amni-prism

v0.1.2 suspicious
4.0
Medium Risk

Shared knowledge atlas built on PRISM-TEX (.ptex) nonce-addressed maps with content-hash dedup

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate level of suspicion due to its unknown author and low activity repository, despite showing no signs of immediate malicious behavior.

  • Unknown author with incomplete details
  • Low activity git repository
Per-check LLM notes
  • Network: The presence of network calls suggests external API interactions which could be legitimate but requires further investigation to confirm the purpose and destination.
  • Shell: No shell execution patterns detected, indicating low risk for direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The package shows some red flags such as an unknown author with a short or missing name and a low activity git repository, suggesting potential unreliability.

📦 Package Quality Overall: Medium (5.2/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_integration.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (3310 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 71 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 7 commits in Amnibro/Amni-Prism
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

  • if stream: r = requests.post(NANO_URL, json=payload, stream=True, timeout=60) fu
  • _text else: r = requests.post(NANO_URL, json=payload, timeout=60) r.raise_for_sta
  • 'temperature': temp} r = requests.post(url, json=payload, headers=headers, timeout=45) r.raise
  • temperature': temp}} r = requests.post(url, json=payload, headers={'x-goog-api-key': key}, timeout=
✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: users.noreply.github.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 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 amni-prism 
Create a Python-based file management system that leverages the 'amni-prism' package to handle large datasets efficiently. This system should allow users to store, retrieve, and manage files using nonce-addressed maps and content-hash deduplication, ensuring minimal storage space usage while maintaining fast access times. Here are the key features and steps to implement the project:

1. **User Interface**: Develop a simple command-line interface (CLI) or a basic web frontend using Flask or Django for users to interact with the file management system.
2. **File Upload**: Implement a feature where users can upload files of any type. The system should use 'amni-prism' to store these files in a manner that minimizes duplicate data across multiple uploads.
3. **File Retrieval**: Allow users to search for and download files based on their content hashes or nonce addresses. Ensure that the retrieval process is quick and efficient.
4. **Data Integrity Checks**: Utilize the content-hash feature of 'amni-prism' to perform integrity checks on stored files, ensuring that no corruption has occurred during storage or transmission.
5. **Analytics and Reporting**: Provide users with reports on storage efficiency, showing how much space has been saved due to deduplication.
6. **Security Measures**: Implement basic security measures such as encryption of files before storage and secure handling of user data.
7. **Integration with Cloud Storage**: Optionally, integrate the system with cloud storage providers like AWS S3 or Google Cloud Storage for seamless off-site backups.

The 'amni-prism' package will be central to this project, providing the underlying technology for storing files efficiently. Your task is to design and develop a robust, user-friendly file management system that showcases the power of 'amni-prism' in handling large volumes of data.

💬 Discussion Feed

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