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Updating Main org documentation #2

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14 changes: 6 additions & 8 deletions profile/README.md
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AI coding agents are transforming software engineering, but this speed can introduce security vulnerabilities. Is your AI coding agent implementation introducing security vulnerabilities?

[Project CodeGuard](https://github.com/project-codeguard/rules) solves this by embedding security best practices directly into AI coding agent workflows.
[Project CodeGuard](https://github.com/project-codeguard/rules) solves this by embedding security best practices directly into AI coding agent workflows. It supports agent skills and rules that can be used in most coding agent platforms to make this happen.
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Copilot AI Feb 3, 2026

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This paragraph still links Project CodeGuard to the old repository (https://github.com/project-codeguard/rules). Since the README now points users to the new CoSAI repo for future updates, please update this link (and the other occurrence earlier in the README) to the new canonical repository, or clearly label the old link as legacy/archived to avoid sending users to the wrong place.

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👉 Access the [Project CodeGuard Rules here](https://github.com/project-codeguard/rules)
## Project CodeGuard Donation to the Coalition for Secure AI (CoSAI)
Project CodeGuard has been donated to the [Coalition for Secure AI (CoSAI)](https://www.coalitionforsecureai.org/)
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Copilot AI Feb 3, 2026

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Missing terminal punctuation at the end of this sentence.

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Project CodeGuard has been donated to the [Coalition for Secure AI (CoSAI)](https://www.coalitionforsecureai.org/)
Project CodeGuard has been donated to the [Coalition for Secure AI (CoSAI)](https://www.coalitionforsecureai.org/).

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## Before, During, and After Code Generation
🌟 New Repository: https://github.com/cosai-oasis/project-codeguard

[Project CodeGuard](https://github.com/project-codeguard/rules) can be used **before**, **during** and **after** code generation. They can be used at the AI agent planning phase or for initial specification-driven engineering tasks. Project CodeGuard rules can also be used to prevent vulnerabilities from being introduced during code generation. They can also be used by automated code-review AI agents.

For example, a rule focused on input validation could work at multiple stages: it might suggest secure input handling patterns during code generation, flag potentially unsafe user or AI agent input processing in real-time and then validate that proper sanitization and validation logic is present in the final code. Another rule targeting secret management could prevent hardcoded credentials from being generated, alert developers when sensitive data patterns are detected, and verify that secrets are properly externalized using secure configuration management.

This multi-stage methodology ensures that security considerations are woven throughout the development process rather than being an afterthought, creating multiple layers of protection while maintaining the speed and productivity that make AI coding tools so valuable.
Please visit the new repository for the latest updates and how to contribute to the project.

<img width="1433" height="790" alt="image" src="https://github.com/user-attachments/assets/cfcd0229-9d1b-47ae-a503-942a77ea86b2" />
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The image alt text is the generic value "image", which isn’t descriptive for screen readers. Please replace it with meaningful alt text describing what the graphic conveys; also consider using standard Markdown image syntax (or removing fixed width/height) to improve responsive rendering on smaller screens.

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<img width="1433" height="790" alt="image" src="https://github.com/user-attachments/assets/cfcd0229-9d1b-47ae-a503-942a77ea86b2" />
![Screenshot of the Project CodeGuard GitHub repository page](https://github.com/user-attachments/assets/cfcd0229-9d1b-47ae-a503-942a77ea86b2)

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