🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risk due to unverified network calls and an untraceable repository, raising concerns about potential supply-chain attacks.

Moderate network risk due to insecure or illegitimate network calls.
Unverified maintainer with a single package and no traceable repository.

Per-check LLM notes

Network: The presence of network calls is typical for an SDK that interfaces with external services, but further review is needed to ensure requests are secure and legitimate.
Shell: No shell execution patterns were detected, which is expected and indicates the absence of immediate risks related to command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The repository is not found, and the maintainer has only one package, which could indicate a less established or potentially suspicious activity.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

ry.""" self._client = httpx.AsyncClient( base_url=self.base_url, timeout=sel
try: with httpx.Client(timeout=request_timeout) as client: resp
e: self._client = httpx.AsyncClient(timeout=30.0) return self._client async def _se
" try: async with httpx.AsyncClient() as client: response = await client.get(f"{serv

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ 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 score 3.0

Repository not found (deleted or private)

Repository not found (deleted or private)

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Agent Control Team" 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 agent-control-sdk

Develop a mini-application named 'AI Guardian' using the Python package 'agent-control-sdk'. This application will serve as a robust control panel for managing and safeguarding AI agents deployed across various environments. Your task is to create a user-friendly interface where users can define rules, monitor agent activities, and enforce security measures dynamically.

### Features:
1. **Agent Registration**: Allow users to register new AI agents by providing essential details such as agent name, type, and environment.
2. **Rule Creation**: Enable users to create custom control rules based on specific criteria (e.g., time of day, location, data sensitivity).
3. **Activity Monitoring**: Implement real-time monitoring of agent activities, including logs and performance metrics.
4. **Security Enforcement**: Automatically apply security measures according to defined rules, such as pausing operations during off-hours or blocking access to sensitive data.
5. **User Interface**: Design a simple and intuitive web-based UI for easy management and interaction.
6. **Reporting**: Generate periodic reports summarizing agent activities and compliance with control rules.

### Utilization of 'agent-control-sdk':
- Use the SDK to integrate its core functionalities into each feature of the application, ensuring seamless interaction with AI agents and enforcement of control policies.
- Leverage the SDK's capabilities for defining and enforcing rules, monitoring activities, and securing AI operations.
- Ensure that all interactions with AI agents are protected and controlled as per the guidelines provided by the SDK documentation.