🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to incomplete maintainer information and insecure external links, which may indicate potential supply-chain risks.

Incomplete maintainer information
Insecure external links

Per-check LLM notes

Network: The package appears to make network calls to retrieve data from URLs, which could be normal behavior if the package is designed to fetch experimental data or update itself.
Shell: No shell execution patterns were detected, indicating no immediate risk from executing system commands.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer's author information is incomplete and the external links are non-secure.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

tbyname(hostname) socket.create_connection((host, 443), 2).close() return True exce
])) try: urllib.request.urlretrieve(experimental_data_url, experimental_data_down_lo
es) try: urllib.request.urlretrieve(experimental_data_species_url, experimental_data
])) try: urllib.request.urlretrieve(current_version_url, experimental_data_dir)
imental_data_dir) urllib.request.urlretrieve(experimental_data_url, experimental_data_down_lo

✓ 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

Email domain looks legitimate: tuni.fi>

⚠ Suspicious Page Links score 4.0

Found 2 suspicious link(s) on the package page

Non-HTTPS external link: http://gtrd.biouml.org/
Non-HTTPS external link: http://fantom.gsc.riken.jp/

✓ Git Repository History

Repository thirtysix/TFBS_footprinting3 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 TFBS-footprinting3

Create a web-based application using Python and Flask that leverages the 'TFBS-footprinting3' package to identify and visualize conserved transcription factor binding sites (TFBSs) across multiple vertebrate species. This application will allow users to input a DNA sequence and select one or more vertebrate species to compare. The application should then use TFBS-footprinting3 to analyze the provided sequence and highlight conserved TFBSs across the selected species. Additionally, implement features such as a user-friendly interface for uploading sequences, a results page displaying the identified TFBSs, and interactive visualizations of the conservation levels. Ensure the application includes error handling for invalid inputs and provides clear documentation on how to install and run the app locally.