GDAL

v3.13.1 safe
4.0
Medium Risk

GDAL: Geospatial Data Abstraction Library

🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with no direct evidence of malicious intent. While there are some indicators that could suggest obfuscation or unusual behavior, these do not strongly point towards a supply-chain attack.

  • No network or shell risks detected
  • Potential obfuscation through use of eval, but likely related to functionality
  • Single package from maintainer account
Per-check LLM notes
  • Network: No network calls detected, which is normal.
  • Shell: Shell execution is used for executing GDAL tools like 'listgeo', suggesting the package is functioning as intended for its purpose.
  • Obfuscation: The use of eval with dynamic namespaces might indicate an attempt to obfuscate code execution, but it could also be part of complex logic handling in GDAL.
  • Credentials: No clear signs of credential harvesting detected.
  • Metadata: The maintainer has only one package on PyPI, which may indicate a new or less active account. The non-HTTPS external link is suspicious but does not necessarily imply malice.

🔬 Heuristic Checks

Outbound Network Calls

No suspicious network call patterns found

Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • myResult = eval(this_calc, global_namespace, local_namespace)
Shell / Subprocess Execution score 8.0

Found 4 shell execution pattern(s)

  • Error: pass rc = os.system(htdp_path + " < " + control_fn) if rc != 0: prin
  • try: output = subprocess.check_output(["listgeo", filename]).decode("LATIN1") except Excep
  • s = None output = subprocess.check_output(["listgeo", tmp_filename]).decode("LATIN1") os.r
  • lit()[1] try: p = subprocess.Popen([command, args], stdout=subprocess.PIPE) except OSError:
Credential Harvesting

No credential harvesting patterns detected

Typosquatting

No typosquatting candidates detected

Registered Email Domain

Email domain looks legitimate: pobox.com

Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://www.gdal.org
Git Repository History

Repository OSGeo/gdal appears legitimate

Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Frank Warmerdam, Howard Butler, Even Rouault" 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 GDAL
Create a Python-based mini-application called 'GeoTiler' which takes a large geospatial raster dataset as input and divides it into smaller, more manageable tiles based on user-defined criteria such as tile size and overlap. The application should also allow users to specify an area of interest (AOI) to focus on within the larger dataset. Utilize the GDAL package to read, manipulate, and write geospatial data efficiently.

Step 1: Define the application's main functionality:
- Read a geospatial raster dataset using GDAL.
- Divide the dataset into smaller tiles based on user input.
- Optionally, apply a transformation (e.g., re-projection) to the tiles if needed.
- Write each tile to disk as a separate file.

Step 2: Suggested Features:
- User interface for selecting the input dataset and specifying parameters like tile size and AOI.
- Option to visualize the tiles before saving them.
- Support for different output formats (e.g., GeoTIFF).
- Logging and error handling to ensure robust operation.

Step 3: Implementation Details:
- Use GDAL's `gdal.Open()` function to open the input raster dataset.
- Implement logic to determine the extent of the AOI and calculate tile boundaries.
- Use GDAL's `gdal.Translate()` or similar functions to create and save each tile.
- Provide feedback to the user about progress and completion status.