aegis-memory

v2.4.0 safe
4.0
Medium Risk

Secure context engineering layer for AI agents. Content security, integrity verification, trust hierarchy. Self-hosted, Apache 2.0.

🤖 AI Analysis

Final verdict: SAFE

The package shows low risk across multiple categories with no evidence of malicious activities such as shell execution, obfuscation, or credential theft. While there are some concerns about the author's metadata, these alone do not indicate a supply-chain attack.

  • Low network risk
  • No shell execution detected
  • No obfuscation detected
  • No credential harvesting detected
  • Incomplete author metadata
Per-check LLM notes
  • Network: The observed network calls to a server for health checks are likely legitimate and expected for monitoring or reporting purposes.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or sensitive information being stolen.
  • Metadata: The author information is incomplete and the maintainer has a single package, suggesting potential lack of credibility.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

  • try: response = httpx.get(f"{server}/health", timeout=5.0) if response.status_
  • try: response = httpx.get(f"{server_url}/health", timeout=5.0) if response.sta
  • /") self.client = httpx.AsyncClient( base_url=self.base_url, hea
  • ") self.client = httpx.Client( base_url=self.base_url, h
✓ 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: quantifylabs.ai>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository quantifylabs/aegis-memory 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 aegis-memory 
Develop a secure note-taking application called 'SecureMemo' using Python and the 'aegis-memory' package. This application will allow users to create, store, and manage encrypted notes while ensuring content security, integrity verification, and maintaining a trust hierarchy among different user accounts.

### Features:
1. **User Registration & Authentication:** Implement a simple registration process where users provide a username and password. Use 'aegis-memory' to securely store user credentials.
2. **Note Creation & Encryption:** Users can create new notes. Each note will be encrypted using AES encryption before being stored in the database. Utilize 'aegis-memory' to handle the encryption keys securely.
3. **Integrity Verification:** When a user retrieves a note, ensure its integrity by verifying the hash of the note against a previously stored hash value using 'aegis-memory'.
4. **Trust Hierarchy Management:** Allow users to establish trust relationships with each other. For example, if User A trusts User B, then any note shared between them will be verified for authenticity through 'aegis-memory'.
5. **Self-Hosted & Scalable:** Design the application to be self-hosted on a local server or cloud service. Ensure it scales well as more users join.
6. **User Interface:** Provide a basic command-line interface (CLI) for interaction, though a web-based UI could also be considered as an advanced feature.

### Steps to Build the Application:
1. **Setup Project Environment:** Create a virtual environment and install necessary packages including 'aegis-memory', 'flask' for a web interface (optional), and 'cryptography' for encryption.
2. **Design Database Schema:** Define tables for users, notes, and trust relationships. Use SQLite for simplicity.
3. **Implement User Authentication:** Develop functions for user registration and login, storing hashed passwords securely with 'aegis-memory'.
4. **Note Handling Functions:** Write functions to encrypt, decrypt, and verify notes using 'aegis-memory' for key management and integrity checks.
5. **Trust Hierarchy Implementation:** Integrate 'aegis-memory' functionalities to manage trust hierarchies among users and verify note authenticity based on these hierarchies.
6. **Testing & Deployment:** Test all functionalities thoroughly and deploy the application on a local server or cloud platform.
7. **Documentation:** Document all steps and configurations needed for setting up and running 'SecureMemo', emphasizing the use of 'aegis-memory' for security purposes.