AI Analysis
Final verdict: SUSPICIOUS
The package exhibits moderate network and metadata risks, with potential for unexpected network behavior and concerns around its maintenance status.
- Moderate network risk
- Metadata red flags including anonymous maintainer and low activity
Per-check LLM notes
- Network: Network calls to a controlled endpoint may be part of legitimate functionality, but should be scrutinized for unexpected behavior.
- Shell: Shell executions with trusted constants are less suspicious, but the package's purpose should be verified to ensure these commands are intended.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or sensitive information being stolen.
- Metadata: The package shows some red flags such as an anonymous maintainer and low activity, but no clear signs of typosquatting or malicious intent.
Package Quality Overall: Medium (6.6/10)
✦ High
Test Suite
9.0
Test suite present — 7 test file(s) found
Test runner config found: pyproject.toml7 test file(s) detected (e.g. test_anthropic_batch.py)
✦ High
Documentation
9.0
Well-documented package
Documentation URL: "Documentation" -> https://github.com/Smart-AI-Memory/attune-author/blob/main/RDetailed PyPI description (12256 chars)Classifier: Documentation
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium
Type Annotations
7.0
Partial type annotation coverage
Type checker (mypy / pyright / pytype) referenced in project342 type-annotated function signatures detected in source
◈ Medium
Multiple Contributors
6.0
Limited contributor diversity
2 unique contributor(s) across 99 commits in Smart-AI-Memory/attune-authorTwo distinct contributors found
Heuristic Checks
Outbound Network Calls
score 9.0
Found 6 network call pattern(s)
)}).encode("utf-8") req = urllib.request.Request( f"{sidecar.url}/api/corpus/resolve",, ) try: with urllib.request.urlopen(req, timeout=5.0) as resp: # noqa: S310r ``corpus_id``.""" req = urllib.request.Request( f"{sidecar.url}/api/corpus", header//127.0.0.1"}, ) with urllib.request.urlopen(req, timeout=5.0) as resp: # noqa: S310 bod"}).encode("utf-8") req = urllib.request.Request( f"{sidecar.url}/api/corpus/register",method="POST", ) with urllib.request.urlopen(req, timeout=5.0) as resp: # noqa: S310 ent
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
score 10.0
Found 6 shell execution pattern(s)
ath) try: proc = subprocess.Popen( # noqa: S603 — cmd is constructed from a fixed allowlistass try: result = subprocess.run( [cli, "--version"], capture_output=one try: result = subprocess.run( [cli, *subcommand_chain, "--help"],try: result = subprocess.run( # noqa: S603 - args are trusted constantsp"] try: result = subprocess.run( # noqa: S603 - args are trusted manifest input""" try: output = subprocess.run( ["git", "diff", "--name-only", "HEAD~1", "HEAD"
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
Email domain looks legitimate: smartaimemory.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 attune-author
Create a Python-based documentation management tool named 'DocCraft' using the 'attune-author' package. DocCraft should streamline the process of generating, maintaining, and validating technical documentation within a development team. Here’s a step-by-step guide on what your application should achieve: 1. **Setup and Configuration**: Initialize DocCraft with configuration options for different types of documentation (API docs, user guides, etc.). Use 'attune-author' to set up templates and initial content structures. 2. **Content Generation**: Implement a feature where developers can input code snippets or API endpoints, and DocCraft automatically generates corresponding documentation based on these inputs. Leverage 'attune-author' for AI-driven content generation. 3. **Version Control Integration**: Integrate DocCraft with version control systems like Git to track changes in documentation over time. Ensure that each commit message includes a brief description of the changes made to the documentation. 4. **Collaboration Features**: Enable real-time collaboration among team members by allowing multiple users to edit and review documentation simultaneously. Utilize 'attune-author' to manage access controls and ensure that only authorized users can make changes. 5. **Validation and Quality Assurance**: Incorporate a feature that validates the generated documentation against predefined standards and best practices. Use 'attune-author' to run checks for consistency, accuracy, and completeness. 6. **Reporting and Analytics**: Provide insights into the usage and effectiveness of the documentation through reporting and analytics tools. Highlight areas for improvement and suggest enhancements based on user feedback and usage patterns. 7. **User Interface**: Develop a user-friendly interface that simplifies the process of managing documentation. Include features such as search functionality, a dashboard for tracking progress, and easy navigation between different sections of the documentation. Ensure that 'attune-author' is utilized throughout the development process to assist in automating repetitive tasks, improving the quality of the generated content, and ensuring that all documentation adheres to established guidelines and standards.
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