Detector for Log4Shell exploitation attempts

Overview

log4shell-detector

Detector for Log4Shell exploitation attempts

Idea

The problem with the log4j CVE-2021-44228 exploitation is that the string can be heavily obfuscated in many different ways. It is impossible to cover all possible forms with a reasonable regular expression.

The idea behind this detector is that the respective characters have to appear in a log line in a certain order to match.

${jndi:ldap:

Split up into a list it would look like this:

['$', '{', 'j', 'n', 'd', 'i', ':', 'l', 'd', 'a', 'p', ':']

I call these lists 'detection pads' in my script and process each log line character by character. I check if each character matches the first element of the detection pads. If the character matches a character in one of the detection pads, a pointer moves forward.

When the pointer reaches the end of the list, the detection triggered and the script prints the file name, the complete log line, the detected string and the number of the line in the file.

I've included a decoder for URL based encodings. If we need more, please let me know.

Usage

usage: log4shell-detector.py [-h] [-p path [path ...]] [-d maxdis] [--quick] [--defaultpaths] [--debug]

Log4Shell Exploitation Detectors

optional arguments:
  -h, --help          show this help message and exit
  -p path [path ...]  Path to scan
  -d distance         Maximum distance between each character
  --quick             Skip log lines that don't contain a 2021 or 2022 time stamp
  --defaultpaths      Scan a set of default paths that should contain relevant log files.
  --debug             Debug output

Special Flags

--quick

Only checks log lines that contain a 2021 or 2022 to exclude all scanning of older log entries. We assume that the vulnerability wasn't exploited in 2019 and earlier.

--defaultpaths

Check a list of default log paths used by different software products.

Requirements

  • Python3

No further or special Python modules are required. It should run on any system that runs Python3.

Screenshots

Screen1

Screen2

Help

There are different ways how you can help.

A. Test it against the payloads that you find in-the-wild and let me know if we miss something B. Help me find and fix bugs C. Test if the scripts runs with Python 2; if not, we can add a slightly modified version to the repo

Contact

Twitter: @cyberops

Owner
Florian Roth
#DFIR #Python #YARA #Golang #SIEM #SOC #Sigma #Malware
Florian Roth
Implementation of the GBST block from the Charformer paper, in Pytorch

Charformer - Pytorch Implementation of the GBST (gradient-based subword tokenization) module from the Charformer paper, in Pytorch. The paper proposes

Phil Wang 105 Dec 26, 2022
A deep learning object detector framework written in Python for supporting Land Search and Rescue Missions.

AIR: Aerial Inspection RetinaNet for supporting Land Search and Rescue Missions AIR is a deep learning based object detection solution to automate the

Accenture 13 Dec 22, 2022
Source code for Acorn, the precision farming rover by Twisted Fields

Acorn precision farming rover This is the software repository for Acorn, the precision farming rover by Twisted Fields. For more information see twist

Twisted Fields 198 Jan 02, 2023
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch

Learning to Communicate with Deep Multi-Agent Reinforcement Learning This is a PyTorch implementation of the original Lua code release. Overview This

Minqi 297 Dec 12, 2022
Speech Recognition is an important feature in several applications used such as home automation, artificial intelligence

Speech Recognition is an important feature in several applications used such as home automation, artificial intelligence, etc. This article aims to provide an introduction on how to make use of the S

RISHABH MISHRA 1 Feb 13, 2022
💛 Code and Dataset for our EMNLP 2021 paper: "Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes"

Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes Official PyTorch implementation and EmoCause evaluatio

Hyunwoo Kim 51 Jan 06, 2023
An Industrial Grade Federated Learning Framework

DOC | Quick Start | 中文 FATE (Federated AI Technology Enabler) is an open-source project initiated by Webank's AI Department to provide a secure comput

Federated AI Ecosystem 4.8k Jan 09, 2023
A customisable game where you have to quickly click on black tiles in order of appearance while avoiding clicking on white squares.

W.I.P-Aim-Memory-Game A customisable game where you have to quickly click on black tiles in order of appearance while avoiding clicking on white squar

dE_soot 1 Dec 08, 2021
Implementing DeepMind's Fast Reinforcement Learning paper

Fast Reinforcement Learning This is a repo where I implement the algorithms in the paper, Fast reinforcement learning with generalized policy updates.

Marcus Chiam 6 Nov 28, 2022
PyTorch implementation of the paper Dynamic Token Normalization Improves Vision Transfromers.

Dynamic Token Normalization Improves Vision Transformers This is the PyTorch implementation of the paper Dynamic Token Normalization Improves Vision T

Wenqi Shao 20 Oct 09, 2022
This is a yolo3 implemented via tensorflow 2.7

YoloV3 - an object detection algorithm implemented via TF 2.x source code In this article I assume you've already familiar with basic computer vision

2 Jan 17, 2022
Code for the paper "Can Active Learning Preemptively Mitigate Fairness Issues?" presented at RAI 2021.

Can Active Learning Preemptively Mitigate Fairness Issues? Code for the paper "Can Active Learning Preemptively Mitigate Fairness Issues?" presented a

ElementAI 7 Aug 12, 2022
Exact Pareto Optimal solutions for preference based Multi-Objective Optimization

Exact Pareto Optimal solutions for preference based Multi-Objective Optimization

Debabrata Mahapatra 40 Dec 24, 2022
A state of the art of new lightweight YOLO model implemented by TensorFlow 2.

CSL-YOLO: A New Lightweight Object Detection System for Edge Computing This project provides a SOTA level lightweight YOLO called "Cross-Stage Lightwe

Miles Zhang 54 Dec 21, 2022
Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018

Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples This project is for the paper "Training Confidence-Calibrated Clas

168 Nov 29, 2022
Perspective: Julia for Biologists

Perspective: Julia for Biologists 1. Examples Speed: Example 1 - Single cell data and network inference Domain: Single cell data Methodology: Network

Elisabeth Roesch 55 Dec 02, 2022
Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation (ICLR 2020)

U-GAT-IT — Official TensorFlow Implementation (ICLR 2020) : Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization fo

Junho Kim 6.2k Jan 04, 2023
Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D.

ApproxMVBB Status Build UnitTests Homepage Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in

Gabriel Nützi 390 Dec 31, 2022
Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition (AGRA, ACM 2020, Oral)

Cross Domain Facial Expression Recognition Benchmark Implementation of papers: Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchm

89 Dec 09, 2022
Fast and customizable reconnaissance workflow tool based on simple YAML based DSL.

Fast and customizable reconnaissance workflow tool based on simple YAML based DSL, with support of notifications and distributed workload of that work

Américo Júnior 3 Mar 11, 2022