🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has moderate risks due to potential shell command execution and low maintainer activity, which raises concerns about its reliability and security.

High shell risk indicating potential for unauthorized command execution
Low maintainer activity suggesting poor package upkeep

Per-check LLM notes

Network: The network call to GitHub appears legitimate for fetching resources or updates.
Shell: Executing shell commands can be risky if not properly sanitized or controlled, potentially allowing unauthorized command execution.
Obfuscation: The use of base64 decoding might indicate an attempt to obfuscate code, but it could also be used for legitimate purposes such as encoding signatures.
Credentials: No clear patterns indicative of credential harvesting have been detected.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, but there's no clear evidence of malicious intent.

📦 Package Quality Overall: Low (2.8/10)

○ 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 (10174 chars)

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

◈ Medium Type Annotations 5.0

Partial type annotation coverage

221 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

keeps base CLI lean with httpx.Client(timeout=10.0) as client: response = client.get(GITHU

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

try: signature = base64.b64decode(signature_b64) except Exception as exc: # pragma: no co

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

".join(cmd), cwd) return subprocess.run( # noqa: S603 cmd, cwd=cwd, capture

✓ 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with agentops-accelerator

Create a Python-based mini-application that leverages the 'agentops-accelerator' package to manage release readiness for Microsoft Foundry agents. Your application should include the following key functionalities:

1. **Agent Registration**: Users should be able to register new agents by providing necessary details such as agent type, environment (e.g., staging, production), and specific configurations.
2. **Release Gates Management**: Implement a feature where users can define different release gates for their agents. These gates could include checks for code quality, security scans, performance benchmarks, etc.
3. **Evidence Submission and Verification**: After passing the defined gates, users should submit evidence (like logs, screenshots, reports) to prove compliance. The app should verify these submissions against predefined criteria.
4. **Dashboard for Monitoring**: Develop a simple dashboard where users can monitor the status of their agents across different environments. This includes visual indicators for each gate's status (passed, failed, pending).
5. **Notification System**: Integrate a notification system that alerts users via email or SMS when a gate fails or when evidence submission is required.

The 'agentops-accelerator' package will be utilized primarily for handling the registration and verification processes, ensuring that all operations align with Microsoft Foundry standards. Additionally, explore how you can use this package to streamline the evidence submission process, making it easier for developers to maintain compliance without manual intervention.