evasion-attack

There are 2 repositories under evasion-attack topic.

aeverj / NimShellCodeLoader
免杀，bypassav，免杀框架，nim，shellcode，使用nim编写的shellcode加载器
nim shellcode-loader offensive evasion-attack
Language:C 668
AIJack
Koukyosyumei / AIJack
Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)
adversarial-attacks adversarial-examples adversarial-machine-learning dbms deep-learning differential-privacy evasion-attack federated-learning homomorphic-encryption k-anonymity machine-learning membership-inference model-inversion-attacks paillier paillier-cryptosystem poisoning-attacks privacy security
Language:C++ 408
DamonMohammadbagher / NativePayloads
All my Source Codes (Repos) for Red-Teaming & Pentesting + Blue Teaming
blueteam blueteaming bypass-antivirus csharp defensive defensive-programming evasion evasion-attack memoryscanner monitoring-tool offensive offensive-security pentest pentesting redteam redteaming detection remote-thread-injection thread-injection
Language:C# 231
njcve / inflate.py
Artificially inflate a given binary to exceed common EDR file size limits. Can be used to bypass common EDR.
antivirus antivirus-evasion av-bypass av-evasion bugbounty edr-bypass endpoint-security evasion-attack
Language:Python 120
OlivierLaflamme / DNSWho
transmit cs beacon (shellcode) over self-made dns to avoid anti-kill and AV
redteam dns cobaltstrike bypass-antivirus exfiltration shellcode beacon evasion-attack evasion antivirus-evasion bypass-av
Language:C# 50
scy-phy / ICS-Evasion-Attacks
Public Code for ICS Evasion Attack Generation
concealment-attack ics-evasion-attacks evasion-attack adversarial-machine-learning
Language:Jupyter Notebook 42
edoardottt / defangjs
URL / IP / Email defanging with Javascript. Make IoC harmless.
url ip defang defanging url-defanging javascript javascript-library email email-security phishing phishing-attacks evasion-attack phishing-protection security-tools emailjs nodejs cti ioc malware malware-protection
Language:JavaScript 32
qwqoro / ML-Talk
📄 [Talk] OFFZONE 2022 / ODS Data Halloween 2022: Black-box attacks on ML models + with use of open-source tools
adversarial-attacks adversarial-examples attack-model black-box-attacks black-box-model conference conference-talk evasion-attack evasion-attacks fast-track model-attack model-extraction model-inversion model-inversion-attack model-inversion-attacks talk talk-materials talk-notes talk-slides
Language:Jupyter Notebook 12
zero2504 / Shadow-Rebirth
Shadow Rebirth - An Aggressive Outbreak Anti-Debugging Technique
anti-analysis anti-debugging anti-reversing dll-unhooking evasion-attack malware
Language:C++ 10
La-Casette / malicious_pdf_detection
This project compares the performance of K-Nearest Neighbors, Support Vector Machines, and Decision Trees models for detecting malicious PDF files, with an emphasis on optimizing model performance and analyzing evasion techniques. It provides a comprehensive overview of machine learning for malicious PDF detection and potential vulnerabilities.
adversarial-learning decision-trees evasion-attack knn machine-learning malicious pdf pdf-malware random-forest svm
Language:Jupyter Notebook 6
JavierYuste / Optimization-of-code-caves-in-malware-binaries-to-evade-Machine-Learning-detectors
Generation of adversarial examples for ML-based malware detectors through the use of Genetic Algorithms.
machine-learning malware malware-research malware-detection evasion-attack
Language:Python 4
ProfiterolePuff / nvita
The n-Values Time Series Attack (nVITA) is a sparse indirect black-box evasion attack that aims to achieve the adversarial goal (such as enforcing a certain output of the model) on TSF models by altering n values in an input time series. This repository is based on PyTorch. It also contains the implementations of FGSM and BIM for TSF models.
adversarial-machine-learning evasion-attack time-series-forecasting convolutional-neural-networks pytorch recurrent-neural-networks
Language:Jupyter Notebook 4
FrostbiteXSW / SCAE_Attack
An Evasion Attack against Stacked Capsule Autoencoder
attack evasion-attack
Language:Python 2
cawandmilk / evasion_attack
Training, inference, and evaluate of the speaker identification and verification model are carried out, and evasion attacks (FGSM, PGD) are performed.
speaker-identification speaker-verification evasion-attack tensorflow2
Language:Python 1
n1ghtf4l1 / jubilant-robot-hacker
Collecting flags by evading, poisoning, stealing, and fooling AI/ML.
capture-the-flag clustering dimensionality-reduction image-classification image-processing kaggle-competition machine-learning embeddings evasion-attack tensorflow-keras tsne waf-bypass pca-reduction
Language:Jupyter Notebook 1
pepealessio / Adversarial-Face-Identification
An University Project for the AI4Cybersecurity class.
adversarial-attacks adversarial-detection adversarial-robustness-toolbox art evasion-attack face-identification fgsm-attack pgd-adversarial-attacks resnet-50 adversarial-faces bim-attack adversarial-machine-learning
Language:Jupyter Notebook 1
kotstot6 / EvasionAttacks
Two white-box evasion attacks– FGSM + PGD– on a LeNet-5 model trained on Fashion MNIST
deep-learning evasion-attack fashion-mnist pytorch
Language:Python 0
vitorglemos / evasion-phishing-ai
The Machine Learning Security Evasion Competition (MLSEC) 2022 took place from August 12th to September 23th 2022 and was organized by Adversa AI, CUJO AI, and Robust Intelligence. I will explain here what I use as a method to bypass the machine learning models produced for this competition.
cybersecurity evasion-attack machinelearning
Language:HTML 0

evasion-attack

aeverj / NimShellCodeLoader

Koukyosyumei / AIJack

DamonMohammadbagher / NativePayloads

njcve / inflate.py

OlivierLaflamme / DNSWho

scy-phy / ICS-Evasion-Attacks

edoardottt / defangjs

qwqoro / ML-Talk

zero2504 / Shadow-Rebirth

La-Casette / malicious_pdf_detection

JavierYuste / Optimization-of-code-caves-in-malware-binaries-to-evade-Machine-Learning-detectors

ProfiterolePuff / nvita

FrostbiteXSW / SCAE_Attack

cawandmilk / evasion_attack

n1ghtf4l1 / jubilant-robot-hacker

pepealessio / Adversarial-Face-Identification

kotstot6 / EvasionAttacks

vitorglemos / evasion-phishing-ai