AI Analysis
Final verdict: SAFE
The package appears to be legitimate with minimal risk indicators. The low scores across all categories suggest that it performs its intended functions without exhibiting malicious behavior.
- Low network and shell risks consistent with package functionality.
- No evidence of obfuscation, credential theft, or unusual metadata suggesting supply-chain compromise.
Per-check LLM notes
- Network: No network calls are expected unless the package is intended to communicate with Azure Storage services, which is normal and expected behavior for this type of package.
- Shell: Executing shell commands is not expected behavior for this package, but the absence of shell execution patterns does not necessarily indicate risk since the primary function of this package is not related to system administration.
- Obfuscation: The observed patterns appear to be related to data encoding and path manipulation, likely for legitimate purposes such as handling file paths or encoding data.
- Credentials: No suspicious patterns indicating credential harvesting were found.
- Metadata: The author has only one package, which may indicate a new or less active account, but no other suspicious flags were raised.
Package Quality Overall: Medium (5.0/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (15401 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
313 type-annotated function signatures detected in source
✦ High
Multiple Contributors
10.0
Active multi-contributor project
35 unique contributor(s) across 100 commits in Azure/azure-sdk-for-pythonActive community — 5 or more distinct contributors
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
score 6.0
Found 3 obfuscation pattern(s)
ta.encode("utf-8") return base64.b64decode(data) def decode_base64_to_text(data): decoded_bytes =__path__ = __import__('pkgutil').extend_path(__path__, __name__) # type: ignore __path__ =) # type: ignore __path__ = __import__('pkgutil').extend_path(__path__, __name__) # type: ignore # --------
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: microsoft.com
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository Azure/azure-sdk-for-python appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Microsoft Corporation" 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 azure-storage-file-datalake
Create a data management utility that leverages the Azure Data Lake Storage service through the 'azure-storage-file-datalake' Python package. This utility will enable users to perform basic operations such as uploading files, downloading files, listing all files within a specified directory, and deleting files from their Azure Data Lake Storage account. Additionally, include a feature that allows users to search for files based on metadata tags (such as file creation date or custom tags). The application should also support logging of actions performed on the Data Lake Storage, such as timestamped logs indicating when files were uploaded, downloaded, deleted, or modified. Users should be able to authenticate using Azure Active Directory credentials. Ensure the application is well-documented and includes error handling for common issues like incorrect credentials or network failures. Use this package to interact with Azure Data Lake Storage and manage files efficiently.
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