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
Code related to the manuscript "Averting A Crisis In Simulation-Based Inference"

Abstract We present extensive empirical evidence showing that current Bayesian simulation-based inference algorithms are inadequate for the falsificat

Montefiore Artificial Intelligence Research 3 Nov 14, 2022
Remote sensing change detection using PaddlePaddle

Change Detection Laboratory Developing and benchmarking deep learning-based remo

Lin Manhui 15 Sep 23, 2022
PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"

Smoothed Mutual Information ``Lower Bound'' Estimator PyTorch implementation for the ICLR 2020 paper Understanding the Limitations of Variational Mutu

50 Nov 09, 2022
CausaLM: Causal Model Explanation Through Counterfactual Language Models

CausaLM: Causal Model Explanation Through Counterfactual Language Models Authors: Amir Feder, Nadav Oved, Uri Shalit, Roi Reichart Abstract: Understan

Amir Feder 39 Jul 10, 2022
The official implementation of CircleNet: Anchor-free Detection with Circle Representation, MICCAI 2030

CircleNet: Anchor-free Detection with Circle Representation The official implementation of CircleNet, MICCAI 2020 [PyTorch] [project page] [MICCAI pap

The Biomedical Data Representation and Learning Lab 45 Nov 18, 2022
Algorithmic Trading using RNN

Deep-Trading This an implementation adapted from Rachnog Neural networks for algorithmic trading. Part One — Simple time series forecasting and this c

Hazem Nomer 29 Sep 04, 2022
Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed. KDD 2019.

gHHC Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, D

Nicholas Monath 35 Nov 16, 2022
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data

Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data This is the official PyTorch implementation of the SeCo paper: @articl

ElementAI 101 Dec 12, 2022
TorchX: A PyTorch Extension Library for More Efficient Deep Learning

TorchX TorchX: A PyTorch Extension Library for More Efficient Deep Learning. @misc{torchx, author = {Ansheng You and Changxu Wang}, title = {T

Donny You 8 May 28, 2022
All public open-source implementations of convnets benchmarks

convnet-benchmarks Easy benchmarking of all public open-source implementations of convnets. A summary is provided in the section below. Machine: 6-cor

Soumith Chintala 2.7k Dec 30, 2022
A large-scale face dataset for face parsing, recognition, generation and editing.

CelebAMask-HQ [Paper] [Demo] CelebAMask-HQ is a large-scale face image dataset that has 30,000 high-resolution face images selected from the CelebA da

switchnorm 1.7k Dec 26, 2022
System-oriented IR evaluations are limited to rather abstract understandings of real user behavior

Validating Simulations of User Query Variants This repository contains the scripts of the experiments and evaluations, simulated queries, as well as t

IR Group at Technische Hochschule Köln 2 Nov 23, 2022
PyTorch implementation of the YOLO (You Only Look Once) v2

PyTorch implementation of the YOLO (You Only Look Once) v2 The YOLOv2 is one of the most popular one-stage object detector. This project adopts PyTorc

申瑞珉 (Ruimin Shen) 433 Nov 24, 2022
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow. The main features of this library are: High level API (just

Pavel Yakubovskiy 4.2k Jan 09, 2023
[ICCV2021] 3DVG-Transformer: Relation Modeling for Visual Grounding on Point Clouds

3DVG-Transformer This repository is for the ICCV 2021 paper "3DVG-Transformer: Relation Modeling for Visual Grounding on Point Clouds" Our method "3DV

22 Dec 11, 2022
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing

PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing

943 Jan 07, 2023
AAAI 2022: Stationary diffusion state neural estimation

Stationary Diffusion State Neural Estimation Although many graph-based clustering methods attempt to model the stationary diffusion state in their obj

绽琨 33 Nov 24, 2022
Gym environments used in the paper: "Developmental Reinforcement Learning of Control Policy of a Quadcopter UAV with Thrust Vectoring Rotors"

gym_multirotor Gym to train reinforcement learning agents on UAV platforms Quadrotor Tiltrotor Requirements This package has been tested on Ubuntu 18.

Aditya M. Deshpande 19 Dec 29, 2022
Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.

Robotic Arm Simulation in ROS2 and Gazebo General Overview This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZE

David Valencia 12 Jan 02, 2023
Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition

GCN_LogsigRNN This repository holds the codebase for the paper: Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition

7 Oct 14, 2022