Awesome-Red-Teaming

This is an offensive tool for Red Teaming. It is a list of resources for anyone wishing to learn about Red Teaming, including initial access, execution, persistence, privilege escalation, defense evasion, credential access, discovery, lateral movement, collection, exfiltration, command and contro...

OpenAttack - An Open-Source Package For Textual Adversarial Attack

OpenAttack is an open-source Python-based textual adversarial attack toolkit, which handles the whole process of textual adversarial attacking, including preprocessing text, accessing the victim model, generating adversarial examples and evaluation. Features & Uses OpenAttack has following...

WAF-A-MoLE - A Guided Mutation-Based Fuzzer For ML-based Web Application Firewalls

A guided mutation-based fuzzer for ML-based Web Application Firewalls, inspired by AFL and based on the FuzzingBook by Andreas Zeller et al. Given an input SQL injection query, it tries to produce a semantic invariant query that is able to bypass the target WAF. You can use this tool for assessin...

How to confuse antimalware neural networks. Adversarial attacks and protection

Introduction Nowadays, cybersecurity companies implement a variety of methods to discover new, previously unknown malware files. Machine learning ML is a powerful and widely used approach for this task. At Kaspersky we have a number of complex ML models based on different file features, including...

The Supreme Court Narrowed the CFAA

In a 6-3 ruling, the Supreme Court just narrowed the scope of the Computer Fraud and Abuse Act: In a ruling delivered today, the court sided with Van Buren and overturned his 18-month conviction. In a 37-page opinion written and delivered by Justice Amy Coney Barrett, the court explained that the...

Kill chains: Part 1→Strategic and operational value

It really is a good thing The term “kill chain” sounds extremely harsh. Almost as if after something is killed, it gets moved down the chain to be killed again. How dramatic! Indeed, the original definition was to describe how an enemy combatant of the military might attack; that is, the steps th...

U.S. Intelligence Agencies Warn About 5G Network Weaknesses

Inadequate implementation of telecom standards, supply chain threats, and weaknesses in systems architecture could pose major cybersecurity risks to 5G networks, potentially making them a lucrative target for cybercriminals and nation-state adversaries to exploit for valuable intelligence. The...

AI security risk assessment using Counterfit

Today, we are releasing Counterfit, an automation tool for security testing AI systems as an open-source project. Counterfit helps organizations conduct AI security risk assessments to ensure that the algorithms used in their businesses are robust, reliable, and trustworthy. AI systems are...

AI security risk assessment using Counterfit

Today, we are releasing Counterfit, an automation tool for security testing AI systems as an open-source project. Counterfit helps organizations conduct AI security risk assessments to ensure that the algorithms used in their businesses are robust, reliable, and trustworthy. AI systems are...

TAU Threat Analysis: Insights on the SolarWinds Breach

In light of the SolarWinds breach, we want to help our customers who may have questions as well as the larger security community. The VMware Carbon Black Threat Analysis Unit TAU has been steadfastly monitoring the evolving situation as we learn more about the supply chain compromise. We caught u...

SoReL-20M: A Huge Dataset of 20 Million Malware Samples Released Online

Cybersecurity firms Sophos and ReversingLabs on Monday jointly released the first-ever production-scale malware research dataset to be made available to the general public that aims to build effective defenses and drive industry-wide improvements in security detection and response. "SoReL-20M"...

U.S. Dept Of Defense: IDOR on https://██████ via POST UID enables database scraping

Summary: The UID parameter on █████████ in the ██████ ███████ system, with ███████, does not validate that the caller has permission to view information on the UID entered, thereby enabling personnel and student data extraction. Description: The user operations API endpoint for the ███ ██████████...

Pesidious - Malware Mutation Using Reinforcement Learning And Generative Adversarial Networks

Malware Mutation using Deep Reinforcement Learning and GANs The purpose of the tool is to use artificial intelligence to mutate a malware PE32 only sample to bypass AI powered classifiers while keeping its functionality intact. In the past, notable work has been done in this domain with researche...

New Framework Released to Protect Machine Learning Systems From Adversarial Attacks

Microsoft, in collaboration with MITRE, IBM, NVIDIA, and Bosch, has released a new open framework that aims to help security analysts detect, respond to, and remediate adversarial attacks against machine learning ML systems. Called the Adversarial ML Threat Matrix, the initiative is an attempt to...

New Framework Released to Protect Machine Learning Systems From Adversarial Attacks

Microsoft, in collaboration with MITRE, IBM, NVIDIA, and Bosch, has released a new open framework that aims to help security analysts detect, respond to, and remediate adversarial attacks against machine learning ML systems. Called the Adversarial ML Threat Matrix, the initiative is an attempt to...

Cyberattacks against machine learning systems are more common than you think

Machine learning ML is making incredible transformations in critical areas such as finance, healthcare, and defense, impacting nearly every aspect of our lives. Many businesses, eager to capitalize on advancements in ML, have not scrutinized the security of their ML systems. Today, along with...

Cyberattacks against machine learning systems are more common than you think

Machine learning ML is making incredible transformations in critical areas such as finance, healthcare, and defense, impacting nearly every aspect of our lives. Many businesses, eager to capitalize on advancements in ML, have not scrutinized the security of their ML systems. Today, along with...

Adversarial Machine Learning and the CFAA

I just co-authored a paper on the legal risks of doing machine learning research, given the current state of the Computer Fraud and Abuse Act: Abstract: Adversarial Machine Learning is booming with ML researchers increasingly targeting commercial ML systems such as those used in Facebook, Tesla,...

Availability Attacks against Neural Networks

New research on using specially crafted inputs to slow down machine-learning neural network systems: Sponge Examples: Energy-Latency Attacks on Neural Networks shows how to find adversarial examples that cause a DNN to burn more energy, take more time, or both. They affect a wide range of DNN...

Trend Micro’s Top Ten MITRE Evaluation Considerations

The introduction of the MITRE ATT&CK evaluations is a welcomed addition to the third-party testing arena. The ATT&CK framework, and the evaluations in particular, have gone such a long way in helping advance the security industry as a whole, and the individual security products serving the market...