Anonymous

See the latest Anonymous jobs on CV-Library. Browse Full and Part Time roles from Anonymous, upload your CV and apply in minutes - CV-Library.

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I have a new follower on Twitter

Grufy Ana
Launch Strategy: a case study in How to get 10000 Twitter Followers a week. see here https://t.co/MtxYM9ffOS


Following: 1479 - Followers: 74

February 17, 2018 at 03:14PM via Twitter http://twitter.com/ebuwucatacaq

Learn Ethical Hacking Online — 9 Courses At Lowest Price Ever

How to become a Professional Hacker? This is one of the most frequently asked queries we came across on a daily basis. Do you also want to learn real-world hacking techniques but don’t know where to start? This week's THN deal is for you. Today THN Deal Store has announced a new Super-Sized Ethical Hacking Bundle that let you get started your career in hacking and penetration testing

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Anonymous

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Toast POS Review: Server by Anonymous Reviewer

What are the best aspects of this product? Keeps us organized and works the kinks out all on its own. What aspects are problematic or could work better? The learning curve is problematic for some and the fact that there is not enough practice time before it goes live. What specific problems in your ...

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Anonymous Threats Put Schools On Edge After Mass Shooting

The mass shooting at Marjory Stoneman Douglas High School in Parkland has caused increased awareness and tension at schools across South Florida.

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Reference Anonymous Data

I've made a drop down ("Dropdown1") which I have populated with an explicit list. Like this: DATA Items: ["Tempe","San.

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GOP director takes sole responsibility for anonymous website

AUGUSTA, Maine (AP) - The Maine Republican Party's executive director says he alone was responsible for running an anonymous website that published articles Democrats say slandered their unsuccessful local candidate. The state ethics commission's staff on Friday said GOP Executive Director ...

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The Fringe: Emotions Anonymous

Guest: Peter Guess, Initiator - Emotions Anonymous Host: Sara-Jayne King, Late Nights Topic: The Fringe: Emotions Anonymous You may be familiar with the saying 'no man (or woman) is an island'- well its true even when it comes to emotions. But where can we go and talk freely about how we are ...

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I have a new follower on Twitter

Heart of MLB
Follow for all things #MLB.

https://t.co/RBr3M6gnSr
Following: 1304 - Followers: 869

February 16, 2018 at 03:14PM via Twitter http://twitter.com/HeartofMLB

Anonymous - BOH Positions

Anonymous – BOH Positions. Posted on February 16, 2018. BOH positions available for a new Brookline restaurant. Seeking dedicated, hard working professionals for a new Coolidge Corner restaurant. Line cooks, prep cooks, pastry cooks, and dishwashers. Their food is inspired by the spirit of the ...

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Re: [FD] Defense in depth -- the Microsoft way (part 51): Skype's home-grown updater allows escalation of privilege to SYSTEM

[FD] Local Privilege Escalation in CrashPlan’s Windows Client Version 4

[FD] F-Secure Radar Login Page Unvalidated Redirect Vulnerability

F-Secure Radar Login Page Unvalidated Redirect Vulnerability CVE-2018-6324 http://ift.tt/2EvoVbX # Summary The application will upon successfully logging in redirect the user to a user-controlled destination. A victim user may not recognise that a redirection takes place as they expect to be sent to a new page. # Vendor Description F-Secure Radar is a turnkey vulnerability scanning and management platform. It allows you to identify and manage both internal and external threats, report risks, and be compliant with current and future regulations (such as PCI and GDPR compliance). It gives you visibility into shadow IT - to map your full attack surface and respond to critical vulnerabilities associated with cyber threats. Source: http://ift.tt/2qlIHuG # Remediation F-Secure has remediated this issue; no action required for cloud users or on-premise users receiving updates. # Technical Details Navigating to the Radar application at http://ift.tt/2CpzBmF will result in the user being sent to http://ift.tt/2EzdsrW. Upon successful authentication, the value of the ReturnURL query parameter will be used to determine the redirect destination. It is possible to set this to any arbitrary domain as the value is neither validated nor forced to be a relative path. The following URL would redirect the user to example.com after logging in: http://ift.tt/2CqeZuj This could be used to send the user to a phishing site, prompting them to re-authenticate (e.g. "Wrong password or username, please try again"). # Vulnerability Disclosure Timeline 2018-02-05 - Vulnerability discovered 2018-02-05 - Vendor contact & response 2018-02-09 - Vendor confirms fix 2018-02-15 - Public disclosure This post is also available at http://ift.tt/2Ez8LhS Best regards, Oscar Hjelm

Source: Gmail -> IFTTT-> Blogger

[FD] F-Secure Radar Persistent Cross-Site Scripting Vulnerability

F-Secure Radar Persistent Cross-Site Scripting Vulnerability CVE-2018-6189 http://ift.tt/2CqdgFa # Summary The application can suggest metadata tags for assets, and in doing so it can execute JavaScript entered previously by a malicious user. # Vendor Description F-Secure Radar is a turnkey vulnerability scanning and management platform. It allows you to identify and manage both internal and external threats, report risks, and be compliant with current and future regulations (such as PCI and GDPR compliance). It gives you visibility into shadow IT - to map your full attack surface and respond to critical vulnerabilities associated with cyber threats. Source: http://ift.tt/2qlIHuG # Remediation F-Secure has remediated this issue; no action required for cloud users or on-premise users receiving updates. # Technical Details The frontend application issues a PUT request to the server when metadata tags are updated: PUT /api/latest/vulnerabilityscans/tags/batch HTTP/1.1 Host: portal.radar.f-secure.com [...] The Tags parameter in the JSON request body can be modified to contain arbitrary JavaScript, e.g.: [...], "Tags":[""], [...] This script will execute whenever the frontend attempts to suggest tags, e.g. when a user opts to add tags to a new asset. # Vulnerability Disclosure Timeline 2018-01-24 - Vulnerability discovered 2018-01-24 - Vendor contact & response 2018-02-01 - Vendor confirms fix 2018-02-15 - Public disclosure This post is also available at http://ift.tt/2CqdgVG Best regards, Oscar Hjelm

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Use meshgrid to evaluate anonymous function which accepts vector inputs

Use meshgrid to evaluate anonymous function... Learn more about mesh grid, anonymous, vector input.

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Ravens prepared to create cap room by relying on self-described 'last resort' - Jamison Hensley (ESPN)

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📈 MLB Stock Watch: Hey Orioles fans ... you're keeping Manny for this? - Bradford Doolittle (ESPN)

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Anonymous Tip Form

Anonymous Tip Form. For technical questions and comments regarding this website, please contact the Webmaster. Back to Top. School Links. USD 290 Home · About Ottawa High School · Academics · Art · Computer Science · Foreign Language · I.T. · Language Arts · Mathematics · Music · P.E. ...

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Guest Relations Manager

View details and apply for this guest relations manager job in East London (E2) with Anonymous on Caterer.com. Job Description: The successful applicant will act primarily as a guest relations director.

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[[16/02/2018]] O9- mining Bitcoin process. Bitcoin generator by anonymous

[16/02/2018]] O9- mining Bitcoin process. Bitcoin generator by anonymous.

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Anonymous Ism - Hot Dog-Embroidered Cotton-Blend Socks

Japan's obsession with Americana started in the '60s and hasn't let up. Anonymous Ism's socks are embroidered with one of the nation's favourite foods - the hot dog (an estimated 20 billion are eaten every year in the States alone). This pair is made from a soft, stretchy cotton-blend that's thick enough ...

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ISS Daily Summary Report – 2/15/2018

69 Progress (69P) Docking:  This morning the 69P vehicle docked to the SM aft port of the ISS.  Rendezvous and docking both completed successfully in the automated mode with a preliminary docking capture time of 4:38:43 AM CST.   Lighting Effects: Upon wakeup, a 53S subject provided a daily sleep log entry to track his sleep … Continue reading "ISS Daily Summary Report – 2/15/2018"

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Business administration apprentice

View details and apply for this business administration apprentice job in Knott Mill, Manchester (M1) with Anonymous on RetailChoice. We are looking for a Driven, Enthusiastic and motivated young person to join our team and grow with us whilst learning new skills for your future.

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Customer Relationship Management Assistant-University of Huddersfield at Anonymous

View and apply for the role of Customer Relationship Management Assistant-University of Huddersfield with Anonymous.

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Teacher of Science, Chesterfield School

View and apply for the role of Teacher of Science, Chesterfield School with Anonymous.

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How I built a public, anonymous chat app in JavaScript

We're all familiar with instant messaging and using it to chat to people in realtime. Sometimes, though, we might want an app which allows us to send messages anonymously to friends, or to chat…

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Comet PanSTARRS is near the Edge

The comet PanSTARRS, also known as the blue comet (C/2016 R2), really is near the lower left edge of this stunning, wide field view recorded on January 13. Spanning nearly 20 degrees on the sky, the cosmic landscape is explored by well-exposed and processed frames from a sensitive digital camera. It consists of colorful clouds and dusty dark nebulae otherwise too faint for your eye to see, though. At top right, the California Nebula (aka NGC 1499) does have a familiar shape. Its coastline is over 60 light-years long and lies some 1,500 light-years away. The nebula's pronounced reddish glow is from hydrogen atoms ionized by luminous blue star Xi Persei just below it. Near bottom center, the famous Pleiades star cluster is some 400 light-years distant and around 15 light-years across. Its spectacular blue color is due to the reflection of starlight by interstellar dust. In between are hot stars of the Perseus OB2 association and dusty, dark nebulae along the edge of the nearby, massive Taurus and Perseus molecular clouds. Emission from unusually abundant ionized carbon monoxide (CO+) molecules fluorescing in sunlight is largely responsible for the telltale blue tint of the remarkable comet's tail. The comet was about 17 light minutes from Earth. via NASA http://ift.tt/2F7FQ1p

Toast POS Review: Best POS on the Market by Anonymous Reviewer

What are the best aspects of this product? Cost effective way to get a powerful, easy to use system. What aspects are problematic or could work better? I wish the integrations were a bit more robust, but it will get there. With payroll providers, etc. What features/services would you like to see in future ...

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golang/go

decoding JSON into anonymous struct works in go 1.8.7 but fails silently in go 1.9.4 #23861. Open. nkhumphreys opened this Issue 23 hours from now · 0 comments ...

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CMU Student Charged In Anonymous Rooftop Sniper Threat

A Carnegie Mellon University student is facing charges after sending an anonymous message about using a sniper rifle from a rooftop; KDKA's Julie Grant reports.

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Health Physics|dukekunshan.edu.cn

02/15/2018 - 22:04, node/2126/track, Anonymous (not verified), details. 02/15/2018 - 21:59, node/2126/track · tanglei · details. 02/15/2018 - 21:54, node/2126/track, Anonymous (not verified), details. 02/15/2018 - 20:55, node/2126/track, Anonymous (not verified), details. 02/15/2018 - 20:54, node/2126/ ...

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Orioles, P Andrew Cashner agree to 2-year, $16 million contract - MASN (ESPN)

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Authentication defaults to anonymous. Basic creden...

Hi, I am experiencing an issue where a report created on desktop works and refreshes but when published to the cloud I receive this error when trying to schedule: Webcontents failed to get contents. When I check the dialog box for credentials, 'Anonymous' is selected. I switch it to 'Basic' and include ...

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I have a new follower on Twitter

AirClass
AirClass, from @LenovoSoftware. The rich, immersive experience of a live training environment, anytime, anywhere. Virtual Training #MadeSmarter.
United States
http://t.co/pOo0B6CNuP
Following: 2153 - Followers: 2374

February 15, 2018 at 01:43PM via Twitter http://twitter.com/AirClassApp

why is the anonymous function slower than a function call

I have the following test. I run a for loop and use it to populate the sigma value of a gaussian distribution. I then either call a function or evaluate the expression directly or call a function handle or use an anonymous function. The latter is the slowest. Why? Here is my code for the test: % define inputs ...

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Anonymous Rants

Listen to Anchor audio from Anonymous Rants: Some girl who rants.

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ISS Daily Summary Report – 2/14/2018

Lighting Effects: Upon wakeup, a 53S subject provided a daily sleep log entry to track his sleep patterns and wakefulness. The Lighting Effects experiment hopes to better quantify and qualify how lighting can effect habitability of spacecraft. The light bulbs on the ISS are being replaced with a new system designed for improved crew health … Continue reading "ISS Daily Summary Report – 2/14/2018"

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🌴 Key Spring Training Players: Orioles RF Austin Hays among names to watch for all 30 teams - Schoenfield (ESPN)

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I have a new follower on Twitter

Kyle
Virtualization, Security 😎 👻🍕🐟🎮☕🍺🎧


Following: 1527 - Followers: 618

February 15, 2018 at 09:43AM via Twitter http://twitter.com/nottharealkyle

[15/02/2018] 0{6[ Ripple generator anonymous

0{6[ [15/02/2018] 0{6[ⓐ Ripple generator anonymous ⓐ. Ripple mining gtx 770. [15/02/2018] 0{6[ⓐ Ripple generator anonymous · Ripple mining gtx 770 · Ripple generator anonymous · best bitcoin mining pool for beginners. get free Ripple automatically; Ripple mining slaves; Ripple mining uk reddit ...

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Store Manager

View details and apply for this store manager job in Luton, Bedfordshire with Anonymous Recruiter on RetailChoice. Salary - Competitive salary based upon experience Fantastic benefits package – contributory pension, staff discount and life assurance.

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Techers Anonymous

Hi, I'm StickyBun and I'm an addict. <<hey StickyBun>> It all started about a week ago, I'd risen to Rank 10 for the first time and was excited to see how far I could take it. I'd only ever really played with decks I found on the internet, assuming these were finely honed instruments of perfection and not to be ...

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Microsoft/TypeScript

TypeScript Version: 2.7.1, 2.8.0-dev.20180214 (last good version is 2.6.2). Search Terms: TS2369, parameter property, constructor, declaration, anonymous class. Code. bug.ts : export class X { constructor(readonly a: number) {} } export function y() { return class extends X {} }. Run with tsc --declaration ...

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Cat hoarders anonymous

From a report, shared by an anonymous reader: If people are hoarding ether-cats or whatever these things are, how does that make the world worse? Watch the Jennifer and Ron/Jill full episode from Season 1, Episode 1 of A&E's series Hoarders. Anonymous at - Reply. 'Hoarders Anonymous Helping ...

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[InsideNothing] Kelsey Schmitt liked your post "[FD] [CORE-2017-0009] - Dell EMC Isilon OneFS Multiple Vulnerabilities"

Kelsey Schmitt liked your post on InsideNothing They thought [FD] [CORE-2017-0009] - Dell EMC Isilon OneFS Multiple Vulnerabilities was pretty awesome. You should go see what they're up to. Maybe you'll like their blog as much as they liked yours! Great posts worth seeing from Kelsey Schmitt: Home page Most Instagrammable Spots in Barcelona Building a Successful Blog Want less email? Modify your Notification Options. Moderate comments on the go Check out the mobile WordPress Apps. Thanks for flying with WordPress.com

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[InsideNothing] Kelsey Schmitt liked your post "[FD] DSA-2018-024: Dell EMC VMAX Virtual Appliance (vApp) Manager Multiple Vulnerabilities"

Kelsey Schmitt liked your post on InsideNothing They thought [FD] DSA-2018-024: Dell EMC VMAX Virtual Appliance (vApp) Manager Multiple Vulnerabilities was pretty awesome. You should go see what they're up to. Maybe you'll like their blog as much as they liked yours! Great posts worth seeing from Kelsey Schmitt: Home page Most Instagrammable Spots in Barcelona Building a Successful Blog Want less email? Modify your Notification Options. Moderate comments on the go Check out the mobile WordPress Apps. Thanks for flying with WordPress.com

Source: Gmail -> IFTTT-> Blogger

Anonymous - General Manager

Anonymous – General Manager. Posted on February 14, 2018. A popular Boston restaurant is in search of a talented and motivated General Manager. Requirements & Responsibilities Include: Minimum 5 years' restaurant management experience. Passion for hospitality and exceeding guest ...

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I have a new follower on Twitter

Mitch McConnell's Jowl
I am the jowl of a reprehensible plutocratic libertarian turtle in disguise as an American Senator. What he says in political double speak... I say plainly.
Capitol Hill, Washington
https://t.co/dUnJxst4hE
Following: 1370 - Followers: 148

February 14, 2018 at 05:43PM via Twitter http://twitter.com/scottlefty90

Anonymous donor gives $250000 to Lynchburg Christian Academy

LYNCHBURG, Va. (WSET) -- An anonymous donor has given Liberty Christian Academy $250000 after hearing of the 65% state tax credit. The tax-deductible donation to Virginia's Education Improvement Scholarship Tax Credit Program can provide assistance to new.

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Division of Science at CCNY receives $5.3M anonymous gift

The City College of New York's Division of Science announces a new $5.3 million gift for the Program for Graduate Studies in the Sciences and Undergraduate Scholarships in Science and Mathematics. The gift comes from a former alumnus of the Division of Science. The generosity of this gift will have ...

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[FD] DSA-2018-024: Dell EMC VMAX Virtual Appliance (vApp) Manager Multiple Vulnerabilities

-----BEGIN PGP SIGNED MESSAGE-

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[FD] [CORE-2017-0009] - Dell EMC Isilon OneFS Multiple Vulnerabilities

Core Security - Corelabs Advisory http://ift.tt/140w507 Dell EMC Isilon OneFS Multiple Vulnerabilities 1. **Advisory Information** Title: Dell EMC Isilon OneFS Multiple Vulnerabilities Advisory ID: CORE-2017-0009 Advisory URL: http://ift.tt/2nZEL4m Date published: 2018-02-14 Date of last update: 2018-02-14 Vendors contacted: Dell EMC Release mode: Coordinated release 2. **Vulnerability Information** Class: Cross-Site Request Forgery [CWE-352], Improper Privilege Management [CWE-269], Improper Privilege Management [CWE-269], Improper Neutralization of Input During Web Page Generation [CWE-79], Improper Neutralization of Input During Web Page Generation [CWE-79], Improper Neutralization of Input During Web Page Generation [CWE-79], Improper Neutralization of Input During Web Page Generation [CWE-79], Improper Neutralization of Input During Web Page Generation [CWE-79], Improper Neutralization of Input During Web Page Generation [CWE-79] Impact: Code execution Remotely Exploitable: Yes Locally Exploitable: Yes CVE Name: CVE-2018-1213, CVE-2018-1203, CVE-2018-1204, CVE-2018-1186, CVE-2018-1187, CVE-2018-1188, CVE-2018-1189, CVE-2018-1201, CVE-2018-1202 3. **Vulnerability Description** Dell EMC's website states that:[1] The EMC Isilon scale-out NAS storage platform combines modular hardware with unified software to harness unstructured data. Powered by the OneFS operating system, an EMC Isilon cluster delivers a scalable pool of storage with a global namespace. The platform's unified software provides centralized Web-based and command-line administration to manage the following features: - A cluster that runs a distributed file system - Scale-out nodes that add capacity and performance - Storage options that manage files and tiering - Flexible data protection and high availability - Software modules that control costs and optimize resources Multiple vulnerabilities were found in the Isilon OneFS Web console that would allow a remote attacker to gain command execution as root. 4. **Vulnerable Packages** . Dell EMC Isilon OneFS version 8.1.1.0 (CVE-2018-1203, CVE-2018-1204) . Dell EMC Isilon OneFS versions between 8.1.0.0 - 8.1.0.1 (all CVEs) . Dell EMC Isilon OneFS versions between 8.0.1.0 - 8.0.1.2 (all CVEs) . Dell EMC Isilon OneFS versions between 8.0.0.0 - 8.0.0.6 (all CVEs) . Dell EMC Isilon OneFS versions 7.2.1.x (CVE-2018-1186, CVE-2018-1188,   CVE-2018-1201, CVE-2018-1204, CVE-2018-1213) . Dell EMC Isilon OneFS version 7.1.1.11 (CVE-2018-1186, CVE-2018-1201,   CVE-2018-1202, CVE-2018-1204, CVE-2018-1213) Other products and versions might be affected, but they were not tested. 5. **Vendor Information, Solutions and Workarounds** Dell EMC provided a link to the Download for Isilon OneFS page which contains the patches: . http://ift.tt/1UkWYza 6. **Credits** These vulnerabilities were discovered and researched by Ivan Huertas and Maximiliano Vidal from Core Security Consulting Services. The publication of this advisory was coordinated by Alberto Solino from Core Advisories Team. 7. **Technical Description / Proof of Concept Code** The Web console contains several sensitive features that are vulnerable to cross-site request forgery. We describe this issue in section 7.1. Sections 7.2 and 7.3 show two vectors to escalate privileges to root. Various persistent cross-site scripting issues are presented in the remaining sections (7.4, 7.5, 7.6, 7.7, 7.8, 7.9). 7.1. **Cross-site request forgery leading to command execution** [CVE-2018-1213] There are no anti-CSRF tokens in any forms on the Web interface. This would allow an attacker to submit authenticated requests when an authenticated user browses an attacker-controlled domain. The Web console contains a plethora of sensitive actions that can be abused, such as adding new users with SSH access or re-mapping existing storage directories to allow read-write-execute access to all users. All requests are JSON-encoded, which in some cases might hinder exploitation of CSRF vulnerabilities. However, the application does not verify the content-type set. This allows an attacker to exploit the CSRF vulnerabilities by setting a text/plain content-type and sending the request body as JSON_PAYLOAD=ignored. The following proof of concept creates a new user and assigns him a new role with enough privileges to log in via SSH, configure identifies, manage authentication providers, configure the cluster and run the remote support tools. /--

Source: Gmail -> IFTTT-> Blogger

Anonymous text apps iphone

Download Anonymous Texting . Select an app for your iPhone. Fixed multiple iPhone X display issues Best messaging apps for iPhone Best messaging apps for iPhone More great messaging apps for iPhone Whether you've purchased yourself a iPhone 5S or iPhone 5C, How to send anonymous text ...

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Hackers Exploiting 'Bitmessage' Zero-Day to Steal Bitcoin Wallet Keys

Bitmessage developers have warned of a critical 'remotely executable' zero-day vulnerability in the PyBitmessage application that was being exploited in the wild. Bitmessage is a Peer-to-Peer (P2P) communications protocol used to send encrypted messages to users. Since it is decentralized and trustless communications, one need-not inherently trust any entities like root certificate

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ISS Daily Summary Report – 2/13/2018

69 Progress (69P) Launch:  69P launched from the Baikonur, Kazakhstan this morning at 2:13am CST and achieved nominal insertion with all antennas and solar arrays deployed.  Due to orbital phasing, this will be a 34-orbit rendezvous profile.  69P docking is scheduled for Thursday morning at 4:43am CST.  Lighting Effects: Upon wakeup, a 53S subject began … Continue reading "ISS Daily Summary Report – 2/13/2018"

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Profile anonymous theme suggestion is too important

The following commit that introduced Public Group support added a theme hook for profiles that is used when anonymous users view the page: http://ift.tt/2srzreF.... However, because that suggestion is simply added to the stack it is used over ...

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Google anonymous proxy

Protect your Privacy with Startpage! 5 Top Google Chrome Extensions For Anonymous Surfing But which is the best Google chrome extension to stay anonymous is the question of this article. This Proxy hides You can save your online identity from hackers and websites by browsing anonymously using ...

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Anonymous Project on the stories behind its vast found photographic archive

In its collection of nearly half a million found photographic slides, Anonymous Project has captured something familiar to everyone. “We found amazing scenes in these little windows into our past,” says co-founder Lee Shulman. “All aspects of daily life, all the more fascinating and arresting because of ...

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Anonymous Dizzy

Creating, Sharing and Celebrating the World's Visual Language.

from Google Alert - anonymous http://ift.tt/2BsnXKM
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Microsoft Won't Patch a Severe Skype Vulnerability Anytime Soon

A serious vulnerability has been discovered in Microsoft-owned most popular free web messaging and voice calling service Skype that could potentially allow attackers to gain full control of the host machine by granting system-level privileges to a local, unprivileged user. The worst part is that this vulnerability will not be patched by Microsoft anytime soon. It's not because the flaw is

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Microsoft Issues Security Patch Update for 14 New Critical Vulnerabilities

Microsoft's Patch Tuesday for this month falls the day before the most romantic day of the year. Yes, it's Valentine's, and the tech giant has released its monthly security update for February 2018, addressing a total of 50 CVE-listed vulnerabilities in its Windows operating system, Microsoft Office, web browsers and other products. Fourteen of the security updates are listed as critical, 34

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Is flagging of content anonymous to regular members who aren't staff?

Is flagging of content anonymous to regular members who aren't staff? Or is that a setting that you can determine yourself? Thanks. P.S. By anonymous I mean no one can see who posted the flag.

from Google Alert - anonymous http://ift.tt/2sqz2cp
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Anonymous Ism 5 Colour Mix Crew Sock

Buy the Anonymous Ism 5 Colour Mix Crew Sock in Red & Green from leading mens fashion retailer END. - only $25.00. Fast shipping on all latest Anonymous Ism products.

from Google Alert - anonymous http://ift.tt/2ECAn4K
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UK Group Senior Accountant

UK Group Senior Accountant in Accounting and public practice, Accountant with Anonymous. Apply Today.

from Google Alert - anonymous http://ift.tt/2sxHlDs
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Consolidation accountant

Consolidation accountant in Accounting and public practice, Accountant with Anonymous. Apply Today.

from Google Alert - anonymous http://ift.tt/2EEFNw5
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Hr Officer

Apply for the Hr officer vacancy at Anonymous Employer today! Subscribe to alerts for similar jobs from top companies and employers.

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Attorneys argue that Powerball winner should remain anonymous

Lawyers for the winner of a $560 million Powerball jackpot argued in a Nashua courtroom Tuesday that she should be able to remain anonymous.

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assistant financial controller

ASSISTANT FINANCIAL CONTROLLER in Transport and rail, Financial controller with Anonymous. Apply Today.

from Google Alert - anonymous http://ift.tt/2sqyUJX
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Software Business Analyst

Software Business Analyst in IT, Accountant with Anonymous. Apply Today.

from Google Alert - anonymous http://ift.tt/2EGVAKI
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Accounts Assistant

Accounts Assistant in Transport and rail, Accounts assistant with Anonymous. Apply Today.

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This Anonymous Instagram Account is Outing Sexual Harassers in Advertising

This Anonymous Instagram Account is Outing Sexual Harassers in Advertising. Diet Madison Avenue has emerged as the industry's leading voice for the #MeToo movement. On February 1, world-renowned advertising agency Droga5 fired Chief Creative Officer Ted Royer. The agency didn't address the ...

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Judge to decide whether Powerball winner can stay anonymous

A New Hampshire state judge is deciding whether to allow a woman who won a $559.7 million Powerball jackpot to remain anonymous.

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New Hampshire Powerball winner wants to remain anonymous

The woman who won half a billion dollars in January filed a complaint in a New Hampshire court to remain anonymous and her attorney argued her case on Tuesday. Colette Luke reports.

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I have a new follower on Twitter

Morgan Bagshaw
Mama to two little people. Gin drinker. Freelance #SocialMedia manager. #DigitalMum. I help businesses connect with their online audience.
Abergavenny, Wales
https://t.co/Nz9rJAenzY
Following: 7998 - Followers: 9271

February 13, 2018 at 05:43PM via Twitter http://twitter.com/socialgoalsuk

Insomniacs Anonymous

Buy Insomniacs Anonymous: Read Movies & TV Reviews - Amazon.com.

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Americans Anonymous by Barry Delaney

In 2016, election year, I traversed America - from Times Square, New York to the Gold coast of California - all by Greyhound bus; armed with my trusted antique film camera - these are the results of my take of a declining Empire - a country so close to my heart, for it was in America I became educated in ...

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Judge To Decide Whether Powerball Winner Can Stay Anonymous

A judge is deciding whether to allow a woman who won a $559.7 million Powerball jackpot to remain anonymous. Matt Yurus reports.

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[FD] SSD Advisory – CloudMe Unauthenticated Remote Buffer Overflow

Re: [FD] SoapUI v5.3.0 Code Execution

[FD] Multiple SQL injection vulnerabilities in dotCMS (2x CVE)

Title: Multiple SQL injection vulnerabilities in dotCMS (2x CVE) Credit: Elar Lang / http://ift.tt/1WV5vQa Vendor/Product: dotCMS (http://dotcms.com/) Vulnerability: SQL injection Vulnerable version: before 4.1.1. Theoretically would be fixed in 3.7.2 (not released yet) CVE: CVE-2016-10007, CVE-2016-10008 # Multiple SQL injections in dotCMS framework. I had already reported 8 SQL injection vulnerabilities to dotCMS and I was curious as to how they fixed it. With checking fixes I found 2 new vulnerabilites but for those I had to bypass blacklist defence. ## CVE-2016-10007 - "Marketing" > Forms" page, _EXT_FORM_HANDLER_orderBy parameter An SQL injection vulnerability in the "Marketing > Forms" screen in dotCMS before 3.7.2 (not released) and 4.1.1 allows remote authenticated attackers to execute arbitrary SQL commands via the _EXT_FORM_HANDLER_orderBy parameter. Preconditions: the attacker must be authenticated and authorized as an administrator. Proof-of-Concept URL (from "Admin Site" UI: "Marketing > Forms", click on some column title in the resultset table): /c/portal/layout?p_l_id=89594b95-1354-4a63-8867-c922880107df&p_p_id=EXT_FORM_HANDLER&p_p_action=1&p_p_state=maximized&p_p_mode=view&_EXT_FORM_HANDLER_struts_action=%2Fext%2Fformhandler%2Fview_form&_EXT_FORM_HANDLER_orderBy=SQLi&_EXT_FORM_HANDLER_direction=asc Proof-of-Concept values for parameter _EXT_FORM_HANDLER_orderBy. Precondition for this example: there must be at least 2 different rows in the resultset and ordering by name and description field should give different ordering (if they don't, use some other field names) -- boolean true - output is ordered by name field _EXT_FORM_HANDLER_orderBy=case when 1=1 then name else description end -- boolean false - output is ordered by descriotion field _EXT_FORM_HANDLER_orderBy=case when 1=0 then name else description end ## CVE-2016-10008 - "Content Types > Content Types" page, _EXT_STRUCTURE_direction parameter An SQL injection vulnerability in the "Content Types > Content Types" screen in dotCMS before 3.7.2 (not released) and 4.1.1 allows remote authenticated attackers to execute arbitrary SQL commands via the _EXT_STRUCTURE_direction parameter parameter. Preconditions: the attacker must be authenticated and authorized as an administrator. Proof-of-Concept URL (from "Admin Site" UI: "Content Types > Content Types", click on some column title in the resultset table): demo.dotcms.com/c/portal/layout?p_l_id=56fedb43-dbbf-4ce2-8b77-41fb73bad015&p_p_id=EXT_STRUCTURE&p_p_action=1&p_p_state=maximized&p_p_mode=view&_EXT_STRUCTURE_struts_action=%2Fext%2Fstructure%2Fview_structure&_EXT_STRUCTURE_orderBy=velocity_var_name&_EXT_STRUCTURE_direction=SQLi # Vulnerability Disclosure Timeline 2016-10-24 | me > dotCMS | SQLi Poc 2016-10-25 | dotCMS > me | Thanks for PoC 2016-12-19 | me > dotCMS | Informed CVE numbers, asked status for reported issues. 2016-12-19 | dotCMS > me | Low priority, not planning fixing in next release 2016-12-19 | me > dotCMS | agreed with low priority (requires authenticated user in administrator privileges) 2017-03-03 | me > dotCMS | I can see many new releases, is it fixed? [2] 2017-03-06 | dotCMS > me | No. Probably will be not addressed until the project to refactor our admin interface is completed. 2017-06-16 | dotCMS | dotCMS version 4.1.1 release 2017-07-18 | me > dotCMS | As I need to publich CVEs at some point, what is the status? 2017-07-21 | dotCMS > me | Fixes are available on 4.1.1. Would it be possible to wait 3 to 4 weeks so we can release 3.7.2? 2017-10-10 | me > dotCMS | "3 to 4 weeks" passed, how it is going with 3.7.2? 2017-10-17 | dotCMS > me | "Thank you for your patience! Thank you for your email! It prompted me to push the developer to finish getting this release out the door. I will email you next week with an update." This "next week" never arrived ;) 2018-02-11 | me | Full Disclosure on http://ift.tt/2fchtRJ # Related fixes and releases http://ift.tt/2EoWIzz # More detailed (inc some code review and blacklist bypass) description is available in blog: http://ift.tt/2F2kSkw

Source: Gmail -> IFTTT-> Blogger

Bears and Ravens will play in Hall of Fame game on Aug. 2 in Canton, Ohio (ESPN)

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ISS Daily Summary Report – 2/12/2018

69 Progress (69P) Launch Abort:  Over the weekend, the planned launch of 69P did not occur.  The vehicle issued an abort command shortly before launch and successfully shut down the launch sequence.  The root cause is under investigation, and the forward plan is in work.  The next available launch opportunity is tomorrow morning, Tuesday, February … Continue reading "ISS Daily Summary Report – 2/12/2018"

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OAuth2 reverting back to Anonymous

Hello, I recently updloaded a PBI desktop file to the service that uses 7 different Excel workbooks stored in OneDrive for Business as the data.

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Powerball winner continues fight to remain anonymous

Lawyers for a New Hampshire women who won the January 6th, $560 million dollar US Powerball Lottery will be in court today arguing she should be allowed to remain anonymous.

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Hackers Exploit 'Telegram Messenger' Zero-Day Flaw to Spread Malware

A zero-day vulnerability has been discovered in the desktop version for end-to-end encrypted Telegram messaging app that was being exploited in the wild in order to spread malware that mines cryptocurrencies such as Monero and ZCash. The Telegram vulnerability was uncovered by security researcher Alexey Firsh from Kaspersky Lab last October and affects only the Windows client of Telegram

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Manitoba Crime Stoppers

Our program provides a safe and anonymous way for the Manitoba public to pass on information to local police agencies. Tipsters can report information about any non-urgent illegal activity. If you are providing tip information on a crime occurring in the cities of Winnipeg or Brandon, please click the ...

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Anonymous Modeling Opportunity

I'm seeking women for underwear modeling. I provide the underwear, you slip them on, I snap a few photos and that's it. We can do up to 5 different pair. If this is something that interests you,...

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Thousands of Government Websites Hacked to Mine Cryptocurrencies

There was a time when hackers simply defaced websites to get attention, then they started hijacking them to spread banking trojan and ransomware, and now the trend has shifted towards injecting scripts into sites to mine cryptocurrencies. Thousands of government websites around the world have been found infected with a specific script that secretly forces visitors' computers to mine

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Pine Tree ISD Launches Anonymous Bullying Reporting App

Pine Tree ISD launched an anonymous bullying reporting app that their students can use.

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Audrey Anonymous

Can Audrey recognize what is truly important before she loses everything? Audrey Anonymous is a powerful portrayal of one woman's struggle to confront her own selfishness and rediscover the gift of motherhood. Kimberly Conn delivers another poignant novel about the necessity of human connection.

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Category:Anonymous writers

Pages in category "Anonymous writers". This category contains only the following page. This list may not reflect recent changes (learn more). ... Retrieved from "http://ift.tt/2EoPT4P". Categories: Anonymous people · Writers ...

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Getting started with the Intel Movidius Neural Compute Stick

Let me ask you three questions:

1. What if you could could run state-of-the-art neural networks on a USB stick?
2. What if you could see over 10x performance on this USB stick compared to your CPU?
3. And what if this entire device costs under $100?

Sound interesting?

Enter Intel’s Movidius Neural Compute Stick (NCS).

Raspberry Pi users will especially welcome the device as it can dramatically improve upon image classification and object detection speeds and capabilities. You may find that the Movidius is “just what you needed” to speedup network inference time in (1) a small form factor and (2) a good price.

Inside today’s post we’ll discuss:

• What the Movidius Neural Compute Stick is capable of
• If you should buy one
• How to quickly and easily get up and running with the Movidius
• Benchmarks comparing network inference times on a MacBook Pro and Raspberry Pi

Next week I’ll provide additional benchmarks and object detection scripts using the Movidius as well.

To get started with the Intel Movidius Neural Compute Stick and to learn how you can deploy a CNN model to your Raspberry Pi + NCS, just keep reading.

Looking for the source code to this post?
Jump right to the downloads section.

Getting started with the Intel Movidius Neural Compute Stick

Today’s blog post is broken into five parts.

First, I’ll answer:

What is the Intel Movidius Neural Compute Stick and should I buy one?

From there I’ll explain the workflow of getting up and running with the Movidius Neural Compute Stick. The entire process is relatively simple, but it needs to be spelled out so that we understand how to work with the NCS

We’ll then setup our Raspberry Pi with the NCS in API-only mode. We’ll also do a quick sanity check to ensure we have communication to the NCS.

Next up, I’ll walk through my custom Raspberry Pi + Movidius NCS image classification benchmark script. We’ll be using SqueezeNet, GoogLeNet, and AlexNet.

We’ll wrap up the blog post by comparing benchmark results.

What is the Intel Movidius Neural Compute Stick?

Intel’s Neural Compute Stick is a USB-thumb-drive-sized deep learning machine.

You can think of the NCS like a USB powered GPU, although that is quite the overstatement — it is not a GPU, and it can only be used for prediction/inference, not training.

I would actually classify the NCS as a coprocessor. It’s got one purpose: running (forward-pass) neural network calculations. In our case, we’ll be using the NCS for image classification.

The NCS should not be used for training a neural network model, rather it is designed for deployable models. Since the device is meant to be used on single board computers such as the Raspberry Pi, the power draw is meant to be minimal, making it inappropriate for actually training a network.

So now you’re wondering: Should I buy the Movidius NCS?

At only $77 dollars, the NCS packs a punch. You can buy the device on Amazon or at any of the retailers listed on Intel’s site.

Under the hood of the NCS is a Myriad 2 processor (28 nm) capable of 80-150 GFLOPS performance. This processor is also known as a Vision Processing Unit (or vision accelerator) and it consumes only 1W of power (for reference, the Raspberry Pi 3 B consumes 1.2W with HDMI off, LEDs off, and WiFi on).

Whether buying the NCS is worth it to you depends on the answers to several questions:

1. Do you have an immediate use case or do you have $77 to burn on another toy?
2. Are you willing to deal with the growing pains of joining a young community? While certainly effective, we don’t know if these “vision processing units” are here to stay.
3. Are you willing to devote a machine (or VM) to the SDK?
4. Pi Users: Are you willing to devote a separate Pi or at least a separate microSD to the NCS? Are you aware that the device based on it’s form factor dimensions will block 3 USB ports unless you use a cable to go to the NCS dongle?

Question 1 is up to you.

The reason I’m asking question 2 is because Intel is notorious for poor documentation and even discontinuing their products as they did with the Intel Galileo.

I’m not suggesting that either will occur with the NCS. The NCS is in the deep learning domain which is currently heading full steam ahead, so the future of this product does look bright. It also doesn’t hurt that there aren’t too many competing products.

Questions 2 and 3 (and their answers) are related. In short, you can’t isolate the development environments with virtual environments and the installer actually removes previous installations of OpenCV from your system. For this reason you should not get the installer scripts anywhere near your current projects and working environments. I learned the hard way. Trust me.

Hopefully I haven’t scared you off — that is not my intention. Most people will be purchasing the Movidius NCS to pair with a Raspberry Pi or other single board computer.

Question 4 is for Pi users. When it comes to the Pi, if you’ve been following any other tutorials on PyImageSearch.com, you’re aware that I recommend Python virtual environments to isolate your Python projects and associated dependencies. Python virtual environments are a best practice in the Python community.

One of my biggest gripes with the Neural Compute Stick is that Intel’s install scripts will actually make your virtual environments nearly unusable. The installer downloads packages from the Debian/Ubuntu Aptitude repos and changes your PYTHONPATH system variable.

It get really messy real quick and to be on the safe side, you should use a fresh microSD (purchase a 32GB 98MB/s microSD on Amazon) with Raspbian Stretch. You might even buy another Pi to marry to the NCS if you’re working on a deployable project.

When I received my NCS I was excited to plug it into my Pi…but unfortunately I was off to a rough start.

Check out the image below.

I found out that with the NCS plugged in, it blocks all 3 other USB ports on my Pi. I can’t even plug my wireless keyboard/mouse dongle in another port!

Now, I understand that the NCS is meant to be used with devices other than the Raspberry Pi, but given that the Raspberry Pi is one of the most used single board systems, I was a bit surprised that Intel didn’t consider this — perhaps it’s because the device consumes a lot of power and they want you to think twice about plugging in additional peripherals to your Pi.

Figure 1: The Intel Movidius NCS blocks the 3 other USB ports from easy access.

This is very frustrating. The solution is to buy a 6in USB 3.0 extension such as this one:

Figure 2: Using a 6in USB extension dongle with the Movidius NCS and Raspberry Pi allows access the other 3 USB ports.

With those considerations in mind, the Movidius NCS is actually a great device at a good value. So let’s dive into the workflow.

Movidius NCS Workflow

Figure 3: The Intel Movidius NCS workflow (image credit: Intel)

Working with the NCS is quite easy once you understand the workflow.

The bottom line is that you need a graph file to deploy to the NCS. This graph file can live in the same directory as your Python script if you’d like — it will get sent to the NCS using the NCS API.

In general, the workflow of using the NCS is:

1. Use a pre-trained TensorFlow/Caffe model or train a network with Tensorflow/Caffe on Ubuntu or Debian.
2. Use the NCS SDK toolchain to generate a graph file.
3. Deploy the graph file and NCS to your single board computer running a Debian flavor of Linux. I used a Raspberry Pi 3 B running Raspbian (Debian based).
4. With Python, use the NCS API to send the graph file to the NCS and request predictions on images. Process the prediction results and take an (arbitrary) action based on the results.

Today, we’ll set up the Raspberry Pi in with the NCS API-only mode toolchain. This setup also generates the bare-minimum SDK tools to create graph files. It does not install Caffe, Tensorflow, etc.

For the sake of simplicity, we’ll be using a pre-trained Caffe model and prototxt files that come from the Movidius GitHub page (indirectly a Makefile downloads them from the DeepScale GitHub repo).

Executing the Makefile will:

1. Download the Caffe files
2. Use the NCS API to generate a graph file

From there, we’ll try out the Movidius using their example script + a single static image.

Finally, we’ll create our own custom image classification benchmarking script. You’ll notice that this script is based heavily on a previous post on Deep learning with the Raspberry Pi and OpenCV.

First, let’s prepare our Raspberry Pi.

Setting up your Raspberry Pi and the NCS in API-only mode

I learned the hard way that the Raspberry Pi can’t handle the SDK (what was I thinking?) by reading some sparse documentation.

I later started from square one and found better documentation that instructed me to set up my Pi in API-only mode (now this makes sense). I was quickly up and running in this fashion and I’ll show you how to do the same thing.

For your Pi, I recommend that you install the SDK in API-only mode on a fresh installation of Raspbian Stretch.

To install the Raspbian Stretch OS on your Pi, grab the Stretch image here and then flash the card using these instructions.

From there, boot up your Pi and connect to WiFi. You can complete all of the following actions over an SSH connection or using a monitor + keyboard/mouse (with the 6inch dongle listed above as the USB ports are blocked by the NCS) if you prefer.

Let’s update the system:

$ sudo apt-get update && sudo apt-get upgrade

Then let’s install a bunch of packages:

$ sudo apt-get install -y libusb-1.0-0-dev libprotobuf-dev
$ sudo apt-get install -y libleveldb-dev libsnappy-dev
$ sudo apt-get install -y libopencv-dev
$ sudo apt-get install -y libhdf5-serial-dev protobuf-compiler
$ sudo apt-get install -y libatlas-base-dev git automake 
$ sudo apt-get install -y byacc lsb-release cmake 
$ sudo apt-get install -y libgflags-dev libgoogle-glog-dev 
$ sudo apt-get install -y liblmdb-dev swig3.0 graphviz 
$ sudo apt-get install -y libxslt-dev libxml2-dev 
$ sudo apt-get install -y gfortran 
$ sudo apt-get install -y python3-dev python-pip python3-pip 
$ sudo apt-get install -y python3-setuptools python3-markdown 
$ sudo apt-get install -y python3-pillow python3-yaml python3-pygraphviz
$ sudo apt-get install -y python3-h5py python3-nose python3-lxml 
$ sudo apt-get install -y python3-matplotlib python3-numpy 
$ sudo apt-get install -y python3-protobuf python3-dateutil 
$ sudo apt-get install -y python3-skimage python3-scipy 
$ sudo apt-get install -y python3-six python3-networkx

Notice that we’ve installed

libopencv-dev

  from the Debian repositories. This is the first time I’m ever recommending it and hopefully the last time as well. Installing OpenCV via apt-get (1) installs an older version of OpenCV, (2) does not install the full version of OpenCV, and (3) does not take advantage of various system operations. Again, I do not recommend this method to installing OpenCV.

Additionally, you can see we’re installing a whole bunch of packages that I generally prefer to manage inside Python virtual environments with pip. Be sure you are using a fresh memory card so you don’t mess up other projects that you’ve been working on, on your Pi.

From there, let’s make a workspace directory and clone the NCSDK:

$ cd ~
$ mkdir workspace
$ cd workspace
$ git clone https://github.com/movidius/ncsdk

And while we’re at it, let’s clone down the NC App Zoo as we’ll want it for later.

$ git clone https://github.com/movidius/ncappzoo

And from there, navigate into the following directory:

$ cd ncsdk/api/src

In that directory we’ll use the Makefile to install SDK in API-only mode:

$ make
$ sudo make install

Test the Raspberry Pi installation on the NCS

Let’s test the installation by using code from the NC App Zoo. Be sure that the NCS is plugged into your Pi at this point.

$ cd ncappzoo/apps/hello_ncs_py
$ make run

making run
python3 hello_ncs.py;
Hello NCS! Device opened normally.
Goodbye NCS! Device closed normally.
NCS device working.

You should see the exact output as above.

Generating your Movidius NCS neural network

SqueezeNet is included with the NC App Zoo and it is easy to generate the required graph file. The Makefile does it all for us:

$ cd ~/workspace/ncappzoo/caffe/SqueezeNet
$ make all
$ python run.py
...
------- predictions --------

     electric guitar 99.12 %
              vacuum 0.34 %
     acoustic guitar 0.15 %
           corkscrew 0.10 %
                hook 0.07 %

Classification with the Movidius NCS

If you open up the

run.py

  file that we just created with the Makefile, you’ll notice that most inputs are hardcoded and that the file is ugly in general.

Instead, we’re going to create our own file for classification and benchmarking.

In a previous post, Deep learning on the Raspberry Pi with OpenCV, I described how to use the OpenCV’s DNN module to perform object classification.

Today, we’re going to modify that exact same script to make it compatible with the Movidius NCS.

If you compare both scripts you’ll see that they are nearly identical. For this reason, I’ll simply be pointing out the differences, so I encourage you to refer to the previous post for full explanations.

Each script is included in the “Downloads” section of this blog post, so be sure to grab the zip and follow along.

Let’s review the differences in the modified file named 

pi_ncs_deep_learning.py

 :

# import the necessary packages
from mvnc import mvncapi as mvnc
import numpy as np
import argparse
import time
import cv2

Here we are importing our packages — the only difference is on Line 2 where we import the

mvncapi as mvnc

 . This import is for the NCS API.

From there, we need to parse our command line arguments:

# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
        help="path to input image")
ap.add_argument("-g", "--graph", required=True,
        help="path to graph file")
ap.add_argument("-d", "--dim", type=int, required=True,
        help="dimension of input to network")
ap.add_argument("-l", "--labels", required=True,
        help="path to ImageNet labels (i.e., syn-sets)")
args = vars(ap.parse_args())

In this block I’ve removed two arguments (

--prototxt

  and

--model

 ) while adding two arguments (

--graph

  and

--dim

 ).

The

--graph

  argument is the path to our graph file — it takes the place of the prototxt and model.

Graph files can be generated via the NCS SDK, which we’ll cover in next week’s blog post. I’ve included the graph files for this week in the “Downloads“ for convenience. In the case of Caffe the graph is generated from the prototxt and model files with the SDK.

The

--dim

  argument simply specifies the pixel dimensions of the (square) image we’ll be sending through the neural network. Dimensions of the image were hardcoded in the previous post.

Next, we’ll load the class labels and input image from disk:

# load the class labels from disk
rows = open(args["labels"]).read().strip().split("\n")
classes = [r[r.find(" ") + 1:].split(",")[0] for r in rows]

# load the input image from disk, make a copy, resize it, and convert to float32
image_orig = cv2.imread(args["image"])
image = image_orig.copy()
image = cv2.resize(image, (args["dim"], args["dim"]))
image = image.astype(np.float32)

Here we’re loading the class labels from 

synset_words.txt

  with the same method as previously.

Then, we utilize OpenCV to load the image.

One slight change is that we’re making a copy of the original image on Line 26. We need two copies — one for preprocessing/normalization/classification and one for displaying to our screen later on.

Line 27 resizes our image and you’ll notice that we’re using

args["dim"]

  — our command line argument value.

Common choices for width and height image dimensions inputted to Convolutional Neural Networks include 32 × 32, 64 × 64, 224 × 224, 227 × 227, 256 × 256, and 299 × 299. Your exact image dimensions will depend on which CNN you are using.

Line 28 converts the image array data to

float32

  format which is a requirement for the NCS and the graph files we’re working with.

Next, we perform mean subtraction, but we’ll do it in a slightly different way this go around:

# load the mean file and normalize
ilsvrc_mean = np.load("ilsvrc_2012_mean.npy").mean(1).mean(1)
image[:,:,0] = (image[:,:,0] - ilsvrc_mean[0])
image[:,:,1] = (image[:,:,1] - ilsvrc_mean[1])
image[:,:,2] = (image[:,:,2] - ilsvrc_mean[2])

We load the

ilsvrc_2012_mean.npy

  file on Line 31. This comes from the ImageNet Large Scale Visual Recognition Challenge and can be used for SqueezeNet, GoogLeNet, AlexNet, and typically all other networks trained on ImageNet that utilize mean subtraction (we hardcode the path for this reason).

The image mean subtraction is computed on Lines 32-34 (using the same method shown in the Movidius example scripts on GitHub).

From there, we need to establish communication with the NCS and load the graph into the NCS:

# grab a list of all NCS devices plugged in to USB
print("[INFO] finding NCS devices...")
devices = mvnc.EnumerateDevices()

# if no devices found, exit the script
if len(devices) == 0:
        print("[INFO] No devices found. Please plug in a NCS")
        quit()

# use the first device since this is a simple test script
print("[INFO] found {} devices. device0 will be used. "
        "opening device0...".format(len(devices)))
device = mvnc.Device(devices[0])
device.OpenDevice()

# open the CNN graph file
print("[INFO] loading the graph file into RPi memory...")
with open(args["graph"], mode="rb") as f:
        graph_in_memory = f.read()

# load the graph into the NCS
print("[INFO] allocating the graph on the NCS...")
graph = device.AllocateGraph(graph_in_memory)

As you can tell, the above code block is completely different because last time we didn’t use the NCS at all.

Let’s walk through it — it’s actually very straightforward.

In order to prepare to use a neural network on the NCS we need to perform the following actions:

1. List all connected NCS devices (Line 38).
2. Break out of the script altogether if there’s a problem finding one NCS (Lines 41-43).
3. Select and open

   device0
   

     (Lines 48 and 49).
4. Load the graph file into Raspberry Pi memory so that we can transfer it to the NCS with the API (Lines 53 and 54).
5. Load/allocate the graph on the NCS (Line 58).

The Movidius developers certainly got this right — their API is very easy to use!

In case you missed it above, it is worth noting here that we are loading a pre-trained graph. The training step has already been performed on a more powerful machine and the graph was generated by the NCS SDK. Training your own network is outside the scope of this blog post, but covered in detail in both PyImageSearch Gurus and Deep Learning for Computer Vision with Python.

You’ll recognize the following block if you read the previous post, but you’ll notice three changes:

# set the image as input to the network and perform a forward-pass to
# obtain our output classification
start = time.time()
graph.LoadTensor(image.astype(np.float16), "user object")
(preds, userobj) = graph.GetResult()
end = time.time()
print("[INFO] classification took {:.5} seconds".format(end - start))

# clean up the graph and device
graph.DeallocateGraph()
device.CloseDevice()

# sort the indexes of the probabilities in descending order (higher
# probabilitiy first) and grab the top-5 predictions
preds = preds.reshape((1, len(classes)))
idxs = np.argsort(preds[0])[::-1][:5]

Here we will classify the image with the NCS and the API.

Using our graph object, we call

graph.LoadTensor

  to make a prediction and

graph.GetResult

  to grab the resulting predictions. This is a two-step action, where before we simply called

net.forward

  on a single line.

We time these actions to compute our benchmark while displaying the result to the terminal just like previously.

We perform our housekeeping duties next by clearing the graph memory and closing the connection to the NCS on Lines 69 and 70.

From there we’ve got one remaining block to display our image to the screen (with a very minor change):

# loop over the top-5 predictions and display them
for (i, idx) in enumerate(idxs):
        # draw the top prediction on the input image
        if i == 0:
                text = "Label: {}, {:.2f}%".format(classes[idx],
                        preds[0][idx] * 100)
                cv2.putText(image_orig, text, (5, 25), cv2.FONT_HERSHEY_SIMPLEX,
                        0.7, (0, 0, 255), 2)

        # display the predicted label + associated probability to the
        # console
        print("[INFO] {}. label: {}, probability: {:.5}".format(i + 1,
                classes[idx], preds[0][idx]))

# display the output image
cv2.imshow("Image", image_orig)
cv2.waitKey(0)

In this block, we draw the highest prediction and probability on the top of the image. We also print the top-5 predictions + probabilities in the terminal.

The very minor change in this block is that we’re drawing the text on

image_orig

  rather than

image

 .

Finally, we display the output

image_orig

  on the screen. If you are using SSH to connect with your Raspberry Pi this will only work if you supply the 

-X

  flag for X11 forwarding when SSH’ing into your Pi.

To see the results of applying deep learning image classification on the Raspberry Pi using the Intel Movidius Neural Compute Stick and Python, proceed to the next section.

Raspberry Pi and deep learning results

For this benchmark, we’re going to compare using the Pi CPU to using the Pi paired with the NCS coprocessor.

Just for fun, I also threw in the results from using my Macbook Pro with and without the NCS (which requires an Ubuntu 16.04 VM that we’ll be building and configuring next week).

We’ll be using three models:

1. SqueezeNet
2. GoogLeNet
3. AlexNet

Just to keep things simple, we’ll be running the classification on the same image each time — a barber chair:

Figure 4: A barber chair in a barbershop is our test input image for deep learning on the Raspberri Pi with the Intel Movidius Neural Compute Stick.

Since the terminal output results are quite long, I’m going to leave them out of the following blocks. Instead, I’ll be sharing a table of the results for easy comparison.

Here are the CPU commands (you can actually run this on your Pi or on your desktop/laptop despite

pi

  in the filename):

# SqueezeNet with OpenCV DNN module using the CPU
$ python pi_deep_learning.py --prototxt models/squeezenet_v1.0.prototxt \
        --model models/squeezenet_v1.0.caffemodel --dim 227 \
        --labels synset_words.txt --image images/barbershop.png
[INFO] loading model...
[INFO] classification took 0.42588 seconds
[INFO] 1. label: barbershop, probability: 0.8526
[INFO] 2. label: barber chair, probability: 0.10092
[INFO] 3. label: desktop computer, probability: 0.01255
[INFO] 4. label: monitor, probability: 0.0060597
[INFO] 5. label: desk, probability: 0.004565

# GoogLeNet with OpenCV DNN module using the CPU
$ python pi_deep_learning.py --prototxt models/bvlc_googlenet.prototxt \
        --model models/bvlc_googlenet.caffemodel --dim 224 \
        --labels synset_words.txt --image images/barbershop.png
...

# AlexNet with OpenCV DNN module using the CPU
$ python pi_deep_learning.py --prototxt models/bvlc_alexnet.prototxt \
        --model models/bvlc_alexnet.caffemodel --dim 227 \
        --labels synset_words.txt --image images/barbershop.png
...

Note:  In order to use the OpenCV DNN module, you must have OpenCV 3.3 at a minimum. You can install an optimized OpenCV 3.3 on your Raspberry Pi using these instructions.

And here are the NCS commands using the new modified script that we just walked through above (you can actually run this on your Pi or on your desktop/laptop despite

pi

  in the filename):

# SqueezeNet on NCS
$ python pi_ncs_deep_learning.py --graph graphs/squeezenetgraph \
        --dim 227 --labels synset_words.txt --image images/barbershop.png
[INFO] finding NCS devices...
[INFO] found 1 devices. device0 will be used. opening device0...
[INFO] loading the graph file into RPi memory...
[INFO] allocating the graph on the NCS...
[INFO] classification took 0.085902 seconds
[INFO] 1. label: barbershop, probability: 0.94482
[INFO] 2. label: restaurant, probability: 0.013901
[INFO] 3. label: shoe shop, probability: 0.010338
[INFO] 4. label: tobacco shop, probability: 0.005619
[INFO] 5. label: library, probability: 0.0035152

# GoogLeNet on NCS
$ python pi_ncs_deep_learning.py --graph graphs/googlenetgraph \
        --dim 224 --labels synset_words.txt --image images/barbershop.png
...

# AlexNet on NCS
$ python pi_ncs_deep_learning.py --graph graphs/alexnetgraph \
        --dim 227 --labels synset_words.txt --image images/barbershop.png
...

Note: In order to use the NCS, you must have a Raspberry Pi loaded with a fresh install of Raspbian (Stretch preferably) and the NCS API-only mode toolchain installed as per the instructions in this blog post. Alternatively you may use an Ubuntu machine or VM.

Please pay attention to both Notes above. You’ll need two separate microSD cards to complete these experiments. The NCS API-only mode toolchain uses OpenCV 2.4 and therefore does not have the new DNN module. You cannot use virtual environments with the NCS, so you need completely isolated systems. Do yourself a favor and get a few spare microSD cards — I like the 32 GB 98MB/s cards. Dual booting your Pi might be an option, but I’ve never tried it and don’t want to deal with the hassle of partitioned microSD cards.

Now for the results summarized in a table:

Figure 5: Intel NCS with the Raspberry Pi benchmarks. I compared classification using the Pi CPU and using the Movidius NCS. On ImageNet, the NCS achieves a 395 to 545% speedup.

The NCS is clearly faster on the Pi when compared to using the Pi’s CPU for classification achieving a 6.45x speedup (545%) on GoogLeNet. The NCS is sure to bring noticeable speed to the table on larger networks such as the three compared here.

Note: The results gathered on the Raspberry Pi used my optimized OpenCV install instructions. If you are not using the optimized OpenCV install, you would see speedups in the range of 10-11x!

When comparing execution on my MacBook Pro with Ubuntu VM to the SDK VM on my MBP, performance is worse — this is expected for a number of reasons.

For starters, my MBP has a much more powerful CPU. It turns out that it’s faster to run the full inference on the CPU versus the added overhead of moving the image from the CPU to the NCS and then pulling the results back.

Second, there is USB overhead when conducting USB passthrough to the VM. USB 3 isn’t supported via the VirtualBox USB passthrough either.

It is worth noting that the Raspberry Pi 3 B has USB 2.0. If you really want speed for a single board computer setup, select a machine that supports USB 3.0. The data transfer speeds alone will be apparent if you are benchmarking.

Next week’s results will be even more evident when we compare real-time video FPS benchmarks, so be sure to check back on Monday.

Where to from here?

I’ll be back soon with another blog post to share with you how to generate your own custom graph files for the Movidius NCS.

I’ll also be describing how to perform object detection in realtime video using the Movidius NCS — we’ll benchmark and compare the FPS speedup and I think you’ll be quite impressed.

In the meantime, be sure to check out the Movidius blog and TopCoder Competition.

Movidus blog on GitHub

Intel and Movidius are keeping their blog up to date on GitHub. Be sure to bookmark their page and/or subscribe to RSS:

developer.movidius.com/blog

You might also want to sign into GitHub and click the “watch” button on the Movidius repos:

• github.com/movidius/ncsdk
• github.com/movidius/ncappzoo

TopCoder Competition

Figure 5: Earn up to $8,000 with the Movidius NCS on TopCoder.

Are you interested in pushing the limits of the Intel Movidius Neural Compute Stick?

Intel is sponsoring a competition on TopCoder.

There are $20,000 in prizes up for grabs (first place wins $8,000)!

Registration and submission close on February 26, 2018.

Keep track of the leaderboard and standings!

Summary

Today we explored Intel’s new Movidius Neural Compute Stick. My goal here today was expose you to this new deep learning device (which we’ll  be using in future blog posts as well). I also demonstrated how to use the NCS workflow and API.

In general, the NCS workflow involes:

1. Training a network with Tensorflow or Caffe using a machine running Ubuntu/Debian (or using a pre-trained network).
2. Using the NCS SDK to generate a graph file.
3. Deploying the graph file and NCS to your single board computer running a Debian flavor of Linux. We used a Raspberry Pi 3 B running Raspbian (Debian based).
4. Performing inference, classification, object detection, etc.

Today, we skipped Steps 1 and 2. Instead I am providing graph files which you can begin using on your Pi immediately.

Then, we wrote our own classification benchmarking Python script and analyzed the results which demonstrate a significant 10x speedup on the Raspberry Pi.

I’m quite impressed with the NCS capabilities so far — it pairs quite well with the Raspberry Pi and I think it is a great value if (1) you have a use case for it or (2) you just want to hack and tinker.

I hope you enjoyed today’s introductory post on Intel’s new Movidius Neural Compute Stick!

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