Learn Machine Learning and AI – Online Training Program @ 93% OFF

Within the next decade, artificial intelligence is likely to play a significant role in our everyday lives. Machine learning already powers image recognition, self-driving cars, and Netflix recommendations. For any aspiring developer, learning how to code smart software is a good move. These skil...

Learn Machine Learning and AI – Online Training Program @ 93% OFF

Within the next decade, artificial intelligence is likely to play a significant role in our everyday lives. Machine learning already powers image recognition, self-driving cars, and Netflix recommendations. For any aspiring developer, learning how to code smart software is a good move. These skil...

Afternoon Cyber Tea: Peak, Plateau, or Plummet? Cyber security trends that are here to stay and how to detect and recover from ransomware attacks

The rapidity of change in the cyberthreat landscape can be daunting for today’s cyber defense teams. Just as they perfect the ability to block one attack method, adversaries change their approach. Tools like artificial intelligence and machine learning allow us to pivot quickly, however, knowing...

Seeing the big picture: Deep learning-based fusion of behavior signals for threat detection

The application of deep learning and other machine learning methods to threat detection on endpoints, email and docs, apps, and identities drives a significant piece of the coordinated defense delivered by Microsoft Threat Protection. Within each domain as well as across domains, machine learning...

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,...

Security Bulletin: WML CE: TensorFlow: In SQLite before 3.32.3, select.c mishandles query-flattener optimization

Summary In SQLite before 3.32.3, select.c mishandles query-flattener optimization, leading to a multiSelectOrderBy heap overflow because of misuse of transitive properties for constant propagation. TensorFlow in WML CE uses SQLite as its embedded SQL database engine. Vulnerability Details CVEID:...

Security Bulletin: WML CE Scikit-learn vulnerable to irresponsible usage

Summary WML containers include scikit-learn. Scikit-learn includes joblib and pickle to cache and load models. Pickle and joblib by extension, has some issues regarding maintainability and security. Because of this, usage of the joblib.load function in scikit-learn must be done in a responsible...

Security Bulletin: WML CE: Pillow before 7.1.0 has multiple out-of-bounds reads

Summary Pillow before 7.1.0 has multiple out-of-bounds reads in libImaging/FliDecode.c. PyTorch and TensorFlow use Pillow. Vulnerability Details CVEID: CVE-2020-10177 DESCRIPTION: Pillow could allow a remote attacker to obtain sensitive information, caused by multiple out-of-bounds reads in...

Security Bulletin: WML CE: TensorBoard: Node.js lodash module is vulnerable to a denial of service, caused by a prototype pollution attack.

Summary Node.js lodash module is vulnerable to a denial of service, caused by a prototype pollution attack. TensorBoard uses lodash. A remote attacker could exploit this vulnerability using the merge, mergeWith, and defaultsDeep functions to inject properties onto Object.prototype to crash the...

Security Bulletin: WML CE: libjpeg-turbo 2.0.4, and mozjpeg 4.0.0, has a heap-based buffer over-read

Summary libjpeg-turbo 2.0.4, and mozjpeg 4.0.0, has a heap-based buffer over-read in getrgbrow in rdppm.c via a malformed PPM input file. Vulnerability Details CVEID: CVE-2020-13790 DESCRIPTION: Libjpeg-turbo is vulnerable to a denial of service, caused by heap-based buffer over-read in getrgbrow...

Cato MDR: Managed Threat Detection and Response Made Easy

Lately, we can't help noticing an endless cycle where the more enterprises invest in threat prevention; the more hackers adapt and continue to penetrate enterprises. To make things worse, detecting these penetrations still takes too long with an average dwell time that exceeds 100 ! days. To keep...

Experts Denounce Racial Bias of Crime-Predictive Facial-Recognition AI

More than 1,000 technology experts and academics from organizations such as MIT, Microsoft, Harvard and Google have signed an open letter denouncing a forthcoming paper describing artificial intelligence AI algorithms that can predict crime based only on a person’s face, calling it out for...

Modernizing the security operations center to better secure a remote workforce

The response to COVID-19 has required many security operations centers SOCs to rethink how they protect their organizations. With so many employees working remotely, IT groups are routing more traffic directly to cloud apps, rather than through the network. In this model, traditional network...

Identifying a Person Based on a Photo, LinkedIn and Etsy Profiles, and Other Internet Bread Crumbs

Interesting story of how the police can identify someone by following the evidence chain from website to website. According to filings in Blumenthal's case, FBI agents had little more to go on when they started their investigation than the news helicopter footage of the woman setting the police c...

Attack Analytics Multi-Sensor Integrations Provide Unmatched Visibility

Since debuting Attack Analytics back in 2018, this groundbreaking security analytics functionality has come a long way. Time and again our customers have told us how powerful they find the tool and how much time it saves them. Attack Analytics better positions Imperva’s customers to focus on what...

Kubernetes Falls to Cryptomining via Machine-Learning Framework

A unique cyberattack campaign that targets Kubeflow, a machine-learning toolkit for Kubernetes, has affected large swathes of container clusters, according to Microsoft. The Kubeflow open-source project is a popular framework for running machine-learning ML tasks in Kubernetes. According to an...

Misconfigured Kubeflow workloads are a security risk

Azure Security Center ASC monitors and defends thousands of Kubernetes clusters running on top of AKS. Azure Security Center regularly searches for and research for new attack vectors against Kubernetes workloads. We recently published a blog post about a large scale campaign against Kubernetes...

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...

Machine Learning Security Evasion Competition 2020 Invites Researchers to Defend and Attack

Machine learning ML is an increasingly valuable tool in cyber security as adversaries continually evolve their tactics and techniques to evade detection. As machine learning has advanced and sophisticated ML models have been developed to assist security professionals in protecting the cloud,...

Machine Learning Security Evasion Competition 2020 Invites Researchers to Defend and Attack

Machine learning ML is an increasingly valuable tool in cyber security as adversaries continually evolve their tactics and techniques to evade detection. As machine learning has advanced and sophisticated ML models have been developed to assist security professionals in protecting the cloud,...