BlackBasta Chat Log Leak Analysis: A Dynamic Marimo Notebook

Thomas Roccia, a Senior Security Researcher at Microsoft, has published a dynamic Marimo notebook analyzing the BlackBasta chat log leak. The notebook is designed to run directly in your browser without any setup. Here’s what the notebook includes:

Data Visualization: Diagrams to visualize the data and extract statistics.
Dynamic Table: A table with extracted IOCs (Indicators of Compromise) that can be browsed and filtered directly in the browser.
Hybrid RAG: A hybrid Retrieval-Augmented Generation (RAG) system using FAISS (semantic search) + BM25 (keyword search) + ensemble retriever.
LLM Verification: The retrieved data is shown with the LLM’s response for verification.
Context Relevancy Checks: Included to reduce hallucinations in the output.

The notebook is fully documented and does not require an API key, though the provided key will be disabled once the limit is reached. GPT-4o Mini was used for cost efficiency, but better results were achieved with o1, so running the code locally with your own API key is recommended.

Notebook URL: https://lnkd.in/gmpzN22C

GitHub Repository: https://github.com/fr0gger/jupyter-collection/blob/main/bb_leak_tr/report.md

Full Notebook on GitHub: https://github.com/fr0gger/jupyter-collection/tree/main/bb_leak_tr

Practice Verified Codes and Commands:


<h1>Clone the repository to run the notebook locally</h1>

git clone https://github.com/fr0gger/jupyter-collection.git
cd jupyter-collection/bb_leak_tr

<h1>Install required dependencies</h1>

pip install -r requirements.txt

<h1>Run the Jupyter notebook</h1>

jupyter notebook


<h1>Example code to load and visualize data using the provided notebook</h1>

import pandas as pd
import matplotlib.pyplot as plt

<h1>Load the data</h1>

data = pd.read_csv('blackbasta_chat_logs.csv')

<h1>Visualize the data</h1>

data['message_length'] = data['message'].apply(len)
plt.hist(data['message_length'], bins=50)
plt.title('Distribution of Message Lengths')
plt.xlabel('Message Length')
plt.ylabel('Frequency')
plt.show()

What Undercode Say:

The BlackBasta chat log leak analysis by Thomas Roccia is a comprehensive example of how to leverage modern tools and techniques for cybersecurity research. The use of dynamic notebooks like Marimo allows for interactive and reproducible analysis, which is crucial in the field of cybersecurity. The notebook’s ability to visualize data, extract IOCs, and perform hybrid RAG with LLM verification showcases the power of combining traditional cybersecurity practices with cutting-edge AI technologies.

For those looking to replicate or build upon this work, the provided GitHub repository is an excellent resource. Running the notebook locally ensures stability, especially given the heavy load on the Marimo server. The use of FAISS and BM25 for semantic and keyword search, respectively, highlights the importance of efficient data retrieval in large datasets.

In addition to the provided notebook, here are some useful Linux and Windows commands for cybersecurity professionals:


<h1>Linux command to monitor network traffic</h1>

sudo tcpdump -i eth0 -w capture.pcap

<h1>Windows command to list all running processes</h1>

tasklist

<h1>Linux command to search for specific strings in files</h1>

grep -r "suspicious_string" /path/to/directory

<h1>Windows command to check open ports</h1>

netstat -an

<h1>Linux command to check for open ports</h1>

sudo netstat -tuln

<h1>Windows command to scan for vulnerabilities using PowerShell</h1>

Invoke-WebRequest -Uri "http://example.com/vulnerability_scanner" -OutFile "scan_results.txt"

<h1>Linux command to check for rootkits</h1>

sudo rkhunter --check

<h1>Windows command to check for malware using Windows Defender</h1>

Start-MpScan -ScanType FullScan

<h1>Linux command to analyze memory dumps</h1>

volatility -f memory_dump.img --profile=Win10x64 pslist

<h1>Windows command to analyze event logs</h1>

Get-WinEvent -LogName Security | Where-Object {$_.ID -eq 4624}

These commands are essential for any cybersecurity professional looking to analyze, monitor, and secure their systems. The combination of traditional command-line tools with modern AI-driven analysis, as demonstrated in Thomas Roccia’s notebook, represents the future of cybersecurity research and practice.

For further reading and resources, consider exploring the following URLs:

This concludes our analysis and practical guide on the BlackBasta chat log leak. Keep exploring, keep learning, and stay secure!