arachnite

v0.11.3 suspicious
5.0
Medium Risk

A biologically-inspired reactive agent framework for Python

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risk due to potential code injection via obfuscated code and a lack of transparency from a new maintainer.

  • High obfuscation risk through pickle.loads usage
  • Single package from a new maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal and expected.
  • Shell: Shell executions appear to be gathering system information, which could be benign if the package is intended for benchmarking or monitoring.
  • Obfuscation: The use of pickle.loads without context suggests potential for code injection and obfuscation.
  • Credentials: No clear signs of credential harvesting detected.
  • Metadata: The maintainer has only one package, which may indicate a new or less active account.

📦 Package Quality Overall: Medium (5.4/10)

✦ High Test Suite 9.0

Test suite present — 1 test file(s) found

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

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/memrecolak/arachnite-oss/tree/main/spec
  • Detailed PyPI description (7468 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

  • Classifier: Typing :: Typed
  • Type checker (mypy / pyright / pytype) referenced in project
  • 434 type-annotated function signatures detected in source
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 14 commits in memrecolak/arachnite-oss
  • Single author with few commits — possibly a personal or throwaway project

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • bytes) -> Any: return pickle.loads(data) # noqa: S301 class NumpyCodec(SignalCodec): """
⚠ Shell / Subprocess Execution score 6.0

Found 3 shell execution pattern(s)

  • ct root. """ result = subprocess.run( [sys.executable, "-m", "benchmarks.memory_footprint
  • bprocess result = subprocess.run( ["wmic", "cpu", "get", "Name", "/value"],
  • bprocess result = subprocess.run( ["sysctl", "-n", "machdep.cpu.brand_string"
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository memrecolak/arachnite-oss appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "memrecolak" 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 arachnite 
Create a fully-functional mini-application called 'Arachnoid Explorer' using the Python package 'arachnite'. This application will simulate a spider-like behavior for web crawling, inspired by the reactive nature of real spiders. Your goal is to design a system where the 'spider agents' can navigate through a predefined virtual environment, identify and classify different types of 'web structures', and report back their findings. Here's a detailed breakdown of what your application should achieve:

1. **Environment Setup**: Define a virtual environment that represents a web structure. This could be a simple grid-based system where each cell can either be empty or contain a specific type of web structure.
2. **Agent Creation**: Use 'arachnite' to create multiple spider agents that can move around this environment. Each agent should have basic reactive behaviors such as moving towards light sources, avoiding obstacles, and returning to a base when energy is low.
3. **Web Structure Identification**: Implement a mechanism within the agents to identify and categorize the different types of web structures they encounter. For example, distinguishing between 'orb webs', 'cobwebs', and 'funnel webs'.
4. **Reporting Mechanism**: Develop a reporting feature where each agent can log its findings into a central database or file. This data should include the type of web structure found, its location, and any other relevant details.
5. **User Interface**: Although not mandatory, consider adding a simple user interface that allows users to visualize the environment and the progress of the spider agents over time.
6. **Energy Management**: Integrate a basic energy management system for the agents. Agents should lose energy while moving and gain it when resting or finding food sources (represented as certain types of web structures).
7. **Interactive Features**: Allow users to manually control one of the agents in real-time, observing how its reactive behaviors interact with the environment.

By utilizing the 'arachnite' package, focus on showcasing its capabilities in creating reactive, autonomous agents. Ensure that the application is modular and well-documented, allowing others to easily extend or modify the agents' behaviors and the environment itself.

💬 Discussion Feed

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