AI Analysis
The package exhibits moderate risks due to potential shell execution and obfuscation techniques, which require closer scrutiny to determine their legitimacy.
- Shell risk due to possible execution of commands
- Potential obfuscation via base64 encoding and json.loads
Per-check LLM notes
- Network: No network calls detected.
- Shell: Shell execution is present but may be for development or testing purposes; requires further investigation into context and commands executed.
- Obfuscation: The use of base64 encoding and json.loads suggests potential obfuscation, but could also be a legitimate use for data encoding.
- Credentials: No clear signs of credential harvesting or secret handling observed.
- Metadata: The repository has low activity and the maintainer's information is sparse, raising some suspicion but not conclusive evidence of malintent.
Package Quality Overall: Medium (6.2/10)
Test suite present — 14 test file(s) found
Test runner config found: pyproject.tomlTest runner config found: conftest.py14 test file(s) detected (e.g. _fake_native.py)
Some documentation present
1 documentation file(s) (e.g. check_structure.py)Detailed PyPI description (4598 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
Classifier: Typing :: Typed129 type-annotated function signatures detected in source
Limited contributor diversity
2 unique contributor(s) across 27 commits in social-home-io/aiolibdatachannelTwo distinct contributors found
Heuristic Checks
No suspicious network call patterns found
Found 1 obfuscation pattern(s)
bject]: return json.loads(base64.b64decode(line.strip())) async def main() -> None: cfg = RTCConf
Found 5 shell execution pattern(s)
IRE_NATIVE"] = "1" return subprocess.run( [sys.executable, "-X", "dev", "-c", textwrap.dedent""" ) proc = subprocess.run( [sys.executable, "-X", "dev", "-c", script],getmtime(self.header) subprocess.run([WorkTree.make_command, 'amalgamate'], cwd=self.tree_dir,continue fuzzer_retval = subprocess.call(["./check-input.sh", filename, "batchmode"], stdout=FNULL, s'dumpbin'): dumpbin_cmd = subprocess.run(['dumpbin', '/linkermember:1', lib_file], stdout=sub
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: nabucasa.com>
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
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
Create a real-time collaborative document editor using the Python package 'aiolibdatachannel'. This application will allow multiple users to simultaneously edit a shared text document in real-time, similar to Google Docs. The app should include the following core functionalities: 1. User Authentication: Implement a simple user authentication system where users can sign in or create an account. 2. Real-Time Collaboration: Users should be able to see each other's cursor movements and text changes as they happen, ensuring a seamless collaborative experience. 3. Document History: Maintain a history of all edits made to the document, allowing users to revert to previous versions if needed. 4. Conflict Resolution: Handle situations where two users attempt to modify the same part of the document simultaneously, ensuring that both changes are eventually applied without loss of data. 5. Offline Support: Allow users to continue editing the document even when disconnected from the internet, syncing changes once reconnected. 6. Notifications: Send notifications to users about new collaborators joining the session or when conflicts arise during editing. To achieve these functionalities, you'll primarily use 'aiolibdatachannel' for establishing and managing WebRTC Data Channels between connected clients. These channels will facilitate real-time communication between users, enabling instantaneous sharing of cursor positions, text updates, and other collaboration-related data. Additionally, integrate asyncio for handling asynchronous operations efficiently, ensuring smooth performance even under heavy load conditions.
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