Systran Pure Neural Server Cross-Site Scripting Vulnerability

Systran Pure Neural Server is a Web platform product for document translation from Systran, Germany. A cross-site scripting vulnerability previously existed in Systran Pure Neural Server 9.7.0, which stemmed from a cross-site scripting XSS issue in WebUI Translation that allowed a threat actor to...

PT-2020-17184

Name of the Vulnerable Software and Affected Versions Systran Pure Neural Server versions prior to 9.7.0 Description A Cross-Site Scripting XSS issue in WebUI Translation allows a threat actor to have a remote authenticated user run JavaScript from a malicious site. Recommendations For versions...

Systran Pure Neural Server Resource Management Error Vulnerability

Systran Pure Neural Server is a web platform product for document translation from Systran, Germany. A security vulnerability exists in Systran Pure Neural Server prior to version 9.7.0 that stems from an API call in the Translation API function Systran Pure Neural Server prior to 9.7.0 that allo...

PT-2020-17185

Name of the Vulnerable Software and Affected Versions Systran Pure Neural Server versions prior to 9.7.0 Description The issue allows a threat actor to use the Systran Pure Neural Server as a Denial-of-Service proxy by sending a large amount of translation requests to a destination host on any...

CVE-2020-29539: Improper Neutralization of Input During Web Page Generation

A Cross-Site Scripting XSS issue in WebUI Translation in Systran Pure Neural Server before 9.7.0 allows a threat actor to have a remote authenticated user run JavaScript from a malicious site...

CVE-2020-29540: Undefined Security Weakness

API calls in the Translation API feature in Systran Pure Neural Server before 9.7.0 allow a threat actor to use the Systran Pure Neural Server as a Denial-of-Service proxy by sending a large amount of translation requests to a destination host on any given TCP port regardless of whether a web...

Deep learning: An explanation and a peek into the future

Deep learning is one of the most advanced forms of machine learning, and is showing new developments in many industries. In this article, well explain the concept and give some examples of the latest and greatest ways its being used. What is deep learning? There have been many attempts at creatin...

Google Android Pixel Neural Core component buffer overflow vulnerability (CNVD-2020-60494)

Android is a Linux-based open source operating system from Google and the Open Handset Alliance OHA in the U.S. Pixel Neural Core is one of the image processing components. A security vulnerability exists in the Pixel Neural Core component of Google Android. An attacker can exploit the...

Google Android Pixel Neural Core Component Buffer Overflow Vulnerability

Android is a Linux-based open source operating system from Google and the Open Handset Alliance OHA in the U.S. Pixel Neural Core is one of the image processing components. A security vulnerability exists in the Pixel Neural Core component of Google Android. An attacker can exploit the...

Security Unlocked—A new podcast exploring the people and AI that power Microsoft Security solutions

It’s hard to keep pace with all the changes happening in the world of cybersecurity. Security experts and leaders must continue learning and unlearning to stay ahead of the ever-evolving threat landscape. In fact, many of us are in this field because of our desire to continuously challenge...

[Podcast] How Entrepreneur Christian Wentz Takes On Identity Authentication and Data Integrity One Line of Code at a Time

!\Podcast\ How Entrepreneur Christian Wentz Takes On Identity Authentication and Data Integrity One Line of Code at a Timehttps://blog.rapid7.com/content/images/2020/09/-Podcast--How-Entrepreneur-Christian-Wentz-Takes-On-Identity-Authentication-and-Data-Integrity-One-Line-of-Code-at-a-Time-2.jpg ...

Locating malicious drone operators through deep neural networks

By Zara Khan Researchers at Ben Gurion University have developed a technique... This is a post from HackRead.com Read the original post: Locating malicious drone operators through deep neural networks...

CVE-2020-5910: Missing Authentication for Critical Function

In versions 3.0.0-3.5.0, 2.0.0-2.9.0, and 1.0.1, the Neural Autonomic Transport System NATS messaging services in use by the NGINX Controller do not require any form of authentication, so any successful connection would be authorized...

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...

Friday Squid Blogging: Squid Can Edit Their Own Genomes

This is new news: Revealing yet another super-power in the skillful squid, scientists have discovered that squid massively edit their own genetic instructions not only within the nucleus of their neurons, but also within the axon -- the long, slender neural projections that transmit electrical...

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...

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...

Tackling DGA Based Malware Detection in DNS Traffic

Earlier this year, Akamai's Enterprise team tackled the problem of DGA detection in the wild by using Neural Networks, essentially creating a state-of-the-art solution for near online detection of DGA communication...

Manipulating Machine Learning Systems by Manipulating Training Data

Interesting research: "TrojDRL: Trojan Attacks on Deep Reinforcement Learning Agents": Abstract:: Recent work has identified that classification models implemented as neural networks are vulnerable to data-poisoning and Trojan attacks at training time. In this work, we show that these training-ti...

Attention is All They Need: Combatting Social Media Information Operations With Neural Language Models

Information operations have flourished on social media in part because they can be conducted cheaply, are relatively low risk, have immediate global reach, and can exploit the type of viral amplification incentivized by platforms. Using networks of coordinated accounts, social media-driven...