aws-parallelcluster-node

v3.15.1 suspicious
6.0
Medium Risk

aws-parallelcluster-node provides the scripts for an AWS ParallelCluster node.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows signs of potential obfuscation and shell execution risks, which could indicate attempts to evade detection or perform unauthorized actions.

  • High obfuscation risk
  • Potential shell execution with elevated permissions
Per-check LLM notes
  • Network: No network calls detected, which is not necessarily suspicious.
  • Shell: Shell execution with elevated permissions might be risky if not properly sanitized or controlled, suggesting potential for command injection attacks.
  • Obfuscation: The use of __import__ with dynamic strings may indicate an attempt to evade static analysis and could be used for malicious purposes.
  • Credentials: No patterns indicative of credential harvesting were found.
  • Metadata: The author has only one package, which might indicate a new or less active account, but there are no other suspicious flags.

📦 Package Quality Overall: Low (4.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ 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

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

Active multi-contributor project

  • 13 unique contributor(s) across 100 commits in aws/aws-parallelcluster-node
  • 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)

  • """ # import module __import__(module) # get module from the loaded maps scheduler_module
  • overrides_module = __import__(f"{func_parent_module}.overrides", fromlist=function_name) overrided_func = getattr(overrides_module,
⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

  • _command, _env, _preexec_fn: subprocess.run( _command, env=_env, pre
  • ror, timeout=command_timeout, shell=True ) def update_partitions(partitions, state): s
  • state}", raise_on_error=True, shell=True ) succeeded_partitions.append(parti
  • and, timeout=command_timeout, shell=True) # nosec B604 return _parse_nodes_info(nodeinfo_str)
  • and, timeout=command_timeout, shell=True # nosec B604 ) partitions_info = _parse_partition_
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository aws/aws-parallelcluster-node appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Amazon Web Services" 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 aws-parallelcluster-node 
Create a fully functional mini-application called 'ParallelClusterTaskManager' that leverages the 'aws-parallelcluster-node' package to manage tasks across multiple nodes in an AWS ParallelCluster environment. This application should serve as a task scheduler, allowing users to submit tasks to the cluster, monitor their progress, and retrieve results. The main goal is to demonstrate the ease of task distribution and management using AWS ParallelCluster with 'aws-parallelcluster-node'.

### Features:
1. **Task Submission**: Users should be able to submit Python scripts or simple computational tasks to the cluster. Each task will be executed on a different node.
2. **Progress Tracking**: Implement a feature where users can track the status of their submitted tasks. This includes details like start time, estimated completion time, and current progress.
3. **Result Retrieval**: Once a task completes, its output or result should be retrievable from the application.
4. **Node Management**: The application should provide basic node management capabilities such as adding or removing nodes from the cluster dynamically based on load.
5. **User Interface**: Develop a simple web interface using Flask or similar framework to interact with the application. This UI should allow users to upload tasks, check task statuses, and download results.
6. **Logging and Alerts**: Implement logging for all actions taken within the application and set up alerts for critical events such as task failures.

### Utilization of 'aws-parallelcluster-node':
- Use 'aws-parallelcluster-node' scripts to configure and manage the nodes within your AWS ParallelCluster setup.
- Ensure that the Python scripts submitted as tasks can leverage the environment configured by 'aws-parallelcluster-node' for optimal performance.
- Utilize 'aws-parallelcluster-node' functionalities to scale the cluster according to the number of tasks in queue.

### Steps to Build the Application:
1. Set up an AWS ParallelCluster environment using 'aws-parallelcluster-node'.
2. Design and implement the backend logic for task submission, tracking, and retrieval.
3. Develop the frontend using Flask to provide a user-friendly interface.
4. Integrate logging and alerting mechanisms.
5. Test the application thoroughly under various conditions to ensure reliability and performance.

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