awsibox

v1.0.2 suspicious
6.0
Medium Risk

AWS Infrastructure in a Box

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits significant obfuscation techniques and lacks detailed metadata, raising concerns about its true intentions. While there is no direct evidence of malicious activity, the high obfuscation score warrants further scrutiny.

  • High obfuscation risk due to use of eval and unusual string patterns
  • Inadequate maintainer metadata
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external API interactions.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands.
  • Obfuscation: The code shows signs of deliberate obfuscation through the use of eval and unusual string patterns, which may indicate an attempt to hide malicious activities.
  • Credentials: No clear evidence of credential harvesting is present, but the use of eval and other suspicious patterns should be closely monitored.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, which may indicate a lower level of trustworthiness.

📦 Package Quality Overall: Low (2.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (474 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in mello7tre/AwsIBox
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 10.0

Found 5 obfuscation pattern(s)

  • ondition(", "dict(", "eval(", "str(", "int(", "list(", "getattr(",
  • update(globals()) return eval(code, cfg.BUILD_ENVS, conf) def stack_add_res(): for n
  • le_lines.extend([f"{tks[0]}", eval(tks[1]), tks[2]]) continue
  • if module: mod = __import__(f"troposphere.{module}") my_module = getattr(mod, module) else:
  • nit__ my_module = __import__("troposphere") my_class = getattr(my_module, cls) obj = m
✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: ankot.org>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository mello7tre/AwsIBox 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 awsibox 
Your task is to develop a Python-based utility named 'CloudDeployer' using the 'awsibox' package. This tool aims to simplify the deployment of a basic web application onto Amazon Web Services (AWS). The application will guide users through setting up an EC2 instance, configuring an RDS database, and deploying a sample Flask web app. Additionally, it will provide options for security group configurations and automatic backups.

### Core Features:
- **EC2 Instance Setup**: Users can specify the region, instance type, and key pair for SSH access.
- **RDS Database Configuration**: Options to choose between MySQL and PostgreSQL, set up a database name, username, and password.
- **Flask App Deployment**: Automatically upload a pre-configured Flask app to the EC2 instance and connect it to the RDS database.
- **Security Group Management**: Allow users to define inbound and outbound rules for security groups.
- **Backup Scheduling**: Implement a feature to schedule automatic backups of the RDS database.

### Utilizing 'awsibox':
- Use 'awsibox' to streamline the creation and management of AWS resources such as EC2 instances and RDS databases.
- Leverage its functionalities to handle complex configurations more efficiently.
- Ensure all AWS operations are performed securely and in compliance with best practices.

### Development Steps:
1. **Setup Project Environment**: Initialize your Python environment and install 'awsibox'.
2. **Define User Inputs**: Create a user-friendly interface for specifying deployment parameters.
3. **Resource Creation**: Write functions to create EC2 instances and RDS databases using 'awsibox'.
4. **App Deployment**: Develop logic to deploy the Flask app onto the EC2 instance and configure it to use the RDS database.
5. **Security Group Configurations**: Implement methods to manage security groups according to user inputs.
6. **Backup Scheduling**: Integrate functionality to schedule regular backups for the RDS database.
7. **Testing and Validation**: Thoroughly test each feature to ensure reliability and accuracy.
8. **Documentation and Packaging**: Prepare comprehensive documentation and package your application for easy distribution.

Your goal is to create a robust, user-friendly tool that leverages 'awsibox' to make deploying applications on AWS simpler and more accessible.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!