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
MonoScene: Monocular 3D Semantic Scene Completion

MonoScene: Monocular 3D Semantic Scene Completion MonoScene: Monocular 3D Semantic Scene Completion] [arXiv + supp] | [Project page] Anh-Quan Cao, Rao

298 Jan 08, 2023
Yolov5 deepsort inference,使用YOLOv5+Deepsort实现车辆行人追踪和计数,代码封装成一个Detector类,更容易嵌入到自己的项目中

使用YOLOv5+Deepsort实现车辆行人追踪和计数,代码封装成一个Detector类,更容易嵌入到自己的项目中。

813 Dec 31, 2022
Fast Scattering Transform with CuPy/PyTorch

Announcement 11/18 This package is no longer supported. We have now released kymatio: http://www.kymat.io/ , https://github.com/kymatio/kymatio which

Edouard Oyallon 289 Dec 07, 2022
Multi-Modal Fingerprint Presentation Attack Detection: Evaluation On A New Dataset

PADISI USC Dataset This repository analyzes the PADISI-Finger dataset introduced in Multi-Modal Fingerprint Presentation Attack Detection: Evaluation

USC ISI VISTA Computer Vision 6 Feb 06, 2022
Deep Image Search is an AI-based image search engine that includes deep transfor learning features Extraction and tree-based vectorized search.

Deep Image Search - AI-Based Image Search Engine Deep Image Search is an AI-based image search engine that includes deep transfer learning features Ex

139 Jan 01, 2023
Pytorch implementation of TailCalibX : Feature Generation for Long-tail Classification

TailCalibX : Feature Generation for Long-tail Classification by Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi [arXiv] [

Rahul Vigneswaran 34 Jan 02, 2023
Deeplab-resnet-101 in Pytorch with Jaccard loss

Deeplab-resnet-101 Pytorch with Lovász hinge loss Train deeplab-resnet-101 with binary Jaccard loss surrogate, the Lovász hinge, as described in http:

Maxim Berman 95 Apr 15, 2022
Efficient 6-DoF Grasp Generation in Cluttered Scenes

Contact-GraspNet Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes Martin Sundermeyer, Arsalan Mousavian, Rudolph Triebel, Dieter

NVIDIA Research Projects 148 Dec 28, 2022
Stacked Generative Adversarial Networks

Stacked Generative Adversarial Networks This repository contains code for the paper "Stacked Generative Adversarial Networks", CVPR 2017. Part of the

Xun Huang 241 May 07, 2022
BanditPAM: Almost Linear-Time k-Medoids Clustering

BanditPAM: Almost Linear-Time k-Medoids Clustering This repo contains a high-performance implementation of BanditPAM from BanditPAM: Almost Linear-Tim

254 Dec 12, 2022
This is the official pytorch implementation of the BoxEL for the description logic EL++

BoxEL: Box EL++ Embedding This is the official pytorch implementation of the BoxEL for the description logic EL++. BoxEL++ is a geometric approach bas

1 Nov 03, 2022
An interactive DNN Model deployed on web that predicts the chance of heart failure for a patient with an accuracy of 98%

Heart Failure Predictor About A Web UI deployed Dense Neural Network Model Made using Tensorflow that predicts whether the patient is healthy or has c

Adit Ahmedabadi 0 Jan 09, 2022
PyTorch implementation of DeepUME: Learning the Universal Manifold Embedding for Robust Point Cloud Registration (BMVC 2021)

DeepUME: Learning the Universal Manifold Embedding for Robust Point Cloud Registration [video] [paper] [supplementary] [data] [thesis] Introduction De

Natalie Lang 10 Dec 14, 2022
Malware Bypass Research using Reinforcement Learning

Malware Bypass Research using Reinforcement Learning

Bobby Filar 76 Dec 26, 2022
Training code and evaluation benchmarks for the "Self-Supervised Policy Adaptation during Deployment" paper.

Self-Supervised Policy Adaptation during Deployment PyTorch implementation of PAD and evaluation benchmarks from Self-Supervised Policy Adaptation dur

Nicklas Hansen 101 Nov 01, 2022
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System

Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System Authors: Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai

Amazon Web Services - Labs 123 Dec 23, 2022
Temporal Segment Networks (TSN) in PyTorch

TSN-Pytorch We have released MMAction, a full-fledged action understanding toolbox based on PyTorch. It includes implementation for TSN as well as oth

1k Jan 03, 2023
Universal Probability Distributions with Optimal Transport and Convex Optimization

Sylvester normalizing flows for variational inference Pytorch implementation of Sylvester normalizing flows, based on our paper: Sylvester normalizing

Rianne van den Berg 172 Dec 13, 2022
Scripts for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation and a convolutional neural network (CNN) for image classification

About subwAI subwAI - a project for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation

82 Jan 01, 2023