Emulation and Feedback Fuzzing of Firmware with Memory Sanitization

Related tags

Deep LearningBaseSAFE
Overview

BaseSAFE

base safe paper

This repository contains the BaseSAFE Rust APIs, introduced by "BaseSAFE: Baseband SAnitized Fuzzing through Emulation".

The example/ directory contains two harnesses emulating parts of the firmware for MediaTek’s Helio X10 (MT6795) baseband processor. _EMM_ demonstrates a crash inside the decoder for ATTACH/ACCEPT messages as part of the Mobility Management. _ERRC_ emulates various ASN.1 decoders which are being used for Radio Resource Control messages. Example inputs can be found inside the _data/_ directories.


Setup

Make AFL++ and build AFLplusplus/unicorn_mode.

./build_afl.sh

A single emulation run can be started by navigating into e.g. examples/errc and executing the harness on the provided data:

cd examples/errc/
cargo run data/pcch.raw

The emulated code can be fuzzed with AFL++ in Unicorn mode:

cd examples/errc
cargo build --release
../../AFLplusplus/afl-fuzz -U -i connections/ -o out/ -m none -- target/release/errc_fuzz @@
Owner
Security in Telecommunications
The Computer Security Group at Berlin University of Technology
Security in Telecommunications
Orchestrating Distributed Materials Acceleration Platform Tutorial

Orchestrating Distributed Materials Acceleration Platform Tutorial This tutorial for orchestrating distributed materials acceleration platform was pre

BIG-MAP 1 Jan 25, 2022
Keras-1D-NN-Classifier

Keras-1D-NN-Classifier This code is based on the reference codes linked below. reference 1, reference 2 This code is for 1-D array data classification

Jae-Hoon Shim 6 May 18, 2021
S2s2net - Sentinel-2 Super-Resolution Segmentation Network

S2S2Net Sentinel-2 Super-Resolution Segmentation Network Getting started Install

Wei Ji 10 Nov 10, 2022
This is a repository for a semantic segmentation inference API using the OpenVINO toolkit

BMW-IntelOpenVINO-Segmentation-Inference-API This is a repository for a semantic segmentation inference API using the OpenVINO toolkit. It's supported

BMW TechOffice MUNICH 34 Nov 24, 2022
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)

PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J

AI Wizards for Software Management (AWSM) Research Group 14 Nov 13, 2022
Human annotated noisy labels for CIFAR-10 and CIFAR-100.

Dataloader for CIFAR-N CIFAR-10N noise_label = torch.load('./data/CIFAR-10_human.pt') clean_label = noise_label['clean_label'] worst_label = noise_lab

<a href=[email protected]"> 117 Nov 30, 2022
Dynamic Environments with Deformable Objects (DEDO)

DEDO - Dynamic Environments with Deformable Objects DEDO is a lightweight and customizable suite of environments with deformable objects. It is aimed

Rika 32 Dec 22, 2022
(CVPR 2022) A minimalistic mapless end-to-end stack for joint perception, prediction, planning and control for self driving.

LAV Learning from All Vehicles Dian Chen, Philipp Krähenbühl CVPR 2022 (also arXiV 2203.11934) This repo contains code for paper Learning from all veh

Dian Chen 300 Dec 15, 2022
Self-supervised Augmentation Consistency for Adapting Semantic Segmentation (CVPR 2021)

Self-supervised Augmentation Consistency for Adapting Semantic Segmentation This repository contains the official implementation of our paper: Self-su

Visual Inference Lab @TU Darmstadt 132 Dec 21, 2022
This is the implementation of our work Deep Extreme Cut (DEXTR), for object segmentation from extreme points.

This is the implementation of our work Deep Extreme Cut (DEXTR), for object segmentation from extreme points.

Sergi Caelles 828 Jan 05, 2023
The official implementation of A Unified Game-Theoretic Interpretation of Adversarial Robustness.

This repository is the official implementation of A Unified Game-Theoretic Interpretation of Adversarial Robustness. Requirements pip install -r requi

Jie Ren 17 Dec 12, 2022
CAMoE + Dual SoftMax Loss (DSL): Improving Video-Text Retrieval by Multi-Stream Corpus Alignment and Dual Softmax Loss

CAMoE + Dual SoftMax Loss (DSL): Improving Video-Text Retrieval by Multi-Stream Corpus Alignment and Dual Softmax Loss This is official implement of "

程星 87 Dec 24, 2022
Official PyTorch implementation for FastDPM, a fast sampling algorithm for diffusion probabilistic models

Official PyTorch implementation for "On Fast Sampling of Diffusion Probabilistic Models". FastDPM generation on CIFAR-10, CelebA, and LSUN datasets. S

Zhifeng Kong 68 Dec 26, 2022
State-of-the-art data augmentation search algorithms in PyTorch

MuarAugment Description MuarAugment is a package providing the easiest way to a state-of-the-art data augmentation pipeline. How to use You can instal

43 Dec 12, 2022
[CVPR 2021] Counterfactual VQA: A Cause-Effect Look at Language Bias

Counterfactual VQA (CF-VQA) This repository is the Pytorch implementation of our paper "Counterfactual VQA: A Cause-Effect Look at Language Bias" in C

Yulei Niu 94 Dec 03, 2022
What can linearized neural networks actually say about generalization?

What can linearized neural networks actually say about generalization? This is the source code to reproduce the experiments of the NeurIPS 2021 paper

gortizji 11 Dec 09, 2022
[NeurIPS'20] Self-supervised Co-Training for Video Representation Learning. Tengda Han, Weidi Xie, Andrew Zisserman.

CoCLR: Self-supervised Co-Training for Video Representation Learning This repository contains the implementation of: InfoNCE (MoCo on videos) UberNCE

Tengda Han 271 Jan 02, 2023
PyTorch Implementation of Realtime Multi-Person Pose Estimation project.

PyTorch Realtime Multi-Person Pose Estimation This is a pytorch version of Realtime_Multi-Person_Pose_Estimation, origin code is here Realtime_Multi-P

Dave Fang 157 Nov 12, 2022
Object detection (YOLO) with pytorch, OpenCV and python

Real Time Object/Face Detection Using YOLO-v3 This project implements a real time object and face detection using YOLO algorithm. You only look once,

1 Aug 04, 2022
Making Structure-from-Motion (COLMAP) more robust to symmetries and duplicated structures

SfM disambiguation with COLMAP About Structure-from-Motion generally fails when the scene exhibits symmetries and duplicated structures. In this repos

Computer Vision and Geometry Lab 193 Dec 26, 2022