AI Analysis
Final verdict: SUSPICIOUS
The package exhibits a moderate risk due to potential shell execution risks and a possible typosquatting attempt targeting 'arrow'. Further investigation into the legitimacy of the package and its usage scenarios is recommended.
- Potential shell command injection
- Typosquatting suspicion
Per-check LLM notes
- Network: No network calls detected.
- Shell: Subprocess execution may indicate potential for shell command injection or execution, which could be risky if not properly sanitized.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
- Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
- Metadata: The maintainer has only one package, which might indicate a new or less active account.
- ⚠ Typosquatting target: arrow
Package Quality Overall: Medium (6.2/10)
✦ High
Test Suite
9.0
Test suite present — 11 test file(s) found
11 test file(s) detected (e.g. smoke_nlp.py)
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (2877 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
5.0
Partial type annotation coverage
113 type-annotated function signatures detected in source
✦ High
Multiple Contributors
10.0
Active multi-contributor project
6 unique contributor(s) across 100 commits in NatLabRockies/arcoActive community — 5 or more distinct contributors
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
score 6.0
Found 3 shell execution pattern(s)
er to fail") """ result = subprocess.run( [sys.executable, "-c", script], check=Falseen to fail") """ result = subprocess.run( [sys.executable, "-c", script], check=False] ) completed = subprocess.run( command, cwd=ROOT, env=env,
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
score 6.0
Possible typosquat of: arrow, arq
"arco" is 2 edit(s) from "arrow""arco" is 2 edit(s) from "arq"
Registered Email Domain
Email domain looks legitimate: users.noreply.github.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository NatLabRockies/arco appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Arco maintainers" 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 arco
Create a Python-based mini-application named 'OptiCraft' that leverages the Arco optimization library through its Python bindings ('arco') to help users optimize their crafting recipes in a virtual world simulation game. This application will allow players to input their current resources and desired output items, and then it will use advanced optimization algorithms provided by the 'arco' package to suggest the most efficient way to craft the desired items.
Step 1: Define the Input Interface
- Users should be able to enter a list of available resources they have in their inventory, including the quantity of each resource.
- They should also specify the target item(s) they wish to craft, along with the desired quantities.
Step 2: Crafting Recipe Database Integration
- OptiCraft must include a database of crafting recipes, which maps required inputs to possible outputs.
- Each recipe should detail the exact quantities of resources needed to produce specific items.
Step 3: Optimization with 'arco'
- Utilize the 'arco' package to formulate and solve the optimization problem based on user inputs and the crafting recipe database.
- The optimization process should aim to minimize resource wastage while maximizing the production of the desired items.
Step 4: Output Results
- Display the optimized crafting plan to the user, detailing how many times each recipe should be executed to achieve the desired outcome efficiently.
- Include an option to visualize the results, such as a chart showing resource usage over time or a breakdown of total savings achieved.
Suggested Features:
- Interactive GUI using PyQt or Tkinter for better user experience.
- Option to save and load crafting plans.
- Ability to add custom recipes to the database.
- Real-time updates of resource availability as the user crafts items.
How 'arco' is utilized:
- 'arco' is used to set up the mathematical model representing the crafting scenario, including constraints (resource limits) and objectives (minimizing waste).
- It solves the optimization problem, providing the best strategy for crafting the desired items given the available resources.
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