apyrobo

v3.0.0 suspicious
5.0
Medium Risk

Open-source AI orchestration layer for robotics, built on ROS 2

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risk due to its execution of shell commands and interactions with external services, despite having no signs of obfuscation or credential harvesting. Given the newness of the package and limited maintainer activity, further scrutiny is warranted.

  • Executing shell commands
  • Interactions with external services
Per-check LLM notes
  • Network: The network calls seem to be for health checks and JSON data retrieval, which could be legitimate if the package interacts with services over HTTP.
  • Shell: Executing shell commands, especially related to Docker, without clear justification in a package's functionality suggests potential misuse or unexpected behavior.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
  • Metadata: The package is newly created and the maintainer has limited activity, which raises some suspicion but does not strongly indicate malice.

📦 Package Quality Overall: Medium (6.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/apyrobo/Apyrobo/tree/main/docs
  • Detailed PyPI description (16528 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 554 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in apyrobo/Apyrobo
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • CheckResult: try: urllib.request.urlopen("http://localhost:8080/health", timeout=2) r
  • ry)}" try: req = urllib.request.Request(url, headers={"Accept": "application/json"})
  • lication/json"}) with urllib.request.urlopen(req, timeout=10) as resp: results = json
  • n, }).encode() req = urllib.request.Request( url, data=payload, headers=
  • ) try: with urllib.request.urlopen(req, timeout=10) as resp: result = json.
  • (task).encode() req = urllib.request.Request( url, data=payload,
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

  • sult: try: proc = subprocess.run( ["docker", "info"], capture_output=
  • try: subprocess.Popen(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
  • try: subprocess.run(cmd, check=False, stdout=subprocess.DEVNULL, stderr=subproce
  • }}"] try: subprocess.run(cmd, check=False, stdout=subprocess.DEVNULL, stderr=subproce
  • et)] try: subprocess.run(cmd, check=False, stdout=subprocess.DEVNULL, stderr=subproce
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://`
✓ Git Repository History

Repository apyrobo/Apyrobo appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "APYROBO Contributors" 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 apyrobo 
Develop a mini-application named 'RoboNav' which leverages the apyrobo package to enable navigation and obstacle avoidance for a robotic platform in a simulated environment. This application will showcase the capabilities of ROS 2 and the apyrobo package through a series of interactive tasks. Here’s a detailed breakdown of the project steps and features:

1. **Setup Environment**: Begin by setting up your development environment with ROS 2 and the apyrobo package. Ensure you have a simulation environment like Gazebo installed.

2. **Robot Model**: Integrate a pre-existing robot model into the Gazebo simulation. This model should include sensors such as LIDAR for obstacle detection and IMU for orientation data.

3. **Navigation Goal Setting**: Implement a feature where users can set navigation goals for the robot using a simple GUI. The GUI should allow users to click on any point in the simulation to set the goal.

4. **Obstacle Avoidance**: Utilize the LIDAR sensor data to implement an obstacle avoidance algorithm. The robot should dynamically adjust its path to avoid obstacles while moving towards the goal.

5. **Real-time Feedback**: Display real-time feedback on the robot's progress towards the goal. This could include distance to goal, current speed, and any detected obstacles.

6. **Logging and Analysis**: Implement logging of key metrics such as time taken to reach the goal, number of obstacles encountered, and paths taken. Provide a basic analysis tool within the application to visualize this data.

7. **Interactive Controls**: Add interactive controls that allow users to manually control the robot's movement (forward, backward, left, right) in case of emergencies or manual testing.

8. **Documentation and Testing**: Document each step of the process and ensure thorough testing of all features to guarantee smooth operation in the simulation environment.

This project will not only demonstrate the integration and use of the apyrobo package but also provide a practical example of ROS 2's capabilities in a real-world scenario.

💬 Discussion Feed

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