ableton-for-ai

v0.1.7 suspicious
6.0
Medium Risk

Bridge between Ableton Live and AI models via MCP — make your DAW hearable and visible to AI.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risks due to its network and shell execution behaviors, though it lacks clear indicators of malicious intent such as obfuscation or credential harvesting.

  • High network risk
  • High shell risk
  • Low metadata and obfuscation risks
Per-check LLM notes
  • Network: The network call pattern suggests the package may be attempting to communicate over a specific port, which could indicate unexpected behavior or potential C2 communication.
  • Shell: The shell execution pattern indicates that the package might execute system commands, which can be risky if not properly sanitized, potentially leading to unauthorized actions or data exfiltration.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository's low activity and the maintainer's lack of information suggest potential risk, but there are no clear signs of typosquatting or other malicious intent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • ON_PORT try: with socket.create_connection((host, port), timeout=1.0): return True exce
  • ON_PORT try: with socket.create_connection((host, port), timeout=1.0) as s: req = json.dump
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • f).""" try: out = subprocess.check_output( ["lsof", "-ti", f"tcp:{port}"], std
  • es are visible. process = subprocess.Popen( cmd, stdout=subprocess.DEVNULL, std
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: peterkolbe.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ 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 ableton-for-ai 
Create a mini-application called 'AI Beat Analyzer' that leverages the 'ableton-for-ai' package to analyze and generate musical beats in real-time from within Ableton Live. This application should allow users to feed their live music tracks into an AI model which can then provide insights such as tempo detection, beat classification, and even suggest variations or remixes based on the input audio. 

Steps to develop this application:
1. Set up a virtual environment and install the 'ableton-for-ai' package.
2. Integrate the package with Ableton Live's MIDI and audio processing capabilities to capture live input.
3. Design a simple UI within Ableton Live to interact with the AI model, including options to start/stop analysis, view results, and control AI suggestions.
4. Implement a basic AI model using a pre-trained framework or library capable of handling time-series data (such as LSTM or GRU).
5. Develop functions to preprocess the captured audio data before feeding it into the AI model.
6. Create algorithms to process the AI model's output, translating its suggestions back into MIDI or audio signals that can be played back in Ableton Live.
7. Test the application thoroughly with various types of music to ensure accuracy and responsiveness.
8. Enhance the application with additional features like visualizing the analyzed data, providing feedback on the music's structure, or even allowing users to train the AI model with their own datasets.

Utilize the 'ableton-for-ai' package to establish a seamless connection between Ableton Live and the AI model, ensuring that the application can run smoothly without requiring manual intervention to sync the two systems.