Uncensored AI Models Stop Refusing. Then They Break Your Agent.

Description and use

A developer migrated their agent stack to uncensored models to avoid OpenAI bans during reverse‑engineering tasks.

Problem

A developer’s OpenAI account was banned after using Codex to test a reverse‑engineering tool, and other users reported that Codex generated its own security boundary questions, leading to automatic bans even when no model output was produced.

Outcome

The agent stack was successfully migrated to uncensored models, eliminating automatic bans while maintaining reverse‑engineering functionality.

Workflow

• 1. Identify the reverse‑engineering use case and the prompts that trigger bans.
• 2. Choose an uncensored model (e.g., Heretic‑edited Gemma 3 12B).
• 3. Deploy the model via one of three routes: local (Ollama/LM Studio), rented GPU (RunPod), or hosted API (abliteration.ai/Sogni).
• 4. Configure the agent to use the chosen OpenAI‑compatible endpoint (set baseURL).
• 5. Adjust context window and tool‑calling settings if necessary (e.g., raise num_ctx to 16K‑32K for Ollama).
• 6. Test the agent with the reverse‑engineering tool (REA) to ensure functionality without bans.

Evidence

A developer watched his 4‑year‑old OpenAI account get banned for asking Codex to test REA, a reverse engineering tool.

Source

On the Anthropic side, Claude Code cuts the request dead and points at its terms of service on reverse engineering.

Source

Heretic covers the first: pip install heretic-llm, then heretic MODEL, and it runs the whole edit in one command.

Source

RunPod’s serverless vLLM worker deploys any Hugging Face model that vLLM supports.

Source