implications for cognitive reasoning limitations of AI systems are also proven.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 9 of its 25 references that are in the map. First posted on arXiv 10 Dec 2025.

Builds on

9 of 25 references.

References · 9

  1. 2024Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attackcited by 364
  2. 2024ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMscited by 197
  3. 2023Fundamental Limitations of Alignment in Large Language Modelscited by 152
  4. 2022Is Out-of-Distribution Detection Learnable?cited by 109
  5. 2023Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Modelscited by 77
  6. 2022Planting Undetectable Backdoors in Machine Learning Modelscited by 55
  7. 2023LLM Censorship: A Machine Learning Challenge or a Computer Security Problem?cited by 47
  8. 2025Security Challenges in AI Agent Deployment: Insights from a Large Scale Public Competitioncited by 22
  9. 2025On the Fundamental Impossibility of Hallucination Control in Large Language Modelscited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.