agentx-security-sdk

v0.2.11 suspicious
4.0
Medium Risk

The self-healing exception handler for autonomous AI agents.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some red flags due to its metadata and unavailability of the git repository, but the network and shell risks are low.

  • Metadata risk score is 5 out of 10 due to a single package from an unknown maintainer.
  • Git repository not found, adding to the suspicion.
Per-check LLM notes
  • Network: The observed network calls appear to be for telemetry and policy fetching, which could be legitimate for a security SDK aiming to sync policies or gather operational data.
  • Shell: No shell execution patterns were detected.
  • Metadata: The maintainer has only one package and the git repository is not found, raising suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (3.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_agentx_sdk.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (14902 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

  • 6 type-annotated function signatures (partial)
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • try: telemetry_res = requests.get(f"{gateway_url}/v1/telemetry", headers=headers, timeout=2.0)
  • ut=2.0) policy_res = requests.get(f"{gateway_url}/v1/debug/policies", headers=headers, timeout
  • pi_key}"} response = requests.get(f"{control_plane_url}/api/edge/sync", headers=headers, timeo
  • try: response = requests.get(f"{gateway_url}/v1/debug/policies", headers=headers, timeout
  • try: response = requests.post( f"{self.gateway_url}/v1/evaluate",
  • status_check = requests.get( f"{_client.gateway_url}/v1/sta
✓ 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

Email domain looks legitimate: agentx-core.com

✓ 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 "AgentX Core 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 agentx-security-sdk 
Your task is to create a Python-based mini-application named 'AutoGuardian' which leverages the 'agentx-security-sdk' package to provide robust security and self-healing capabilities for autonomous AI agents. AutoGuardian will serve as a watchdog that monitors and manages a fleet of AI agents, ensuring they operate securely and efficiently. Here’s a detailed breakdown of the application’s functionality and features:

1. **Initialization**: Upon startup, AutoGuardian will initialize its connection with the fleet of AI agents. It will authenticate each agent using the 'agentx-security-sdk' for secure communication.
2. **Monitoring**: AutoGuardian will continuously monitor the health and security status of each AI agent. This includes checking for any anomalies, unauthorized access attempts, and performance degradation.
3. **Self-Healing**: In case of any detected issues, such as exceptions or security breaches, AutoGuardian will automatically apply predefined remediation strategies. For example, it might restart the affected agent or isolate it from the network temporarily until the issue is resolved.
4. **Reporting**: The application will maintain logs of all activities, including alerts and actions taken. These logs will be stored locally and can also be exported for further analysis.
5. **User Interface**: A simple command-line interface (CLI) will be provided for users to interact with AutoGuardian. Users should be able to view the current status of all agents, manually trigger a self-healing process, and configure settings such as alert thresholds.
6. **Configuration**: AutoGuardian should allow for customization via configuration files, enabling users to tailor the monitoring and self-healing behaviors according to their specific needs.
7. **Security Enhancements**: Utilize the 'agentx-security-sdk' to implement advanced security measures, such as encryption for data in transit and at rest, and enhanced authentication mechanisms.

To achieve these objectives, you will need to utilize the core features of the 'agentx-security-sdk', including but not limited to exception handling, security protocols, and self-healing mechanisms. Your implementation should demonstrate a deep understanding of both the SDK’s capabilities and best practices for securing and managing autonomous AI systems.