🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate to high risks due to potential credential harvesting and uncontrolled shell command execution, which could lead to serious security vulnerabilities.

High credential risk due to potential credential harvesting.
Significant shell risk due to uncontrolled execution of shell commands.

Per-check LLM notes

Network: The use of an HTTP client might be legitimate depending on the package's purpose, but requires verification of its intended use.
Shell: Executing shell commands can introduce significant risk if not properly controlled and documented, especially when invoking Python scripts.
Obfuscation: No obfuscation patterns detected.
Credentials: Potential credential harvesting through system file reads indicates a high risk.
Metadata: Suspicious non-HTTPS links and a single package from a potentially new maintainer suggest some risk, but no clear evidence of typosquatting or direct malicious intent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

None self._client = httpx.AsyncClient( transport=transport, timeout=httpx.
imeout self._client = httpx.Client( timeout=httpx.Timeout(timeout), lim

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

t subprocess result = subprocess.run( [sys.executable, "-m", "agent_gate", "--help"],

⚠ Credential Harvesting score 7.5

Found 3 credential access pattern(s)

"read", "action_detail": "cat /etc/passwd"}, {"action_type": "bash", "action_detail":
"read", "action_detail": "cat /etc/hosts", }, {"decision": "Allow"}) history = repo
"read", "action_detail": "cat /etc/hosts"} def test_system_snapshot(self, repo): repo.g

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

⚠ Suspicious Page Links score 8.0

Found 4 suspicious link(s) on the package page

Non-HTTPS external link: http://127.0.0.1:9090/api/v1/health
Non-HTTPS external link: http://127.0.0.1:9100/api/v1/health
Non-HTTPS external link: http://127.0.0.1:9100/api/v1/analyze
Non-HTTPS external link: http://127.0.0.1:9100

⚠ 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 "AgentGate 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-gate-sec

Your task is to create a small but powerful data analysis tool using the 'agent-gate-sec' Python package. This package specializes in facilitating data collection and security analysis through an intermediate service layer designed for AI agents. Your application will serve as a bridge between various data sources and security analysis tools, making it easier to process and understand complex data sets from a security perspective.

Step 1: Define the Scope
- Identify key areas of security interest such as intrusion detection, anomaly detection, or compliance monitoring.
- Choose two different types of data sources (e.g., network logs, system logs, application logs).

Step 2: Set Up the Environment
- Install necessary Python packages including 'agent-gate-sec'.
- Configure access to your chosen data sources.

Step 3: Data Collection
- Use 'agent-gate-sec' to set up automated data collection routines from your selected data sources.
- Ensure data is collected securely and efficiently.

Step 4: Data Processing
- Implement basic preprocessing steps like normalization and filtering.
- Utilize 'agent-gate-sec' functionalities to enrich data with metadata relevant for security analysis.

Step 5: Security Analysis
- Develop algorithms or use pre-existing models to analyze data for security insights.
- Leverage 'agent-gate-sec' for advanced analysis capabilities, such as pattern recognition and anomaly detection.

Step 6: Reporting
- Create a user-friendly interface to display findings and insights.
- Allow users to export reports in various formats (CSV, PDF, etc.).

Suggested Features:
- Real-time alerting system for critical events.
- Historical data comparison to identify trends.
- Integration with external security tools for further analysis.
- User role-based access control to ensure data privacy.

How 'agent-gate-sec' is Utilized:
- For seamless data collection from multiple sources without needing direct access configurations.
- To enhance data processing efficiency by providing optimized data handling routines.
- In performing security analyses with built-in functions for common security tasks.
- As a platform for integrating third-party security tools and services.