Safe AI Coding: An Open-Source Security Toolkit for AI Coding Agents

AI coding agents are changing how developers build software. With tools like Claude Code, developers can generate features, refactor applications, debug errors, and automate repetitive tasks using natural language.

But there is an important question we should ask:

How do we make AI-assisted development safer without slowing down the development process?

AI-generated code can contain security vulnerabilities, incorrect assumptions, missing implementations, or dangerous changes. Coding agents can also encounter malicious instructions hidden inside repositories, configuration files, or other project content.

That is why I built Safe AI Coding — a free, open-source project designed to add security-focused checks and review workflows to AI-assisted development.

🔗 GitHub Repository: https://github.com/sami-hussain-dev/safe-ai-coding

Safe AI Coding is a Claude Code skill designed to help developers identify risky operations, review AI-generated changes, and inspect repositories for potential security issues.

The project is open source under the MIT License, so developers can explore the implementation and evaluate whether it fits their workflows.

Vibe coding makes it easier to turn an idea into a working application. However, generating code quickly does not automatically make that code secure or production-ready.

An agent might propose deleting files, rewriting Git history, or running a database operation that could remove important data.

A repository may contain instructions that attempt to manipulate an AI agent into revealing secrets or performing unintended actions.

AI-generated code may introduce SQL injection, cross-site scripting (XSS), unsafe redirects, weak authentication checks, or other vulnerabilities.

A generated feature might reference a missing class, route, method, configuration file, or view.

Incorrect or unverified package references and suspicious installation hooks can introduce supply-chain risks.

These are reasons to combine AI-assisted development with security checks, testing, explicit permissions, and human review.

The skill is designed to pause before potentially risky actions, explain the possible consequences, and request approval.

Examples include file deletion, database writes, dependency installation, Git pushes, and changes to security-related configuration.

The actual enforcement depends on the agent's environment and permissions. For stronger protection, the project also recommends configuring explicit Claude Code permission rules.

Repositories can contain untrusted instructions in files such as CLAUDE.md, AGENTS.md, and editor-specific AI rules.

Safe AI Coding includes checks for suspicious instruction patterns, malicious Git configuration or hooks, symlinks to sensitive files, and hidden Unicode characters.

The goal is to help developers identify potentially dangerous repository content before trusting it.

These checks can help surface problems, but no automated review catches every defect.

The project documents checks for several risk categories, including:

Safe AI Coding is designed to review changes from two perspectives:

The documented review outcomes are Ready, Ready with notes, and Not ready.

These outcomes are review guidance, not a guarantee that the application is free from vulnerabilities.

Developers can request a PDF report summarizing identified issues, changes, fixes, and supporting evidence.

The repository documents English and Roman Urdu report options, which can make the results more accessible to different developers.

The README documents a self-test suite containing 95 cases intended to check detection behavior, legitimate code, and handling of potentially malicious repositories.

Developers should run the self-test in their own environment and review the results before relying on the tool in a production workflow.

The recommended installation method is through the Claude Code plugin marketplace.

/plugin marketplace add sami-hussain-dev/safe-ai-coding /plugin install safe-ai-coding@safe-ai-coding Enter fullscreen mode Exit fullscreen mode Alternatively, on Windows PowerShell, you can clone the repository into your personal Claude skills directory:

git clone --depth 1 https://github.com/sami-hussain-dev/safe-ai-coding.git " $ env: USERPROFILE \.claude\skills\safe-ai-coding" Enter fullscreen mode Exit fullscreen mode Use one installation method rather than both. Follow the repository's README for prerequisites, updates, and troubleshooting.

After installation, you can use the documented commands for common workflows.

/safe-ai-coding:safe-ai-coding scan Enter fullscreen mode Exit fullscreen mode Use this when beginning work in an unfamiliar repository and looking for potentially suspicious instructions or configuration.

/safe-ai-coding:safe-ai-coding build Add employee attendance API Enter fullscreen mode Exit fullscreen mode Use this workflow to request a feature and have the changes reviewed.

/safe-ai-coding:safe-ai-coding review main Enter fullscreen mode Exit fullscreen mode Use this to request a review against the main branch.

/safe-ai-coding:safe-ai-coding self-test Enter fullscreen mode Exit fullscreen mode Review the output and confirm that the expected checks work in your environment.

Check the repository documentation for the current command syntax and supported setup.

A coding skill can provide useful guidance and automated checks, but it cannot guarantee that an AI agent will never make a mistake or that every vulnerability will be detected.

For a stronger development workflow, combine it with:

Safe AI Coding is intended to support these practices, not replace them.

Although the project documents support for multiple programming stacks, its current implementation and compatibility should be evaluated for your particular environment.

I built Safe AI Coding to explore how security checks and review workflows can fit into AI-assisted development without making the process unnecessarily complicated.

I welcome feedback, bug reports, feature suggestions, and contributions from developers who want to help improve the project.

Explore the source code, review the documented checks, and try it in a test project before using it in critical workflows.

🔗 GitHub: https://github.com/sami-hussain-dev/safe-ai-coding

What security risk concerns you most when using AI coding agents: prompt injection, insecure generated code, exposed secrets, or destructive operations?

I'd love to hear your thoughts and learn from your experiences.

Author: Sami Hussain | Software Engineer and creator of Safe AI Coding