Of the most recent mega 100Gbps attacks in the last quarter, most of them were directly attributed to the Mirai botnet. The Mirai botnet works by exploiting the weak security on many Internet of Things (IoT) devices. The program finds its victims by constantly scanning the internet for IoT devices, which use factory default or hard-coded usernames and passwords.
Unless you’ve been living under a rock, you heard that some researchers managed to create a SHA-1 collision. The short story as to why this matters is the whole purpose of a hashing algorithm is to make it impossible to generate collisions on purpose. Unfortunately though impossible things are usually also impossible so in reality we just make sure it’s really really hard to generate a collision. Thanks to Moore’s Law, hard things don’t stay hard forever. This is why MD5 had to go live on a farm out in the country, and we’re not allowed to see it anymore … because it’s having too much fun. SHA-1 will get to join it soon.
Happy SHA1 collision day everybody!
If you extract the differences between the good.pdf and bad.pdf attached to the paper, you'll find it all comes down to a small ~128 byte chunk of random-looking binary data that varies between the files.
Android users and apps have become a major part of payments and financial services, carrying an increased risk for web crime.
It is estimated that there are 107.7 million Android Smartphone users in the U.S. who have downloaded more than 65 million apps from the Google App Store, and each one of them represents a smorgasbord of opportunity for hackers to steal user credentials and other information.
Red Hat Product Security has published details of an "important" security vulnerability in the Linux kernel. The IPv6 implementation of the DCCP protocol means that it is possible for a local, unprivileged user to alter kernel memory and escalate their privileges.
Known as the "use-after-free" flaw, CVE-2017-6074 affects a number of Red Hat products including Red Hat Enterprise Linux 6, Red Hat Enterprise Linux 7 and Red Hat Openshift Online v2. Mitigating factors include the requirement for a potential attacker to have access to a local account on a machine, and for IPV6 to be enabled, but it is still something that will be of concern to Linux users.
Describing the vulnerability, Red Hat says: "This flaw allows an attacker with an account on the local system to potentially elevate privileges. This class of flaw is commonly referred to as UAF (Use After Free.) Flaws of this nature are generally exploited by exercising a code path that accesses memory via a pointer that no longer references an in use allocation due to an earlier free() operation. In this specific issue, the flaw exists in the DCCP networking code and can be reached by a malicious actor with sufficient access to initiate a DCCP network connection on any local interface. Successful exploitation may result in crashing of the host kernel, potential execution of code in the context of the host kernel or other escalation of privilege by modifying kernel memory structures."
The man behind the Android operating system is apparently building a new company to take on Apple with, and it seems his dream team just added a new member.
Jason Mackenzie, HTC's former global executive vice president, said in a Tweet that he's joined Rubin's "stealth startup." It comes around two months after Mackenzie ended his 12-year tenure at HTC.
Surprisingly, the MXNet Machine Learning project was this month accepted by the Apache Software Foundation as an open-source project.
What's surprising about the announcement isn't so much that the ASF is accepting this face in the crowd to its ranks – it's hard to turn around in the software world these days without tripping over ML tools – but rather that MXNet developers, most of whom are from Amazon, believe ASF is relevant.
During the past decade, enterprises have begun using machine learning (ML) to collect and analyze large amounts of data to obtain a competitive advantage. Now some are looking to go even deeper – using a subset of machine learning techniques called deep learning (DL), they are seeking to delve into the more esoteric properties hidden in the data. The goal is to create predictive applications for such areas as fraud detection, demand forecasting, click prediction, and other data-intensive analyses.
Machine learning has become a buzzword. A branch of Artificial Intelligence, it adds marketing sparkle to everything from intrusion detection tools to business analytics. What is it, exactly, and how can you code it?
Dropbox has released the code for the chatbot it uses to question employees about interactions with corporate systems, in the hope that it can help other organizations automate security processes and improve employee awareness of security concerns.
"One of the hardest, most time-consuming parts of security monitoring is manually reaching out to employees to confirm their actions," said Alex Bertsch, formerly a Dropbox intern and now a teaching assistant at Brown University, in a blog post. "Despite already spending a significant amount of time on reach-outs, there were still alerts that we didn't have time to follow up on."