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...

adversarial-labeller (0.1.8), ali-cli (>=0.5.1, <=0.7.2) +218 more potentially affected by CVE-2020-7212 via urllib3 (>=1.25.2, <=1.25.7)

urllib3 PYPI version =1.25.2, =0.5.1, =1.1.28, =0.0.22, =0.0.6, =0.27.1, =0.45.0, =0.1.0, =0.0.1, =0.2.0, =0.0.5a0, =3.1.0, =0.3.4, =0.3.8 and more Source cves: CVE-2020-7212 Source advisory: GHSA-HMV2-79Q8-FV6G...

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...

adapt-diagnostics (1.2.0), adversarial-friend (1.1.8) +56 more potentially affected by CVE-2020-15203 via tensorflow (2.3.0)

tensorflow PYPI version 2.3.0 is affected by a known vulnerability. The following packages have a transitive dependency on tensorflow and may be impacted: - adapt-diagnostics 1.2.0 - adversarial-friend 1.1.8 - apifish 0.6.2a1 - armcor 0.2.0 - biobeaker 0.0.1 - bmstu-ovchinnikov-capsnet =0.0.1a0,...

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...

Fooling NLP Systems Through Word Swapping

MIT researchers have built a system that fools natural-language processing systems by swapping words with synonyms: The software, developed by a team at MIT, looks for the words in a sentence that are most important to an NLP classifier and replaces them with a synonym that a human would find...

Monitoring ICS Cyber Operation Tools and Software Exploit Modules To Anticipate Future Threats

There has only been a small number of broadly documented cyber attacks targeting operational technologies OT / industrial control systems ICS over the last decade. While fewer attacks is clearly a good thing, the lack of an adequate sample size to determine risk thresholds can make it difficult f...

Machine learning classifiers trained via gradient descent are vulnerable to arbitrary misclassification attack

Overview Machine learning models trained using gradient descent can be forced to make arbitrary misclassifications by an attacker that can influence the items to be classified. The impact of a misclassification varies widely depending on the ML model's purpose and of what systems it is a part...

Bruce Schneier Proposes 'Hacking Society' for a Better Tomorrow

SAN FRANCISCO – Cybersecurity experts have long stayed in their problem-solving lane when it comes to finding vulnerabilities, patching bugs and keeping networks safe. But maybe it is time they applied their defensive skillsets and adversarial understanding of cyberthreats to help solve some of...

Introduction and Application of Model Hacking

ARCHIVED STORY Introduction and Application of Model Hacking By Steve Povolny · Febraury 19, 2020 Catherine Huang, Ph.D., and Shivangee Trivedi contributed to this blog. The term “Adversarial Machine Learning” AML is a mouthful! The term describes a research field regarding the study and design o...