aistore

v1.25.0 suspicious
4.0
Medium Risk

Client-side APIs to access and utilize clusters, buckets, and objects on AIStore.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in network, shell, and credential aspects, but the presence of base64 decoding and an incomplete maintainer metadata suggest potential issues that require further investigation.

  • Base64 decoding present
  • Incomplete maintainer metadata
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network interaction for its functionality.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing external commands.
  • Obfuscation: Base64 decoding is commonly used for data serialization and may not indicate malicious intent.
  • Credentials: No patterns indicative of credential harvesting were detected.
  • Metadata: The maintainer has a new or inactive account and lacks a full author name, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://aistore.nvidia.com/docs/python-sdk
  • Brief PyPI description (672 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 173 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 9 unique contributor(s) across 100 commits in NVIDIA/aistore
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • not None: code = base64.b64decode(code) return code @field_validator("spec")
  • not None: spec = base64.b64decode(spec) return spec class ETLObjError(BaseModel):
✓ 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: nvidia.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository NVIDIA/aistore 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 aistore 
Create a Python-based mini-application called 'AIStoreManager' that leverages the 'aistore' package to manage data storage and retrieval within AIStore clusters. This application will serve as a simplified interface for users to interact with their AIStore environments, providing functionalities such as uploading files, downloading files, listing bucket contents, and deleting files.

The application should include the following features:
1. **User Authentication**: Implement a basic authentication mechanism where users provide credentials to access their specific AIStore cluster.
2. **Bucket Management**: Allow users to create new buckets, delete existing ones, and list all available buckets in their cluster.
3. **File Operations**: Enable users to upload files to a specified bucket, download files from a bucket, and delete files from a bucket.
4. **Progress Tracking**: Display progress bars for file uploads and downloads to give users real-time feedback on the status of these operations.
5. **Error Handling**: Implement robust error handling to manage issues such as invalid credentials, non-existent buckets, and failed file operations.
6. **CLI Interface**: Develop a command-line interface (CLI) for the application, making it accessible via terminal commands.
7. **Configuration File**: Introduce a configuration file where users can store their cluster details and preferred settings.

To achieve these objectives, you will need to utilize the 'aistore' package's core functionalities, including connecting to AIStore clusters, interacting with buckets, and performing operations on objects within those buckets. Additionally, explore the package's documentation to discover any advanced features or best practices that could enhance your application's performance and user experience.

💬 Discussion Feed

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