atomic-spec

v0.2.0 suspicious
6.0
Medium Risk

Atomic Traceability for AI-Driven Development — a governance framework that constrains AI coding agents via gated, atomic, context-pinned phases.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risks due to high credential harvesting concerns and insufficient documentation for shell command usage, which could indicate potential malicious intent or poor coding practices.

  • High credential risk
  • Insufficient documentation for shell commands
Per-check LLM notes
  • Network: TLS client usage indicates secure network communication, but requires context to determine legitimacy.
  • Shell: Use of subprocess.run for shell commands can be legitimate but raises concerns without clear documentation or purpose.
  • Obfuscation: No obfuscation patterns detected.
  • Credentials: High risk of credential harvesting observed in the code.
  • Metadata: The maintainer's author information is incomplete and may indicate a new or less active account, but no other red flags were identified.

📦 Package Quality Overall: Medium (5.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/Chappygo-OS/Atomic-Spec#readme
  • Detailed PyPI description (31561 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 25 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 10 unique contributor(s) across 100 commits in Chappygo-OS/Atomic-Spec
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • PROTOCOL_TLS_CLIENT) client = httpx.Client(verify=ssl_context) # Release source — where this CLI fetch
  • ent is None: client = httpx.Client(verify=ssl_context) if verbose: console.print("
  • se local_client = httpx.Client(verify=local_ssl_context) download_and_extract_
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • capture: result = subprocess.run(cmd, check=check_return, capture_output=True, text=True, she
  • p() else: subprocess.run(cmd, check=check_return, shell=shell) return Non
  • if inside a work tree subprocess.run( ["git", "rev-parse", "--is-inside-work-tree"],
  • epository...[/cyan]") subprocess.run(["git", "init"], check=True, capture_output=True, text=True)
  • tput=True, text=True) subprocess.run(["git", "add", "."], check=True, capture_output=True, text=T
  • tput=True, text=True) subprocess.run(["git", "commit", "-m", "Initial commit from Atomic Spec tem
⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • n or os.getenv("GH_TOKEN") or os.getenv("GITHUB_TOKEN") or "").strip()) or None def _github_auth_headers(cli_tok
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Chappygo-OS/Atomic-Spec appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with atomic-spec 
Develop a mini-application named 'AI Code Auditor' that leverages the 'atomic-spec' package to ensure the integrity and traceability of code generated by AI-driven development tools. This tool will serve as a governance layer to monitor and control the AI's coding process, ensuring that it adheres to predefined constraints and standards.

Step 1: Define the Core Functionality
The application should be able to:
- Accept a piece of code as input, which could be generated by any AI coding assistant.
- Analyze the code based on predefined rules or specifications.
- Apply 'atomic-spec' to break down the code analysis into gated, atomic phases, ensuring each phase is context-pinned.
- Provide a report detailing whether the code meets the specified criteria or not.

Step 2: Feature Implementation
- **Rule Definition**: Users should be able to define their own rules or use pre-defined ones provided by the system. These rules could include coding style guidelines, security checks, performance metrics, etc.
- **Atomic Phases**: Implement atomic phases such as syntax check, semantic validation, security assessment, and performance evaluation. Each phase should be isolated and independently executable.
- **Context-Pinning**: Ensure that each phase operates within a specific context, meaning that the results from one phase should not influence another phase directly. For example, a syntax error should halt the process but not affect the security assessment.
- **Reporting**: Generate comprehensive reports after each phase and a final summary report that highlights any issues found during the audit.

Step 3: Utilizing 'atomic-spec'
- Use 'atomic-spec' to enforce the gated, atomic nature of the code audit process. This ensures that the AI-generated code is evaluated in a controlled manner, preventing any single failure point from derailing the entire process.
- Leverage 'atomic-spec' to pin each phase to its respective context, maintaining the integrity and independence of each phase's execution.
- Integrate 'atomic-spec' to provide real-time feedback and adjustments if certain phases fail, allowing for iterative improvements in the code generation process.

By following these steps and utilizing the 'atomic-spec' package, the 'AI Code Auditor' will become a powerful tool for developers and organizations looking to harness AI-driven development while maintaining strict control over the quality and integrity of the generated code.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!