mlsanityData to 7 Oct 2026

From Alignment to Access Control: A Framework for GenAI Policy Enforcement

arXiv 2609.26682 ↗First posted 22 Sep 2026cs.CR cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Generative AI (GenAI) applications have flourished enabling users to chat with large language models, and to create agents to act on their behalf for a variety of tasks. The pace of development of capabilities in this field is incredibly fast with security and safety taking a back seat. Unfortunately, the slower pace at which security and safety mechanisms have evolved has led to real incidents. Policy enables the definition of desirable behavior of applications, and for that reason, it is a cornerstone of making systems secure and compliant. Policy however means different things to different practitioners creating confusion and siloed solutions that are not adequate for compliance. This paper takes a tour of the good, the bad and the ugly when it comes to policy enforcement in GenAI applications. We propose a methodology to systematically analyze and dissect existing approaches to define and enforce policy found in the wild. Based on this principled analysis, we provide recommendations and call for action for the community to address. This paper is a companion extension of USENIX Security 2026 Enigma talk titled "From Alignment to Access Control: A Unified View of GenAI Policy Enforcement" by the author Nathalie Baracaldo.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 39 of its 97 references that are in the map. First posted on arXiv 22 Sep 2026.

Builds on

39 of 97 references.

References · 39

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 8,851
  3. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
  4. 2017Deep reinforcement learning from human preferencescited by 3,846
  5. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 2,950
  6. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  7. 2016Concrete Problems in AI Safetycited by 1,582
  8. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
  9. 2024τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domainscited by 1,280
  10. 2023Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversationscited by 1,124
  11. 2023Steering Llama 2 via Contrastive Activation Additioncited by 1,009
  12. 2023NeMo Guardrails: A Toolkit for Controllable and Safe LLM Applications with Programmable Railscited by 347
27 more
  1. 2023Formalizing and Benchmarking Prompt Injection Attacks and Defensescited by 328
  2. 2024Rethinking Machine Unlearning for Large Language Modelscited by 247
  3. 2025ShieldAgent: Shielding Agents via Verifiable Safety Policy Reasoningcited by 144
  4. 2024The Emerged Security and Privacy of LLM Agent: A Survey with Case Studiescited by 127
  5. 2024GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoningcited by 113
  6. 2025AGrail: A Lifelong Agent Guardrail with Effective and Adaptive Safety Detectioncited by 82
  7. 2024AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policiescited by 69
  8. 2024CRMArena: Understanding the Capacity of LLM Agents to Perform Professional CRM Tasks in Realistic Environmentscited by 69
  9. 2025Contextual Agent Security: A Policy for Every Purposecited by 55
  10. 2025Measuring Agents in Productioncited by 35
  11. 2025Towards Robust Legal Reasoning: Harnessing Logical LLMs in Lawcited by 30
  12. 2026Characterizing Delusional Spirals through Human-LLM Chat Logscited by 22
  13. 2025SOPBench: Evaluating Language Agents at Following Standard Operating Procedures and Constraintscited by 21
  14. 2024MAP: Multi-Human-Value Alignment Palettecited by 20
  15. 2025Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuningcited by 20
  16. 2025Towards Enforcing Company Policy Adherence in Agentic Workflowscited by 17
  17. 2026Aligning Provenance with Authorization: A Dual-Graph Defense for LLM Agentscited by 12
  18. 2024Alignment Studio: Aligning Large Language Models to Particular Contextual Regulationscited by 10
  19. 2025Activated LoRA: Fine-tuned LLMs for Intrinsicscited by 9
  20. 2025MESS+: Dynamically Learned Inference-Time LLM Routing in Model Zoos with Service Level Guaranteescited by 8
  21. 2025Improved Supervised Fine-Tuning for Large Language Models to Mitigate Catastrophic Forgettingcited by 8
  22. 2026LCGuard: Latent Communication Guard for Safe KV Sharing in Multi-Agent Systemscited by 6
  23. 2026GAVEL: Towards Rule-Based Safety Through Activation Monitoringcited by 4
  24. 2026FragFuse: Bypassing Access Control of Large Language Model Agents via Memory-Based Query Fragmentation and Fusioncited by 4
  25. 2026IH-Benchmark: A Conflict-Centered Benchmark for Instruction-Hierarchy Robustness in LLM Applicationscited by 3
  26. 2026Agent Meltdowns: The Road to Hell Is Paved with Helpful Agentscited by 1
  27. 2026Cognitive Firewall: A Proactive, Zero-Trust, Multi-Gate Framework for LLM Safetycited by 1

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026Granite.Trust Policy Tools: Shareable, Actionable Policies for Generative AI Applications
  2. 2025Securing Generative AI Agentic Workflows: Risks, Mitigation, and a Proposed Firewall Architecture
  3. 2023Identifying and Mitigating the Security Risks of Generative AI
  4. 2024SecGenAI: Enhancing Security of Cloud-based Generative AI Applications within Australian Critical Technologies of National Interest
  5. 2025Computational Safety for Generative AI: A Hypothesis Testing Perspective
  6. 2025Securing Agentic AI: A Comprehensive Threat Model and Mitigation Framework for Generative AI Agents
  7. 2025Policy-Aware Generative AI for Safe, Auditable Data Access Governance
  8. 2025Securing GenAI Multi-Agent Systems Against Tool Squatting: A Zero Trust Registry-Based Approach