AI Analysis
The package shows some potential risks related to network calls, shell execution, and metadata, but these are within expected norms for a legitimate package integrating with Google services. There's no evidence of malicious activity.
- Normal network and shell execution risks due to Google service integration
- No signs of credential harvesting or malicious obfuscation
Per-check LLM notes
- Network: Network calls are expected for interacting with Google services, indicating normal behavior for a package that integrates with Google providers.
- Shell: Shell execution might be used for running local commands like gcloud, which is reasonable for a package managing Google cloud operations, but could pose risks if not properly sanitized or controlled.
- Obfuscation: The observed patterns are likely related to legitimate data decoding and not malicious obfuscation.
- Credentials: No signs of credential harvesting detected.
- Metadata: The package has a non-secure external link and an author with limited information, but no clear indicators of malicious intent.
Package Quality Overall: Medium (6.2/10)
No test suite detected
No test files or test-runner configuration detected
Well-documented package
Documentation URL: "Documentation" -> https://airflow.apache.org/docs/apache-airflow-providers-goo1 documentation file(s) (e.g. conf.py)Detailed PyPI description (12793 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
Type checker (mypy / pyright / pytype) referenced in project742 type-annotated function signatures detected in source
Active multi-contributor project
46 unique contributor(s) across 100 commits in apache/airflowActive community — 5 or more distinct contributors
Heuristic Checks
Found 6 network call pattern(s)
oint_path) response = requests.get(url, headers=self._headers) self._raise_for_status(roint_path) response = requests.get(url, headers=self._headers, params=params) self._raioint_path) response = requests.post(url, headers=self._headers, data=json.dumps(body_request))endpoint) response = requests.post(url, headers=self._headers, data=json.dumps(body_request))} response = requests.post(url, headers=self._headers, data=json.dumps(body_request))oint_path) response = requests.delete(url, headers=self._headers) self._raise_for_status(r
Found 3 obfuscation pattern(s)
secret_data = json.loads(base64.b64decode(secret.payload.data)) if cert_name in secret_data:tring to bytes.""" return base64.b64decode(s.encode("utf-8")) class CloudKMSHook(GoogleBaseHook):under the License. __path__ = __import__("pkgutil").extend_path(__path__, __name__) # Licensed to the Apache S
Found 2 shell execution pattern(s)
arameters()) result = subprocess.check_output(command_to_run).decode("utf-8") matched = re.search(_gcloud(): proc = subprocess.run(cmd, check=False, capture_output=True) if proc.retu
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: airflow.apache.org>
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://www.apache.org/licenses/LICENSE-2.0
Repository apache/airflow appears legitimate
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Build a simple Python application using the apache-airflow-providers-google package to demonstrate its core features.
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