aurochs-recall

v0.1.0 suspicious
4.0
Medium Risk

Memory architecture for your AI conversations.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package aurochs-recall v0.1.0 is considered suspicious due to the author's minimal profile and history, despite showing no signs of obfuscation or credential harvesting.

  • Low obfuscation risk
  • Low credential risk
  • Minimal author information
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package appears suspicious due to the author's lack of details and history, but there's no concrete evidence of malice.

📦 Package Quality Overall: Medium (6.0/10)

✦ High Test Suite 9.0

Test suite present — 24 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 24 test file(s) detected (e.g. __init__.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/skovalik/aurochs-recall#readme
  • Detailed PyPI description (6428 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 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 304 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 24 commits in skovalik/aurochs-recall
  • Single author but highly active (24 commits)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 8.0

Found 4 shell execution pattern(s)

  • ROUP = 0x00000200 subprocess.Popen( cmd, creationflags=DETACHED
  • ) else: subprocess.Popen(cmd, start_new_session=True, close_fds=True) print("
  • it(editor) + [src] return subprocess.call(cmd) # ---------------------------------------------------
  • .exists(): return subprocess.run( [sys.executable, "-m", "tests.fixtures.search.build
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: aurochs.agency>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository skovalik/aurochs-recall appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 aurochs-recall 
Create a conversational memory app called 'RecallMate' using the Python package 'aurochs-recall'. RecallMate will allow users to have persistent, context-aware conversations with an AI assistant, where the assistant remembers previous interactions and can reference them in future conversations. The app should include the following features:

1. User Authentication: Users should be able to create accounts and log in securely.
2. Persistent Conversations: Each user should have their own conversation history stored locally and/or remotely. Conversations should persist even if the session is closed and reopened.
3. Contextual Responses: The AI assistant should be able to recall previous parts of the conversation to provide more relevant and personalized responses.
4. Search Functionality: Users should be able to search through their past conversations by keywords or phrases.
5. Export Conversations: Users should have the option to export their conversation history as a text file or share it via email.
6. Customizable Assistant Personality: Users should be able to choose from different personality types for the AI assistant, each with its own tone and style of response.
7. Notifications: Users should receive notifications when the assistant recalls information from a previous conversation to emphasize the continuity of the interaction.

To utilize the 'aurochs-recall' package, integrate it into the backend of the app to handle the storage and retrieval of conversation data. Specifically, use 'aurochs-recall' to manage the context of each conversation, ensuring that the AI assistant can effectively recall and reference past exchanges. This will enhance the natural flow of the conversation and make interactions feel more human-like and engaging.

💬 Discussion Feed

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