mlsanityData to 14 Oct 2026

EncGPT: A Multi-Agent Workflow for Dynamic Encryption Algorithms

arXiv 2503.23138 ↗First posted 29 Mar 2025cs.CR cs.MAcited by 0

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

Abstract (arXiv)

Communication encryption is crucial in computer technology, but existing algorithms struggle with balancing cost and security. We propose EncGPT, a multi-agent framework using large language models (LLM). It includes rule, encryption, and decryption agents that generate encryption rules and apply them dynamically. This approach addresses gaps in LLM-based multi-agent systems for communication security. We tested GPT-4o's rule generation and implemented a substitution encryption workflow with homomorphism preservation, achieving an average execution time of 15.99 seconds.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 8 of its 28 references that are in the map. First posted on arXiv 29 Mar 2025.

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8 of 28 references.

References · 8

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Frameworkcited by 1,808
  3. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,395
  4. 2018TarMAC: Targeted Multi-Agent Communicationcited by 208
  5. 2024MapCoder: Multi-Agent Code Generation for Competitive Problem Solvingcited by 177
  6. 2023Agents: An Open-source Framework for Autonomous Language Agentscited by 116
  7. 2024TimeArena: Shaping Efficient Multitasking Language Agents in a Time-Aware Simulationcited by 23
  8. 2023Dynamic S-BOX using Chaotic Map for VPN Data Securitycited by 1

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  1. 2025AgentCrypt: Advancing Privacy and (Secure) Computation in AI Agent Collaboration
  2. 2025D-CIPHER: Dynamic Collaborative Intelligent Multi-Agent System with Planner and Heterogeneous Executors for Offensive Security
  3. 2026KryptoPilot: An Open-World Knowledge-Augmented LLM Agent for Automated Cryptographic Exploitation
  4. 2026Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation
  5. 2025FHE-Agent: Automating CKKS Configuration for Practical Encrypted Inference via an LLM-Guided Agentic Framework
  6. 2025CipherBank: Exploring the Boundary of LLM Reasoning Capabilities through Cryptography Challenges
  7. 2025Seven Security Challenges in Cross-domain Multi-agent LLM Systems
  8. 2024AutoSafeCoder: A Multi-Agent Framework for Securing LLM Code Generation through Static Analysis and Fuzz Testing