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https://github.com/copyleftdev/noisy-log

Noisy Log is a Python library inspired by STOK's "Weaponizing Plain Text: ANSI Escape Sequences as a Forensic Nightmare". Tailored for developers who value the craft of code and the intricacies of cybersecurity, this tool enables sophisticated manipulation of log files and telemetry data through ANSI escape sequences.

https://github.com/copyleftdev/noisy-log

Science Score: 26.0%

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    CITATION.cff file
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    Found .zenodo.json file
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    Scientific vocabulary similarity
    Low similarity (10.3%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Noisy Log is a Python library inspired by STOK's "Weaponizing Plain Text: ANSI Escape Sequences as a Forensic Nightmare". Tailored for developers who value the craft of code and the intricacies of cybersecurity, this tool enables sophisticated manipulation of log files and telemetry data through ANSI escape sequences.

Basic Info
  • Host: GitHub
  • Owner: copyleftdev
  • Language: Python
  • Default Branch: main
  • Size: 2.93 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme

readme.md

Noisy Log

Overview

Noisy Log is a Python library inspired by STOK's "Weaponizing Plain Text: ANSI Escape Sequences as a Forensic Nightmare". Tailored for developers who value the craft of code and the intricacies of cybersecurity, this tool enables sophisticated manipulation of log files and telemetry data through ANSI escape sequences.

Features

  • Advanced Data Obfuscation: Injects ANSI escape sequences into data streams, obscuring log readability and complicating forensic analysis.
  • Seamless Integration: Easily integrates into any software service, allowing for strategic deployment and immediate impact.
  • Comprehensive Command Set: Provides a robust selection of ANSI commands and styles, empowering users to customize their obfuscation techniques.

Implications

Using Noisy Log introduces: - Complex Log Analysis: Transforms straightforward logs into intricate puzzles, challenging conventional forensic techniques. - Increased Analytical Demands: Necessitates advanced analytical methods to decode the altered data. - Evasion Capabilities: Offers a refined method to mask potentially malicious activities within obscured logs.

Ideal Use Cases

  • Enhanced Security Testing: Assess the resilience of log analysis tools against complex obfuscation.
  • Red Team Operations: Equip red teams with advanced tools for simulating threats that manipulate log outputs.
  • Cybersecurity Research: Investigate the impact of log manipulation in various security scenarios.

Getting Started

Prerequisites

  • Python 3.6 or newer

Usage

Deploy obfuscation with the EscapeFuzzer class from libs\escape_fuzz.py: ```python from libs.escape_fuzz import EscapeFuzzer

fuzzer = EscapeFuzzer()

Example obfuscation commands

print(fuzzer.setwindowtitle("My Custom Terminal")) print(fuzzer.sendnotification("Notification: Task Completed!")) print(fuzzer.sethyperlink("https://www.example.com", "Visit our website")) print(fuzzer.set256colorfg(125)) print(fuzzer.settruecolorfg(255, 100, 100)) print(fuzzer.display_unicode('ℜ')) print(fuzzer.fuzz(5)) ```

Contributing

Contribute to Noisy Log: - Fork the Project - Create your Feature Branch (git checkout -b feature/YourNewFeature) - Commit your Changes (git commit -m 'Add some YourNewFeature') - Push to the Branch (git push origin feature/YourNewFeature) - Open a Pull Request

Credits

This project was inspired by the research of STOK Fredrik. His innovative insights into ANSI escape sequences have significantly influenced the development of Noisy Log.

Contact

copyleftdev - @copyleftdev

Owner

  • Name: Donald Johnson
  • Login: copyleftdev
  • Kind: user
  • Location: Los Angeles

GitHub Events

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Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 2
  • Total Committers: 1
  • Avg Commits per committer: 2.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Don Johnson dj@c****o 2
Committer Domains (Top 20 + Academic)
codetestcode.io: 1

Issues and Pull Requests

Last synced: about 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Dependencies

Pipfile pypi