I have a new follower on Twitter

Laurent Dunys 🤓
#Startup #Entrepreneur #Chatbot #NLP #Engineer | Organisateur du #Meetup #voitureconnectee à #Paris
Paris
https://t.co/xnrgnmfn5P
Following: 4492 - Followers: 4465

November 12, 2016 at 05:47AM via Twitter http://twitter.com/LDunys

Russian Court bans LinkedIn in Russia; Facebook and Twitter Could be Next

As reported late October, the world's largest online professional network LinkedIn is going to ban in Russia beginning Monday following a Moscow court decision this week that found Microsoft-owned LinkedIn to be in violation of the country's data protection laws. Here's why LinkedIn is facing ban in Russia: In July 2014, Russia approved amendments to the Russian Personal Data Law that came

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Facebook Bug Declares Millions of Users Dead, Including Zuckerberg!

Last night, Facebook declared everyone dead, including the company's CEO Mark Zuckerberg, in a massive memorial 'remembering' profile glitch. Well, that's awkward. Despite being very much alive, Facebook users, when logged on to their accounts on Friday afternoon, found their accounts turned to a "memorialized account," strongly suggesting that they are dead to everyone who visits their

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Rumor Central: Orioles pursuing free-agent OF Josh Reddick - MLB Network; 10 HR, 37 RBI in 2016 (ESPN)

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Anonymous access to owncloud server

I need to know if it is possible to access a owncloud server without an account. I want to have a owncloud server in a university intranet, so that ...

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[FD] Trango Systems hidden default root login (all models)

[+] Credits: Ian Ling [+] Website: iancaling.com [+] Source: http://ift.tt/2fk1fJH Vendor: ================= www.trangosys.com Products: ====================== All models. Newer versions use a different password. Vulnerability Type: =================== Default Root Account CVE Reference: ============== N/A Vulnerability Details: ===================== Trango devices all have a built-in, hidden root account, with a default password that is the same across many devices and software revisions. This account is accessible via ssh and grants access to the underlying embedded unix OS on the device, allowing full control over it. Recent software updates for some models have changed this password, but have not removed this backdoor. See source above for details on how the password was found. The particular password I found is 9 characters, all lowercase, no numbers: "bakergiga" Their support team informed me that there is a different password on newer devices. The password I found works on the following devices: -Apex <= 2.1.1 (latest) -ApexLynx < 2.0 -ApexOrion < 2.0 -ApexPlus <= 3.2.0 (latest) -Giga <= 2.6.1 (latest) -GigaLynx < 2.0 -GigaOrion < 2.0 -GigaPlus <= 3.2.3 (latest) -GigaPro <= 1.4.1 (latest) -StrataLink < 3.0 -StrataPro - all versions? Impact: The remote attacker has full control over the device, including shell access. This can lead to packet sniffing and tampering, bricking the device, and use in botnets. Disclosure Timeline: =================================== Vendor Notification: October 7, 2016 Public Disclosure: November 10, 2016 Exploitation Technique: ======================= Remote Severity Level: ================ Critical

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[FD] Google Chrome blink Serializer::doSerialize bad cast details

Throughout November, I plan to release details on vulnerabilities I found in web-browsers which I've not released before. This is the ninth entry in that series, and the first to not target a Microsoft browser. The below information is available in more detail on my blog at http://ift.tt/2fKbJRg. Follow me on http://twitter.com/berendjanwever for daily browser bugs. Google Chrome blink Serializer::doSerialize bad cast ==================================================== (This fix and CVE number for this issue are not known) Synopsis

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Google Pixel Phone Hacked in 60 Seconds at PwnFest 2016

The brand new Android smartphone launched by Google just a few months back has been hacked by Chinese hackers just in less than a minute. Yes, the Google's latest Pixel smartphone has been hacked by a team white-hat hackers from Qihoo 360, besides at the 2016 PwnFest hacking competition in Seoul. The Qihoo 360 team demonstrated a proof-of-concept exploit that used a zero-day vulnerability in

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5 Major Russian Banks Hit With Powerful DDoS Attacks

Distributed Denial of Service (DDoS) attacks have risen enormously in past few months and, mostly, they are coming from hacked and insecure internet-connected devices, most commonly known as Internet of Things (IoT). Recent DDoS attack against DNS provider Dyn that brought down a large chunk of the Internet came from hacked and vulnerable IoT devices such as DVRs, security cameras, and smart

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I have a new follower on Twitter

Nutanix Inc.
Nutanix delivers an enterprise cloud platform that natively converges compute, virtualization and storage into a resilient, software-defined solution.
San Jose, CA
http://t.co/dHATyUqEES
Following: 5430 - Followers: 56716

November 11, 2016 at 10:52AM via Twitter http://twitter.com/nutanix

I have a new follower on Twitter

Solvitur Systems
#Cybersecurity #InformationAssurance #Governance, #Risk & #Compliance #Information #Security #InfoSec #Cloud #HIPAA #PCIDSS #CISO #FedRAMP #Consulting Services

http://t.co/zPCCcB0zsT
Following: 5772 - Followers: 6636

November 11, 2016 at 04:52AM via Twitter http://twitter.com/Solvitursystems

Warning: Beware of Post-Election Phishing Emails Targeting NGOs and Think Tanks

Just a few hours after Donald Trump had won the 2016 US Presidential Election, a hacking group launched a wave of cyber attacks targeting U.S.-based policy think-tanks with a new spear phishing campaign designed to fool victims into installing malware. The group of nation-state hackers, also known as Cozy Bear, APT29, and CozyDuke, is the one of those involved in the recent data breach of the

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I have a new follower on Twitter

Marcos Battisti
European Growth & Venture Capitalist - Investing in tech since 98 - Unashamed Europhile - Geopolitics lover, science geek and bon vivant - Opinions are my own
London, England
https://t.co/5122Ttdbry
Following: 943 - Followers: 1239

November 11, 2016 at 01:57AM via Twitter http://twitter.com/Marcolino748

Early 2016 Winter Storm Melts Arctic Sea Ice

Arctic sea ice grows during the winter months, reaching its largest extent sometime in March. When something disrupts the cold, dry, winter Arctic atmosphere, sea ice can feel the effects, and these impacts may linger through the season. At the end of December 2015, a low pressure system formed in the north Atlantic and swept into the central Arctic, disrupting sea ice formation. As a result of this weather event, the concentration of sea ice in this region decreased by around ten percent. Sea ice extent stayed low throughout the month of January and large parts of the region remained unseasonably ice-free, which probably helped contribute to a record low Arctic sea ice maximum.

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Weekly Animation of Arctic Sea Ice Age with Two Graphs: 1984 - 2016

One significant change in the Arctic region in recent years has been the rapid decline in perennial sea ice. Perennial sea ice, also known as multi-year ice, is the portion of the sea ice that survives the summer melt season. Perennial ice may have a life-span of nine years or more and represents the thickest component of the sea ice; perennial ice can grow up to four meters thick. By contrast, first year ice that grows during a single winter is generally at most two meters thick. Below is an animation of the weekly sea ice age between 1984 and 2016. The animation shows the seasonal variability of the ice, growing in the Arctic winter and melting in the summer. In addition, this also shows the changes from year to year, depicting the age of the sea ice in different colors. Younger sea ice, or first-year ice, is shown in a dark shade of blue while the ice that is four years old or older is shown as white. A color scale identifies the age of the intermediary years. A graph in the lower, right corner the quantifies the change over time by showing the area in millions of square kilometers covered by each age category of perennial sea ice. This graph also includes a memory bar - the green line that here represents the current maximum value seen thus far in the animation for the particular week displayed. For example, when showing the first week in September, the memory bar will show the maximum value seen for all prior years' first week of September since the beginning of the animation (January 1, 1984). A graph in the lower, left corner the quantifies the change over time by showing each age category of sea ice as a percent of total ice cover in the Arctic Ocean. The lavender outline on the map indicates the spatial region covered by the Arctic Ocean and thus included in the graph.

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Ravens: Breshad Perriman registers first career TD with a 27-yard catch in the 4th quarter against the Browns (ESPN)

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[FD] Teradata Virtual Machine Community Edition v15.10 has insecure file permission

Computationally Efficient Target Classification in Multispectral Image Data with Deep Neural Networks. (arXiv:1611.03130v1 [cs.CV])

Detecting and classifying targets in video streams from surveillance cameras is a cumbersome, error-prone and expensive task. Often, the incurred costs are prohibitive for real-time monitoring. This leads to data being stored locally or transmitted to a central storage site for post-incident examination. The required communication links and archiving of the video data are still expensive and this setup excludes preemptive actions to respond to imminent threats. An effective way to overcome these limitations is to build a smart camera that transmits alerts when relevant video sequences are detected. Deep neural networks (DNNs) have come to outperform humans in visual classifications tasks. The concept of DNNs and Convolutional Networks (ConvNets) can easily be extended to make use of higher-dimensional input data such as multispectral data. We explore this opportunity in terms of achievable accuracy and required computational effort. To analyze the precision of DNNs for scene labeling in an urban surveillance scenario we have created a dataset with 8 classes obtained in a field experiment. We combine an RGB camera with a 25-channel VIS-NIR snapshot sensor to assess the potential of multispectral image data for target classification. We evaluate several new DNNs, showing that the spectral information fused together with the RGB frames can be used to improve the accuracy of the system or to achieve similar accuracy with a 3x smaller computation effort. We achieve a very high per-pixel accuracy of 99.1%. Even for scarcely occurring, but particularly interesting classes, such as cars, 75% of the pixels are labeled correctly with errors occurring only around the border of the objects. This high accuracy was obtained with a training set of only 30 labeled images, paving the way for fast adaptation to various application scenarios.

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Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence. (arXiv:1611.03218v1 [cs.AI])

Learning your first language is an incredible feat and not easily duplicated. Doing this using nothing but a few pictureless books, a corpus, would likely be impossible even for humans. As an alternative we propose to use situated interactions between agents as a driving force for communication, and the framework of Deep Recurrent Q-Networks (DRQN) for learning a common language grounded in the provided environment. We task the agents with interactive image search in the form of the game Guess Who?. The images from the game provide a non trivial environment for the agents to discuss and a natural grounding for the concepts they decide to encode in their communication. Our experiments show that it is possible to learn this task using DRQN and even more importantly that the words the agents use correspond to physical attributes present in the images that make up the agents environment.

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A stochastically verifiable autonomous control architecture with reasoning. (arXiv:1611.03372v1 [cs.RO])

A new agent architecture called Limited Instruction Set Agent (LISA) is introduced for autonomous control. The new architecture is based on previous implementations of AgentSpeak and it is structurally simpler than its predecessors with the aim of facilitating design-time and run-time verification methods. The process of abstracting the LISA system to two different types of discrete probabilistic models (DTMC and MDP) is investigated and illustrated. The LISA system provides a tool for complete modelling of the agent and the environment for probabilistic verification. The agent program can be automatically compiled into a DTMC or a MDP model for verification with Prism. The automatically generated Prism model can be used for both design-time and run-time verification. The run-time verification is investigated and illustrated in the LISA system as an internal modelling mechanism for prediction of future outcomes.

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XCSP3: An Integrated Format for Benchmarking Combinatorial Constrained Problems. (arXiv:1611.03398v1 [cs.AI])

We propose a major revision of the format XCSP 2.1, called XCSP3, to build integrated representations of combinatorial constrained problems. This new format is able to deal with mono/multi optimization, many types of variables, cost functions, reification, views, annotations, variable quantification, distributed, probabilistic and qualitative reasoning. The new format is made compact, highly readable, and rather easy to parse. Interestingly, it captures the structure of the problem models, through the possibilities of declaring arrays of variables, and identifying syntactic and semantic groups of constraints. The number of constraints is kept under control by introducing a limited set of basic constraint forms, and producing almost automatically some of their variations through lifting, restriction, sliding, logical combination and relaxation mechanisms. As a result, XCSP3 encompasses practically all constraints that can be found in major constraint solvers developed by the CP community. A website, which is developed conjointly with the format, contains many models and series of instances. The user can make sophisticated queries for selecting instances from very precise criteria. The objective of XCSP3 is to ease the effort required to test and compare different algorithms by providing a common test-bed of combinatorial constrained instances.

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Importance Sampling with Unequal Support. (arXiv:1611.03451v1 [cs.LG])

Importance sampling is often used in machine learning when training and testing data come from different distributions. In this paper we propose a new variant of importance sampling that can reduce the variance of importance sampling-based estimates by orders of magnitude when the supports of the training and testing distributions differ. After motivating and presenting our new importance sampling estimator, we provide a detailed theoretical analysis that characterizes both its bias and variance relative to the ordinary importance sampling estimator (in various settings, which include cases where ordinary importance sampling is biased, while our new estimator is not, and vice versa). We conclude with an example of how our new importance sampling estimator can be used to improve estimates of how well a new treatment policy for diabetes will work for an individual, using only data from when the individual used a previous treatment policy.

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Song From PI: A Musically Plausible Network for Pop Music Generation. (arXiv:1611.03477v1 [cs.AI])

We present a novel framework for generating pop music. Our model is a hierarchical Recurrent Neural Network, where the layers and the structure of the hierarchy encode our prior knowledge about how pop music is composed. In particular, the bottom layers generate the melody, while the higher levels produce the drums and chords. We conduct several human studies that show strong preference of our generated music over that produced by the recent method by Google. We additionally show two applications of our framework: neural dancing and karaoke, as well as neural story singing.

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A fast PC algorithm for high dimensional causal discovery with multi-core PCs. (arXiv:1502.02454v3 [cs.AI] UPDATED)

Discovering causal relationships from observational data is a crucial problem and it has applications in many research areas. The PC algorithm is the state-of-the-art constraint based method for causal discovery. However, runtime of the PC algorithm, in the worst-case, is exponential to the number of nodes (variables), and thus it is inefficient when being applied to high dimensional data, e.g. gene expression datasets. On another note, the advancement of computer hardware in the last decade has resulted in the widespread availability of multi-core personal computers. There is a significant motivation for designing a parallelised PC algorithm that is suitable for personal computers and does not require end users' parallel computing knowledge beyond their competency in using the PC algorithm. In this paper, we develop parallel-PC, a fast and memory efficient PC algorithm using the parallel computing technique. We apply our method to a range of synthetic and real-world high dimensional datasets. Experimental results on a dataset from the DREAM 5 challenge show that the original PC algorithm could not produce any results after running more than 24 hours; meanwhile, our parallel-PC algorithm managed to finish within around 12 hours with a 4-core CPU computer, and less than 6 hours with a 8-core CPU computer. Furthermore, we integrate parallel-PC into a causal inference method for inferring miRNA-mRNA regulatory relationships. The experimental results show that parallel-PC helps improve both the efficiency and accuracy of the causal inference algorithm.

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Learning Natural Language Inference with LSTM. (arXiv:1512.08849v2 [cs.CL] UPDATED)

Natural language inference (NLI) is a fundamentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Inference (SNLI) corpus has made it possible to develop and evaluate learning-centered methods such as deep neural networks for natural language inference (NLI). In this paper, we propose a special long short-term memory (LSTM) architecture for NLI. Our model builds on top of a recently proposed neural attention model for NLI but is based on a significantly different idea. Instead of deriving sentence embeddings for the premise and the hypothesis to be used for classification, our solution uses a match-LSTM to perform word-by-word matching of the hypothesis with the premise. This LSTM is able to place more emphasis on important word-level matching results. In particular, we observe that this LSTM remembers important mismatches that are critical for predicting the contradiction or the neutral relationship label. On the SNLI corpus, our model achieves an accuracy of 86.1%, outperforming the state of the art.

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Ravens: 5-time Pro Bowl G Marshal Yanda (shoulder) among inactives against the Browns (ESPN)

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Imagination Library Clears Waiting List With Anonymous Donation

The anonymous donor will help bring their total number to over 750 kids who receive a free book every month from birth to age five. Sawatzky notes it ...

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I have a new follower on Twitter

MSFT in Business
The official Twitter page for Microsoft in Business: designed exclusively for business leaders to discover thought leadership content and trends in technology.
Redmond, Washington
https://t.co/8FD8lQw2wV
Following: 97471 - Followers: 198796

November 10, 2016 at 05:14PM via Twitter http://twitter.com/MSFT_Business

I have a new follower on Twitter

Vidao App Android
Start chatting, calling, and sharing for free with all your friends on Vidao Messenger.

https://t.co/FuEMtnOjbU
Following: 1000 - Followers: 707

November 10, 2016 at 03:05PM via Twitter http://twitter.com/VidaoAppBetaBD

[FD] Weak validation of Amazon SNS push messages in W3 Total Cache WordPress Plugin

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[FD] Persistent Cross-Site Scripting in WP Google Maps Plugin via CSRF

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OpenSSL Releases Patch For "High" Severity Vulnerability

As announced on Tuesday, the OpenSSL project team released OpenSSL version 1.1.0c that addresses three security vulnerabilities in its software. The most serious of all is a heap-based buffer overflow bug (CVE-2016-7054) related to Transport Layer Security (TLS) connections using *-CHACHA20-POLY1305 cipher suites. The vulnerability, reported by Robert Święcki of the Google Security Team on

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Facebook Buys Leaked Passwords From Black Market, But Do You Know Why?

Facebook is reportedly buying stolen passwords that hackers are selling on the underground black market in an effort to keep its users' accounts safe. On the one hand, we just came know that Yahoo did not inform its users of the recently disclosed major 2014 hacking incident that exposed half a billion user accounts even after being aware of the hack in 2014. On the other hand, Facebook

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encoding/json: Doesn't Unmarshal anonymous field with custom unmarshaler

encoding/json: Doesn't Unmarshal anonymous field with custom unmarshaler #17877. Open. epelc opened this Issue 14 minutes ago · 0 comments ...

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[FD] [CT-2016-1110] Unauthenticated RCE in Observium network monitor

############# Computest security advisory CT-2016-1110 ############### Summary: Unauthenticated remote command execution as root Affected software: Observium Reference URL: https://computest.nl/advisories/ CT-2016-1110_Observium.txt Affected versions: Versions downloaded before 26-10-2016. (First affected version is not known) Credit: Ronald Volgers (rvolgers@computest.nl) Date of publication: 2016-11-10 During a recent penetration test Computest found and exploited various issues in Observium, going from unauthenticated user to full shell access as root. We reported these issues to the Observium project for the benefit of our customer and other members of the community. This was not a full audit and further issues may or may not be present. ( Note about affected versions: The Observium project does not provide a way to download older releases for non-paying users, so there was no way to check whether these problems exist in older versions. All information given here applies to the latest Community Edition as of 2016-10-05. ) About Observium

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[FD] e107 CMS <= 2.1.2 Privilege Escalation

# Exploit Title: e107 CMS 2.1.2 Privilege Escalation # Date: 09-11-2016 # Software Link: http://e107.org/ # Exploit Author: Kacper Szurek # Contact: http://twitter.com/KacperSzurek # Website: http://security.szurek.pl/ # Category: webapps 1. Description Datas from `$_POST['updated_data']` inside `usersettings.php` are not properly validated so we can set `user_admin`. http://security.szurek.pl/e107-cms-211-privilege-escalation.html 2. Proof of Concept

[FD] CA20161109-01: Security Notice for CA Unified Infrastructure Management

-----BEGIN PGP SIGNED MESSAGE-

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[FD] CA20161109-02: Security Notice for CA Service Desk Manager

-----BEGIN PGP SIGNED MESSAGE-

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[FD] Vlany: A Linux (LD_PRELOAD) rootkit

Features: Process hiding User hiding Network hiding LXC container Anti-Debug Anti-Forensics Persistent (re)installation & Anti-Detection Dynamic linker modifications Backdoors accept() backdoor (derived from Jynx2) PAM backdoor PAM auth logger vlany-exclusive commands Download: https://github.com/mempodippy/vlany

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Re: [FD] WININET CHttpHeaderParser::ParseStatusLine out-of-bounds read details

Some additional information: It was pointed out to me that I did not adequately explain that WININET is widely used by Microsoft applications to handle HTTP requests, *AND* probably be all third-party applications that use Windows APIs to make HTTP requests. All these applications may be vulnerable to the issue, though it may be hard to exploit in most (if not all). According to Microsoft this issue affected MSIE and Edge and was fixed through MS16-104 (MSIE) and MS16-105 (Edge). Unfortunately, the below email failed to mention MS16-104. I do not know why Microsoft did not mention other applications in their bulletins, nor why they have two fixes for specific applications (their browsers), rather than one fix for a component of the Windows Operating System. One wonders what would happen on a system where you have previously uninstalled both MSIE and Edge: do neither of the fixes apply and will your system be left vulnerable? Let me know if you found out! Cheers, SkyLined On 10-11-2016 10:49, Berend-Jan Wever wrote: > Throughout November, I plan to release details on vulnerabilities I > found in web-browsers which I've not released before. This is the > eight entry in that series, although this particular vulnerability does > not just affect web-browsers, but all applications that use WININET to > make HTTP requests. > > The below information is available in more detail on my blog at > http://blog.skylined.nl/20161110001.html. There you can find a repro > that triggered this issue in addition to the information below. > > Follow me on http://twitter.com/berendjanwever for daily browser bugs. > > WININET CHttpHeaderParser::ParseStatusLine out-of-bounds read > ============================================================= > (MS16-105, CVE-2016-3325) > > Synopsis >

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[FD] WININET CHttpHeaderParser::ParseStatusLine out-of-bounds read details

Throughout November, I plan to release details on vulnerabilities I found in web-browsers which I've not released before. This is the eight entry in that series, although this particular vulnerability does not just affect web-browsers, but all applications that use WININET to make HTTP requests. The below information is available in more detail on my blog at http://blog.skylined.nl/20161110001.html. There you can find a repro that triggered this issue in addition to the information below. Follow me on http://twitter.com/berendjanwever for daily browser bugs. WININET CHttpHeaderParser::ParseStatusLine out-of-bounds read ============================================================= (MS16-105, CVE-2016-3325) Synopsis

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[FD] MSIE 9-11 MSHTML PROPERTYDESC::HandleStyleComponentProperty OOB read details

Throughout November, I plan to release details on vulnerabilities I found in web-browsers which I've not released before. This is the seventh entry in that series. The below information is available in more detail on my blog at http://blog.skylined.nl/20161109001.html. There you can find a repro that triggered this issue in addition to the information below. Follow me on http://twitter.com/berendjanwever for daily browser bugs. MSIE 9-11 MSHTML PROPERTYDESC::HandleStyleComponentProperty OOB read ==================================================================== (MS16-104, CVE-2016-3324) Synopsis

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ISS Daily Summary Report – 11/09/2016

Oxygen Generation System (OGS) Maintenance:  Overnight the decision was made not to perform the Recirc loop flush.  Earlier this morning the crew installed the new Oxygen Generation Assembly (OGA) Hydrogen Orbital Replacement Unit (ORU) into the OGS rack. However, the crew was not able to fully mate the Hydrogen ORU Quick Disconnect (QD), same as the issue yesterday regarding the QD mate issue for the Recirc loop flush.  The crew reported that the QD was at 90% connected or ¼ turn from fully mated in both cases. Ground teams recommended that Kapton tape be applied to the QD in order to prevent backout. In this configuration it is expected that the primary seal on the QD should be engaged and the QD poppet opened. Ground teams are working to vent the Hydrogen ORU dome and activate the OGA, which will take several hours. Meteor Hard Drive Swap: The crew performed a regular changeout of the Meteor hard drive located in the Window Observational Research Facility (WORF).  The Meteor payload is a visible spectroscopy instrument with the primary purpose of observing meteors in Earth orbit. Meteor uses image analysis to provide information on the physical and chemical properties of the meteoroid dust, such as size, density, and chemical composition. Since the parent comets or asteroids for most of the meteor showers are identified, the study of the meteoroid dust on orbit provides information about the parent comets and asteroids. Sally Ride EarthKAM Lens Changeout: The crew changed out and configured the 180mm lens and 72mm Bumper Ring on the Sally Ride EarthKAM, removing and stowing the 50mm lens and 52mm Bumper ring. The EarthKAM team, in association with middle school students around the world, select image targets which are then downlinked and used in the study of physics, computers, geography, math, earth science, biology, art, history, and cultural studies.  The objective of Sally Ride EarthKam is to integrate Earth images with inquiry-based learning to enhance curricula in support of national and state education standards; to provide students and educators the opportunity to participate in a space mission and to develop teamwork, communication, and problem solving skills; to engage teams of students, educators, and researchers in collaborative investigations using remotely-sensed data; and to incorporate the active use of Web-based tools and resources in support of the learning process. Zbook Server Deployment:  The crew set up two ZBook laptops as SSC Server-1 and SSC Server-2 in preparation for loading and transition.  Thursday the new ZBook laptops will be loaded with the new SSC Server software.  The transition to the new SSC Servers is currently planned for Friday. International Docking Adapter (IDA) Survey: Over the next two days the robotics team will perform dynamic surveys that simulate the view of an incoming docking vehicle as it approaches the recently installed IDA at Pressurized Mating Adapter 2 (PMA-2). These surveys will use the Special Purpose Dexterous Manipulator (SPDM) Camera Light Pan Tilt Assembly (CLPA) and pre-configured automatic trajectories to simulate vehicle motion. They will be performed in various lighting conditions. Today’s Planned Activities All activities were completed unless otherwise noted. Oxygen Generation System (OGS) Hydrogen ORU Remove and Replace Removal of Potable Water Container (КПВ) hoses, audit of СРВ-К2М hoses Progress 433 (DC1) Transfers and IMS Ops Verification of ИП-1 Flow Sensor Position Saving personal data on RSK1, 2 prior to installation of new SW version DAN. Experiment Tagup with specialists Meteor Hard Drive Swapout Oxygen Generation System (OGS) Final Quick Disconnect (QD) Mates Station Support Computer Server Hardware Setup Installation of Picasa application on station RSK1 laptop (SW version 4.2). Filling (separation) of ЕДВ (КОВ) for Elektron or ЕДВ-СВ СОЖ maintenance Installation of Picasa application on station RSK2 laptop EarthKAM. Camera Lens Change Preparation steps for finding the cause of current overload in FGB ПШО31 exchange bus via SM-FGB Docking Assembly -X Video Recording of Greetings Replacement of Filters in FGB Dust Collectors 1, 2 IMS Update Dose Tracker Data Entry Subject CONTENT. Experiment Ops Completed Task List Items None Ground Activities All activities were completed unless otherwise noted. IDA Survey Using SSRMS Three-Day Look Ahead: Thursday, 11/10: FSL, OGA Tool Stow, Cygnus Cargo Ops Friday, 11/11:  GCM Troubleshooting, PFS PuFF Calibration Syringe Maintenance Saturday, 11/12: Weekly Housekeeping QUICK ISS Status – Environmental Control Group:                               Component Status Elektron On Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) On [СКВ] 2 – SM Air Conditioner System (“SKV2”) Off Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Operate Major Constituent Analyzer (MCA) Node 3 Idle Oxygen Generation Assembly (OGA) Venting H2 Dome Urine Processing Assembly (UPA) Reprocess Trace Contaminant Control System (TCCS) Lab Off Trace Contaminant Control System (TCCS) Node 3 Full Up  

from ISS On-Orbit Status Report https://blogs.nasa.gov/stationreport/2016/11/09/iss-daily-summary-report-11092016/
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Ravens: WR Mike Wallace's redemption tour extends beyond just rebounding from career-worst 2015 season - Jamison Hensley (ESPN)

from ESPN http://espn.go.com/nfl/team/_/name/bal/baltimore-ravens?ex_cid=espnapi_affiliate_IFTTT
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Anonymous user 954036

Name, Anonymous user 954036. User since, May 3, 2016. Number of add-ons developed, 1 theme. Average rating of developer's add-ons, Not yet ...

from Google Alert - anonymous https://www.google.com/url?rct=j&sa=t&url=https://addons.mozilla.org/en-US/thunderbird/user/anonymous-95403676dfbf2c9a5a271f575fce3304/&ct=ga&cd=CAIyGjgxMzAxNTQ0ZWE3M2NhMmQ6Y29tOmVuOlVT&usg=AFQjCNHlAdHDpznXNa5EOHBunvCsrawV6Q
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SWIFT Hack: Bangladesh Bank Recovers $15 Million from a Philippines Casino

Part of the $81 Million stolen from Bangladesh bank's New York Federal Reserve account earlier this year in the wake of the major malware attack on the SWIFT interbank transfer network has been tracked down to a casino in the Philippines. SWIFT, or Society for Worldwide Interbank Telecommunication, is a global financial messaging system that thousands of banks and organizations around the

from The Hacker News http://thehackernews.com/2016/11/bangladesh-swift-hack-casino_9.html
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I have a new follower on Twitter

Environmental Info
Environmental news. Environmental events. Environmental jobs. Environmental education. LinkedIn http://t.co/zonCZ4Uy6I
Australia
http://t.co/EoICNFBIk2
Following: 7934 - Followers: 9377

November 10, 2016 at 01:57AM via Twitter http://twitter.com/ejn_greencareer

Icesat-2 Measurements Over Antarctica (prelaunch)

The ATLAS lidar on ICESat-2 uses 6 laser beams to measure the earth's elevation and elevation change. As a global mission, ICESat-2 will collect data over the entire globe, however the ATLAS instrument is optimized to measure land ice and sea ice elevation in the polar regions. ICESat-2 reports elevations with respect to a reference surface, called an ellipsoid. In this measurement system, shared by GPS devices, an elevation of zero meters indicates the notional sea level, although tides, wind, and waves can make the actual sea level either greater than or less than zero. The Antarctic ice sheet, shown here, ranges up to 4000m above sea level. Over the course of 91 days, ATLAS will generate 1387 ground tracks across Antarctica for each of it's 6 beams.

from NASA's Scientific Visualization Studio: Most Recent Items http://svs.gsfc.nasa.gov/cgi-bin/details.cgi?aid=4492
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Correlation Between GLOBE CItizen Science and NASA Satellite Observations

Between October 1 and October 22, NASA asked museums and science centers around the world to participate in a global experiment collecting observations of clouds while NASA satellites were overhead. As part of the part of International Science Center and Science Museum Day (ISCSMD), the experiment built upon UNESCO's theme of "Science for Peace and Development." The goal was to create new ways for museums and science centers worldwide to proactively address global sustainability while reaching increasingly diverse audiences. More than 900 cloud observations, including more than 5,500 photos, came in. The white dots on this map show each observation submitted through the app in that period. The red dots represent science centers participating in the global experiment. The observations are distributed internationally. Several of the observations lined up with satellite overpasses, and this video shows three examples (from September 2016) from the early afternoon overpasses of Aqua, CALIPSO, and CloudSat, NASA satellites that fly together in formation as part of the A-train constellation of satellites. By taking ground-based cloud observations at the same time, citizen scientists are helping NASA scientists interpret the satellite data. Through the GLOBE Observer app, a person can report what kind of clouds are in the atmosphere, estimate how high the clouds are, and indicate how much of the sky is cloudy. Satellites can do some of the same things, but see clouds from above. By combining both citizen and satellite observations, scientists get a much more complete understanding of what is happening in the atmosphere. This will help address questions about changes in the water cycle and freshwater availability. The first satellite example (starting at about 35 seconds) shows an overpass over North America on September 7. Dots represent citizen science observations taken at or near the same time as the overpass. Blue dots represent a report of clear skies, while white dots are cloudy skies. Partially blue dots are partially cloudy skies. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on NASA's Aqua satellite provides a natural color view of clouds over a broad swath of the continent. This view shows the clouds as a person might see them from space. Tiny clouds are scattered across the southern United States corresponding to areas where citizen scientists reported clear skies. The vertical band shows CALIPSO data from the ground to 30 kilometers into the atmosphere. CALIPSO carries a lidar instrument that uses a laser to measure the vertical structure of thin clouds and aerosols (particles in the atmosphere like pollution, smoke, dust, sea salt, and so forth). Thin clouds and aerosols are difficult to see with other satellites and from the ground. The laser bounces off these features, making it possible to detect them. The scattered yellow band indicates that there were thin clouds and/or aerosols in the atmosphere, even though citizen scientists reported clear skies. By looking at three different satellites along with citizen science observations, scientists can learn about the structure of cloud systems and better understand what the satellites are measuring. Why do clouds matter so much? Clouds are a key mechanism in distributing fresh water around the planet. In a changing climate, scientists are uncertain how clouds might change, and as a result, how access to fresh water might change.

from NASA's Scientific Visualization Studio: Most Recent Items http://svs.gsfc.nasa.gov/cgi-bin/details.cgi?aid=4524
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M63: The Sunflower Galaxy from Hubble

One of the bright spiral galaxies visible in the north sky is M63, the Sunflower Galaxy. M63, also catalogued as NGC 5055, can be found with a small telescope toward the constellation of Hunting Dogs (Canes Venatici). The featured picture from the Hubble Space Telescope exhibits the center of M63, complete with long winding spiral arms glowing blue from a few bright young stars, emission nebulae glowing red from hot ionized hydrogen gas, and dark dust in numerous filaments. M63 interacts gravitationally with M51 (the Whirlpool Galaxy) and several smaller galaxies. Light takes about 35 million years to reach us from M63, and about 60,000 years to cross the spiral galaxy. Stars in the outer regions of the Sunflower Galaxy rotate about the center at a speed so high that, given the matter seen and assuming normal gravity, they should fly off into space. The fact that the stars remain indicates the presence of sort of invisible, gravitationally-binding, dark matter. via NASA http://antwrp.gsfc.nasa.gov/apod/ap161109.html

I have a new follower on Twitter

David Corrigan
I help orgs become truly #customercentric w new tech #CustomerIntelligenceManagement. #CMO @Infotrellis. Disrupting the #customerdata market w @AllSightBigData
Toronto, Canada
https://t.co/nOKsyx0JrD
Following: 4378 - Followers: 4709

November 09, 2016 at 11:12PM via Twitter http://twitter.com/DCorrigan

The New Cyber Bully: Apps Allow Anonymous Threats

After School is an anonymous app, so the student who posted the threat was not immediately identified. Several students reported the threatening post ...

from Google Alert - anonymous https://www.google.com/url?rct=j&sa=t&url=http://www.centerdigitaled.com/k-12/The-New-Cyber-Bully-Apps-Allow-Anonymous-Threats.html&ct=ga&cd=CAIyGjgxMzAxNTQ0ZWE3M2NhMmQ6Y29tOmVuOlVT&usg=AFQjCNESjMtw0GGQaDPf2W0k8jT8gjeJyA
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I have a new follower on Twitter

Intersog®
We build custom software solutions & provide on-demand IT resources for in-house & offshore software development projects. Email us: contact@intersog.com
Chicago, IL, USA
http://t.co/mDSENJutKt
Following: 2845 - Followers: 4044

November 09, 2016 at 10:52PM via Twitter http://twitter.com/Intersog

Recursive Decomposition for Nonconvex Optimization. (arXiv:1611.02755v1 [cs.AI])

Continuous optimization is an important problem in many areas of AI, including vision, robotics, probabilistic inference, and machine learning. Unfortunately, most real-world optimization problems are nonconvex, causing standard convex techniques to find only local optima, even with extensions like random restarts and simulated annealing. We observe that, in many cases, the local modes of the objective function have combinatorial structure, and thus ideas from combinatorial optimization can be brought to bear. Based on this, we propose a problem-decomposition approach to nonconvex optimization. Similarly to DPLL-style SAT solvers and recursive conditioning in probabilistic inference, our algorithm, RDIS, recursively sets variables so as to simplify and decompose the objective function into approximately independent sub-functions, until the remaining functions are simple enough to be optimized by standard techniques like gradient descent. The variables to set are chosen by graph partitioning, ensuring decomposition whenever possible. We show analytically that RDIS can solve a broad class of nonconvex optimization problems exponentially faster than gradient descent with random restarts. Experimentally, RDIS outperforms standard techniques on problems like structure from motion and protein folding.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02755
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RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning. (arXiv:1611.02779v1 [cs.AI])

Deep reinforcement learning (deep RL) has been successful in learning sophisticated behaviors automatically; however, the learning process requires a huge number of trials. In contrast, animals can learn new tasks in just a few trials, benefiting from their prior knowledge about the world. This paper seeks to bridge this gap. Rather than designing a "fast" reinforcement learning algorithm, we propose to represent it as a recurrent neural network (RNN) and learn it from data. In our proposed method, RL$^2$, the algorithm is encoded in the weights of the RNN, which are learned slowly through a general-purpose ("slow") RL algorithm. The RNN receives all information a typical RL algorithm would receive, including observations, actions, rewards, and termination flags; and it retains its state across episodes in a given Markov Decision Process (MDP). The activations of the RNN store the state of the "fast" RL algorithm on the current (previously unseen) MDP. We evaluate RL$^2$ experimentally on both small-scale and large-scale problems. On the small-scale side, we train it to solve randomly generated multi-arm bandit problems and finite MDPs. After RL$^2$ is trained, its performance on new MDPs is close to human-designed algorithms with optimality guarantees. On the large-scale side, we test RL$^2$ on a vision-based navigation task and show that it scales up to high-dimensional problems.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02779
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Tuning Recurrent Neural Networks with Reinforcement Learning. (arXiv:1611.02796v1 [cs.LG])

Sequence models can be trained using supervised learning and a next-step prediction objective. This approach, however, suffers from known failure modes. For example, it is notoriously difficult to ensure multi-step generated sequences have coherent global structure. Motivated by the fact that reinforcement learning (RL) can be used to impose arbitrary properties on generated data by choosing appropriate reward functions, in this paper we propose a novel approach for sequence training which combines Maximum Likelihood (ML) and RL training. We refine a sequence predictor by optimizing for some imposed reward functions, while maintaining good predictive properties learned from data. We propose efficient ways to solve this by augmenting deep Q-learning with a cross-entropy reward and deriving novel off-policy methods for RNNs from stochastic optimal control (SOC). We explore the usefulness of our approach in the context of music generation. An LSTM is trained on a large corpus of songs to predict the next note in a musical sequence. This Note-RNN is then refined using RL, where the reward function is a combination of rewards based on rules of music theory, as well as the output of another trained Note-RNN. We show that by combining ML and RL, this RL Tuner method can not only produce more pleasing melodies, but that it can significantly reduce unwanted behaviors and failure modes of the RNN.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02796
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Encoding monotonic multi-set preferences using CI-nets: preliminary report. (arXiv:1611.02885v1 [cs.AI])

CP-nets and their variants constitute one of the main AI approaches for specifying and reasoning about preferences. CI-nets, in particular, are a CP-inspired formalism for representing ordinal preferences over sets of goods, which are typically required to be monotonic.

Considering also that goods often come in multi-sets rather than sets, a natural question is whether CI-nets can be used more or less directly to encode preferences over multi-sets. We here provide some initial ideas on how to achieve this, in the sense that at least a restricted form of reasoning on our framework, which we call "confined reasoning", can be efficiently reduced to reasoning on CI-nets. Our framework nevertheless allows for encoding preferences over multi-sets with unbounded multiplicities. We also show the extent to which it can be used to represent preferences where multiplicites of the goods are not stated explicitly ("purely qualitative preferences") as well as a potential use of our generalization of CI-nets as a component of a recent system for evidence aggregation.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02885
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Harnessing disordered quantum dynamics for machine learning. (arXiv:1602.08159v2 [quant-ph] UPDATED)

Quantum computer has an amazing potential of fast information processing. However, realisation of a digital quantum computer is still a challenging problem requiring highly accurate controls and key application strategies. Here we propose a novel platform, quantum reservoir computing, to solve these issues successfully by exploiting natural quantum dynamics, which is ubiquitous in laboratories nowadays, for machine learning. In this framework, nonlinear dynamics including classical chaos can be universally emulated in quantum systems. A number of numerical experiments show that quantum systems consisting of at most seven qubits possess computational capabilities comparable to conventional recurrent neural networks of 500 nodes. This discovery opens up a new paradigm for information processing with artificial intelligence powered by quantum physics.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1602.08159
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MCMC assisted by Belief Propagaion. (arXiv:1605.09042v4 [stat.ML] UPDATED)

Markov Chain Monte Carlo (MCMC) and Belief Propagation (BP) are the most popular algorithms for computational inference in Graphical Models (GM). In principle, MCMC is an exact probabilistic method which, however, often suffers from exponentially slow mixing. In contrast, BP is a deterministic method, which is typically fast, empirically very successful, however in general lacking control of accuracy over loopy graphs. In this paper, we introduce MCMC algorithms correcting the approximation error of BP, i.e., we provide a way to compensate for BP errors via a consecutive BP-aware MCMC. Our framework is based on the Loop Calculus (LC) approach which allows to express the BP error as a sum of weighted generalized loops. Although the full series is computationally intractable, it is known that a truncated series, summing up all 2-regular loops, is computable in polynomial-time for planar pair-wise binary GMs and it also provides a highly accurate approximation empirically. Motivated by this, we first propose a polynomial-time approximation MCMC scheme for the truncated series of general (non-planar) pair-wise binary models. Our main idea here is to use the Worm algorithm, known to provide fast mixing in other (related) problems, and then design an appropriate rejection scheme to sample 2-regular loops. Furthermore, we also design an efficient rejection-free MCMC scheme for approximating the full series. The main novelty underlying our design is in utilizing the concept of cycle basis, which provides an efficient decomposition of the generalized loops. In essence, the proposed MCMC schemes run on transformed GM built upon the non-trivial BP solution, and our experiments show that this synthesis of BP and MCMC outperforms both direct MCMC and bare BP schemes.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1605.09042
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I have a new follower on Twitter

Daniel Peter
Salesforce MVP. Bay Area Salesforce Developer User Group Organizer. https://t.co/PEIpb72j3O MacGyver, 20x certifed, biz/IT, Ham Radio K6DJP, work at @kenandy
Foster City, CA
https://t.co/Tn8Fg4JzEX
Following: 14372 - Followers: 16265

November 09, 2016 at 08:37PM via Twitter http://twitter.com/danieljpeter

and '!' for JavaScript self-calling anonymous function modular pattern?

Participate in discussions with other Treehouse members and learn.

from Google Alert - anonymous https://www.google.com/url?rct=j&sa=t&url=https://teamtreehouse.com/community/is-there-a-difference-between-and-for-javascript-selfcalling-anonymous-function-modular-pattern&ct=ga&cd=CAIyGjgxMzAxNTQ0ZWE3M2NhMmQ6Y29tOmVuOlVT&usg=AFQjCNHLqlsndfrgxhRlMT657WEWXFipzA
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Thank you for your service

A Florida fire station got a welcoming gift last week when an anonymous donor paid for their groceries when some firefighters left them behind to ...

from Google Alert - anonymous https://www.google.com/url?rct=j&sa=t&url=http://www.powerathens.com/news/national/thank-you-for-your-service-anonymous-person-buys-fire-stateion-groceries/3N9UhDT1WSxgJoh0x6b7zO/&ct=ga&cd=CAIyGjgxMzAxNTQ0ZWE3M2NhMmQ6Y29tOmVuOlVT&usg=AFQjCNHSh0WE8kaNDPkPY66dB3mR1d5aHg
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Anonymous

Anonymous. World Finance - World Class Loan and Tax Service. Home Office. (864) 298-9800. 108 Frederick Street Greenville, SC 29607. National ...

from Google Alert - anonymous https://www.google.com/url?rct=j&sa=t&url=https://www.worldacceptance.com/testimonial/anonymous/&ct=ga&cd=CAIyGjgxMzAxNTQ0ZWE3M2NhMmQ6Y29tOmVuOlVT&usg=AFQjCNFEe3c_1hSY_wj7PG8flbDER9zp-g
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Microsoft Patches Windows Zero-Day Flaw Disclosed by Google

Microsoft was very upset with Google last week when its Threat Analysis Group publically disclosed a critical Windows kernel vulnerability (CVE-2016-7255) that had yet to be patched. The company criticized Google's move, claiming that the disclosure of the vulnerability, which was being exploited in the wild, put its customers "at potential risk." <!-- adsense --> The vulnerability affects

from The Hacker News http://thehackernews.com/2016/11/microsoft-windows-update.html
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[FD] Avira Antivirus >= 15.0.21.86 Command Execution (SYSTEM)

# Title : Avira Antivirus >= 15.0.21.86 Command Execution (SYSTEM) # Date : 08/11/2016 # Author : R-73eN # Tested on: Avira Antivirus 15.0.21.86 in Windows 7 # Vendor : https://www.avira.com/ # Disclosure Timeline: # 2016-06-28 - Reported to Vendor through Bugcrowd. # 2016-06-29 - Vendor Replied. # 2016-07-05 - Vendor Replicated the vulnerability. # 2016-09-02 - Vendor released updated version which fix the vulnerability. # 2016-11-08 - Public Disclosure # I would like to thank Avira security team for the quick response. # # Vulnerability Description: # When the Avira Launcher manual update imports a zip file doesn't checks for " ../ " # characters which makes it possible to do a path traversal and write anywhere in the system. # Vulnerability Replication # 1. Create a special crafted zip file with the python script attached. # 2. The script will create a zip file named xvdf_fusebundle.zip with a filename test.bat (this can be changed) and will write this file to the root directory C:\ # 3. You can change the directory go to startup and when the user reboots the script will get executed or you can write a malicious dll to a program directory or # system32 directory which will get loaded and we gain remote command execution. # 4. Open avira free antivirus # 5. Go to update -> Manual Update # 6. Select the malicious file # 7. Directory traversal was sucessfull # Youtube Video: https://www.youtube.com/watch?v=IIEgWiDcw2Q

Source: Gmail -> IFTTT-> Blogger

ISS Daily Summary Report – 11/08/2016

Veg-03 Operations: The crew checked and photo documented the status of the plants in the Veggie facility, and evaluated the plant pillows to determine if additional watering is required.  The overall goal of Veg-03 is to further demonstrate proof-of concept for the Veggie plant growth chamber and the planting pillows using ‘Outredgeous’ Red Romaine lettuce.  Future long-duration missions into the solar system, will require a fresh food supply to supplement crew diets, which means growing crops in space. Previous investigations focused on improving productivity in controlled environments, but the limited quarters of the space shuttle and ISS made it difficult to conduct large-scale crop production tests. Veg-03 expands on previous validation tests of the new Veggie hardware, which crew members will soon use to grow cabbage, lettuce and other fresh vegetables in space. Tests determine which types of microorganisms are present in space-grown cabbage, providing baseline data for future crop-growing efforts.  Behavioral health surveys assess the impact of growing plants on crew morale and mood. Oxygen Generation System (OGS) Maintenance: The OGS Inlet Deionizing (DI) Bed was removed and replaced successfully this morning.  The crew also began a series of activities to purge the Oxygen Generation Assembly (OGA) recirculation loop. This is designed to help flush Total Organic Carbons (TOC) and other potential contaminants from the recirculation loop prior to installing the new Hydrogen Orbital Replacement Unit (ORU), which is scheduled for tomorrow. The crew had issues mating a Quick Disconnect (QD) in the chain of hoses and was not able to flush all of the water from the system. Ground teams are currently assessing options for completing the flush. Additional time will be added to tomorrow’s plan to implement troubleshooting steps ahead of the scheduled replacement of the OGS Hydrogen ORU. Orbital ATK (OA)-5 Cargo Operations:  The crew performed one hour of Cygnus cargo transfer operations today.  As of the last report the crew had completed 18 hours of cargo transfer with an estimated 8 hours remaining. Today’s Planned Activities All activities were completed unless otherwise noted. Oxygen Generation System (OGS) Deionization (DI) Bed R&R SM Ventilation Subsystem Preventive Maintenance. Group C Photography of windows No. 2, 13, 14 in SM, EV1, EV2 Hatch windows in MRM2 Oxygen Generation System (OGS) Flush OTKLIK. Sensor functional test and point of impact accuracy check. Measuring CO partial pressure at Central Post using CSA-CP analyzer Replacement of СО2 Gas Analyzer ИК 0501 Filters. Transfer Cygnus Cargo Operations Flushing Water Supply System [СВО] Elektron-VM Gas-Liquid Mixture (ГЖС) Imagery of Flushing Water Supply System [СВО] Elektron-VM Gas-Liquid Mixture (ГЖС) Imagery Downlink of Water Supply System [СВО] Elektron-VM Gas-Liquid Mixture (ГЖС) Flushing via OCA Progress 433 (DC1) Transfers and IMS Ops Cygnus Cargo Operations Conference Audit of Personal Hygiene Articles (СЛГ). Consolidation of Personal Hygiene Article for Priority Use Health Maintenance System (HMS) Automated External Defibrillator (AED) Inspection Manufacturing Device Bed Re-install VEG-03 Plant Photo Oxygen Generation System (OGS) Flush Teardown CONTENT. Experiment Ops 49 Soyuz Wireless Station Support Computer (SSC) Connect Completed Task List Items None Ground Activities All activities were completed unless otherwise noted. Battery 4B3 reconditioning OGS Flush Three-Day Look Ahead: Wednesday, 11/09: OGA Flush and H2 Dome R&R Thursday, 11/10: FSL, OGA Tool Stow, Cygnus Cargo Ops Friday, 11/11:  GCM Troubleshooting, PFS PuFF Calibration Syringe Maintenance  QUICK ISS Status – Environmental Control Group:                               Component Status Elektron On Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) On [СКВ] 2 – SM Air Conditioner System (“SKV2”) Off Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Operate Major Constituent Analyzer (MCA) Node 3 Idle Oxygen Generation Assembly (OGA) Shutdown Urine Processing Assembly (UPA) Reprocess Trace Contaminant Control System (TCCS) Lab Off Trace Contaminant Control System (TCCS) Node 3 Full Up  

from ISS On-Orbit Status Report https://blogs.nasa.gov/stationreport/2016/11/08/iss-daily-summary-report-11082016/
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Ocean City, MD's surf is Good

November 08, 2016 at 07:00PM, the surf is Good!

Ocean City, MD Summary


Surf: shoulder to head high
Maximum: 1.53m (5.02ft)
Minimum: 1.224m (4.02ft)

Maryland-Delaware Summary


from Surfline http://www.surfline.com/surfdata/spot_forecast.cfm?id=4406
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DDoS Attack Takes Down Central Heating System Amidst Winter In Finland

Just Imaging — What if, you enter into your home from a chilling weather outside, and the heating system fails to work because of a cyber attack, leaving you in the sense of panic? The same happened late last month when an attack knocks heating system offline in Finland. Last week, a Distributed Denial of Service (DDoS) attack led to the disruption of the heating systems for at least two

from The Hacker News http://thehackernews.com/2016/11/heating-system-hacked.html
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Over 300,000 Android Devices Hacked Using Chrome Browser Vulnerability

A vulnerability in Chrome for Android is actively being exploited in the wild that allows hackers to quietly download banking trojan apps (.apk) onto victim's’ device without their confirmation. You might have encountered a pop-up advertisement that appears out of nowhere and surprise you that your mobile device has been infected with a dangerous virus and instructs you to install a security

from The Hacker News http://thehackernews.com/2016/11/chrome-android-virus.html
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Normalizing Flows on Riemannian Manifolds. (arXiv:1611.02304v1 [stat.ML])

We consider the problem of density estimation on Riemannian manifolds. Density estimation on manifolds has many applications in fluid-mechanics, optics and plasma physics and it appears often when dealing with angular variables (such as used in protein folding, robot limbs, gene-expression) and in general directional statistics. In spite of the multitude of algorithms available for density estimation in the Euclidean spaces $\mathbf{R}^n$ that scale to large n (e.g. normalizing flows, kernel methods and variational approximations), most of these methods are not immediately suitable for density estimation in more general Riemannian manifolds. We revisit techniques related to homeomorphisms from differential geometry for projecting densities to sub-manifolds and use it to generalize the idea of normalizing flows to more general Riemannian manifolds. The resulting algorithm is scalable, simple to implement and suitable for use with automatic differentiation. We demonstrate concrete examples of this method on the n-sphere $\mathbf{S}^n$.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02304
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Learning from Untrusted Data. (arXiv:1611.02315v1 [cs.LG])

The vast majority of theoretical results in machine learning and statistics assume that the available training data is a reasonably reliable reflection of the phenomena to be learned or estimated. Similarly, the majority of machine learning and statistical techniques used in practice are brittle to the presence of large amounts of biased or malicious data. In this work we propose two novel frameworks in which to study estimation, learning, and optimization in the presence of significant fractions of arbitrary data. The first framework, which we term list-decodable learning, asks whether it is possible to return a list of answers, with the guarantee that at least one of them is accurate. For example, given a dataset of $n$ points for which an unknown subset of $\alpha n$ points are drawn from a distribution of interest, and no assumptions are made about the remaining $(1-\alpha)n$ points, is it possible to return a list of $poly(1/\alpha)$ answers, one of which is correct? The second framework, which we term the semi-verified learning model considers the extent to which a small dataset of trusted data (drawn from the distribution in question) can be leveraged to enable the accurate extraction of information from a much larger but untrusted dataset (of which only an $\alpha$-fraction is drawn from the distribution).

We show strong positive results in both settings, and provide an algorithm for robust learning in a very general stochastic optimization setting. This general result has immediate implications for robust estimation in a number of settings, including for robustly estimating the mean of distributions with bounded second moments, robustly learning mixtures of such distributions, and robustly finding planted partitions in random graphs in which significant portions of the graph have been perturbed by an adversary.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02315
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Combining observational and experimental data to find heterogeneous treatment effects. (arXiv:1611.02385v1 [cs.AI])

Every design choice will have different effects on different units. However traditional A/B tests are often underpowered to identify these heterogeneous effects. This is especially true when the set of unit-level attributes is high-dimensional and our priors are weak about which particular covariates are important. However, there are often observational data sets available that are orders of magnitude larger. We propose a method to combine these two data sources to estimate heterogeneous treatment effects. First, we use observational time series data to estimate a mapping from covariates to unit-level effects. These estimates are likely biased but under some conditions the bias preserves unit-level relative rank orderings. If these conditions hold, we only need sufficient experimental data to identify a monotonic, one-dimensional transformation from observationally predicted treatment effects to real treatment effects. This reduces power demands greatly and makes the detection of heterogeneous effects much easier. As an application, we show how our method can be used to improve Facebook page recommendations.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02385
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Proceedings of the First International Workshop on Argumentation in Logic Programming and Non-Monotonic Reasoning (Arg-LPNMR 2016). (arXiv:1611.02439v1 [cs.AI])

This volume contains the papers presented at Arg-LPNMR 2016: First International Workshop on Argumentation in Logic Programming and Nonmonotonic Reasoning held on July 8-10, 2016 in New York City, NY.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02439
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The Data Complexity of Description Logic Ontologies. (arXiv:1611.02453v1 [cs.AI])

We analyze the data complexity of ontology-mediated querying where the ontologies are formulated in a description logic (DL) of the ALC family and queries are conjunctive queries, positive existential queries, or acyclic conjunctive queries. Our approach is non-uniform in the sense that we aim to understand the complexity of each single ontology instead of for all ontologies formulated in a certain language. While doing so, we quantify over the queries and are interested, for example, in the question whether all queries can be evaluated in polynomial time w.r.t. a given ontology. Our results include a PTime/coNP-dichotomy for ontologies of depth one in the description logic ALCFI, the equivalence of a PTime/coNP-dichotomy for ALC and ALCI-ontologies of unrestricted depth to the famous dichotomy conjecture for CSPs by Feder and Vardi, and the failure of PTime/coNP-dichotomy theorem for ALCF-ontologies. Regarding the latter DL, we also show that it is undecidable whether a given ontology admits PTime query evaluation.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02453
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Cognitive Discriminative Mappings for Rapid Learning. (arXiv:1611.02512v1 [cs.AI])

Humans can learn concepts or recognize items from just a handful of examples, while machines require many more samples to perform the same task. In this paper, we build a computational model to investigate the possibility of this kind of rapid learning. The proposed method aims to improve the learning task of input from sensory memory by leveraging the information retrieved from long-term memory. We present a simple and intuitive technique called cognitive discriminative mappings (CDM) to explore the cognitive problem. First, CDM separates and clusters the data instances retrieved from long-term memory into distinct classes with a discrimination method in working memory when a sensory input triggers the algorithm. CDM then maps each sensory data instance to be as close as possible to the median point of the data group with the same class. The experimental results demonstrate that the CDM approach is effective for learning the discriminative features of supervised classifications with few training sensory input instances.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02512
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The Neural Noisy Channel. (arXiv:1611.02554v1 [cs.CL])

We formulate sequence to sequence transduction as a noisy channel decoding problem and use recurrent neural networks to parameterise the source and channel models. Unlike direct models which can suffer from explaining-away effects during training, noisy channel models must produce outputs that explain their inputs, and their component models can be trained with not only paired training samples but also unpaired samples from the marginal output distribution. Using a latent variable to control how much of the conditioning sequence the channel model needs to read in order to generate a subsequent symbol, we obtain a tractable and effective beam search decoder. Experimental results on abstractive sentence summarisation, morphological inflection, and machine translation show that noisy channel models outperform direct models, and that they significantly benefit from increased amounts of unpaired output data that direct models cannot easily use.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02554
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On interestingness measures of formal concepts. (arXiv:1611.02646v1 [cs.AI])

Formal concepts and closed itemsets proved to be of big importance for knowledge discovery, both as a tool for concise representation of association rules and a tool for clustering and constructing domain taxonomies and ontologies. Exponential explosion makes it difficult to consider the whole concept lattice arising from data, one needs to select most useful and interesting concepts. In this paper interestingness measures of concepts are considered and compared with respect to various aspects, such as efficiency of computation and applicability to noisy data and performing ranking correlation.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02646
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Sentence Ordering using Recurrent Neural Networks. (arXiv:1611.02654v1 [cs.CL])

Modeling the structure of coherent texts is a task of great importance in NLP. The task of organizing a given set of sentences into a coherent order has been commonly used to build and evaluate models that understand such structure. In this work we propose an end-to-end neural approach based on the recently proposed set to sequence mapping framework to address the sentence ordering problem. Our model achieves state-of-the-art performance in the order discrimination task on two datasets widely used in the literature. We also consider a new interesting task of ordering abstracts from conference papers and research proposals and demonstrate strong performance against recent methods. Visualizing the sentence representations learned by the model shows that the model has captured high level logical structure in these paragraphs. The model also learns rich semantic sentence representations by learning to order texts, performing comparably to recent unsupervised representation learning methods in the sentence similarity and paraphrase detection tasks.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1611.02654
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Truth Serums for Massively Crowdsourced Evaluation Tasks. (arXiv:1507.07045v3 [cs.GT] UPDATED)

A major challenge in crowdsourcing evaluation tasks like labeling objects, grading assignments in online courses, etc., is that of eliciting truthful responses from agents in the absence of verifiability. In this paper, we propose new reward mechanisms for such settings that, unlike many previously studied mechanisms, impose minimal assumptions on the structure and knowledge of the underlying generating model, can account for heterogeneity in the agents' abilities, require no extraneous elicitation from them, and furthermore allow their beliefs to be (almost) arbitrary. These mechanisms have the simple and intuitive structure of an output agreement mechanism: an agent gets a reward if her evaluation matches that of her peer, but unlike the classic output agreement mechanism, this reward is not the same across evaluations, but is inversely proportional to an appropriately defined popularity index of each evaluation. The popularity indices are computed by leveraging the existence of a large number of similar tasks, which is a typical characteristic of these settings. Experiments performed on MTurk workers demonstrate higher efficacy (with a $p$-value of $0.02$) of these mechanisms in inducing truthful behavior compared to the state of the art.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1507.07045
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Moving Target Defense for Web Applications using Bayesian Stackelberg Games. (arXiv:1602.07024v2 [cs.CR] UPDATED)

The present complexity in designing web applications makes software security a difficult goal to achieve. Moreover, an attacker can explore a deployed service on the web and attack at his/her own leisure. Although Moving Target Defense (MTD) in web applications is an effective mechanism to nullify this advantage of their reconnaissance, the framework demands a good switching strategy when switching between multiple configurations for its web-stack. To address this issue, we propose modeling of a real-world MTD web application as a repeated Bayesian game to generate an effective switching strategy. To incorporate this model into a real system, we propose an automated system for generating attack sets of Common Vulnerabilities and Exposures (CVEs) for input attacker types with predefined capabilities. Our framework obtains realistic reward values for the players (defenders and attackers) in this game by using security domain expertise on CVEs obtained from the National Vulnerability Database (NVD). Also, with our model, we address the issue of prioritizing vulnerabilities that when fixed, improves the security of the MTD system. Lastly, we demonstrate the robustness of our proposed model by evaluating its performance when there is uncertainty about input attacker information.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1602.07024
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Unifying Count-Based Exploration and Intrinsic Motivation. (arXiv:1606.01868v2 [cs.AI] UPDATED)

We consider an agent's uncertainty about its environment and the problem of generalizing this uncertainty across observations. Specifically, we focus on the problem of exploration in non-tabular reinforcement learning. Drawing inspiration from the intrinsic motivation literature, we use density models to measure uncertainty, and propose a novel algorithm for deriving a pseudo-count from an arbitrary density model. This technique enables us to generalize count-based exploration algorithms to the non-tabular case. We apply our ideas to Atari 2600 games, providing sensible pseudo-counts from raw pixels. We transform these pseudo-counts into intrinsic rewards and obtain significantly improved exploration in a number of hard games, including the infamously difficult Montezuma's Revenge.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1606.01868
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Safe and Efficient Off-Policy Reinforcement Learning. (arXiv:1606.02647v2 [cs.LG] UPDATED)

In this work, we take a fresh look at some old and new algorithms for off-policy, return-based reinforcement learning. Expressing these in a common form, we derive a novel algorithm, Retrace($\lambda$), with three desired properties: (1) it has low variance; (2) it safely uses samples collected from any behaviour policy, whatever its degree of "off-policyness"; and (3) it is efficient as it makes the best use of samples collected from near on-policy behaviour policies. We analyze the contractive nature of the related operator under both off-policy policy evaluation and control settings and derive online sample-based algorithms. We believe this is the first return-based off-policy control algorithm converging a.s. to $Q^*$ without the GLIE assumption (Greedy in the Limit with Infinite Exploration). As a corollary, we prove the convergence of Watkins' Q($\lambda$), which was an open problem since 1989. We illustrate the benefits of Retrace($\lambda$) on a standard suite of Atari 2600 games.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1606.02647
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A Fuzzy Logic System to Analyze a Student's Lifestyle. (arXiv:1610.03957v2 [cs.CY] UPDATED)

A college student's life can be primarily categorized into domains such as education, health, social and other activities which may include daily chores and travelling time. Time management is crucial for every student. A self realisation of one's daily time expenditure in various domains is therefore essential to maximize one's effective output. This paper presents how a mobile application using Fuzzy Logic and Global Positioning System (GPS) analyzes a student's lifestyle and provides recommendations and suggestions based on the results.

from cs.AI updates on arXiv.org http://arxiv.org/abs/1610.03957
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Quasi-Recurrent Neural Networks. (arXiv:1611.01576v1 [cs.NE])

Recurrent neural networks are a powerful tool for modeling sequential data, but the dependence of each timestep's computation on the previous timestep's output limits parallelism and makes RNNs unwieldy for very long sequences. We introduce quasi-recurrent neural networks (QRNNs), an approach to neural sequence modeling that alternates convolutional layers, which apply in parallel across timesteps, and a minimalist recurrent pooling function that applies in parallel across channels. Despite lacking trainable recurrent layers, stacked QRNNs have better predictive accuracy than stacked LSTMs of the same hidden size. Due to their increased parallelism, they are up to 16 times faster at train and test time. Experiments on language modeling, sentiment classification, and character-level neural machine translation demonstrate these advantages and underline the viability of QRNNs as a basic building block for a variety of sequence tasks.

from cs.AI updates on arXiv.org http://ift.tt/2fzc0ot
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A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks. (arXiv:1611.01587v1 [cs.CL])

Transfer and multi-task learning have traditionally focused on either a single source-target pair or very few, similar tasks. Ideally, the linguistic levels of morphology, syntax and semantics would benefit each other by being trained in a single model. We introduce such a joint many-task model together with a strategy for successively growing its depth to solve increasingly complex tasks. All layers include shortcut connections to both word representations and lower-level task predictions. We use a simple regularization term to allow for optimizing all model weights to improve one task's loss without exhibiting catastrophic interference of the other tasks. Our single end-to-end trainable model obtains state-of-the-art results on chunking, dependency parsing, semantic relatedness and textual entailment. It also performs competitively on POS tagging. Our dependency parsing layer relies only on a single feed-forward pass and does not require a beam search.

from cs.AI updates on arXiv.org http://ift.tt/2fVB5xW
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Dynamic Coattention Networks For Question Answering. (arXiv:1611.01604v1 [cs.CL])

Several deep learning models have been proposed for question answering. However, due to their single-pass nature, they have no way to recover from local maxima corresponding to incorrect answers. To address this problem, we introduce the Dynamic Coattention Network (DCN) for question answering. The DCN first fuses co-dependent representations of the question and the document in order to focus on relevant parts of both. Then a dynamic pointing decoder iterates over potential answer spans. This iterative procedure enables the model to recover from initial local maxima corresponding to incorrect answers. On the Stanford question answering dataset, a single DCN model improves the previous state of the art from 71.0% F1 to 75.9%, while a DCN ensemble obtains 80.4% F1.

from cs.AI updates on arXiv.org http://ift.tt/2exT6xr
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Anonymous unblock proxy sites

Go Anonymous Unblock Videos Unblock Websites Web Proxy. By using this . ProxFree is a free and powerful anonymous proxy site directly in your ...

from Google Alert - anonymous https://www.google.com/url?rct=j&sa=t&url=http://jm.cmnamarillo.org/Izb&ct=ga&cd=CAIyGjgxMzAxNTQ0ZWE3M2NhMmQ6Y29tOmVuOlVT&usg=AFQjCNHN1rSU69zkAnviM_KK7t-PFGQTDg
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I have a new follower on Twitter

Codeanywhere
A complete toolset for web development. Enabling you to edit, collaborate and run your projects from any device. Check out our Developer Conference @shiftsplit
San Francisco, CA
https://t.co/i6fjwA54ct
Following: 38220 - Followers: 45875

November 08, 2016 at 04:28PM via Twitter http://twitter.com/Codeanywhere

Ravens get midseason grade of C-plus - Jamison Hensley; who to watch, what to expect in 2nd half and give your own grade (ESPN)

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[FD] Stored Cross-Site Scripting vulnerability in 404 to 301 WordPress Plugin

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ISS Daily Summary Report – 11/07/2016

Sally Ride Earth Knowledge Acquired by Middle Schools (EarthKAM): The crew configured the camera, laptop and associated Sally Ride EarthKAM software at the Node 2 Nadir hatch window. Once configured, the EarthKAM team, in association with middle school students around the world, selected image targets which will be downlinked and used in the study of physics, computers, geography, math, earth science, biology, art, history, and cultural studies. The objective of Sally Ride EarthKAM is to integrate Earth images with inquiry-based learning to enhance curricula in support of national and state education standards; to provide students and educators the opportunity to participate in a space mission and to develop teamwork, communication, and problem solving skills; to engage teams of students, educators, and researchers in collaborative investigations using remotely-sensed data; and to incorporate the active use of Web-based tools and resources in support of the learning process. Culture, Values, and Environmental Adaptation in Space (At Home in Space): The crew answered the first of two At Home in Space questionnaires, the second to be scheduled at roughly Return-30 days (R-30).  The Canadian Space Agency (CSA) experiment, At Home in Space, assesses culture, values, and psychosocial adaptation of astronauts to a space environment shared by multinational crews on long-duration missions. It is hypothesized that astronauts develop a shared space culture that is an adaptive strategy for handling cultural differences and they deal with the isolated confined environment of the space craft by creating a home in space. At Home In Space uses a questionnaire battery to investigate individual and culturally related differences, family functioning, values, coping with stress, and post-experience growth. Radi-N2: The Russian crew collected the Radi-N2 detectors from their locations in the Russian Segment and handed them over to the US crew who deployed the eight detectors in the US Lab, then took photographs of their locations.  The detectors will remain in the Lab location for one week. Radi-N2 Neutron Field Study (Radi-N2) is a follow on investigation designed to characterize the neutron radiation environment aboard the International Space Station (ISS). Eight neutron “bubble detectors” produced by the Canadian company Bubble Technology Industries are attached to fixed locations inside the ISS, including one carried by a crew member. The objective of this investigation is to better characterize the ISS neutron environment and define the risk posed to the crew members’ health and provide the data necessary to develop advanced protective measures for future spaceflight. Oxygen Generation System (OGS) Maintenance:  The OGS Hydrogen On-Orbit Replaceable Unit (ORU) has an ailing electrolysis cell that no longer makes it desirable to run. Today the prepared for the significant maintenance scheduled on OGS later this week. Today’s task included a procedure review followed by a conference with ground specialist and the H2 sensor replacement. The work to recover the OGS will include replacing the Deionizing Bed ORU (planned to be performed on Tuesday) and Hydrogen ORU (planned to be performed on Wednesday), as well as a flush of the OGS Recirculation Loop to clear out the build-up of chemical species which have accumulated over years of operation that are potentially harmful to OGS.  Orbital ATK (OA)-5 Cargo Operations:  As of the last report the crew had completed 16 hours of cargo transfer with an estimated 10 hours remaining. Today’s Planned Activities All activities were completed unless otherwise noted. ECLSS Recycle Tank Drain Initiation Total Organic Carbon Analyzer (TOCA) Water Recovery System (WRS) Sample Analysis VIBROLAB. Hardware status check Vacuuming [ГЖТ4]’s [ВТ-7] screen behind FGB panel 108 Nikon camera matrix pollution check Regenerative ECLSS Recycle Tank Drain Termination Advanced Resistive Exercise Device (ARED) Cylinder Flywheel Evacuation Onboard clock and 6 ROS still camera clocks date and time sync FGB’s [ГЖТ 1, 2, 3] removable screen cleaning Auxiliary Computer System [ВКС] Laptop Computer System Virus Definition File Update Exercise Data Downlink via OCA [БД-2] control panel software update. Specialist conference Treadmill 2 System (T2) Monthly Inspection At Home In Space Questionnaire Total Organic Carbon Analyzer (TOCA) Sample Data Record Total Organic Carbon Analyzer (TOCA) Waste Water Bag (WWB) Changeout Regenerative ECLSS Oxygen Regeneration System (OGS) O2 3 Way QD Demate VIBROLAB. Copy & downlink Pre-Soyuz docking Ku-Band MPEG-2 TV test. Regenerative ECLSSOxygen Regeneration System (OGS) Hydrogen Sensor R&R Soyuz 433 (DC1) unstow w/IMS updates MATRYOSHKA-R. BUBBLE dosimeter setup and activation. Specialist conference when required Oxygen Generation System (OGS) Big Picture Words Review Oxygen Generation Assembly-H2 Orbital Replacement Unit Remove and Replace – Conference Radiation Dosimetry Inside ISS-Neutrons Hardware Handover MATRYOSHKA-R. Hand over BUBBLE dosimeters to ROS Radiation Dosimetry Inside ISS-Neutrons MATRYOSHKA-R. BUBBLE dosimeter initialization and deployment; specialist conference when required FSL MPCC1 USB Stick move from MPCC Laptop to SSC11 Laptop Crew Medical Officer (CMO) Proficiency Training EarthKAM Node 2 Setup and Activation-Russian СОЖ maintenance Connects and powers on the TREK Laptop. ISS HAM Service Module Pass  Completed Task List Items Oxygen Generation System Equipment Gather USB Adapter Transfer Glacier 1 Desiccant Pack Swap Glacier 4 Desiccant Pack Swap Build 2 spare ЕДВ’s for future use in Waste and Hygiene Compartment (WHC) ISA Labeling ARED SSC Swap Ground Activities All activities were completed unless otherwise noted. Battery 4B3 reconditioning Three-Day Look Ahead: Wednesday, 11/09: OGA H2 Dome R&R Thursday, 11/10: FSL, OGA Tool Stow, Cygnus Cargo Ops Friday, 11/11: MSPR Combustion Chamber Leak Check, USOS Crew Off Duty QUICK ISS Status – Environmental Control Group:                               Component Status Elektron On Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) Off [СКВ] 2 – SM Air Conditioner System (“SKV2”) Off Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Operate Major Constituent Analyzer (MCA) Node 3 Idle Oxygen Generation Assembly (OGA) Shutdown Urine Processing Assembly (UPA) Reprocess Trace Contaminant Control System (TCCS) Lab Off Trace Contaminant Control System (TCCS) Node 3 Full Up  

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[FD] Cross-Site Scripting in Calendar WordPress Plugin

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I have a new follower on Twitter

Oforth


http://t.co/hTKXLsUvyc
Following: 24 - Followers: 42

November 08, 2016 at 04:46AM via Twitter http://twitter.com/OforthSupport

[FD] Cross Site Scripting Vulnerability In Verint Impact 360

Overview ======== * Title : Cross Site Scripting Vulnerability In Verint Impact 360 * Author: Sanehdeep Singh * Plugin Homepage: http://www.verint.com * Severity: Medium * Version Affected: 11.1 * Version patched: Patches available. Contact Vendor Description =========== About the Product ================= Verint Impact 360 is a quality monitoring/call recording, workforce management, performance management, and eLearning help optimize business operations, customer relationships,and personnel enterprise-wide application. Vulnerable Parameter

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[FD] Crashing Android devices with large Proxy Auto Config (PAC) Files [CVE-2016-6723]

[Original at: http://ift.tt/2fzruJ9] Summary Android devices can be crashed forcing a halt and then a soft reboot by downloading a large proxy auto config (PAC) file when adjusting the Android networking settings. This can also be exploited by an MITM attacker that can intercept and replace the PAC file. However, the bug is mitigated by multiple factors and the likelihood of exploitation is low. This issue has been fixed in the November 2016 Android security bulletin. Background – Proxy Auto Config (PAC) Files Proxy Auto Config (PAC) files are text files that can be used as part of the network settings configuration to allow a web browser and other software that accesses the web. These files define which proxy servers should be used for which types of requests. They usually contain a Javascript function which can be called by the web browser to determine the type of proxy server to use. An example PAC file appears here: function FindProxyForURL(url, host) { if (isResolvable(host)) return "DIRECT"; else return "PROXY proxy.mydomain.com:8080"; } } A related standard called Web Proxy Auto-Discovery Protocol (WPAD) allows devices to find the locations of PAC files via DHCP and/or DNS. However, WPAD is not currently supported on Android. Vulnerability Details When configuring a network in Android, one of the options available in the “Advanced” section is ability to indicate a Proxy Auto Config (PAC) URL which will point to a PAC file described above. The current code in Android does not check whether the PAC file may be too large to load into memory, which allows an MITM attacker to replace a known PAC file (if served without SSL) with a large one of their own and crash the Android phone. The vulnerability is that the Java code does not check how large the data file actually is. If a file is served that is larger than the memory available on the device, this results in all memory being exhausted and the phone halting and then soft rebooting. The soft reboot was sufficient to recover from the crash and no data was lost. While we have not been able to achieve remote code execution, this code path can potentially be exploited for such attacks and would require more research. The vulnerable code resides here – (PacManager.java, lines 120-127): private static String get(Uri pacUri) throws IOException { URL url = new URL(pacUri.toString()); URLConnection urlConnection = url.openConnection(java.net.Proxy.NO_PROXY); return new String(Streams.readFully(urlConnection.getInputStream())); } Specifically, the affected code is using Streams.readFully to read the entire file into memory without any kind of checks on how big the file actually is. Because this attack require a user to configure a PAC file, and an attacker to be present and know about that file, and the file needs to be served without SSL to make the attack work, the possibility of an attacker pulling this off is low. This is also true because Android, unlike other operating systems does not support the WPAD protocol to retrieve PAC files automatically which can be exploited using a rouge access point or network. Steps To Replicate (on Ubuntu 16.04) 1. Install NGINX: sudo apt-get install nginx 2. Use fallocate to create a large PAC file in “/var/www/html/” sudo fallocate -s 2.5G test.pac 3. Go in to advanced network settings on the Android device and add the following URL as the PAC URL: http://ift.tt/2fzsVqR Save the settings which will trigger the bug. Once the phone starts downloading the files, the screen will go black and it will reboot. Mitigation Steps Users should apply the November 2016 Android bulletin. Bounty Information This bug has fulfilled the requirements for Google’s Android Security Rewards and a bounty has been paid. References Android security bulletin: November 2016 http://ift.tt/2fsPbE4 CVE-ID: CVE-2016-6723 http://ift.tt/2fzqzsd Google: Android bug # 215709 / AndroidID-30100884 http://ift.tt/2eHhboF Netscape PAC file format definition: here (via the Internet Archive) http://ift.tt/2eHgAmI WPAD Internet Draft: here http://ift.tt/2anU7sC WPAD not supported on Android: see bug report here http://ift.tt/1B0gIOI Credits Bug discovered by, and advisory written by Yakov Shafranovich. Timeline 2016-07-11: Android bug report filed with Google 2016-07-19: Android bug confirmed as high 2016-08-18: Bug priority downgraded to moderate 2016-09-15: Coordination with Google on public disclosure 2016-11-07: Android security bulletin released with fix 2016-11-07: Public disclosure

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Authenticate with Firebase Anonymously using Unity

You can use Firebase Authentication to create and use temporary anonymous accounts to authenticate with Firebase. These temporary anonymous ...

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Facebook agrees to Stop using UK Users' WhatsApp Data for Targeted Ads

In August, Facebook introduced a hugely controversial data sharing plan to start harvesting data from its WhatsApp messaging app from September 25 for delivering more relevant ads on the social network. Many users were not happy with the move, because there was no real way of opting out from the data sharing – WhatsApp users could only do so within a short period – and even if users did opt

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'Web Of Trust' Browser Add-On Caught Selling Users' Data — Uninstall It Now

Browser extensions have become a standard part of the most popular browsers and essential part of our lives for surfing the Internet. But not all extensions can be trusted. One such innocent looking browser add-on has been caught collecting browsing history of millions of users and selling them to third-parties for making money. <!-- adsense --> An investigation by German television channel

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Inverted City Beneath Clouds

How could that city be upside-down? The city, Chicago, was actually perfectly right-side up. The long shadows it projected onto nearby Lake Michigan near sunset, however, when seen in reflection, made the buildings appear inverted. This fascinating, puzzling, yet beautiful image was captured by a photographer in 2014 on an airplane on approach to Chicago's O'Hare International Airport. The Sun can be seen both above and below the cloud deck, with the latter reflected in the calm lake. As a bonus, if you look really closely -- and this is quite a challenge -- you can find another airplane in the image, likely also on approach to the same airport. via NASA http://ift.tt/2frZ98z