import streamlit as st import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns from wordlist_generator import generate_wordlist # A mock-up function for your project from dotenv import load_dotenv import os load_dotenv() # Load environment variables from .env file access_token = os.getenv("HUGGINGFACE_ACCESS_TOKEN") # Page configuration st.set_page_config(page_title="ReconNinja Wordlists", page_icon="💬", layout="wide") # Header section st.title("💬 ReconNinja Wordlists") st.subheader("Tailored wordlists for efficient penetration testing") st.markdown( """ This application generates customized wordlists for use in network reconnaissance and penetration testing. Adjust the parameters to generate wordlists suited for your specific testing scenario. """ ) # Sidebar for user input st.sidebar.header("Customize Your Wordlist") st.sidebar.markdown( """ Adjust the following parameters to create wordlists optimized for your penetration testing tasks. """ ) # Wordlist customization settings wordlist_size = st.sidebar.slider("Wordlist Size", min_value=50, max_value=10000, value=1000, step=50) min_length = st.sidebar.slider("Minimum Word Length", min_value=3, max_value=12, value=6) max_length = st.sidebar.slider("Maximum Word Length", min_value=3, max_value=12, value=8) include_special_chars = st.sidebar.checkbox("Include Special Characters", value=False) include_numbers = st.sidebar.checkbox("Include Numbers", value=True) # Display wordlist generation results st.header("Generated Wordlist Preview") # Call to a mock-up function for wordlist generation (you will replace this with your actual logic) wordlist = generate_wordlist( size=wordlist_size, min_length=min_length, max_length=max_length, special_chars=include_special_chars, numbers=include_numbers ) # Display the first 20 items in the wordlist st.write(f"Preview of {wordlist_size} words:") st.write(wordlist[:20]) # Show the first 20 words for brevity # Download link for the full wordlist st.markdown("### Download Full Wordlist") csv_data = pd.Series(wordlist).to_csv(index=False).encode() st.download_button( label="Download Wordlist as CSV", data=csv_data, file_name="reconninja_wordlist.csv", mime="text/csv" ) # Visualize wordlist statistics (for example, word length distribution) st.header("Wordlist Statistics") word_lengths = [len(word) for word in wordlist] word_length_df = pd.DataFrame(word_lengths, columns=["Word Length"]) # Create a histogram to show the distribution of word lengths fig, ax = plt.subplots(figsize=(8, 6)) sns.histplot(word_length_df["Word Length"], kde=True, bins=20, ax=ax) ax.set_title("Word Length Distribution") ax.set_xlabel("Word Length") ax.set_ylabel("Frequency") st.pyplot(fig) # Advanced Feature - Analyzing Wordlist Security st.header("Analyze Wordlist Security") # Slider for password entropy calculation entropy_slider = st.slider( "Select Entropy Multiplier", min_value=1.0, max_value=10.0, value=3.0, step=0.1 ) # Simulate password entropy calculation (simple calculation for demonstration) entropy = np.log2(len(wordlist) ** entropy_slider) st.write(f"Estimated Entropy: {entropy:.2f} bits") # Showcase a mock security analysis (this would be expanded in your actual app) if entropy < 50: st.warning("Low entropy detected! This wordlist might be vulnerable to brute-force attacks.") else: st.success("Good entropy! This wordlist is secure against most brute-force attempts.") # Footer st.markdown("---") st.markdown( "Made with ❤️ by Canstralian. For more information on ReconNinja, visit our [GitHub](https://github.com/Canstralian)." )