Fixing security vulnerabilities with Codex Security
Codex Security documentation provides guidance on how to turn an accepted security finding into a focused, verified patch, including evidence and regression testing.
All sources
ChatGPT
https://learn.chatgpt.comChatGPT Documentation for AI Agents & MCP
This ChatGPT documentation guides AI agents on managing security vulnerabilities, customizing agent behavior, and integrating with third-party systems. It enables agents to generate and verify security patches or perform code reviews within complex deployments.
- Pages
- 186
- 2,360
- Tokens
- ~666.9K
- Updated
- Oct 12, 2026
- Monitoring
- Active
Works with
- ChatGPT
- Claude
- Cursor
- MCP clients
Solutions
What AI Agents Can Do With This Source
Use ChatGPT Documentation to complete source-specific tasks, make informed decisions, and follow evidence-backed workflows.
Configuring custom instructions for Codex agents
The AGENTS.md documentation explains how Codex discovers and applies layered guidance, allowing for consistent project-specific instructions.
Integrating Codex with GitHub for pull request reviews
Documentation details how to set up Codex code review to automatically review GitHub pull request diffs, follow repository guidance, and post standard GitHub code reviews.
Running bulk security scans with Codex Security CLI
The source provides instructions on using npx @openai/codex-security bulk-scan to discover repositories and run resumable security campaigns from GitHub or a CSV inventory.
Managing access tokens for programmatic workflows
The documentation explains how Codex access tokens authenticate trusted non-interactive local workflows like CLI and app-server automation with a ChatGPT workspace identity.
Tracking security findings in external issue trackers
The documentation describes how to prepare and track completed Codex Security scan findings as issues in Linear, GitHub, or Jira, integrating with existing workflows.
Coverage
What's Indexed from ChatGPT
A quick look at the main areas Bulkgrid has indexed and keeps ready for AI search, MCP, extraction, and change detection.
Enterprise
/docs/enterprise
41 pages
Guides administrators through setting up, securing, and managing ChatGPT Work and Codex deployments, covering access tokens, plugin controls, and usage analytics for enterprise environments.
Security
/docs/security
22 pages
Explains how to use Codex Security's CLI and plugin to find, confirm, and fix code vulnerabilities, providing guidance on setup, scanning, and managing security findings across local and cloud environments.
Plugin
/docs/security/plugin
10 pages
Details using the Codex Security plugin to run various scans, export and track findings, fix vulnerabilities with verified patches, and review code changes for security improvements.
Config File
/docs/config-file
5 pages
Explains how to configure Codex using config.toml files, covering basic and advanced settings, environment variables, and the configuration precedence for user and project-scoped overrides.
Environments
/docs/environments
5 pages
Describes how to set up and manage different Codex execution environments, including local, cloud, and Git worktrees, to control dependencies and isolate changes during development.
CLI
/docs/security/cli
5 pages
Provides comprehensive documentation for the Codex Security CLI, including command references, FAQs, and instructions for running bulk scans and integrating into CI/CD pipelines.
Agent Configuration
/docs/agent-configuration
4 pages
Guides users on customizing agent behavior through AGENTS.md files for project-specific instructions, defining execution rules, managing processing speed, and utilizing subagents for specialized tasks.
Reference
/docs/reference
4 pages
Provides a comprehensive reference for navigating the ChatGPT app and Codex, detailing available commands, keyboard shortcuts, personalization settings, and slash commands for efficient interaction.
Third Party
/docs/third-party
4 pages
Explains how to integrate Codex with various third-party platforms like GitHub, GitLab, Linear, and Slack to automate code reviews and delegate tasks directly from issues or chat.
Advantages
Why Use Bulkgrid for AI-Ready Sources
Bulkgrid turns important websites into fresh, queryable, AI-ready sources without making teams maintain the infrastructure.
Spend Fewer Tokens
Retrieve the right source context instead of sending large pages, pasted docs, or noisy search results into every prompt.
Improve Answer Accuracy
Ground responses in current, source-backed evidence to reduce hallucinations and avoid relying on stale model memory.
Use Fresh Source Data
Keep important websites automatically recrawled and updated so AI is not working from old content.
Query Instantly
Search already-indexed source content immediately instead of crawling pages at question time.
No Infrastructure Maintenance
Bulkgrid handles crawling, rendering, retries, storage, indexing, recrawls, and change detection.
Change Detection
See when pages are added, removed, updated, or fail so teams can react without checking manually.
Give Your Agents Up-to-Date Knowledge from ChatGPT
Search and use knowledge from ChatGPT in ChatGPT, Claude, Cursor, and any MCP-compatible client.