🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits several suspicious behaviors, including potential obfuscation techniques and interaction with external APIs. While there's no clear evidence of malicious intent, the combination of these factors raises concerns about its true purpose.

High obfuscation risk
Potential for network interactions

Per-check LLM notes

Network: The use of HTTP requests is common for packages that need to interact with external APIs, but the specific endpoints and purposes should be reviewed.
Shell: Executing git commands suggests the package might manage version control operations, which could be legitimate if related to its functionality, but requires further investigation into its purpose.
Obfuscation: The presence of 'curl', 'wget', 'node-gyp', 'eval(', and 'child_process' suggests potential code execution or data retrieval tactics which may be obfuscation or evasion techniques.
Credentials: No clear patterns indicative of credential harvesting were detected.
Metadata: The repository's recent creation, minimal activity, and single contributor raise suspicion.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

try: async with httpx.AsyncClient(timeout=30) as client: res = await client.po
try: async with httpx.AsyncClient(timeout=60) as client: res = await client.po
t) -> str: async with httpx.AsyncClient(base_url=self.config.api_base, timeout=20) as client:
r) -> str: async with httpx.AsyncClient(base_url=self.config.api_base, timeout=30) as client:
str, Any]: async with httpx.AsyncClient(base_url=self.config.api_base, timeout=20) as client:

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

"curl", "wget", "node-gyp", "eval(", "child_process"] if any(token in added for token

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

letedProcess[str]: proc = subprocess.run(["git", *args], cwd=repo, capture_output=True, text=True)
rel: str) -> bool: proc = subprocess.run( ["git", "check-ignore", "--quiet", "--no-index", "-
ceRecord) -> bool: proc = subprocess.run( ["git", "notes", "--ref", "aura/provenance", "add",
anceRecord | None: proc = subprocess.run(["git", "show", "-s", "--format=%B", commit_sha], cwd=Path(r
return None sha_proc = subprocess.run(["git", "rev-parse", commit_sha], cwd=Path(repo_path).resolv
letedProcess[str]: return subprocess.run(["git", *args], cwd=repo, check=True, capture_output=True, t

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 10.0

Git history flags: Repository created very recently: 5 day(s) ago (2026-06-01T01:29:29Z)

Repository created very recently: 5 day(s) ago (2026-06-01T01:29:29Z)
Repository has zero stars and zero forks
Very few commits: 2 total
Single contributor with only 2 commit(s) — possibly throwaway account

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Aegisure" 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 aegisure

Your task is to develop a command-line interface (CLI) tool using the 'aegisure' Python package that allows developers to manage and govern their AI coding assistants. This tool will enable users to create, configure, and monitor AI agents designed to assist with various coding tasks such as code generation, debugging, and documentation.

### Project Overview:
- **Name**: CodeMate
- **Purpose**: To provide a comprehensive CLI tool for managing AI coding assistants, ensuring they operate within specified guidelines and security protocols.
- **Target Audience**: Developers who wish to integrate AI into their coding workflow but need a secure and manageable way to do so.

### Key Features:
1. **Agent Management**:
- Create new AI coding assistants.
- Configure existing assistants with custom settings.
- Delete assistants when no longer needed.
2. **Task Assignment**:
- Assign specific coding tasks to AI assistants (e.g., generating code snippets, fixing bugs).
- Monitor the progress of assigned tasks.
3. **Security Governance**:
- Implement strict access controls over what data the AI assistants can interact with.
- Enforce compliance with predefined coding standards.
4. **Reporting & Analytics**:
- Generate reports on the performance of AI assistants.
- Analyze the effectiveness of different configurations and provide recommendations.

### Utilization of 'aegisure' Package:
- Use 'aegisure' to initialize and manage the lifecycle of AI assistants within your CLI tool.
- Leverage 'aegisure' to enforce governance policies that ensure AI assistants adhere to the specified rules and standards.
- Integrate 'aegisure' functionalities to allow for real-time monitoring and adjustments of AI behavior.

### Development Steps:
1. **Setup Environment**:
- Install necessary dependencies including 'aegisure'.
2. **Design CLI Interface**:
- Develop commands for creating, configuring, and deleting AI assistants.
- Implement task assignment and monitoring functionalities.
3. **Implement Security Controls**:
- Define and apply access controls through 'aegisure'.
- Ensure all operations comply with set security and governance policies.
4. **Develop Reporting Tools**:
- Create scripts to generate performance reports based on AI assistant activities.
- Use 'aegisure' to analyze the effectiveness of different configurations.
5. **Testing & Deployment**:
- Thoroughly test the CLI tool to ensure it meets all functional requirements.
- Deploy the tool for use by developers looking to enhance their coding workflow with AI assistance.

By completing this project, you'll have a powerful tool at your disposal to streamline coding processes while maintaining high levels of security and governance.