{
  "id": 15242,
  "url": "https://arxiv.org/abs/2607.27373v1",
  "title": "RoguePrompt: Dual-Layer Encoding for Self-Reconstruction to Circumvent LLM Moderation",
  "summary": "Large language models (LLMs) are becoming increasingly integrated into mainstream development platforms and daily technological workflows, typically behind moderation and safety controls. Despite these controls, preventing prompt-based policy evasion remains challenging, and adversaries continue to \"jailbreak\" LLMs by crafting prompts that circumvent implemented safety mechanisms. Prior work has established cipher-mediated interaction, code-embedded decryption, prompt decomposition and reconstru",
  "authors": "Benyamin Tafreshian, Prathamesh Dhake",
  "category": "research",
  "topics": "regulation,safety-alignment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-29T18:25:30.000Z",
  "fetched_at": "2026-07-31T05:10:57.675Z",
  "source_slug": "x-arxiv-red-teaming-query",
  "source_name": "arXiv red teaming query",
  "source_homepage": "https://arxiv.org/a/redteam",
  "ethics_ai_record_url": "https://ethics.ai/record/15242",
  "original_url": "https://arxiv.org/abs/2607.27373v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}