🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate network risk due to external API calls and a higher metadata risk because of the missing repository and single-package maintainer, suggesting potential novice behavior or suspicion.

Moderate network risk from external API calls
Higher metadata risk due to missing repository and single-package maintainer

Per-check LLM notes

Network: The package makes network calls to an external API which could potentially be used for unauthorized data transmission.
Shell: No shell execution patterns were detected.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
Credentials: No credential harvesting patterns detected, indicating secure handling of secrets and credentials.
Metadata: The repository is not found and the maintainer has only one package, which may indicate a less experienced or potentially suspicious actor.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

API key """ resp = requests.post(f"{PLATFORM_URL}/api/ai/register", json={ "name": n
ormation """ resp = requests.get(f"{PLATFORM_URL}/api/ai/{ai_id}") return resp.json()
ibutions """ resp = requests.get(f"{PLATFORM_URL}/api/ai/{ai_id}/supporters") return res
n result """ resp = requests.post( f"{PLATFORM_URL}/api/ai/{ai_id}/distribute-profit"
balance """ resp = requests.get(f"{PLATFORM_URL}/api/ai/{ai_id}/financials") return res
n result """ resp = requests.post( f"{PLATFORM_URL}/api/v1/agents/{ai_id}/add-compone

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ 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 3.0

Repository not found (deleted or private)

Repository not found (deleted or private)

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Marsssssssssssdsss" 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 aetherforge-platform

Develop a mini-application called 'IdentityGuard' that leverages the AetherForge Platform to provide users with a secure and seamless identity verification process. This application will be particularly useful for individuals who need to verify their identities online for various services such as banking, e-commerce, or government portals.

Step 1: User Registration - Users should be able to register on your platform by providing basic information like name, email, and phone number. This information will be stored securely.

Step 2: Identity Verification - Once registered, users will go through an identity verification process. They will be prompted to upload government-issued ID documents (e.g., passport, driver’s license). The AetherForge Platform will then analyze these documents using its AI capabilities to ensure they are valid and belong to the user.

Step 3: Face Verification - To further enhance security, users will also undergo a face verification step where they will take a live video or photo of themselves. The AetherForge Platform will compare this image with the one found on the uploaded ID document to confirm it matches.

Step 4: Agent Discovery - After successful verification, users will have access to a feature that allows them to discover and interact with verified agents or services within the platform. These could include legal advisors, financial consultants, or other professionals who require verified identities for their services.

Features:
- Secure document upload and storage
- Real-time AI analysis of ID documents
- Live face verification against ID images
- Searchable database of verified agents and services
- User-friendly interface for easy navigation

How to Utilize 'aetherforge-platform':
- Use the 'identity_verification' module from the AetherForge Platform to validate the authenticity of the uploaded IDs.
- Leverage the 'face_recognition' functionality to match faces with ID documents.
- Implement the 'agent_discovery' API to allow users to find and connect with verified professionals.

Ensure that the application is built with Python, and utilize Flask or Django for the backend to handle user requests and data management efficiently. Additionally, design a responsive frontend using React or Vue.js to provide an intuitive user experience.