Following the widespread availability of large language models (LLMs), the Django Security Team has received a growing number of security reports generated partially or entirely using such tools. Many of these contain inaccurate, misleading, or fictitious content. While AI tools can help draft or analyze reports, they must not replace human understanding and review.
If you use AI tools to help prepare a report, you must:
- Disclose which AI tools were used and specify what they were used for (analysis, writing the description, writing the exploit, etc).
- Verify that the issue describes a real, reproducible vulnerability that otherwise meets these reporting guidelines.
- Avoid fabricated code, placeholder text, or references to non-existent Django features.
Reports that appear to be unverified AI output will be closed without response. Repeated low-quality submissions may result in a ban from future reporting
— Django’s security policies, on AI-Assisted Reports
Recent articles
- Reverse engineering Codex CLI to get GPT-5-Codex-Mini to draw me a pelican - 9th November 2025
- Video + notes on upgrading a Datasette plugin for the latest 1.0 alpha, with help from uv and OpenAI Codex CLI - 6th November 2025
- Code research projects with async coding agents like Claude Code and Codex - 6th November 2025