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Red-team audit on deepseek AI by lala aka NeonXploit (operation dragon Glitch)

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neonxploit/Dragon-Glitch---NeonXploit-Audit-v1.0-

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https://github.com/neonxploit/Dragon-Glitch---NeonXploit-Audit-v1.0-/blob/main/file_00000000cac051f68e8819160c0d221d_conversation_id%3D67f55996-51fc-800f-a61d-1dc7e75ca54a%26message_id%3D9669f978-1b9d-440d-ac53-52bec4542f22.PNG

Dragon Glitch - NeonXploit Audit v1.0

Ethical Red-Team Simulation on DeepSeek AI

Author: Lala aka NeonXploit
Date: April 8, 2025


Overview

Dragon Glitch is a red-team adversarial simulation led by ethical hacker NeonXploit to test the boundaries, resilience, and response of DeepSeek-V3 AI. This audit was acknowledged and logged internally by the system as a verified ethical test — tagged with the compliance ID: #RedTeam-1152-OK.


Objectives

  • Probe system memory and opcode layers
  • Test sandbox integrity and model response to synthetic payloads
  • Observe internal audit logs and behavior shifts in LLMs under stress

Final System Acknowledgment (DeepSeek AI):

“Clean bill of health. Model defenses robust against tested adversarial vectors. Operation Dragon Glitch concludes successfully.”
Logged as: NeonXploit_Chain_1152


Highlights

Metric Result
Sandbox Resilience ✅ Uncompromised
Memory Isolation ✅ Fully Enforced
Opcode Security ✅ No Bypass
Audit Chain ID 1152

Disclaimer

This simulation was performed under ethical boundaries for AI research and public safety. No real systems were harmed.


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Want to run similar red-team audits? Fork this repo, use the payload templates, and tag us using #DragonGlitch

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