🤖 AI Analysis

Final verdict: SUSPICIOUS

The package executes shell commands and makes network calls, which could lead to unauthorized external communications or unintended system actions. However, there is no evidence of obfuscation, credential harvesting, or malicious intent.

High shell execution risk
Moderate network interaction risk

Per-check LLM notes

Network: The network calls suggest legitimate API interactions but could indicate unauthorized external communications if the API endpoints are not controlled by the user.
Shell: Executing shell commands can be risky as it may lead to unintended actions on the system, especially if the commands are influenced by untrusted inputs.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has only one package, indicating a potentially new or less active account.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

-> None: self._http = httpx.Client(base_url=base_url, timeout=timeout) self._public_dir
ovided") self._http = httpx.AsyncClient(base_url=base_url, timeout=timeout) self._token = to
ovided") self._http = httpx.Client(base_url=base_url, timeout=timeout) self._token = to
in_login() -> str: resp = httpx.post( f"{BASE_URL}/v1/disk/admin/login", json={"u
oken: str) -> str: resp = httpx.post( f"{BASE_URL}/v1/disk/admin/api-keys", heade
ame: str) -> dict: resp = httpx.post( f"{BASE_URL}/v1/disk/admin/public-directories",

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

agent_group_id] result = subprocess.run( args, capture_output=True, text=True, cwd=os.path.d

✓ 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 wybug/AgentDisk appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "wangyun" 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 agentdisk

Create a desktop utility called 'DiskGuardian' using the Python package 'agentdisk'. DiskGuardian will serve as a user-friendly tool for monitoring and managing disk space on your computer. It should have the following features:

1. **Real-time Disk Monitoring**: Display real-time information about available disk space on all connected drives.
2. **Threshold Alerts**: Set customizable threshold alerts for when disk usage exceeds a certain percentage of total capacity.
3. **File Search & Cleanup**: Allow users to search for large files and directories and provide options to delete or move them to free up space.
4. **Scheduled Reports**: Users can schedule periodic reports of disk usage statistics via email.
5. **User-Friendly Interface**: Develop a simple, intuitive GUI using a Python library such as PyQt or Tkinter.
6. **Logging**: Keep logs of all actions taken within DiskGuardian, including alerts triggered and files deleted.
7. **Backup Configuration**: Allow users to configure automatic backups of important files before performing cleanup operations.

To achieve these features, you'll utilize the 'agentdisk' package's core functionalities, which include interacting with the AgentDisk API in gateway mode. This involves fetching disk space details, setting up alert configurations, and handling file management tasks through the API endpoints provided by 'agentdisk'. Your task is to write clean, well-documented code and ensure that DiskGuardian is both efficient and reliable.