asqav

v0.5.11 suspicious
7.0
High Risk

AI agent governance - audit trails, policy enforcement, compliance

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant risks due to its network and shell execution capabilities, despite having no direct cryptographic dependencies on the client side. The low metadata risk does not mitigate the operational risks.

  • High network risk due to external HTTP requests
  • High shell risk due to subprocess execution
Per-check LLM notes
  • Network: The observed network patterns indicate the package makes external HTTP requests which could be used for unauthorized data transmission.
  • Shell: The presence of subprocess execution suggests potential arbitrary command execution capabilities, indicating high risk for malicious activities.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (5.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://asqav.com/docs
  • Detailed PyPI description (19628 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 325 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in jagmarques/asqav-sdk
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • not None else b"{}" req = urllib.request.Request( url, method=method, headers
  • , ) try: with urllib.request.urlopen(req, timeout=30) as resp: raw = resp.rea
  • ort urllib.request req = urllib.request.Request( url, method="POST", headers
  • , ) try: with urllib.request.urlopen(req, timeout=60) as resp: body = resp.re
  • d}/download", ) req = urllib.request.Request( url, method="GET", headers=
  • , ) try: with urllib.request.urlopen(req, timeout=60) as resp: data = resp.re
⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • return hmac.compare_digest(base64.b64decode(b64sig), expected) # === HTML (bundled, no external assets
  • * ((-len(s)) % 4) return base64.b64decode(s, validate=False) def _safe_b64(v: str) -> bool: try:
  • try: os_module = __import__("os") os_module.chmod(out, 0o600) except Exce
⚠ Shell / Subprocess Execution score 6.0

Found 3 shell execution pattern(s)

  • d"] try: result = subprocess.run(cmd, cwd=str(base), check=False) except FileNotFoundErro
  • n"] try: result = subprocess.run(cmd, cwd=str(base), check=False) except FileNotFoundErro
  • )]) try: result = subprocess.run(cmd, cwd=str(base), check=False) except FileNotFoundErro
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: asqav.com>

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://`
✓ Git Repository History

Repository jagmarques/asqav-sdk appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 asqav 
Create a mini-application named 'ComplianceGuard' that leverages the 'asqav' package to manage and enforce compliance policies for AI agents within an organization. ComplianceGuard should serve as a robust tool for auditing AI agent activities, ensuring they adhere to specified organizational policies, and maintaining detailed logs for review and analysis. Here’s a detailed breakdown of the application's requirements:

1. **User Interface**: Develop a simple yet intuitive web-based UI using Flask or Django where users can interact with the system.
2. **AI Agent Registration**: Allow users to register new AI agents by providing basic details such as name, type, and purpose. Store these details securely.
3. **Policy Management**: Users should be able to define and manage compliance policies. Each policy should include criteria for acceptable behavior, data handling rules, and restrictions on actions.
4. **Audit Trails**: Implement a feature that automatically records all actions performed by registered AI agents. This includes what the agent did, when it was done, and whether it adhered to the set policies.
5. **Policy Enforcement**: Integrate real-time monitoring to ensure that AI agents comply with the defined policies. If an agent violates a policy, trigger alerts and log the incident.
6. **Reporting**: Provide comprehensive reporting capabilities that allow users to generate detailed reports on AI agent activities and compliance status over specific periods.
7. **Security Measures**: Ensure that all sensitive data, including agent details and policy information, is encrypted and stored securely.

**Utilizing 'asqav'**:
- Use 'asqav' to handle the governance aspect of your application, specifically focusing on its capabilities for audit trails and policy enforcement.
- For audit trails, leverage 'asqav' to automatically track and record every action taken by each AI agent.
- For policy enforcement, integrate 'asqav' to monitor agent activities against predefined policies and take appropriate actions if non-compliance is detected.
- Additionally, utilize 'asqav' to maintain a robust compliance framework that supports the application's core functionalities.

This project will not only demonstrate the practical application of the 'asqav' package but also provide a valuable tool for organizations looking to manage and govern their AI agents effectively.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!