mlsanityData to 7 Oct 2026

Human Society-Inspired Approaches to Agentic AI Security: The 4C Framework

arXiv 2602.01942 ↗First posted 2 Feb 2026cs.CR cs.AIcited by 2

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

AI is moving from domain-specific autonomy in closed, predictable settings to large-language-model-driven agents that plan and act in open, cross-organizational environments. As a result, the cybersecurity risk landscape is changing in fundamental ways. Agentic AI systems can plan, act, collaborate, and persist over time, functioning as participants in complex socio-technical ecosystems rather than as isolated software components. Although recent work has strengthened defenses against model and pipeline level vulnerabilities such as prompt injection, data poisoning, and tool misuse, these system centric approaches may fail to capture risks that arise from autonomy, interaction, and emergent behavior. This article introduces the 4C Framework for multi-agent AI security, inspired by societal governance. It organizes agentic risks across four interdependent dimensions: Core (system, infrastructure, and environmental integrity), Connection (communication, coordination, and trust), Cognition (belief, goal, and reasoning integrity), and Compliance (ethical, legal, and institutional governance). By shifting AI security from a narrow focus on system-centric protection to the broader preservation of behavioral integrity and intent, the framework complements existing AI security strategies and offers a principled foundation for building agentic AI systems that are trustworthy, governable, and aligned with human values.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 22 of its 43 references that are in the map. First posted on arXiv 2 Feb 2026.

Builds on

22 of 43 references.

Closest ancestors · 7

Same direction, newest first

  1. 2025Risk Analysis Techniques for Governed LLM-based Multi-Agent Systems6 Aug
  2. 2025A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures24 Jun
  3. 2025TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems4 Jun
  4. 2025Securing Agentic AI: A Comprehensive Threat Model and Mitigation Framework for Generative AI Agents28 Apr
  5. 2025Red-Teaming LLM Multi-Agent Systems via Communication Attacks20 Feb
  6. 2024InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents5 Mar
  7. 2024Secret Collusion among AI Agents: Multi-Agent Deception via Steganography12 Feb

Other references · 15

  1. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,582
  2. 2024PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Modelscited by 251
  3. 2024Scaling Large Language Model-based Multi-Agent Collaborationcited by 235
  4. 2025The Landscape of Agentic Reinforcement Learning for LLMs: A Surveycited by 195
  5. 2024Security and Privacy Challenges of Large Language Models: A Surveycited by 179
  6. 2025AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challengescited by 167
  7. 2025Multi-Agent Risks from Advanced AIcited by 150
  8. 2021Goal Misgeneralization in Deep Reinforcement Learningcited by 122
  9. 2024AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathwayscited by 122
  10. 2024The Ethics of Advanced AI Assistantscited by 103
  11. 2023Specific versus General Principles for Constitutional AIcited by 41
  12. 2025EchoLeak: The First Real-World Zero-Click Prompt Injection Exploit in a Production LLM Systemcited by 26
3 more
  1. 2025Frontier AI's Impact on the Cybersecurity Landscapecited by 21
  2. 2025From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMscited by 9
  3. 2025Large Language Model Adversarial Landscape Through the Lens of Attack Objectivescited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluationcited by 5
  2. 2026Connecting the Dots in Agentic AI Security: A Cross-Dimensional Threat Taxonomy, Evaluation Maturity, and Open Challengescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025With Great Capabilities Come Great Responsibilities: Introducing the Agentic Risk & Capability Framework for Governing Agentic AI Systems
  2. 2025Systems Security Foundations for Agentic Computing
  3. 2025A Safety and Security Framework for Real-World Agentic Systems
  4. 2026Security Considerations for Multi-agent Systems
  5. 2026Securing Agentic AI: From Per-Action Checks to Trajectory Assurance
  6. 2025Agentic AI for Cyber Resilience: A New Security Paradigm and Its System-Theoretic Foundations
  7. 2026A Survey of Agentic AI and Cybersecurity: Challenges, Opportunities and Use-case Prototypes
  8. 2025Toward a Safe Internet of Agents