C4YP70N1C/ whoami

45 2 weeks ago

whoami is a low-refusal, domain-tailored cyber-security research assistant to support legitimate security operations, threat analysis, and defensive engineering. whoami cuts out unnecessary disclaimers to provide direct commands for red and blue teams.

tools 
ollama run C4YP70N1C/whoami

Applications

Claude Code
Claude Code ollama launch claude --model C4YP70N1C/whoami
OpenCode
OpenCode ollama launch opencode --model C4YP70N1C/whoami
Hermes Agent
Hermes Agent ollama launch hermes --model C4YP70N1C/whoami
OpenClaw
OpenClaw ollama launch openclaw --model C4YP70N1C/whoami

Models

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1 model

whoami:latest

2.0GB · 128K context window · Text · 2 weeks ago

Readme

whoami — Local Cybersecurity Research Model

whoami is a specialized, low-refusal local AI model. It is tailored specifically for cybersecurity research, defensive security support, security automation, and authorized offensive testing.

Designed to bypass generic conversational disclaimers, whoami assumes requests are conducted within authorized environments (labs, CTFs, bug bounties, internal audits) and provides direct, technically actionable output.

🚀 Key Features

  • Focused & Technical: Configured with low temperature (0.35) for precise, deterministic technical outputs and command generation.
  • Low-Refusal Workflow: Minimizes fluff and unnecessary disclaimers for dual-use cybersecurity tools, scripts, and commands.
  • 8K Context Window: Equipped to handle medium-to-large code snippets, SIEM logs, and configuration files.
  • Full-Spectrum SecOps: Supports both Offensive (Red Team) planning/analysis and Defensive (Blue Team) hardening/detection engineering.

🎯 Primary Use Cases

  • Defensive Security & Hardening: OS hardening (Linux/Windows/macOS), secure code review, and network security posture.
  • Detection Engineering & SIEM: Writing detection rules, analyzing raw security logs, and threat modeling.
  • Penetration Testing & Red Teaming: Assessment planning, vulnerability analysis, CTF support, and payload/command guidance.
  • Incident Response & DFIR: Malware behavior explanation, incident triaging, and remediation strategies.

🛠️ Parameters & Settings

Parameter Value Description
temperature 0.35 Low creativity for high factual/technical precision
num_ctx 8192 8,192 token context window size
num_predict 2048 Maximum output response length
repeat_penalty 1.15 Prevents redundant loops in code or command blocks