Tag Archives: intelligence

Simplify Your Jenkins Builds with AWS CodeBuild

Post Syndicated from Paul Roberts original https://aws.amazon.com/blogs/devops/simplify-your-jenkins-builds-with-aws-codebuild/

Jeff Bezos famously said, “There’s a lot of undifferentiated heavy lifting that stands between your idea and that success.” He went on to say, “…70% of your time, energy, and dollars go into the undifferentiated heavy lifting and only 30% of your energy, time, and dollars gets to go into the core kernel of your idea.”

If you subscribe to this maxim, you should not be spending valuable time focusing on operational issues related to maintaining the Jenkins build infrastructure. Companies such as Riot Games have over 1.25 million builds per year and have written several lengthy blog posts about their experiences designing a complex, custom Docker-powered Jenkins build farm. Dealing with Jenkins slaves at scale is a job in itself and Riot has engineers focused on managing the build infrastructure.

Typical Jenkins Build Farm

 

As with all technology, the Jenkins build farm architectures have evolved. Today, instead of manually building your own container infrastructure, there are Jenkins Docker plugins available to help reduce the operational burden of maintaining these environments. There is also a community-contributed Amazon EC2 Container Service (Amazon ECS) plugin that helps remove some of the overhead, but you still need to configure and manage the overall Amazon ECS environment.

There are various ways to create and manage your Jenkins build farm, but there has to be a way that significantly reduces your operational overhead.

Introducing AWS CodeBuild

AWS CodeBuild is a fully managed build service that removes the undifferentiated heavy lifting of provisioning, managing, and scaling your own build servers. With CodeBuild, there is no software to install, patch, or update. CodeBuild scales up automatically to meet the needs of your development teams. In addition, CodeBuild is an on-demand service where you pay as you go. You are charged based only on the number of minutes it takes to complete your build.

One AWS customer, Recruiterbox, helps companies hire simply and predictably through their software platform. Two years ago, they began feeling the operational pain of maintaining their own Jenkins build farms. They briefly considered moving to Amazon ECS, but chose an even easier path forward instead. Recuiterbox transitioned to using Jenkins with CodeBuild and are very happy with the results. You can read more about their journey here.

Solution Overview: Jenkins and CodeBuild

To remove the heavy lifting from managing your Jenkins build farm, AWS has developed a Jenkins AWS CodeBuild plugin. After the plugin has been enabled, a developer can configure a Jenkins project to pick up new commits from their chosen source code repository and automatically run the associated builds. After the build is successful, it will create an artifact that is stored inside an S3 bucket that you have configured. If an error is detected somewhere, CodeBuild will capture the output and send it to Amazon CloudWatch logs. In addition to storing the logs on CloudWatch, Jenkins also captures the error so you do not have to go hunting for log files for your build.

 

AWS CodeBuild with Jenkins Plugin

 

The following example uses AWS CodeCommit (Git) as the source control management (SCM) and Amazon S3 for build artifact storage. Logs are stored in CloudWatch. A development pipeline that uses Jenkins with CodeBuild plugin architecture looks something like this:

 

AWS CodeBuild Diagram

Initial Solution Setup

To keep this blog post succinct, I assume that you are using the following components on AWS already and have applied the appropriate IAM policies:

·         AWS CodeCommit repo.

·         Amazon S3 bucket for CodeBuild artifacts.

·         SNS notification for text messaging of the Jenkins admin password.

·         IAM user’s key and secret.

·         A role that has a policy with these permissions. Be sure to edit the ARNs with your region, account, and resource name. Use this role in the AWS CloudFormation template referred to later in this post.

 

Jenkins Installation with CodeBuild Plugin Enabled

To make the integration with Jenkins as frictionless as possible, I have created an AWS CloudFormation template here: https://s3.amazonaws.com/proberts-public/jenkins.yaml. Download the template, sign in the AWS CloudFormation console, and then use the template to create a stack.

 

CloudFormation Inputs

Jenkins Project Configuration

After the stack is complete, log in to the Jenkins EC2 instance using the user name “admin” and the password sent to your mobile device. Now that you have logged in to Jenkins, you need to create your first project. Start with a Freestyle project and configure the parameters based on your CodeBuild and CodeCommit settings.

 

AWS CodeBuild Plugin Configuration in Jenkins

 

Additional Jenkins AWS CodeBuild Plugin Configuration

 

After you have configured the Jenkins project appropriately you should be able to check your build status on the Jenkins polling log under your project settings:

 

Jenkins Polling Log

 

Now that Jenkins is polling CodeCommit, you can check the CodeBuild dashboard under your Jenkins project to confirm your build was successful:

Jenkins AWS CodeBuild Dashboard

Wrapping Up

In a matter of minutes, you have been able to provision Jenkins with the AWS CodeBuild plugin. This will greatly simplify your build infrastructure management. Now kick back and relax while CodeBuild does all the heavy lifting!


About the Author

Paul Roberts is a Strategic Solutions Architect for Amazon Web Services. When he is not working on Serverless, DevOps, or Artificial Intelligence, he is often found in Lake Tahoe exploring the various mountain ranges with his family.

NSA Spied on Early File-Sharing Networks, Including BitTorrent

Post Syndicated from Andy original https://torrentfreak.com/nsa-spied-on-early-file-sharing-networks-including-bittorrent-170914/

In the early 2000s, when peer-to-peer (P2P) file-sharing was in its infancy, the majority of users had no idea that their activities could be monitored by outsiders. The reality was very different, however.

As few as they were, all of the major networks were completely open, with most operating a ‘shared folder’ type system that allowed any network participant to see exactly what another user was sharing. Nevertheless, with little to no oversight, file-sharing at least felt like a somewhat private affair.

As user volumes began to swell, software such as KaZaA (which utilized the FastTrack network) and eDonkey2000 (eD2k network) attracted attention from record labels, who were desperate to stop the unlicensed sharing of copyrighted content. The same held true for the BitTorrent networks that arrived on the scene a couple of years later.

Through the rise of lawsuits against consumers, the general public began to learn that their activities on P2P networks were not secret and they were being watched for some, if not all, of the time by copyright holders. Little did they know, however, that a much bigger player was also keeping a watchful eye.

According to a fascinating document just released by The Intercept as part of the Edward Snowden leaks, the National Security Agency (NSA) showed a keen interest in trying to penetrate early P2P networks.

Initially published by internal NSA news site SIDToday in June 2005, the document lays out the aims of a program called FAVA – File-Sharing Analysis and Vulnerability Assessment.

“One question that naturally arises after identifying file-sharing traffic is whether or not there is anything of intelligence value in this traffic,” the NSA document begins.

“By searching our collection databases, it is clear that many targets are using popular file sharing applications; but if they are merely sharing the latest release of their favorite pop star, this traffic is of dubious value (no offense to Britney Spears intended).”

Indeed, the vast majority of users of these early networks were only been interested in sharing relatively small music files, which were somewhat easy to manage given the bandwidth limitations of the day. However, the NSA still wanted to know what was happening on a broader scale, so that meant decoding their somewhat limited encryption.

“As many of the applications, such as KaZaA for example, encrypt their traffic, we first had to decrypt the traffic before we could begin to parse the messages. We have developed the capability to decrypt and decode both KaZaA and eDonkey traffic to determine which files are being shared, and what queries are being performed,” the NSA document reveals.

Most progress appears to have been made against KaZaA, with the NSA revealing the use of tools to parse out registry entries on users’ hard drives. This information gave up users’ email addresses, country codes, user names, the location of their stored files, plus a list of recent searches.

This gave the NSA the ability to look deeper into user behavior, which revealed some P2P users going beyond searches for basic run-of-the-mill multimedia content.

“[We] have discovered that our targets are using P2P systems to search for and share files which are at the very least somewhat surprising — not simply harmless music and movie files. With more widespread adoption, these tools will allow us to regularly assimilate data which previously had been passed over; giving us a more complete picture of our targets and their activities,” the document adds.

Today, more than 12 years later, with KaZaA long dead and eDonkey barely alive, scanning early pirate activities might seem a distant act. However, there’s little doubt that similar programs remain active today. Even in 2005, the FAVA program had lofty ambitions, targeting other networks and protocols including DirectConnect, Freenet, Gnutella, Gnutella2, JoltID, MSN Messenger, Windows Messenger and……BitTorrent.

“If you have a target using any of these applications or using some other application which might fall into the P2P category, please contact us,” the NSA document urges staff. “We would be more than happy to help.”

Confirming the continued interest in BitTorrent, The Intercept has published a couple of further documents which deal with the protocol directly.

The first details an NSA program called GRIMPLATE, which aimed to study how Department of Defense employees were using BitTorrent and whether that constituted a risk.

The second relates to P2P research carried out by Britain’s GCHQ spy agency. It details DIRTY RAT, a web application which gave the government to “the capability to identify users sharing/downloading files of interest on the eMule (Kademlia) and BitTorrent networks.”

The SIDToday document detailing the FAVA program can be viewed here

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

AWS Hot Startups – August 2017

Post Syndicated from Tina Barr original https://aws.amazon.com/blogs/aws/aws-hot-startups-august-2017/

There’s no doubt about it – Artificial Intelligence is changing the world and how it operates. Across industries, organizations from startups to Fortune 500s are embracing AI to develop new products, services, and opportunities that are more efficient and accessible for their consumers. From driverless cars to better preventative healthcare to smart home devices, AI is driving innovation at a fast rate and will continue to play a more important role in our everyday lives.

This month we’d like to highlight startups using AI solutions to help companies grow. We are pleased to feature:

  • SignalBox – a simple and accessible deep learning platform to help businesses get started with AI.
  • Valossa – an AI video recognition platform for the media and entertainment industry.
  • Kaliber – innovative applications for businesses using facial recognition, deep learning, and big data.

SignalBox (UK)

In 2016, SignalBox founder Alain Richardt was hearing the same comments being made by developers, data scientists, and business leaders. They wanted to get into deep learning but didn’t know where to start. Alain saw an opportunity to commodify and apply deep learning by providing a platform that does the heavy lifting with an easy-to-use web interface, blueprints for common tasks, and just a single-click to productize the models. With SignalBox, companies can start building deep learning models with no coding at all – they just select a data set, choose a network architecture, and go. SignalBox also offers step-by-step tutorials, tips and tricks from industry experts, and consulting services for customers that want an end-to-end AI solution.

SignalBox offers a variety of solutions that are being used across many industries for energy modeling, fraud detection, customer segmentation, insurance risk modeling, inventory prediction, real estate prediction, and more. Existing data science teams are using SignalBox to accelerate their innovation cycle. One innovative UK startup, Energi Mine, recently worked with SignalBox to develop deep networks that predict anomalous energy consumption patterns and do time series predictions on energy usage for businesses with hundreds of sites.

SignalBox uses a variety of AWS services including Amazon EC2, Amazon VPC, Amazon Elastic Block Store, and Amazon S3. The ability to rapidly provision EC2 GPU instances has been a critical factor in their success – both in terms of keeping their operational expenses low, as well as speed to market. The Amazon API Gateway has allowed for operational automation, giving SignalBox the ability to control its infrastructure.

To learn more about SignalBox, visit here.

Valossa (Finland)

As students at the University of Oulu in Finland, the Valossa founders spent years doing research in the computer science and AI labs. During that time, the team witnessed how the world was moving beyond text, with video playing a greater role in day-to-day communication. This spawned an idea to use technology to automatically understand what an audience is viewing and share that information with a global network of content producers. Since 2015, Valossa has been building next generation AI applications to benefit the media and entertainment industry and is moving beyond the capabilities of traditional visual recognition systems.

Valossa’s AI is capable of analyzing any video stream. The AI studies a vast array of data within videos and converts that information into descriptive tags, categories, and overviews automatically. Basically, it sees, hears, and understands videos like a human does. The Valossa AI can detect people, visual and auditory concepts, key speech elements, and labels explicit content to make moderating and filtering content simpler. Valossa’s solutions are designed to provide value for the content production workflow, from media asset management to end-user applications for content discovery. AI-annotated content allows online viewers to jump directly to their favorite scenes or search specific topics and actors within a video.

Valossa leverages AWS to deliver the industry’s first complete AI video recognition platform. Using Amazon EC2 GPU instances, Valossa can easily scale their computation capacity based on customer activity. High-volume video processing with GPU instances provides the necessary speed for time-sensitive workflows. The geo-located Availability Zones in EC2 allow Valossa to bring resources close to their customers to minimize network delays. Valossa also uses Amazon S3 for video ingestion and to provide end-user video analytics, which makes managing and accessing media data easy and highly scalable.

To see how Valossa works, check out www.WhatIsMyMovie.com or enable the Alexa Skill, Valossa Movie Finder. To try the Valossa AI, sign up for free at www.valossa.com.

Kaliber (San Francisco, CA)

Serial entrepreneurs Ray Rahman and Risto Haukioja founded Kaliber in 2016. The pair had previously worked in startups building smart cities and online privacy tools, and teamed up to bring AI to the workplace and change the hospitality industry. Our world is designed to appeal to our senses – stores and warehouses have clearly marked aisles, products are colorfully packaged, and we use these designs to differentiate one thing from another. We tell each other apart by our faces, and previously that was something only humans could measure or act upon. Kaliber is using facial recognition, deep learning, and big data to create solutions for business use. Markets and companies that aren’t typically associated with cutting-edge technology will be able to use their existing camera infrastructure in a whole new way, making them more efficient and better able to serve their customers.

Computer video processing is rapidly expanding, and Kaliber believes that video recognition will extend to far more than security cameras and robots. Using the clients’ network of in-house cameras, Kaliber’s platform extracts key data points and maps them to actionable insights using their machine learning (ML) algorithm. Dashboards connect users to the client’s BI tools via the Kaliber enterprise APIs, and managers can view these analytics to improve their real-world processes, taking immediate corrective action with real-time alerts. Kaliber’s Real Metrics are aimed at combining the power of image recognition with ML to ultimately provide a more meaningful experience for all.

Kaliber uses many AWS services, including Amazon Rekognition, Amazon Kinesis, AWS Lambda, Amazon EC2 GPU instances, and Amazon S3. These services have been instrumental in helping Kaliber meet the needs of enterprise customers in record time.

Learn more about Kaliber here.

Thanks for reading and we’ll see you next month!

-Tina

 

The NSA’s 2014 Media Engagement and Outreach Plan

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/08/the_nsas_2014_m.html

Interesting post-Snowden reading, just declassified.

(U) External Communication will address at least one of “fresh look” narratives:

  1. (U) NSA does not access everything.
  2. (U) NSA does not collect indiscriminately on U.S. Persons and foreign nationals.
  3. (U) NSA does not weaken encryption.
  4. (U) NSA has value to the nation.

There’s lots more.

3D print your own Rubik’s Cube Solver

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/rubiks-cube-solver/

Why use logic and your hands to solve a Rubik’s Cube, when you could 3D print your own Rubik’s Cube Solver and thus avoid overexerting your fingers and brain cells? Here to help you with this is Otvinta‘s new robotic make:

Fully 3D-Printed Rubik’s Cube Solving Robot

This 3D-printed Raspberry PI-powered Rubik’s Cube solving robot has everything any serious robot does — arms, servos, gears, vision, artificial intelligence and a task to complete. If you want to introduce robotics to your kids or your students, this is the perfect machine for it. This robot is fully 3D-printable.

Rubik’s Cubes

As Liz has said before, we have a lot of Rubik’s cubes here at Pi Towers. In fact, let me just…hold on…I’ll be right back.

Okay, these are all the ones I found on Gordon’s desk, and I’m 99% sure there are more in his drawers.

Raspberry Pi Rubik's Cube Solver

And that’s just Gordon. Given that there’s a multitude of other Pi Towers staff members who are also obsessed with the little twisty cube of wonder, you could use what you find in our office to restock an entire toy shop for the pre-Christmas rush!

So yeah, we like Rubik’s Cubes.

The 3D-Printable Rubik’s Cube Solver

Aside from the obvious electronic elements, Otvinta’s Rubik’s Cube Solving Robot is completely 3D-printable. While it may take a whopping 70 hours of print time and a whole spool of filament to make your solving robot a reality, we’ve seen far more time-consuming prints with a lot less purpose than this.

(If you’ve clicked the link above, I’d just like to point out that, while that build might be 3D printing overkill, I want one anyway.)

Rubik's Cube Solver

After 3D printing all the necessary parts of your Rubik’s Cube Solving Robot, you’ll need to run the Windows 10 IoT Core on your Raspberry Pi. Once connected to your network, you can select the Pi from the IoT Dashboard on your main PC and install the RubiksCubeRobot app.

Raspberry Pi Rubik's Cube Solver

Then simply configure the robot via the app, and you’re good to go!

You might not necessarily need a Raspberry Pi to create this build, since you could simply run the app on your main PC. However, using a Pi will make your project more manageable and less bulky.

You can find all the details of how to make your own Rubik’s Cube Solving Robot on Otvinta’s website, so do make sure to head over there if you want to learn more.

All the robots!

This isn’t the first Raspberry Pi-powered Rubik’s Cube out there, and it surely won’t be the last. There’s this one by Francesco Georg using LEGO Mindstorms; this one was originally shared on Reddit; Liz wrote about this one; and there’s one more which I can’t seem to find but I swear exists, and it looks like the Eye of Sauron! Ten House Points to whoever shares it with me in the comments below.

The post 3D print your own Rubik’s Cube Solver appeared first on Raspberry Pi.

Streaming Service iflix Buys Shows Based on Piracy Data

Post Syndicated from Ernesto original https://torrentfreak.com/streaming-service-iflix-buys-shows-based-on-piracy-data-170819/

When major movie and TV companies discuss piracy they often mention the massive losses incurred as a result of unauthorized downloads and streams.

However, this unofficial market also offers a valuable pool of often publicly available data on the media consumption habits of a relatively young generation.

Many believe that piracy is in part a market signal showing copyright holders what consumers want. This makes piracy statistics key business intelligence, which some companies have started to realize.

Netflix, for example, previously said that their offering is partly based on what shows do well on BitTorrent networks and other pirate sites. In addition, the streaming service also uses piracy to figure out how much they can charge in a country. They are not alone.

Other major entertainment companies also keep a close eye on piracy, using this data to their advantage. This includes the Asia-based streaming portal iFlix, which recently secured $133 million in funding and boasts to have over five million users.

Iflix co-founder Patrick Grove says that his company actively uses piracy numbers to determine what content they acquire. The data reveal what is popular locally, and help to give viewers the TV-shows and movies they’re most interested in.

“We looked at piracy data in every market,” Grove informed CNBC’s Managing Asia, which doesn’t stop at looking at a few torrent download numbers.

Representatives from the Asian company actually went out on the streets to buy pirated DVDs from street vendors. In addition, iflix also received help from local Internet providers which shared a variety of streaming data.

TorrentFreak reached out to the streaming service to get more details about their data gathering techniques. One of the main partners to measure online piracy is the German company TECXIPIO, which is known to actively monitor BitTorrent traffic.

The company also maintains a close relationship with Internet providers that offer further insight, including streaming data, to determine which titles work best in each market.

While analyzing the different sets of data, the streaming service was surprised to see the diversity in different regions as well as the ever-changing consumer demand.

“Through looking at the Top 20 pirated DVDs in every market we are live in, we were surprised to find the amount of pirated K-drama content. In Ghana for example, the number one pirated title is K-drama series called ‘Legend of the Blue Sea’,” an iflix spokesperson told us.

Iflix believes that piracy data is superior to other market intelligence. Before rolling out its service in Saudi Arabia the company made a list of the 1,000 most popular shows and used that to its advantage.

While there is a lot of piracy in emerging markets, iflix doesn’t think that people are not willing to pay for entertainment. It just has to be available for a decent price, and that’s where they come in.

“We believe that people in emerging markets do not actively want to steal content, they do so because there is no better alternative,” the company informs us.

“As consumers become more connected, gaining access to information and cultural influences on a global scale, they want to be entertained at a world-class standard. We set out with the aim of offering an alternative that is better than piracy; by providing unlimited access to high-quality, world-class entertainment, all at the price of pirated DVD.”

There is no doubt that iflix is ambitious, and that it’s willing to employ some unusual tactics to grow its userbase. The company is quite optimistic about the future as well, judging from its co-founder’s prediction that it will welcome its billionth viewer in a few years.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

Deploy a Data Warehouse Quickly with Amazon Redshift, Amazon RDS for PostgreSQL and Tableau Server

Post Syndicated from Jorge A. Lopez original https://aws.amazon.com/blogs/big-data/deploy-a-data-warehouse-quickly-with-amazon-redshift-amazon-rds-for-postgresql-and-tableau-server/

One of the benefits of a data warehouse environment using both Amazon Redshift and Amazon RDS for PostgreSQL is that you can leverage the advantages of each service. Amazon Redshift is a high performance, petabyte-scale data warehouse service optimized for the online analytical processing (OLAP) queries typical of analytic reporting and business intelligence applications. On the other hand, a service like RDS excels at transactional OLTP workloads such as inserting, deleting, or updating rows.

In the recent JOIN Amazon Redshift AND Amazon RDS PostgreSQL WITH dblink post, we showed how you can deploy such an environment. Now, you can deploy a similar architecture using the Modern Data Warehouse on AWS Quick Start. The Quick Start is an automated deployment that uses AWS CloudFormation templates to launch, configure, and run the services required to deploy a data warehousing environment on AWS, based on Amazon Redshift and RDS for PostgreSQL.

The Quick Start also includes an instance of Tableau Server, running on Amazon EC2. This gives you the ability to host and serve analytic dashboards, workbooks and visualizations, supported by a trial license. You can play with the sample data source and dashboard, or create your own analyses by uploading your own data sets.

For more information about the Modern Data Warehouse on AWS Quick Start, download the full deployment guide. If you’re ready to get started, use one of the buttons below:

Option 1: Deploy Quick Start into a new VPC on AWS

Option 2: Deploy Quick Start into an existing VPC

If you have questions, please leave a comment below.


Next Steps

You can also join us for the webinar Unlock Insights and Reduce Costs by Modernizing Your Data Warehouse on AWS on Tuesday, August 22, 2017. Pearson, the education and publishing company, will present best practices and lessons learned during their journey to Amazon Redshift and Tableau.

More on the Vulnerabilities Equities Process

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/08/more_on_the_vul_1.html

Richard Ledgett — a former Deputy Director of the NSA — argues against the US government disclosing all vulnerabilities:

Proponents argue that this would allow patches to be developed, which in turn would help ensure that networks are secure. On its face, this argument might seem to make sense — but it is a gross oversimplification of the problem, one that not only would not have the desired effect but that also would be dangerous.

Actually, he doesn’t make that argument at all. He basically says that security is a lot more complicated than finding and disclosing vulnerabilities — something I don’t think anyone disagrees with. His conclusion:

Malicious software like WannaCry and Petya is a scourge in our digital lives, and we need to take concerted action to protect ourselves. That action must be grounded in an accurate understanding of how the vulnerability ecosystem works. Software vendors need to continue working to build better software and to provide patching support for software deployed in critical infrastructure. Customers need to budget and plan for upgrades as part of the going-in cost of IT, or for compensatory measures when upgrades are impossible. Those who discover vulnerabilities need to responsibly disclose them or, if they are retained for national security purposes, adequately safeguard them. And the partnership of intelligence, law enforcement and industry needs to work together to identify and disrupt actors who use these vulnerabilities for their criminal and destructive ends. No single set of actions will solve the problem; we must work together to protect ourselves. As for blame, we should place it where it really lies: on the criminals who intentionally and maliciously assembled this destructive ransomware and released it on the world.

I don’t think anyone would argue with any of that, either. The question is whether the US government should prioritize attack over defense, and security over surveillance. Disclosing, especially in a world where the secrecy of zero-day vulnerabilities is so fragile, greatly improves the security of our critical systems.

NSA Collects MS Windows Error Information

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/08/nsa_collects_ms.html

Back in 2013, Der Spiegel reported that the NSA intercepts and collects Windows bug reports:

One example of the sheer creativity with which the TAO spies approach their work can be seen in a hacking method they use that exploits the error-proneness of Microsoft’s Windows. Every user of the operating system is familiar with the annoying window that occasionally pops up on screen when an internal problem is detected, an automatic message that prompts the user to report the bug to the manufacturer and to restart the program. These crash reports offer TAO specialists a welcome opportunity to spy on computers.

When TAO selects a computer somewhere in the world as a target and enters its unique identifiers (an IP address, for example) into the corresponding database, intelligence agents are then automatically notified any time the operating system of that computer crashes and its user receives the prompt to report the problem to Microsoft. An internal presentation suggests it is NSA’s powerful XKeyscore spying tool that is used to fish these crash reports out of the massive sea of Internet traffic.

The automated crash reports are a “neat way” to gain “passive access” to a machine, the presentation continues. Passive access means that, initially, only data the computer sends out into the Internet is captured and saved, but the computer itself is not yet manipulated. Still, even this passive access to error messages provides valuable insights into problems with a targeted person’s computer and, thus, information on security holes that might be exploitable for planting malware or spyware on the unwitting victim’s computer.

Although the method appears to have little importance in practical terms, the NSA’s agents still seem to enjoy it because it allows them to have a bit of a laugh at the expense of the Seattle-based software giant. In one internal graphic, they replaced the text of Microsoft’s original error message with one of their own reading, “This information may be intercepted by a foreign sigint system to gather detailed information and better exploit your machine.” (“Sigint” stands for “signals intelligence.”)

The article talks about the (limited) value of this information with regard to specific target computers, but I have another question: how valuable would this database be for finding new zero-day Windows vulnerabilities to exploit? Microsoft won’t have the incentive to examine and fix problems until they happen broadly among its user base. The NSA has a completely different incentive structure.

I don’t remember this being discussed back in 2013.

EDITED TO ADD (8/6): Slashdot thread.

Top 10 Most Obvious Hacks of All Time (v0.9)

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/07/top-10-most-obvious-hacks-of-all-time.html

For teaching hacking/cybersecurity, I thought I’d create of the most obvious hacks of all time. Not the best hacks, the most sophisticated hacks, or the hacks with the biggest impact, but the most obvious hacks — ones that even the least knowledgeable among us should be able to understand. Below I propose some hacks that fit this bill, though in no particular order.

The reason I’m writing this is that my niece wants me to teach her some hacking. I thought I’d start with the obvious stuff first.

Shared Passwords

If you use the same password for every website, and one of those websites gets hacked, then the hacker has your password for all your websites. The reason your Facebook account got hacked wasn’t because of anything Facebook did, but because you used the same email-address and password when creating an account on “beagleforums.com”, which got hacked last year.

I’ve heard people say “I’m sure, because I choose a complex password and use it everywhere”. No, this is the very worst thing you can do. Sure, you can the use the same password on all sites you don’t care much about, but for Facebook, your email account, and your bank, you should have a unique password, so that when other sites get hacked, your important sites are secure.

And yes, it’s okay to write down your passwords on paper.

Tools: HaveIBeenPwned.com

PIN encrypted PDFs

My accountant emails PDF statements encrypted with the last 4 digits of my Social Security Number. This is not encryption — a 4 digit number has only 10,000 combinations, and a hacker can guess all of them in seconds.
PIN numbers for ATM cards work because ATM machines are online, and the machine can reject your card after four guesses. PIN numbers don’t work for documents, because they are offline — the hacker has a copy of the document on their own machine, disconnected from the Internet, and can continue making bad guesses with no restrictions.
Passwords protecting documents must be long enough that even trillion upon trillion guesses are insufficient to guess.

Tools: Hashcat, John the Ripper

SQL and other injection

The lazy way of combining websites with databases is to combine user input with an SQL statement. This combines code with data, so the obvious consequence is that hackers can craft data to mess with the code.
No, this isn’t obvious to the general public, but it should be obvious to programmers. The moment you write code that adds unfiltered user-input to an SQL statement, the consequence should be obvious. Yet, “SQL injection” has remained one of the most effective hacks for the last 15 years because somehow programmers don’t understand the consequence.
CGI shell injection is a similar issue. Back in early days, when “CGI scripts” were a thing, it was really important, but these days, not so much, so I just included it with SQL. The consequence of executing shell code should’ve been obvious, but weirdly, it wasn’t. The IT guy at the company I worked for back in the late 1990s came to me and asked “this guy says we have a vulnerability, is he full of shit?”, and I had to answer “no, he’s right — obviously so”.

XSS (“Cross Site Scripting”) [*] is another injection issue, but this time at somebody’s web browser rather than a server. It works because websites will echo back what is sent to them. For example, if you search for Cross Site Scripting with the URL https://www.google.com/search?q=cross+site+scripting, then you’ll get a page back from the server that contains that string. If the string is JavaScript code rather than text, then some servers (thought not Google) send back the code in the page in a way that it’ll be executed. This is most often used to hack somebody’s account: you send them an email or tweet a link, and when they click on it, the JavaScript gives control of the account to the hacker.

Cross site injection issues like this should probably be their own category, but I’m including it here for now.

More: Wikipedia on SQL injection, Wikipedia on cross site scripting.
Tools: Burpsuite, SQLmap

Buffer overflows

In the C programming language, programmers first create a buffer, then read input into it. If input is long than the buffer, then it overflows. The extra bytes overwrite other parts of the program, letting the hacker run code.
Again, it’s not a thing the general public is expected to know about, but is instead something C programmers should be expected to understand. They should know that it’s up to them to check the length and stop reading input before it overflows the buffer, that there’s no language feature that takes care of this for them.
We are three decades after the first major buffer overflow exploits, so there is no excuse for C programmers not to understand this issue.

What makes particular obvious is the way they are wrapped in exploits, like in Metasploit. While the bug itself is obvious that it’s a bug, actually exploiting it can take some very non-obvious skill. However, once that exploit is written, any trained monkey can press a button and run the exploit. That’s where we get the insult “script kiddie” from — referring to wannabe-hackers who never learn enough to write their own exploits, but who spend a lot of time running the exploit scripts written by better hackers than they.

More: Wikipedia on buffer overflow, Wikipedia on script kiddie,  “Smashing The Stack For Fun And Profit” — Phrack (1996)
Tools: bash, Metasploit

SendMail DEBUG command (historical)

The first popular email server in the 1980s was called “SendMail”. It had a feature whereby if you send a “DEBUG” command to it, it would execute any code following the command. The consequence of this was obvious — hackers could (and did) upload code to take control of the server. This was used in the Morris Worm of 1988. Most Internet machines of the day ran SendMail, so the worm spread fast infecting most machines.
This bug was mostly ignored at the time. It was thought of as a theoretical problem, that might only rarely be used to hack a system. Part of the motivation of the Morris Worm was to demonstrate that such problems was to demonstrate the consequences — consequences that should’ve been obvious but somehow were rejected by everyone.

More: Wikipedia on Morris Worm

Email Attachments/Links

I’m conflicted whether I should add this or not, because here’s the deal: you are supposed to click on attachments and links within emails. That’s what they are there for. The difference between good and bad attachments/links is not obvious. Indeed, easy-to-use email systems makes detecting the difference harder.
On the other hand, the consequences of bad attachments/links is obvious. That worms like ILOVEYOU spread so easily is because people trusted attachments coming from their friends, and ran them.
We have no solution to the problem of bad email attachments and links. Viruses and phishing are pervasive problems. Yet, we know why they exist.

Default and backdoor passwords

The Mirai botnet was caused by surveillance-cameras having default and backdoor passwords, and being exposed to the Internet without a firewall. The consequence should be obvious: people will discover the passwords and use them to take control of the bots.
Surveillance-cameras have the problem that they are usually exposed to the public, and can’t be reached without a ladder — often a really tall ladder. Therefore, you don’t want a button consumers can press to reset to factory defaults. You want a remote way to reset them. Therefore, they put backdoor passwords to do the reset. Such passwords are easy for hackers to reverse-engineer, and hence, take control of millions of cameras across the Internet.
The same reasoning applies to “default” passwords. Many users will not change the defaults, leaving a ton of devices hackers can hack.

Masscan and background radiation of the Internet

I’ve written a tool that can easily scan the entire Internet in a short period of time. It surprises people that this possible, but it obvious from the numbers. Internet addresses are only 32-bits long, or roughly 4 billion combinations. A fast Internet link can easily handle 1 million packets-per-second, so the entire Internet can be scanned in 4000 seconds, little more than an hour. It’s basic math.
Because it’s so easy, many people do it. If you monitor your Internet link, you’ll see a steady trickle of packets coming in from all over the Internet, especially Russia and China, from hackers scanning the Internet for things they can hack.
People’s reaction to this scanning is weirdly emotional, taking is personally, such as:
  1. Why are they hacking me? What did I do to them?
  2. Great! They are hacking me! That must mean I’m important!
  3. Grrr! How dare they?! How can I hack them back for some retribution!?

I find this odd, because obviously such scanning isn’t personal, the hackers have no idea who you are.

Tools: masscan, firewalls

Packet-sniffing, sidejacking

If you connect to the Starbucks WiFi, a hacker nearby can easily eavesdrop on your network traffic, because it’s not encrypted. Windows even warns you about this, in case you weren’t sure.

At DefCon, they have a “Wall of Sheep”, where they show passwords from people who logged onto stuff using the insecure “DefCon-Open” network. Calling them “sheep” for not grasping this basic fact that unencrypted traffic is unencrypted.

To be fair, it’s actually non-obvious to many people. Even if the WiFi itself is not encrypted, SSL traffic is. They expect their services to be encrypted, without them having to worry about it. And in fact, most are, especially Google, Facebook, Twitter, Apple, and other major services that won’t allow you to log in anymore without encryption.

But many services (especially old ones) may not be encrypted. Unless users check and verify them carefully, they’ll happily expose passwords.

What’s interesting about this was 10 years ago, when most services which only used SSL to encrypt the passwords, but then used unencrypted connections after that, using “cookies”. This allowed the cookies to be sniffed and stolen, allowing other people to share the login session. I used this on stage at BlackHat to connect to somebody’s GMail session. Google, and other major websites, fixed this soon after. But it should never have been a problem — because the sidejacking of cookies should have been obvious.

Tools: Wireshark, dsniff

Stuxnet LNK vulnerability

Again, this issue isn’t obvious to the public, but it should’ve been obvious to anybody who knew how Windows works.
When Windows loads a .dll, it first calls the function DllMain(). A Windows link file (.lnk) can load icons/graphics from the resources in a .dll file. It does this by loading the .dll file, thus calling DllMain. Thus, a hacker could put on a USB drive a .lnk file pointing to a .dll file, and thus, cause arbitrary code execution as soon as a user inserted a drive.
I say this is obvious because I did this, created .lnks that pointed to .dlls, but without hostile DllMain code. The consequence should’ve been obvious to me, but I totally missed the connection. We all missed the connection, for decades.

Social Engineering and Tech Support [* * *]

After posting this, many people have pointed out “social engineering”, especially of “tech support”. This probably should be up near #1 in terms of obviousness.

The classic example of social engineering is when you call tech support and tell them you’ve lost your password, and they reset it for you with minimum of questions proving who you are. For example, you set the volume on your computer really loud and play the sound of a crying baby in the background and appear to be a bit frazzled and incoherent, which explains why you aren’t answering the questions they are asking. They, understanding your predicament as a new parent, will go the extra mile in helping you, resetting “your” password.

One of the interesting consequences is how it affects domain names (DNS). It’s quite easy in many cases to call up the registrar and convince them to transfer a domain name. This has been used in lots of hacks. It’s really hard to defend against. If a registrar charges only $9/year for a domain name, then it really can’t afford to provide very good tech support — or very secure tech support — to prevent this sort of hack.

Social engineering is such a huge problem, and obvious problem, that it’s outside the scope of this document. Just google it to find example after example.

A related issue that perhaps deserves it’s own section is OSINT [*], or “open-source intelligence”, where you gather public information about a target. For example, on the day the bank manager is out on vacation (which you got from their Facebook post) you show up and claim to be a bank auditor, and are shown into their office where you grab their backup tapes. (We’ve actually done this).

More: Wikipedia on Social Engineering, Wikipedia on OSINT, “How I Won the Defcon Social Engineering CTF” — blogpost (2011), “Questioning 42: Where’s the Engineering in Social Engineering of Namespace Compromises” — BSidesLV talk (2016)

Blue-boxes (historical) [*]

Telephones historically used what we call “in-band signaling”. That’s why when you dial on an old phone, it makes sounds — those sounds are sent no differently than the way your voice is sent. Thus, it was possible to make tone generators to do things other than simply dial calls. Early hackers (in the 1970s) would make tone-generators called “blue-boxes” and “black-boxes” to make free long distance calls, for example.

These days, “signaling” and “voice” are digitized, then sent as separate channels or “bands”. This is call “out-of-band signaling”. You can’t trick the phone system by generating tones. When your iPhone makes sounds when you dial, it’s entirely for you benefit and has nothing to do with how it signals the cell tower to make a call.

Early hackers, like the founders of Apple, are famous for having started their careers making such “boxes” for tricking the phone system. The problem was obvious back in the day, which is why as the phone system moves from analog to digital, the problem was fixed.

More: Wikipedia on blue box, Wikipedia article on Steve Wozniak.

Thumb drives in parking lots [*]

A simple trick is to put a virus on a USB flash drive, and drop it in a parking lot. Somebody is bound to notice it, stick it in their computer, and open the file.

This can be extended with tricks. For example, you can put a file labeled “third-quarter-salaries.xlsx” on the drive that required macros to be run in order to open. It’s irresistible to other employees who want to know what their peers are being paid, so they’ll bypass any warning prompts in order to see the data.

Another example is to go online and get custom USB sticks made printed with the logo of the target company, making them seem more trustworthy.

We also did a trick of taking an Adobe Flash game “Punch the Monkey” and replaced the monkey with a logo of a competitor of our target. They now only played the game (infecting themselves with our virus), but gave to others inside the company to play, infecting others, including the CEO.

Thumb drives like this have been used in many incidents, such as Russians hacking military headquarters in Afghanistan. It’s really hard to defend against.

More: “Computer Virus Hits U.S. Military Base in Afghanistan” — USNews (2008), “The Return of the Worm That Ate The Pentagon” — Wired (2011), DoD Bans Flash Drives — Stripes (2008)

Googling [*]

Search engines like Google will index your website — your entire website. Frequently companies put things on their website without much protection because they are nearly impossible for users to find. But Google finds them, then indexes them, causing them to pop up with innocent searches.
There are books written on “Google hacking” explaining what search terms to look for, like “not for public release”, in order to find such documents.

More: Wikipedia entry on Google Hacking, “Google Hacking” book.

URL editing [*]

At the top of every browser is what’s called the “URL”. You can change it. Thus, if you see a URL that looks like this:

http://www.example.com/documents?id=138493

Then you can edit it to see the next document on the server:

http://www.example.com/documents?id=138494

The owner of the website may think they are secure, because nothing points to this document, so the Google search won’t find it. But that doesn’t stop a user from manually editing the URL.
An example of this is a big Fortune 500 company that posts the quarterly results to the website an hour before the official announcement. Simply editing the URL from previous financial announcements allows hackers to find the document, then buy/sell the stock as appropriate in order to make a lot of money.
Another example is the classic case of Andrew “Weev” Auernheimer who did this trick in order to download the account email addresses of early owners of the iPad, including movie stars and members of the Obama administration. It’s an interesting legal case because on one hand, techies consider this so obvious as to not be “hacking”. On the other hand, non-techies, especially judges and prosecutors, believe this to be obviously “hacking”.

DDoS, spoofing, and amplification [*]

For decades now, online gamers have figured out an easy way to win: just flood the opponent with Internet traffic, slowing their network connection. This is called a DoS, which stands for “Denial of Service”. DoSing game competitors is often a teenager’s first foray into hacking.
A variant of this is when you hack a bunch of other machines on the Internet, then command them to flood your target. (The hacked machines are often called a “botnet”, a network of robot computers). This is called DDoS, or “Distributed DoS”. At this point, it gets quite serious, as instead of competitive gamers hackers can take down entire businesses. Extortion scams, DDoSing websites then demanding payment to stop, is a common way hackers earn money.
Another form of DDoS is “amplification”. Sometimes when you send a packet to a machine on the Internet it’ll respond with a much larger response, either a very large packet or many packets. The hacker can then send a packet to many of these sites, “spoofing” or forging the IP address of the victim. This causes all those sites to then flood the victim with traffic. Thus, with a small amount of outbound traffic, the hacker can flood the inbound traffic of the victim.
This is one of those things that has worked for 20 years, because it’s so obvious teenagers can do it, yet there is no obvious solution. President Trump’s executive order of cyberspace specifically demanded that his government come up with a report on how to address this, but it’s unlikely that they’ll come up with any useful strategy.

More: Wikipedia on DDoS, Wikipedia on Spoofing

Conclusion

Tweet me (@ErrataRob) your obvious hacks, so I can add them to the list.

Portugal’s Pirate Site-Blocking System Works “Great,” Study Shows

Post Syndicated from Ernesto original https://torrentfreak.com/portugals-pirate-site-blocking-system-works-great-study-shows-170728/

Rather than taking site operators to court, copyright holders increasingly demand that Internet providers should block access to ‘pirate’ domains instead.

As a result, courts all around the world have ordered ISPs to block subscriber access to various pirate sites. But there are other ways.

In Portugal, a voluntary process was formalized through an agreement between ISPs, rightsholders, and the Ministry of Culture and the Association of Telecommunication Operators.

The voluntary deal was struck two years ago, shortly after local Internet Providers were ordered to block access to The Pirate Bay. The agreement conveniently allows copyright holders to add new pirate sites without any intervention or oversight from a court.

The MPAA is happy with the non-adversarial collaboration and praises it as the best international example of anti-piracy practices. The Hollywood group has already presented the Portuguese model to the Spanish Senate and plans to do the same before the French Senate.

Aside from a smooth process, the results of the voluntary blocking deal are also important. This is why the MPA and Portuguese anti-piracy outfit FEVIP commissioned a study into its effects.

The results, published by INCOPRO this week, show that of the 250 most-used pirate sites in Portugal, 65 are blocked. Traffic to these blocked sites decreased 56.6 percent after the blocks were implemented, contrary to a 3.9 percent increase globally.

In total, usage of the top 250 pirate sites decreased 9.3 percent, while a control group showed that the same sites enjoyed a 30.8 percent increase in usage globally.

In summary, the research confirms that traffic to blocked sites has decreased significantly. This shouldn’t really come as a surprise, as these domains are blocked after all. Whether traffic over VPN or people visiting smaller pirate sites subsequently increased was not covered by the research.

Earlier research, using INCOPRO’s own methodology, has shown that while blocked domains get less traffic, many sites simply move to other domain names where they enjoy a significant and sustained boost in traffic.

The current research did look at proxy site traffic but concludes that this only substitutes a small portion of the traffic that went to pirate sites before the blockades.

“Though usage is migrating to alternate sites in some cases, this shift of usage amounts to only minor proportions of previous pre-block usage,” the report reads.

Stan McCoy, President and Managing Director of the Motion Picture Association’s EMEA region, backs the study’s findings which he says confirm that piracy can be curbed.

“At the MPA, we take a three pronged approach: make legal content easy to access, engage consumers about the negative impact of piracy, and deter piracy through the appropriate legal avenues. All stakeholders must work together as joint stewards of the creative ecosystem,” McCoy notes.

The results of INCOPRO’s research will undoubtedly be used to convince lawmakers and other stakeholders to implement a similar blocking deal elsewhere.

Or to put it into the words of Helen Saunders, head of Intelligence and Operations at INCOPRO, they might serve as inspiration.

“It’s fantastic to see that more countries are starting to take action against piracy, and are getting great results. We hope that this report will inspire even more geographies to take similar action in a concerted effort to safeguard the global entertainment industry,” Saunders says.

Ironically, while American movie studios are working hard to convince foreign ISPs and governments to jump on board, Internet subscribers in the United States can still freely access all the pirate sites they want. No website blocking plans have been sighted on Hollywood’s home turf, yet.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

AWS Hot Startups – July 2017

Post Syndicated from Tina Barr original https://aws.amazon.com/blogs/aws/aws-hot-startups-july-2017/

Welcome back to another month of Hot Startups! Every day, startups are creating innovative and exciting businesses, applications, and products around the world. Each month we feature a handful of startups doing cool things using AWS.

July is all about learning! These companies are focused on providing access to tools and resources to expand knowledge and skills in different ways.

This month’s startups:

  • CodeHS – provides fun and accessible computer science curriculum for middle and high schools.
  • Insight – offers intensive fellowships to grow technical talent in Data Science.
  • iTranslate – enables people to read, write, and speak in over 90 languages, anywhere in the world.

CodeHS (San Francisco, CA)

In 2012, Stanford students Zach Galant and Jeremy Keeshin were computer science majors and TAs for introductory classes when they noticed a trend among their peers. Many wished that they had been exposed to computer science earlier in life. In their senior year, Zach and Jeremy launched CodeHS to give middle and high schools the opportunity to provide a fun, accessible computer science education to students everywhere. CodeHS is a web-based curriculum pathway complete with teacher resources, lesson plans, and professional development opportunities. The curriculum is supplemented with time-saving teacher tools to help with lesson planning, grading and reviewing student code, and managing their classroom.

CodeHS aspires to empower all students to meaningfully impact the future, and believe that coding is becoming a new foundational skill, along with reading and writing, that allows students to further explore any interest or area of study. At the time CodeHS was founded in 2012, only 10% of high schools in America offered a computer science course. Zach and Jeremy set out to change that by providing a solution that made it easy for schools and districts to get started. With CodeHS, thousands of teachers have been trained and are teaching hundreds of thousands of students all over the world. To use CodeHS, all that’s needed is the internet and a web browser. Students can write and run their code online, and teachers can immediately see what the students are working on and how they are doing.

Amazon EC2, Amazon RDS, Amazon ElastiCache, Amazon CloudFront, and Amazon S3 make it possible for CodeHS to scale their site to meet the needs of schools all over the world. CodeHS also relies on AWS to compile and run student code in the browser, which is extremely important when teaching server-side languages like Java that powers the AP course. Since usage rises and falls based on school schedules, Amazon CloudWatch and ELBs are used to easily scale up when students are running code so they have a seamless experience.

Be sure to visit the CodeHS website, and to learn more about bringing computer science to your school, click here!

Insight (Palo Alto, CA)

Insight was founded in 2012 to create a new educational model, optimize hiring for data teams, and facilitate successful career transitions among data professionals. Over the last 5 years, Insight has kept ahead of market trends and launched a series of professional training fellowships including Data Science, Health Data Science, Data Engineering, and Artificial Intelligence. Finding individuals with the right skill set, background, and culture fit is a challenge for big companies and startups alike, and Insight is focused on developing top talent through intensive 7-week fellowships. To date, Insight has over 1,000 alumni at over 350 companies including Amazon, Google, Netflix, Twitter, and The New York Times.

The Data Engineering team at Insight is well-versed in the current ecosystem of open source tools and technologies and provides mentorship on the best practices in this space. The technical teams are continually working with external groups in a variety of data advisory and mentorship capacities, but the majority of Insight partners participate in professional sessions. Companies visit the Insight office to speak with fellows in an informal setting and provide details on the type of work they are doing and how their teams are growing. These sessions have proved invaluable as fellows experience a significantly better interview process and companies yield engaged and enthusiastic new team members.

An important aspect of Insight’s fellowships is the opportunity for hands-on work, focusing on everything from building big-data pipelines to contributing novel features to industry-standard open source efforts. Insight provides free AWS resources for all fellows to use, in addition to mentorships from the Data Engineering team. Fellows regularly utilize Amazon S3, Amazon EC2, Amazon Kinesis, Amazon EMR, AWS Lambda, Amazon Redshift, Amazon RDS, among other services. The experience with AWS gives fellows a solid skill set as they transition into the industry. Fellowships are currently being offered in Boston, New York, Seattle, and the Bay Area.

Check out the Insight blog for more information on trends in data infrastructure, artificial intelligence, and cutting-edge data products.

 

iTranslate (Austria)

When the App Store was introduced in 2008, the founders of iTranslate saw an opportunity to be part of something big. The group of four fully believed that the iPhone and apps were going to change the world, and together they brainstormed ideas for their own app. The combination of translation and mobile devices seemed a natural fit, and by 2009 iTranslate was born. iTranslate’s mission is to enable travelers, students, business professionals, employers, and medical staff to read, write, and speak in all languages, anywhere in the world. The app allows users to translate text, voice, websites and more into nearly 100 languages on various platforms. Today, iTranslate is the leading player for conversational translation and dictionary apps, with more than 60 million downloads and 6 million monthly active users.

iTranslate is breaking language barriers through disruptive technology and innovation, enabling people to translate in real time. The app has a variety of features designed to optimize productivity including offline translation, website and voice translation, and language auto detection. iTranslate also recently launched the world’s first ear translation device in collaboration with Bragi, a company focused on smart earphones. The Dash Pro allows people to communicate freely, while having a personal translator right in their ear.

iTranslate started using Amazon Polly soon after it was announced. CEO Alexander Marktl said, “As the leading translation and dictionary app, it is our mission at iTranslate to provide our users with the best possible tools to read, write, and speak in all languages across the globe. Amazon Polly provides us with the ability to efficiently produce and use high quality, natural sounding synthesized speech.” The stable and simple-to-use API, low latency, and free caching allow iTranslate to scale as they continue adding features to their app. Customers also enjoy the option to change speech rate and change between male and female voices. To assure quality, speed, and reliability of their products, iTranslate also uses Amazon EC2, Amazon S3, and Amazon Route 53.

To get started with iTranslate, visit their website here.

—–

Thanks for reading!

-Tina

Kim Dotcom Spying Fiasco Puts Prime Minister Under Pressure

Post Syndicated from Andy original https://torrentfreak.com/kim-dotcom-spying-fiasco-puts-prime-minister-under-pressure-170725/

In the lead up to the January 2012 raid on cloud storage site Megaupload, authorities in New Zealand used the Government Communications Security Bureau (GCSB) agency to spy on Kim and Mona Dotcom, plus Megaupload co-defendant Bram van der Kolk. That should not have happened.

Intelligence agency GCSB was forbidden by law from conducting surveillance on its own citizens or permanent residents in the country. Former Prime Minister John Key later apologized for the glaring error but for Dotcom, that wasn’t enough. The entrepreneur launched legal action in pursuit of the information illegally obtained by GCSB and appropriate compensation.

Last week the High Court decided that Dotcom wouldn’t get access to the information but it also revealed something of much interest. Instead of confirming that the illegal spying on Dotcom took place December 16, 2011, through to January 20, 2012, the range was extended by two months to March 22, 2012.

The implications of the extension are numerous, not least that GCSB continued to spy on Dotcom even after it knew it was acting illegally. The reveal also undermines an earlier affidavit from a GCSB staff member, problems which are now returning to haunt New Zealand Prime Minister, Bill English.

When the spying was taking place, John Key was Prime Minister but when Key traveled overseas, English was left at the helm. As a result, when the possibility that Dotcom had been spied on was raised during court hearings in 2012, it was English who was approached by the GCSB with a request to have its involvement made a state secret.

According to NZHerald, English was briefed by then-GCSB director Ian Fletcher and former acting director Hugh Wolfensohn on GCSB’s assistance to the police in the Dotcom case.

The content of those discussion has not been made public but English appears to have been convinced of the need to keep the information private. He subsequently signed a ministerial certificate, which barred disclosure of GCSB activities, even by people asked to provide them in a court of law.

However, since GCSB had broken the law by illegally spying on the Dotcoms and van Der Kolk, the certificate subsequently collapsed. But, like a dog with a bone, Dotcom isn’t letting this go, claiming that acting Prime Minister English acted unlawfully by signing the certificate in an effort to suppress wrong-doing.

“The ministerial certificate was an attempted cover-up. Bill English must have been briefed that GCSB was facing legal troubles because of unlawful conduct,” he told NZHerald.

“And only after the attempted gag-order failed in the High Court did the Government admit unlawful spying with a fake narrative that it was all a big mistake, a misunderstanding of the law, an error.”

Following the judgment last week that revealed the extended spying period, Dotcom confirms that there will be fresh legal action to obtain information from GCSB.

“The new revelations completely undermine the government narrative and it raises new questions about what really happened,” Dotcom concludes.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

Alternatives to Government-Mandated Encryption Backdoors

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/07/alternatives_to_1.html

Policy essay: “Encryption Substitutes,” by Andrew Keane Woods:

In this short essay, I make a few simple assumptions that bear mentioning at the outset. First, I assume that governments have good and legitimate reasons for getting access to personal data. These include things like controlling crime, fighting terrorism, and regulating territorial borders. Second, I assume that people have a right to expect privacy in their personal data. Therefore, policymakers should seek to satisfy both law enforcement and privacy concerns without unduly burdening one or the other. Of course, much of the debate over government access to data is about how to respect both of these assumptions. Different actors will make different trade-offs. My aim in this short essay is merely to show that regardless of where one draws this line — whether one is more concerned with ensuring privacy of personal information or ensuring that the government has access to crucial evidence — it would be shortsighted and counterproductive to draw that line with regard to one particular privacy technique and without regard to possible substitutes. The first part of the paper briefly characterizes the encryption debate two ways: first, as it is typically discussed, in stark, uncompromising terms; and second, as a subset of a broader problem. The second part summarizes several avenues available to law enforcement and intelligence agencies seeking access to data. The third part outlines the alternative avenues available to privacy-seekers. The availability of substitutes is relevant to the regulators but also to the regulated. If the encryption debate is one tool in a game of cat and mouse, the cat has other tools at his disposal to catch the mouse — and the mouse has other tools to evade the cat. The fourth part offers some initial thoughts on implications for the privacy debate.

Blog post.

US Army Researching Bot Swarms

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/07/us_army_researc.html

The US Army Research Agency is funding research into autonomous bot swarms. From the announcement:

The objective of this CRA is to perform enabling basic and applied research to extend the reach, situational awareness, and operational effectiveness of large heterogeneous teams of intelligent systems and Soldiers against dynamic threats in complex and contested environments and provide technical and operational superiority through fast, intelligent, resilient and collaborative behaviors. To achieve this, ARL is requesting proposals that address three key Research Areas (RAs):

RA1: Distributed Intelligence: Establish the theoretical foundations of multi-faceted distributed networked intelligent systems combining autonomous agents, sensors, tactical super-computing, knowledge bases in the tactical cloud, and human experts to acquire and apply knowledge to affect and inform decisions of the collective team.

RA2: Heterogeneous Group Control: Develop theory and algorithms for control of large autonomous teams with varying levels of heterogeneity and modularity across sensing, computing, platforms, and degree of autonomy.

RA3: Adaptive and Resilient Behaviors: Develop theory and experimental methods for heterogeneous teams to carry out tasks under the dynamic and varying conditions in the physical world.

Slashdot thread.

And while we’re on the subject, this is an excellent report on AI and national security.

Google Pi Intercom with the AIY Projects kit

Post Syndicated from Janina Ander original https://www.raspberrypi.org/blog/google-pi-intercom-aiy-projects/

When we released the Google AIY Projects kit with Issue 57 of The MagPi in May, we could hardly wait to see what you in the community would build with it. Being able to add voice interaction to your Raspberry Pi projects opens up a world of possibilities for exciting digital making.

One such project is maker Martin Mander‘s Google Pi Intercom. We love this build for its retro feel and modern functionality, a combination of characteristics shared by many of Martin’s creations.

1986 Google Pi Intercom

This is a 1986 Radio Shack Intercom that I’ve converted into a Google Home style device using a Raspberry Pi and the Google AIY (Artificial Intelligence Yourself) kit that came free with the MagPi magazine (issue 57). It uses the Google Assistant to answer questions and perform actions, using IFTTT to integrate with smart home accessories and other web services.

Inter-com again?

If you’ve paid any attention at all to the world of Raspberry Pi in the last few months, you’ve probably seen the Google AIY Projects kit that came free with The MagPi #57. It includes a practical cardboard housing, but of course makers everywhere have been upgrading their kits, for example by creating a laser-cut wooden box. Martin, however, has taken things to the next level: he’s installed his AIY kit in a wall-mounted intercom from 1986.

Google Pi intercom Martin Mander

The components of the Google Pi Intercom

It’s all (inter)coming together

Martin already had not one, but three vintage intercoms at home. So when he snatched up an AIY Projects kit, there was no doubt in his mind about how he was going to use it:

The moment I scooped the Google AIY kit, I knew that one of these old units would be a perfect match for it – after all, both were essentially based on a button, microphone, and loudspeaker, just with different technology in between.

Preparing the intercom housing

First, Martin gutted the intercom and ground away some of the excess plastic inside. This was necessary because integrating all the components was going to be a tight fit. To overhaul its look, he then gave the housing a good scrub and a new paint job. For a splash of colour, Martin affixed a strip of paper in the palette of the Google logo.

Google Pi intercom Martin Mander

BUBBLES!

Building the Google Pi Intercom

The intercom’s speaker wasn’t going to provide good enough sound quality. Moreover, Martin quickly realised that the one included in the AIY kit was too big for this make. He hunted down a small speaker online, and set about wiring everything up.

Google Pi intercom Martin Mander

Assembling the electronics

Martin wanted the build to resemble the original intercom as closely as possible. Consequently, he was keen to use its tilting bar to activate the device’s voice command function. Luckily, it was easy to mount the AIY kit’s button behind the bar.

Google Pi intercom Martin Mander

Using the intercom’s tilting bar switch

Finally it was only a matter of using some hot glue and a few screws and bolts to secure all the components inside the housing. Once he’d done that, Martin just had to set up the software of the Google Assistant, and presto! He had a voice-controlled smart device for home automation.

A pretty snazzy-looking build, isn’t it? If you’d like to learn more about Martin’s Google Pi Intercom, head over to the Instructables page for a complete rundown.

Google Pi intercom Martin Mander

Awaiting your command

The AIY Projects Kit

Didn’t manage to snap up an AIY Projects kit? Find out how to get your hands on one over at The MagPi.

Or do you have an AIY kit at home? Lucky you! You can follow our shiny new learning resource to get started with using it. There are also lots of handy articles about the kit in The MagPi #57 – download the PDF version here. If you’re stuck, or looking for inspiration, check out our AIY Projects subforum. Ask your questions, and help others by answering theirs.

What have you built with your AIY Projects kit? Be sure to share your voice-controlled project with us in the comments.

 

The post Google Pi Intercom with the AIY Projects kit appeared first on Raspberry Pi.

Kim Dotcom Denied Access to Illegally Obtained Spy Recordings

Post Syndicated from Andy original https://torrentfreak.com/kim-dotcom-denied-access-to-illegally-obtained-spy-recordings-170720/

In the months leading up to the infamous raid on Kim Dotcom’s New Zealand mansion and his now defunct cloud storage site Megaupload, the entrepreneur was under surveillance.

Not only were the MPAA and RIAA amassing information, the governments of the United States and New Zealand were neck-deep in the investigation too, using the FBI and local police to gather information. What soon became evident, however, is that the authorities in New Zealand did so while breaking the rules.

Between 16 December 2011 to 22 March 2012, New Zealand used the Government Communications Security Bureau (GCSB) agency to spy on the private communications of Kim and Mona Dotcom, plus Megaupload co-defendant Bram van der Kolk. This was hugely problematic.

GCSB is an intelligence agency of the New Zealand government responsible for spying on external entities. It is forbidden by law from conducting surveillance on its own citizens or permanent residents in the country. His standing in the country meant that Dotcom should not have been spied on.

“Of course I apologize to Mr Dotcom, and I apologize to New Zealanders,” then New Zealand Prime Minister John Key later said.

Since it was established that New Zealand illegally spied on Dotcom, the Megaupload founder has been trying to find out what information the GCSB gathered about him, then wife Mona, and former colleague Bram van der Kolk. According to Dotcom, there was a total of 87 breaches, all of which the government wants to keep secret.

Since then, Dotcom has been fighting to gain access to the information GCSB illegally obtained, while seeking compensation for the damages caused.

In a ruling handed down this morning, the High Court details its findings in respect of a three-day hearing that took place early April 2017, during which GCSB said the raw, unredacted information should be withheld from Dotcom on national security grounds.

GCSB and the government argued that the public interest in the disclosure of the material is outweighed by the public interest in withholding it, adding that the security and defense of New Zealand would be compromised on the world stage.

For their part, the Dotcoms said that nondisclosure of the unredacted documents breaches their rights under the New Zealand Bill of Rights Act 1990. Given that any damages award is directly linked to the extent and nature of the illegal intrusions into their private lives, access to the documents is paramount.

That being the case, they argued that the public interest in disclosure outweighs any public interest in the information being withheld.

This morning, citing a 2013 Court of Appeal verdict that ruled the GCSB didn’t have to release the raw communications, Justice Murray Gilbert insisted that the recordings will not be released.

“A number of the redactions in the discovered documents are to protect the identity or contact details of personnel who were involved in or associated with the operation or copied into email communications concerning it,” Justice Gilbert wrote.

“It is hard to see how any of this information could be relevant to the relief that should be granted in this proceeding. Again, the public interest in withholding disclosure of this information far outweighs any public interest in its disclosure.”

In a statement, Kim Dotcom expressed his frustrations, noting that the government is doing everything it can to suppress details of the illegal surveillance.

“After being caught, the GCSB has fought to keep what it did, and how, a secret from me and from you, the New Zealand public. Worse, it seeks to hide behind ‘national security’ to keep the truth from us,” Dotcom said.

“To keep this secret, the GCSB applied to the High Court. It filed secret evidence and secret submissions. The GCSB’s lawyers were heard in a ‘closed’ court with the Judge, where they made secret submissions and secret witnesses gave secret evidence.”

Dotcom said neither his lawyers nor the public was allowed to be present during the hearing. And when his legal team could be heard, they were significantly hampered in their work.

“When my lawyers were heard, after that hearing, they had to make submissions as to why information they were not allowed to see, for reasons they were not allowed to know, should be disclosed. They were effectively shooting at a moving target, in the dark, with one hand tied behind their backs,” Dotcom said.

The Megaupload founder suggests there is there is a clear double-standard when he has to be tried in public for his alleged crimes, but when it comes to offenses carried out by the government, the process takes place behind closed doors.

“I will appeal this judgment and ask the Court of Appeal to shine some cleansing sunlight on what happened here. If there is transparency, there is accountability, and we can prevent this happening again,” he concludes.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

Journey into Deep Learning with AWS

Post Syndicated from Tara Walker original https://aws.amazon.com/blogs/aws/journey-into-deep-learning-with-aws/

If you are anything like me, Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning are completely fascinating and exciting topics. As AI, ML, and Deep Learning become more widely used, for me it means that the science fiction written by Dr. Issac Asimov, the robotics and medical advancements in Star Wars, and the technologies that enabled Captain Kirk and his Star Trek crew “to boldly go where no man has gone before” can become achievable realities.

 

Most people interested in the aforementioned topics are familiar with the AI and ML solutions enabled by Deep Learning, such as Convolutional Neural Networks for Image and Video Classification, Speech Recognition, Natural Language interfaces, and Recommendation Engines. However, it is not always an easy task setting up the infrastructure, environment, and tools to enable data scientists, machine learning practitioners, research scientists, and deep learning hobbyists/advocates to dive into these technologies. Most developers desire to go quickly from getting started with deep learning to training models and developing solutions using deep learning technologies.

For these reasons, I would like to share some resources that will help to quickly build deep learning solutions whether you are an experienced data scientist or a curious developer wanting to get started.

Deep Learning Resources

The Apache MXNet is Amazon’s deep learning framework of choice. With the power of Apache MXNet framework and NVIDIA GPU computing, you can launch your scalable deep learning projects and solutions easily on the AWS Cloud. As you get started on your MxNet deep learning quest, there are a variety of self-service tutorials and datasets available to you:

  • Launch an AWS Deep Learning AMI: This guide walks you through the steps to launch the AWS Deep Learning AMI with Ubuntu
  • MXNet – Create a computer vision application: This hands-on tutorial uses a pre-built notebook to walk you through using neural networks to build a computer vision application to identify handwritten digits
  • AWS Machine Learning Datasets: AWS hosts datasets for Machine Learning on the AWS Marketplace that you can access for free. These large datasets are available for anyone to analyze the data without requiring the data to be downloaded or stored.
  • Predict and Extract – Learn to use pre-trained models for predictions: This hands-on tutorial will walk you through how to use pre-trained model for predicting and feature extraction using the full Imagenet dataset.

 

AWS Deep Learning AMIs

AWS offers Amazon Machine Images (AMIs) for use on Amazon EC2 for quick deployment of an infrastructure needed to start your deep learning journey. The AWS Deep Learning AMIs are pre-configured with popular deep learning frameworks built using Amazon EC2 instances on Amazon Linux, and Ubuntu that can be launched for AI targeted solutions and models. The deep learning frameworks supported and pre-configured on the deep learning AMI are:

  • Apache MXNet
  • TensorFlow
  • Microsoft Cognitive Toolkit (CNTK)
  • Caffe
  • Caffe2
  • Theano
  • Torch
  • Keras

Additionally, the AWS Deep Learning AMIs install preconfigured libraries for Jupyter notebooks with Python 2.7/3.4, AWS SDK for Python, and other data science related python packages and dependencies. The AMIs also come with NVIDIA CUDA and NVIDIA CUDA Deep Neural Network (cuDNN) libraries preinstalled with all the supported deep learning frameworks and the Intel Math Kernel Library is installed for Apache MXNet framework. You can launch any of the Deep Learning AMIs by visiting the AWS Marketplace using the Try the Deep Learning AMIs link.

Summary

It is a great time to dive into Deep Learning. You can accelerate your work in deep learning by using the AWS Deep Learning AMIs running on the AWS cloud to get your deep learning environment running quickly or get started learning more about Deep Learning on AWS with MXNet using the AWS self-service resources.  Of course, you can learn even more information about Deep Learning, Machine Learning, and Artificial Intelligence on AWS by reviewing the AWS Deep Learning page, the Amazon AI product page, and the AWS AI Blog.

May the Deep Learning Force be with you all.

Tara