ANNarchy

v5.0.2 suspicious
4.0
Medium Risk

Artificial Neural Networks architect

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits some concerning metadata issues such as incomplete maintainer information and non-HTTPS links, which could indicate potential supply-chain risks.

  • Incomplete maintainer information
  • Non-HTTPS links
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, suggesting low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
  • Metadata: The package shows some red flags but no clear signs of malicious intent. The maintainer's information is incomplete, and there are non-HTTPS links.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • 1> /dev/null" if os.system(cmd) != 0: Messages.error(
  • Check cython version with subprocess.Popen( sys.base_prefix + "/bin/cython%(major)s -V
  • hon, use the default with subprocess.Popen( "%(cython)s -V > /dev/null 2> /dev/null" % {"cython
  • 11.6) query_result = subprocess.check_output( "nvidia-smi --query-gpu=compute_cap --format=cs
  • eLists make_process = subprocess.Popen( 'cmake -S "{}" -B "{}" {}'.format(target_dir, t
  • ) make_process = subprocess.Popen("make -j4" + verbose, shell=True) # Check for error
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: informatik.tu-chemnitz.de>

⚠ Suspicious Page Links score 4.0

Found 2 suspicious link(s) on the package page

  • Non-HTTPS external link: http://www.gnu.org/licenses/gpl.html
  • Non-HTTPS external link: http://dx.doi.org/10.3389/fninf.2015.00019
✓ Git Repository History

Repository ANNarchy/ANNarchy 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 ANNarchy 
Create a small, educational application that simulates a simple artificial neural network (ANN) using the ANNarchy package in Python. This application will serve as a tool for beginners to understand the basic concepts of ANN architecture and functionality. Here are the steps and features you need to include:

1. **Project Setup**: Start by setting up a virtual environment and installing the ANNarchy package along with any other necessary dependencies.
2. **Network Definition**: Define a simple feedforward neural network with one input layer, one hidden layer, and one output layer. Each layer should have a configurable number of neurons.
3. **Training Module**: Implement a training module where users can choose from different learning algorithms (e.g., backpropagation). The application should allow users to specify the number of epochs, learning rate, and other relevant parameters.
4. **Data Input**: Provide a way for users to input their own data sets or use pre-defined datasets for training the network. Ensure that the data is properly normalized before feeding it into the network.
5. **Visualization Tool**: Include a visualization component that displays the network structure and updates as the training progresses. This could be a simple graphical representation showing the connections between neurons and their weights.
6. **Testing Interface**: After training, provide a testing interface where users can input new data points and see the network's predictions.
7. **Documentation and Help**: Create comprehensive documentation that explains each part of the code and how the ANN works. Include a help section within the application that provides tips and explanations for users.

Throughout the development process, utilize the core functionalities of the ANNarchy package to manage the network's architecture, simulate the network dynamics, and handle the synaptic connections efficiently. The goal is to create an interactive and educational tool that demystifies the workings of artificial neural networks.