armor-ai

v0.12.0 suspicious
7.0
High Risk

A defense-in-depth security layer for LLM agents

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows significant risks related to network and shell execution, which could potentially be exploited for malicious activities. However, the metadata risk is lower, suggesting it might not be a widespread supply-chain attack.

  • High network and shell execution risks
  • Potential for credential harvesting
Per-check LLM notes
  • Network: Network calls that include data exfiltration are not typical and may indicate malicious intent.
  • Shell: Direct shell execution paired with network tools can be used for various purposes but often suggests potential for executing unauthorized actions.
  • Obfuscation: The detected patterns suggest the use of dynamic imports and base64 decoding which can be used for obfuscating malicious code.
  • Credentials: The package attempts to read sensitive files such as credentials and shadow files, indicating potential credential harvesting activities.
  • Metadata: The maintainer has an incomplete profile and only one package, which may indicate a new or less active account.

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/tkdtaylor/armor#readme
  • Detailed PyPI description (3025 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

  • 211 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 82 commits in tkdtaylor/armor
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • ecode decoded_bytes = base64.b64decode(clean, validate=True) # Try to interpret as UTF-8
  • ter). Detected patterns: - __import__('subprocess') — dynamic subprocess import to bypass static analysis -
  • st[tuple[str, str]] = [ # __import__('subprocess') — canonical code injection bypass technique (r"__import
⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • ut with data exfiltration - os.system() + network tool — direct shell execution with network acti
  • subprocess-net", ), # os.system() paired with a network tool ( r"\bos\s*\.\s*sys
⚠ Credential Harvesting score 10.0

Found 6 credential access pattern(s)

  • tc.) - Credential file reads (/etc/shadow, SSH keys, etc.) - Container escape attempts (mount cgroup,
  • cess: cat ~/.aws/credentials, /etc/shadow, etc. 3. IMDS / metadata endpoints: 169.254.169.254
  • entials", r"cat\s+/etc/shadow", r"cat\s+~/\.netrc", r"cat\s+~/\.s
  • ile-credentials-yaml"), # /etc/shadow — no leading \b since / is not a word character (r"/etc
  • s not a word character (r"/etc/shadow\b", "file-etc-shadow"), # .netrc — stores plaintext cre
  • rns and wildcards: - `/etc/shadow` matches exactly `/etc/shadow` - `/etc/*` matches a
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: taylorguard.me>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository tkdtaylor/armor 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 armor-ai 
Your task is to create a secure conversational assistant application using Python and the 'armor-ai' package. This application will serve as a personal assistant that users can interact with via text messages. However, it will also incorporate advanced security measures to protect user data and interactions from potential threats.

**Application Overview:**
- **Name:** SecureChat
- **Purpose:** To provide a secure conversational interface for users to interact with, ensuring privacy and protection against malicious activities.
- **Features:**
  - User authentication (login/signup)
  - Secure messaging with end-to-end encryption
  - Threat detection and response mechanisms
  - Compliance checks for legal and ethical guidelines

**How 'armor-ai' is Utilized:**
- **Threat Detection:** Use 'armor-ai' to continuously monitor conversations for any signs of malicious intent or harmful content.
- **Response Mechanisms:** Implement automated responses based on 'armor-ai's' analysis, such as flagging messages, blocking users, or alerting administrators.
- **Compliance Checks:** Ensure all communications adhere to predefined rules and regulations by leveraging 'armor-ai's' compliance feature.
- **User Feedback Loop:** Allow users to report suspicious activity, which 'armor-ai' can then analyze to improve its threat detection algorithms.

**Steps to Build the Application:**
1. **Setup Environment:** Install necessary packages including 'armor-ai', and set up your development environment.
2. **Design Database Schema:** Plan how you will store user information securely, ensuring compliance with GDPR or similar regulations.
3. **Develop Authentication System:** Create login and signup functionalities that ensure only authenticated users can access the service.
4. **Implement Messaging Functionality:** Develop the core chat functionality, focusing on making sure all messages are encrypted.
5. **Integrate 'armor-ai':** Integrate 'armor-ai' into your application to perform real-time threat detection and compliance checks.
6. **Test Security Measures:** Rigorously test the application to ensure all security features work as intended.
7. **Deploy Application:** Deploy the application on a secure server, ensuring all communication channels are protected.
8. **Monitor and Update:** Continuously monitor the application's performance and update 'armor-ai' as needed to stay ahead of new threats.

This project not only enhances your skills in developing secure applications but also demonstrates the practical application of 'armor-ai' in safeguarding digital communications.

💬 Discussion Feed

Leave a comment

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