Tag Archives: rest

Build your own weather station with our new guide!

Post Syndicated from Richard Hayler original https://www.raspberrypi.org/blog/build-your-own-weather-station/

One of the most common enquiries I receive at Pi Towers is “How can I get my hands on a Raspberry Pi Oracle Weather Station?” Now the answer is: “Why not build your own version using our guide?”

Build Your Own weather station kit assembled

Tadaaaa! The BYO weather station fully assembled.

Our Oracle Weather Station

In 2016 we sent out nearly 1000 Raspberry Pi Oracle Weather Station kits to schools from around the world who had applied to be part of our weather station programme. In the original kit was a special HAT that allows the Pi to collect weather data with a set of sensors.

The original Raspberry Pi Oracle Weather Station HAT – Build Your Own Raspberry Pi weather station

The original Raspberry Pi Oracle Weather Station HAT

We designed the HAT to enable students to create their own weather stations and mount them at their schools. As part of the programme, we also provide an ever-growing range of supporting resources. We’ve seen Oracle Weather Stations in great locations with a huge differences in climate, and they’ve even recorded the effects of a solar eclipse.

Our new BYO weather station guide

We only had a single batch of HATs made, and unfortunately we’ve given nearly* all the Weather Station kits away. Not only are the kits really popular, we also receive lots of questions about how to add extra sensors or how to take more precise measurements of a particular weather phenomenon. So today, to satisfy your demand for a hackable weather station, we’re launching our Build your own weather station guide!

Build Your Own Raspberry Pi weather station

Fun with meteorological experiments!

Our guide suggests the use of many of the sensors from the Oracle Weather Station kit, so can build a station that’s as close as possible to the original. As you know, the Raspberry Pi is incredibly versatile, and we’ve made it easy to hack the design in case you want to use different sensors.

Many other tutorials for Pi-powered weather stations don’t explain how the various sensors work or how to store your data. Ours goes into more detail. It shows you how to put together a breadboard prototype, it describes how to write Python code to take readings in different ways, and it guides you through recording these readings in a database.

Build Your Own Raspberry Pi weather station on a breadboard

There’s also a section on how to make your station weatherproof. And in case you want to move past the breadboard stage, we also help you with that. The guide shows you how to solder together all the components, similar to the original Oracle Weather Station HAT.

Who should try this build

We think this is a great project to tackle at home, at a STEM club, Scout group, or CoderDojo, and we’re sure that many of you will be chomping at the bit to get started. Before you do, please note that we’ve designed the build to be as straight-forward as possible, but it’s still fairly advanced both in terms of electronics and programming. You should read through the whole guide before purchasing any components.

Build Your Own Raspberry Pi weather station – components

The sensors and components we’re suggesting balance cost, accuracy, and easy of use. Depending on what you want to use your station for, you may wish to use different components. Similarly, the final soldered design in the guide may not be the most elegant, but we think it is achievable for someone with modest soldering experience and basic equipment.

You can build a functioning weather station without soldering with our guide, but the build will be more durable if you do solder it. If you’ve never tried soldering before, that’s OK: we have a Getting started with soldering resource plus video tutorial that will walk you through how it works step by step.

Prototyping HAT for Raspberry Pi weather station sensors

For those of you who are more experienced makers, there are plenty of different ways to put the final build together. We always like to hear about alternative builds, so please post your designs in the Weather Station forum.

Our plans for the guide

Our next step is publishing supplementary guides for adding extra functionality to your weather station. We’d love to hear which enhancements you would most like to see! Our current ideas under development include adding a webcam, making a tweeting weather station, adding a light/UV meter, and incorporating a lightning sensor. Let us know which of these is your favourite, or suggest your own amazing ideas in the comments!

*We do have a very small number of kits reserved for interesting projects or locations: a particularly cool experiment, a novel idea for how the Oracle Weather Station could be used, or places with specific weather phenomena. If have such a project in mind, please send a brief outline to [email protected], and we’ll consider how we might be able to help you.

The post Build your own weather station with our new guide! appeared first on Raspberry Pi.

Friday Squid Blogging: Do Cephalopods Contain Alien DNA?

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/06/friday_squid_bl_627.html

Maybe not DNA, but biological somethings.

Cause of Cambrian explosion — Terrestrial or Cosmic?“:

Abstract: We review the salient evidence consistent with or predicted by the Hoyle-Wickramasinghe (H-W) thesis of Cometary (Cosmic) Biology. Much of this physical and biological evidence is multifactorial. One particular focus are the recent studies which date the emergence of the complex retroviruses of vertebrate lines at or just before the Cambrian Explosion of ~500 Ma. Such viruses are known to be plausibly associated with major evolutionary genomic processes. We believe this coincidence is not fortuitous but is consistent with a key prediction of H-W theory whereby major extinction-diversification evolutionary boundaries coincide with virus-bearing cometary-bolide bombardment events. A second focus is the remarkable evolution of intelligent complexity (Cephalopods) culminating in the emergence of the Octopus. A third focus concerns the micro-organism fossil evidence contained within meteorites as well as the detection in the upper atmosphere of apparent incoming life-bearing particles from space. In our view the totality of the multifactorial data and critical analyses assembled by Fred Hoyle, Chandra Wickramasinghe and their many colleagues since the 1960s leads to a very plausible conclusion — life may have been seeded here on Earth by life-bearing comets as soon as conditions on Earth allowed it to flourish (about or just before 4.1 Billion years ago); and living organisms such as space-resistant and space-hardy bacteria, viruses, more complex eukaryotic cells, fertilised ova and seeds have been continuously delivered ever since to Earth so being one important driver of further terrestrial evolution which has resulted in considerable genetic diversity and which has led to the emergence of mankind.

Two commentaries.

This is almost certainly not true.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Read my blog posting guidelines here.

Some quick thoughts on the public discussion regarding facial recognition and Amazon Rekognition this past week

Post Syndicated from Dr. Matt Wood original https://aws.amazon.com/blogs/aws/some-quick-thoughts-on-the-public-discussion-regarding-facial-recognition-and-amazon-rekognition-this-past-week/

We have seen a lot of discussion this past week about the role of Amazon Rekognition in facial recognition, surveillance, and civil liberties, and we wanted to share some thoughts.

Amazon Rekognition is a service we announced in 2016. It makes use of new technologies – such as deep learning – and puts them in the hands of developers in an easy-to-use, low-cost way. Since then, we have seen customers use the image and video analysis capabilities of Amazon Rekognition in ways that materially benefit both society (e.g. preventing human trafficking, inhibiting child exploitation, reuniting missing children with their families, and building educational apps for children), and organizations (enhancing security through multi-factor authentication, finding images more easily, or preventing package theft). Amazon Web Services (AWS) is not the only provider of services like these, and we remain excited about how image and video analysis can be a driver for good in the world, including in the public sector and law enforcement.

There have always been and will always be risks with new technology capabilities. Each organization choosing to employ technology must act responsibly or risk legal penalties and public condemnation. AWS takes its responsibilities seriously. But we believe it is the wrong approach to impose a ban on promising new technologies because they might be used by bad actors for nefarious purposes in the future. The world would be a very different place if we had restricted people from buying computers because it was possible to use that computer to do harm. The same can be said of thousands of technologies upon which we all rely each day. Through responsible use, the benefits have far outweighed the risks.

Customers are off to a great start with Amazon Rekognition; the evidence of the positive impact this new technology can provide is strong (and growing by the week), and we’re excited to continue to support our customers in its responsible use.

-Dr. Matt Wood, general manager of artificial intelligence at AWS

Monitoring your Amazon SNS message filtering activity with Amazon CloudWatch

Post Syndicated from Rachel Richardson original https://aws.amazon.com/blogs/compute/monitoring-your-amazon-sns-message-filtering-activity-with-amazon-cloudwatch/

This post is courtesy of Otavio Ferreira, Manager, Amazon SNS, AWS Messaging.

Amazon SNS message filtering provides a set of string and numeric matching operators that allow each subscription to receive only the messages of interest. Hence, SNS message filtering can simplify your pub/sub messaging architecture by offloading the message filtering logic from your subscriber systems, as well as the message routing logic from your publisher systems.

After you set the subscription attribute that defines a filter policy, the subscribing endpoint receives only the messages that carry attributes matching this filter policy. Other messages published to the topic are filtered out for this subscription. In this way, the native integration between SNS and Amazon CloudWatch provides visibility into the number of messages delivered, as well as the number of messages filtered out.

CloudWatch metrics are captured automatically for you. To get started with SNS message filtering, see Filtering Messages with Amazon SNS.

Message Filtering Metrics

The following six CloudWatch metrics are relevant to understanding your SNS message filtering activity:

  • NumberOfMessagesPublished – Inbound traffic to SNS. This metric tracks all the messages that have been published to the topic.
  • NumberOfNotificationsDelivered – Outbound traffic from SNS. This metric tracks all the messages that have been successfully delivered to endpoints subscribed to the topic. A delivery takes place either when the incoming message attributes match a subscription filter policy, or when the subscription has no filter policy at all, which results in a catch-all behavior.
  • NumberOfNotificationsFilteredOut – This metric tracks all the messages that were filtered out because they carried attributes that didn’t match the subscription filter policy.
  • NumberOfNotificationsFilteredOut-NoMessageAttributes – This metric tracks all the messages that were filtered out because they didn’t carry any attributes at all and, consequently, didn’t match the subscription filter policy.
  • NumberOfNotificationsFilteredOut-InvalidAttributes – This metric keeps track of messages that were filtered out because they carried invalid or malformed attributes and, thus, didn’t match the subscription filter policy.
  • NumberOfNotificationsFailed – This last metric tracks all the messages that failed to be delivered to subscribing endpoints, regardless of whether a filter policy had been set for the endpoint. This metric is emitted after the message delivery retry policy is exhausted, and SNS stops attempting to deliver the message. At that moment, the subscribing endpoint is likely no longer reachable. For example, the subscribing SQS queue or Lambda function has been deleted by its owner. You may want to closely monitor this metric to address message delivery issues quickly.

Message filtering graphs

Through the AWS Management Console, you can compose graphs to display your SNS message filtering activity. The graph shows the number of messages published, delivered, and filtered out within the timeframe you specify (1h, 3h, 12h, 1d, 3d, 1w, or custom).

SNS message filtering for CloudWatch Metrics

To compose an SNS message filtering graph with CloudWatch:

  1. Open the CloudWatch console.
  2. Choose Metrics, SNS, All Metrics, and Topic Metrics.
  3. Select all metrics to add to the graph, such as:
    • NumberOfMessagesPublished
    • NumberOfNotificationsDelivered
    • NumberOfNotificationsFilteredOut
  4. Choose Graphed metrics.
  5. In the Statistic column, switch from Average to Sum.
  6. Title your graph with a descriptive name, such as “SNS Message Filtering”

After you have your graph set up, you may want to copy the graph link for bookmarking, emailing, or sharing with co-workers. You may also want to add your graph to a CloudWatch dashboard for easy access in the future. Both actions are available to you on the Actions menu, which is found above the graph.

Summary

SNS message filtering defines how SNS topics behave in terms of message delivery. By using CloudWatch metrics, you gain visibility into the number of messages published, delivered, and filtered out. This enables you to validate the operation of filter policies and more easily troubleshoot during development phases.

SNS message filtering can be implemented easily with existing AWS SDKs by applying message and subscription attributes across all SNS supported protocols (Amazon SQS, AWS Lambda, HTTP, SMS, email, and mobile push). CloudWatch metrics for SNS message filtering is available now, in all AWS Regions.

For information about pricing, see the CloudWatch pricing page.

For more information, see:

Getting Rid of Your Mac? Here’s How to Securely Erase a Hard Drive or SSD

Post Syndicated from Roderick Bauer original https://www.backblaze.com/blog/how-to-wipe-a-mac-hard-drive/

erasing a hard drive and a solid state drive

What do I do with a Mac that still has personal data on it? Do I take out the disk drive and smash it? Do I sweep it with a really strong magnet? Is there a difference in how I handle a hard drive (HDD) versus a solid-state drive (SSD)? Well, taking a sledgehammer or projectile weapon to your old machine is certainly one way to make the data irretrievable, and it can be enormously cathartic as long as you follow appropriate safety and disposal protocols. But there are far less destructive ways to make sure your data is gone for good. Let me introduce you to secure erasing.

Which Type of Drive Do You Have?

Before we start, you need to know whether you have a HDD or a SSD. To find out, or at least to make sure, you click on the Apple menu and select “About this Mac.” Once there, select the “Storage” tab to see which type of drive is in your system.

The first example, below, shows a SATA Disk (HDD) in the system.

SATA HDD

In the next case, we see we have a Solid State SATA Drive (SSD), plus a Mac SuperDrive.

Mac storage dialog showing SSD

The third screen shot shows an SSD, as well. In this case it’s called “Flash Storage.”

Flash Storage

Make Sure You Have a Backup

Before you get started, you’ll want to make sure that any important data on your hard drive has moved somewhere else. OS X’s built-in Time Machine backup software is a good start, especially when paired with Backblaze. You can learn more about using Time Machine in our Mac Backup Guide.

With a local backup copy in hand and secure cloud storage, you know your data is always safe no matter what happens.

Once you’ve verified your data is backed up, roll up your sleeves and get to work. The key is OS X Recovery — a special part of the Mac operating system since OS X 10.7 “Lion.”

How to Wipe a Mac Hard Disk Drive (HDD)

NOTE: If you’re interested in wiping an SSD, see below.

    1. Make sure your Mac is turned off.
    2. Press the power button.
    3. Immediately hold down the command and R keys.
    4. Wait until the Apple logo appears.
    5. Select “Disk Utility” from the OS X Utilities list. Click Continue.
    6. Select the disk you’d like to erase by clicking on it in the sidebar.
    7. Click the Erase button.
    8. Click the Security Options button.
    9. The Security Options window includes a slider that enables you to determine how thoroughly you want to erase your hard drive.

There are four notches to that Security Options slider. “Fastest” is quick but insecure — data could potentially be rebuilt using a file recovery app. Moving that slider to the right introduces progressively more secure erasing. Disk Utility’s most secure level erases the information used to access the files on your disk, then writes zeroes across the disk surface seven times to help remove any trace of what was there. This setting conforms to the DoD 5220.22-M specification.

  1. Once you’ve selected the level of secure erasing you’re comfortable with, click the OK button.
  2. Click the Erase button to begin. Bear in mind that the more secure method you select, the longer it will take. The most secure methods can add hours to the process.

Once it’s done, the Mac’s hard drive will be clean as a whistle and ready for its next adventure: a fresh installation of OS X, being donated to a relative or a local charity, or just sent to an e-waste facility. Of course you can still drill a hole in your disk or smash it with a sledgehammer if it makes you happy, but now you know how to wipe the data from your old computer with much less ruckus.

The above instructions apply to older Macintoshes with HDDs. What do you do if you have an SSD?

Securely Erasing SSDs, and Why Not To

Most new Macs ship with solid state drives (SSDs). Only the iMac and Mac mini ship with regular hard drives anymore, and even those are available in pure SSD variants if you want.

If your Mac comes equipped with an SSD, Apple’s Disk Utility software won’t actually let you zero the hard drive.

Wait, what?

In a tech note posted to Apple’s own online knowledgebase, Apple explains that you don’t need to securely erase your Mac’s SSD:

With an SSD drive, Secure Erase and Erasing Free Space are not available in Disk Utility. These options are not needed for an SSD drive because a standard erase makes it difficult to recover data from an SSD.

In fact, some folks will tell you not to zero out the data on an SSD, since it can cause wear and tear on the memory cells that, over time, can affect its reliability. I don’t think that’s nearly as big an issue as it used to be — SSD reliability and longevity has improved.

If “Standard Erase” doesn’t quite make you feel comfortable that your data can’t be recovered, there are a couple of options.

FileVault Keeps Your Data Safe

One way to make sure that your SSD’s data remains secure is to use FileVault. FileVault is whole-disk encryption for the Mac. With FileVault engaged, you need a password to access the information on your hard drive. Without it, that data is encrypted.

There’s one potential downside of FileVault — if you lose your password or the encryption key, you’re screwed: You’re not getting your data back any time soon. Based on my experience working at a Mac repair shop, losing a FileVault key happens more frequently than it should.

When you first set up a new Mac, you’re given the option of turning FileVault on. If you don’t do it then, you can turn on FileVault at any time by clicking on your Mac’s System Preferences, clicking on Security & Privacy, and clicking on the FileVault tab. Be warned, however, that the initial encryption process can take hours, as will decryption if you ever need to turn FileVault off.

With FileVault turned on, you can restart your Mac into its Recovery System (by restarting the Mac while holding down the command and R keys) and erase the hard drive using Disk Utility, once you’ve unlocked it (by selecting the disk, clicking the File menu, and clicking Unlock). That deletes the FileVault key, which means any data on the drive is useless.

FileVault doesn’t impact the performance of most modern Macs, though I’d suggest only using it if your Mac has an SSD, not a conventional hard disk drive.

Securely Erasing Free Space on Your SSD

If you don’t want to take Apple’s word for it, if you’re not using FileVault, or if you just want to, there is a way to securely erase free space on your SSD. It’s a little more involved but it works.

Before we get into the nitty-gritty, let me state for the record that this really isn’t necessary to do, which is why Apple’s made it so hard to do. But if you’re set on it, you’ll need to use Apple’s Terminal app. Terminal provides you with command line interface access to the OS X operating system. Terminal lives in the Utilities folder, but you can access Terminal from the Mac’s Recovery System, as well. Once your Mac has booted into the Recovery partition, click the Utilities menu and select Terminal to launch it.

From a Terminal command line, type:

diskutil secureErase freespace VALUE /Volumes/DRIVE

That tells your Mac to securely erase the free space on your SSD. You’ll need to change VALUE to a number between 0 and 4. 0 is a single-pass run of zeroes; 1 is a single-pass run of random numbers; 2 is a 7-pass erase; 3 is a 35-pass erase; and 4 is a 3-pass erase. DRIVE should be changed to the name of your hard drive. To run a 7-pass erase of your SSD drive in “JohnB-Macbook”, you would enter the following:

diskutil secureErase freespace 2 /Volumes/JohnB-Macbook

And remember, if you used a space in the name of your Mac’s hard drive, you need to insert a leading backslash before the space. For example, to run a 35-pass erase on a hard drive called “Macintosh HD” you enter the following:

diskutil secureErase freespace 3 /Volumes/Macintosh\ HD

Something to remember is that the more extensive the erase procedure, the longer it will take.

When Erasing is Not Enough — How to Destroy a Drive

If you absolutely, positively need to be sure that all the data on a drive is irretrievable, see this Scientific American article (with contributions by Gleb Budman, Backblaze CEO), How to Destroy a Hard Drive — Permanently.

The post Getting Rid of Your Mac? Here’s How to Securely Erase a Hard Drive or SSD appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

[$] Killing processes that don’t want to die

Post Syndicated from jake original https://lwn.net/Articles/754980/rss

Suppose you have a program running on your system that you don’t quite
trust. Maybe it’s a program submitted by a student to an automated
grading system. Or maybe it’s a QEMU device model running in a Xen
control domain ("domain 0" or “dom0”), and you want to make sure
that even
if an attacker from a rogue virtual machine manages to take over the QEMU
process,
they can’t do any further harm. There are many things you want to do as far
as restricting its ability
to do mischief. But one thing in particular you probably want to do
is to be able to reliably kill the process once you think it should be
done. This turns out to be quite a bit more tricky than you’d think.

Project Floofball and more: Pi pet stuff

Post Syndicated from Janina Ander original https://www.raspberrypi.org/blog/project-floofball-pi-pet-stuff/

It’s a public holiday here today (yes, again). So, while we indulge in the traditional pastime of barbecuing stuff (ourselves, mainly), here’s a little trove of Pi projects that cater for our various furry friends.

Project Floofball

Nicole Horward created Project Floofball for her hamster, Harold. It’s an IoT hamster wheel that uses a Raspberry Pi and a magnetic door sensor to log how far Harold runs.

Project Floofball: an IoT hamster wheel

An IoT Hamsterwheel using a Raspberry Pi and a magnetic door sensor, to see how far my hamster runs.

You can follow Harold’s runs in real time on his ThingSpeak channel, and you’ll find photos of the build on imgur. Nicole’s Python code, as well as her template for the laser-cut enclosure that houses the wiring and LCD display, are available on the hamster wheel’s GitHub repo.

A live-streaming pet feeder

JaganK3 used to work long hours that meant he couldn’t be there to feed his dog on time. He found that he couldn’t buy an automated feeder in India without paying a lot to import one, so he made one himself. It uses a Raspberry Pi to control a motor that turns a dispensing valve in a hopper full of dry food, giving his dog a portion of food at set times.

A transparent cylindrical hopper of dry dog food, with a motor that can turn a dispensing valve at the lower end. The motor is connected to a Raspberry Pi in a plastic case. Hopper, motor, Pi, and wiring are all mounted on a board on the wall.

He also added a web cam for live video streaming, because he could. Find out more in JaganK3’s Instructable for his pet feeder.

Shark laser cat toy

Sam Storino, meanwhile, is using a Raspberry Pi to control a laser-pointer cat toy with a goshdarned SHARK (which is kind of what I’d expect from the guy who made the steampunk-looking cat feeder a few weeks ago). The idea is to keep his cats interested and active within the confines of a compact city apartment.

Raspberry Pi Automatic Cat Laser Pointer Toy

Post with 52 votes and 7004 views. Tagged with cat, shark, lasers, austin powers, raspberry pi; Shared by JeorgeLeatherly. Raspberry Pi Automatic Cat Laser Pointer Toy

If I were a cat, I would definitely be entirely happy with this. Find out more on Sam’s website.

And there’s more

Michel Parreno has written a series of articles to help you monitor and feed your pet with Raspberry Pi.

All of these makers are generous in acknowledging the tutorials and build logs that helped them with their projects. It’s lovely to see the Raspberry Pi and maker community working like this, and I bet their projects will inspire others too.

Now, if you’ll excuse me. I’m late for a barbecue.

The post Project Floofball and more: Pi pet stuff appeared first on Raspberry Pi.

Security and Human Behavior (SHB 2018)

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/05/security_and_hu_7.html

I’m at Carnegie Mellon University, at the eleventh Workshop on Security and Human Behavior.

SHB is a small invitational gathering of people studying various aspects of the human side of security, organized each year by Alessandro Acquisti, Ross Anderson, and myself. The 50 or so people in the room include psychologists, economists, computer security researchers, sociologists, political scientists, neuroscientists, designers, lawyers, philosophers, anthropologists, business school professors, and a smattering of others. It’s not just an interdisciplinary event; most of the people here are individually interdisciplinary.

The goal is to maximize discussion and interaction. We do that by putting everyone on panels, and limiting talks to 7-10 minutes. The rest of the time is left to open discussion. Four hour-and-a-half panels per day over two days equals eight panels; six people per panel means that 48 people get to speak. We also have lunches, dinners, and receptions — all designed so people from different disciplines talk to each other.

I invariably find this to be the most intellectually stimulating conference of my year. It influences my thinking in many different, and sometimes surprising, ways.

This year’s program is here. This page lists the participants and includes links to some of their work. As he does every year, Ross Anderson is liveblogging the talks. (Ross also maintains a good webpage of psychology and security resources.)

Here are my posts on the first, second, third, fourth, fifth, sixth, seventh, eighth, ninth, and tenth SHB workshops. Follow those links to find summaries, papers, and occasionally audio recordings of the various workshops.

Next year, I’ll be hosting the event at Harvard.

Protecting your API using Amazon API Gateway and AWS WAF — Part I

Post Syndicated from Chris Munns original https://aws.amazon.com/blogs/compute/protecting-your-api-using-amazon-api-gateway-and-aws-waf-part-i/

This post courtesy of Thiago Morais, AWS Solutions Architect

When you build web applications or expose any data externally, you probably look for a platform where you can build highly scalable, secure, and robust REST APIs. As APIs are publicly exposed, there are a number of best practices for providing a secure mechanism to consumers using your API.

Amazon API Gateway handles all the tasks involved in accepting and processing up to hundreds of thousands of concurrent API calls, including traffic management, authorization and access control, monitoring, and API version management.

In this post, I show you how to take advantage of the regional API endpoint feature in API Gateway, so that you can create your own Amazon CloudFront distribution and secure your API using AWS WAF.

AWS WAF is a web application firewall that helps protect your web applications from common web exploits that could affect application availability, compromise security, or consume excessive resources.

As you make your APIs publicly available, you are exposed to attackers trying to exploit your services in several ways. The AWS security team published a whitepaper solution using AWS WAF, How to Mitigate OWASP’s Top 10 Web Application Vulnerabilities.

Regional API endpoints

Edge-optimized APIs are endpoints that are accessed through a CloudFront distribution created and managed by API Gateway. Before the launch of regional API endpoints, this was the default option when creating APIs using API Gateway. It primarily helped to reduce latency for API consumers that were located in different geographical locations than your API.

When API requests predominantly originate from an Amazon EC2 instance or other services within the same AWS Region as the API is deployed, a regional API endpoint typically lowers the latency of connections. It is recommended for such scenarios.

For better control around caching strategies, customers can use their own CloudFront distribution for regional APIs. They also have the ability to use AWS WAF protection, as I describe in this post.

Edge-optimized API endpoint

The following diagram is an illustrated example of the edge-optimized API endpoint where your API clients access your API through a CloudFront distribution created and managed by API Gateway.

Regional API endpoint

For the regional API endpoint, your customers access your API from the same Region in which your REST API is deployed. This helps you to reduce request latency and particularly allows you to add your own content delivery network, as needed.

Walkthrough

In this section, you implement the following steps:

  • Create a regional API using the PetStore sample API.
  • Create a CloudFront distribution for the API.
  • Test the CloudFront distribution.
  • Set up AWS WAF and create a web ACL.
  • Attach the web ACL to the CloudFront distribution.
  • Test AWS WAF protection.

Create the regional API

For this walkthrough, use an existing PetStore API. All new APIs launch by default as the regional endpoint type. To change the endpoint type for your existing API, choose the cog icon on the top right corner:

After you have created the PetStore API on your account, deploy a stage called “prod” for the PetStore API.

On the API Gateway console, select the PetStore API and choose Actions, Deploy API.

For Stage name, type prod and add a stage description.

Choose Deploy and the new API stage is created.

Use the following AWS CLI command to update your API from edge-optimized to regional:

aws apigateway update-rest-api \
--rest-api-id {rest-api-id} \
--patch-operations op=replace,path=/endpointConfiguration/types/EDGE,value=REGIONAL

A successful response looks like the following:

{
    "description": "Your first API with Amazon API Gateway. This is a sample API that integrates via HTTP with your demo Pet Store endpoints", 
    "createdDate": 1511525626, 
    "endpointConfiguration": {
        "types": [
            "REGIONAL"
        ]
    }, 
    "id": "{api-id}", 
    "name": "PetStore"
}

After you change your API endpoint to regional, you can now assign your own CloudFront distribution to this API.

Create a CloudFront distribution

To make things easier, I have provided an AWS CloudFormation template to deploy a CloudFront distribution pointing to the API that you just created. Click the button to deploy the template in the us-east-1 Region.

For Stack name, enter RegionalAPI. For APIGWEndpoint, enter your API FQDN in the following format:

{api-id}.execute-api.us-east-1.amazonaws.com

After you fill out the parameters, choose Next to continue the stack deployment. It takes a couple of minutes to finish the deployment. After it finishes, the Output tab lists the following items:

  • A CloudFront domain URL
  • An S3 bucket for CloudFront access logs
Output from CloudFormation

Output from CloudFormation

Test the CloudFront distribution

To see if the CloudFront distribution was configured correctly, use a web browser and enter the URL from your distribution, with the following parameters:

https://{your-distribution-url}.cloudfront.net/{api-stage}/pets

You should get the following output:

[
  {
    "id": 1,
    "type": "dog",
    "price": 249.99
  },
  {
    "id": 2,
    "type": "cat",
    "price": 124.99
  },
  {
    "id": 3,
    "type": "fish",
    "price": 0.99
  }
]

Set up AWS WAF and create a web ACL

With the new CloudFront distribution in place, you can now start setting up AWS WAF to protect your API.

For this demo, you deploy the AWS WAF Security Automations solution, which provides fine-grained control over the requests attempting to access your API.

For more information about deployment, see Automated Deployment. If you prefer, you can launch the solution directly into your account using the following button.

For CloudFront Access Log Bucket Name, add the name of the bucket created during the deployment of the CloudFormation stack for your CloudFront distribution.

The solution allows you to adjust thresholds and also choose which automations to enable to protect your API. After you finish configuring these settings, choose Next.

To start the deployment process in your account, follow the creation wizard and choose Create. It takes a few minutes do finish the deployment. You can follow the creation process through the CloudFormation console.

After the deployment finishes, you can see the new web ACL deployed on the AWS WAF console, AWSWAFSecurityAutomations.

Attach the AWS WAF web ACL to the CloudFront distribution

With the solution deployed, you can now attach the AWS WAF web ACL to the CloudFront distribution that you created earlier.

To assign the newly created AWS WAF web ACL, go back to your CloudFront distribution. After you open your distribution for editing, choose General, Edit.

Select the new AWS WAF web ACL that you created earlier, AWSWAFSecurityAutomations.

Save the changes to your CloudFront distribution and wait for the deployment to finish.

Test AWS WAF protection

To validate the AWS WAF Web ACL setup, use Artillery to load test your API and see AWS WAF in action.

To install Artillery on your machine, run the following command:

$ npm install -g artillery

After the installation completes, you can check if Artillery installed successfully by running the following command:

$ artillery -V
$ 1.6.0-12

As the time of publication, Artillery is on version 1.6.0-12.

One of the WAF web ACL rules that you have set up is a rate-based rule. By default, it is set up to block any requesters that exceed 2000 requests under 5 minutes. Try this out.

First, use cURL to query your distribution and see the API output:

$ curl -s https://{distribution-name}.cloudfront.net/prod/pets
[
  {
    "id": 1,
    "type": "dog",
    "price": 249.99
  },
  {
    "id": 2,
    "type": "cat",
    "price": 124.99
  },
  {
    "id": 3,
    "type": "fish",
    "price": 0.99
  }
]

Based on the test above, the result looks good. But what if you max out the 2000 requests in under 5 minutes?

Run the following Artillery command:

artillery quick -n 2000 --count 10  https://{distribution-name}.cloudfront.net/prod/pets

What you are doing is firing 2000 requests to your API from 10 concurrent users. For brevity, I am not posting the Artillery output here.

After Artillery finishes its execution, try to run the cURL request again and see what happens:

 

$ curl -s https://{distribution-name}.cloudfront.net/prod/pets

<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
<HTML><HEAD><META HTTP-EQUIV="Content-Type" CONTENT="text/html; charset=iso-8859-1">
<TITLE>ERROR: The request could not be satisfied</TITLE>
</HEAD><BODY>
<H1>ERROR</H1>
<H2>The request could not be satisfied.</H2>
<HR noshade size="1px">
Request blocked.
<BR clear="all">
<HR noshade size="1px">
<PRE>
Generated by cloudfront (CloudFront)
Request ID: [removed]
</PRE>
<ADDRESS>
</ADDRESS>
</BODY></HTML>

As you can see from the output above, the request was blocked by AWS WAF. Your IP address is removed from the blocked list after it falls below the request limit rate.

Conclusion

In this first part, you saw how to use the new API Gateway regional API endpoint together with Amazon CloudFront and AWS WAF to secure your API from a series of attacks.

In the second part, I will demonstrate some other techniques to protect your API using API keys and Amazon CloudFront custom headers.

Detecting Lies through Mouse Movements

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/05/detecting_lies_.html

Interesting research: “The detection of faked identity using unexpected questions and mouse dynamics,” by Merulin Monaro, Luciano Gamberini, and Guiseppe Sartori.

Abstract: The detection of faked identities is a major problem in security. Current memory-detection techniques cannot be used as they require prior knowledge of the respondent’s true identity. Here, we report a novel technique for detecting faked identities based on the use of unexpected questions that may be used to check the respondent identity without any prior autobiographical information. While truth-tellers respond automatically to unexpected questions, liars have to “build” and verify their responses. This lack of automaticity is reflected in the mouse movements used to record the responses as well as in the number of errors. Responses to unexpected questions are compared to responses to expected and control questions (i.e., questions to which a liar also must respond truthfully). Parameters that encode mouse movement were analyzed using machine learning classifiers and the results indicate that the mouse trajectories and errors on unexpected questions efficiently distinguish liars from truth-tellers. Furthermore, we showed that liars may be identified also when they are responding truthfully. Unexpected questions combined with the analysis of mouse movement may efficiently spot participants with faked identities without the need for any prior information on the examinee.

Boing Boing post.

C is to low level

Post Syndicated from Robert Graham original https://blog.erratasec.com/2018/05/c-is-too-low-level.html

I’m in danger of contradicting myself, after previously pointing out that x86 machine code is a high-level language, but this article claiming C is a not a low level language is bunk. C certainly has some problems, but it’s still the closest language to assembly. This is obvious by the fact it’s still the fastest compiled language. What we see is a typical academic out of touch with the real world.

The author makes the (wrong) observation that we’ve been stuck emulating the PDP-11 for the past 40 years. C was written for the PDP-11, and since then CPUs have been designed to make C run faster. The author imagines a different world, such as where CPU designers instead target something like LISP as their preferred language, or Erlang. This misunderstands the state of the market. CPUs do indeed supports lots of different abstractions, and C has evolved to accommodate this.


The author criticizes things like “out-of-order” execution which has lead to the Spectre sidechannel vulnerabilities. Out-of-order execution is necessary to make C run faster. The author claims instead that those resources should be spent on having more slower CPUs, with more threads. This sacrifices single-threaded performance in exchange for a lot more threads executing in parallel. The author cites Sparc Tx CPUs as his ideal processor.

But here’s the thing, the Sparc Tx was a failure. To be fair, it’s mostly a failure because most of the time, people wanted to run old C code instead of new Erlang code. But it was still a failure at running Erlang.

Time after time, engineers keep finding that “out-of-order”, single-threaded performance is still the winner. A good example is ARM processors for both mobile phones and servers. All the theory points to in-order CPUs as being better, but all the products are out-of-order, because this theory is wrong. The custom ARM cores from Apple and Qualcomm used in most high-end phones are so deeply out-of-order they give Intel CPUs competition. The same is true on the server front with the latest Qualcomm Centriq and Cavium ThunderX2 processors, deeply out of order supporting more than 100 instructions in flight.

The Cavium is especially telling. Its ThunderX CPU had 48 simple cores which was replaced with the ThunderX2 having 32 complex, deeply out-of-order cores. The performance increase was massive, even on multithread-friendly workloads. Every competitor to Intel’s dominance in the server space has learned the lesson from Sparc Tx: many wimpy cores is a failure, you need fewer beefy cores. Yes, they don’t need to be as beefy as Intel’s processors, but they need to be close.

Even Intel’s “Xeon Phi” custom chip learned this lesson. This is their GPU-like chip, running 60 cores with 512-bit wide “vector” (sic) instructions, designed for supercomputer applications. Its first version was purely in-order. Its current version is slightly out-of-order. It supports four threads and focuses on basic number crunching, so in-order cores seems to be the right approach, but Intel found in this case that out-of-order processing still provided a benefit. Practice is different than theory.

As an academic, the author of the above article focuses on abstractions. The criticism of C is that it has the wrong abstractions which are hard to optimize, and that if we instead expressed things in the right abstractions, it would be easier to optimize.

This is an intellectually compelling argument, but so far bunk.

The reason is that while the theoretical base language has issues, everyone programs using extensions to the language, like “intrinsics” (C ‘functions’ that map to assembly instructions). Programmers write libraries using these intrinsics, which then the rest of the normal programmers use. In other words, if your criticism is that C is not itself low level enough, it still provides the best access to low level capabilities.

Given that C can access new functionality in CPUs, CPU designers add new paradigms, from SIMD to transaction processing. In other words, while in the 1980s CPUs were designed to optimize C (stacks, scaled pointers), these days CPUs are designed to optimize tasks regardless of language.

The author of that article criticizes the memory/cache hierarchy, claiming it has problems. Yes, it has problems, but only compared to how well it normally works. The author praises the many simple cores/threads idea as hiding memory latency with little caching, but misses the point that caches also dramatically increase memory bandwidth. Intel processors are optimized to read a whopping 256 bits every clock cycle from L1 cache. Main memory bandwidth is orders of magnitude slower.

The author goes onto criticize cache coherency as a problem. C uses it, but other languages like Erlang don’t need it. But that’s largely due to the problems each languages solves. Erlang solves the problem where a large number of threads work on largely independent tasks, needing to send only small messages to each other across threads. The problems C solves is when you need many threads working on a huge, common set of data.

For example, consider the “intrusion prevention system”. Any thread can process any incoming packet that corresponds to any region of memory. There’s no practical way of solving this problem without a huge coherent cache. It doesn’t matter which language or abstractions you use, it’s the fundamental constraint of the problem being solved. RDMA is an important concept that’s moved from supercomputer applications to the data center, such as with memcached. Again, we have the problem of huge quantities (terabytes worth) shared among threads rather than small quantities (kilobytes).

The fundamental issue the author of the the paper is ignoring is decreasing marginal returns. Moore’s Law has gifted us more transistors than we can usefully use. We can’t apply those additional registers to just one thing, because the useful returns we get diminish.

For example, Intel CPUs have two hardware threads per core. That’s because there are good returns by adding a single additional thread. However, the usefulness of adding a third or fourth thread decreases. That’s why many CPUs have only two threads, or sometimes four threads, but no CPU has 16 threads per core.

You can apply the same discussion to any aspect of the CPU, from register count, to SIMD width, to cache size, to out-of-order depth, and so on. Rather than focusing on one of these things and increasing it to the extreme, CPU designers make each a bit larger every process tick that adds more transistors to the chip.

The same applies to cores. It’s why the “more simpler cores” strategy fails, because more cores have their own decreasing marginal returns. Instead of adding cores tied to limited memory bandwidth, it’s better to add more cache. Such cache already increases the size of the cores, so at some point it’s more effective to add a few out-of-order features to each core rather than more cores. And so on.

The question isn’t whether we can change this paradigm and radically redesign CPUs to match some academic’s view of the perfect abstraction. Instead, the goal is to find new uses for those additional transistors. For example, “message passing” is a useful abstraction in languages like Go and Erlang that’s often more useful than sharing memory. It’s implemented with shared memory and atomic instructions, but I can’t help but think it couldn’t better be done with direct hardware support.

Of course, as soon as they do that, it’ll become an intrinsic in C, then added to languages like Go and Erlang.

Summary

Academics live in an ideal world of abstractions, the rest of us live in practical reality. The reality is that vast majority of programmers work with the C family of languages (JavaScript, Go, etc.), whereas academics love the epiphanies they learned using other languages, especially function languages. CPUs are only superficially designed to run C and “PDP-11 compatibility”. Instead, they keep adding features to support other abstractions, abstractions available to C. They are driven by decreasing marginal returns — they would love to add new abstractions to the hardware because it’s a cheap way to make use of additional transitions. Academics are wrong believing that the entire system needs to be redesigned from scratch. Instead, they just need to come up with new abstractions CPU designers can add.

Acunetix v12 – More Comprehensive More Accurate & 2x Faster

Post Syndicated from Darknet original https://www.darknet.org.uk/2018/05/acunetix-v12-more-comprehensive-more-accurate-2x-faster/?utm_source=rss&utm_medium=social&utm_campaign=darknetfeed

Acunetix v12 – More Comprehensive More Accurate & 2x Faster

Acunetix, the pioneer in automated web application security software, has announced the release of Acunetix v12. This new version provides support for JavaScript ES7 to better analyse sites which rely heavily on JavaScript such as SPAs. This coupled with a new AcuSensor for Java web applications, sets Acunetix ahead of the curve in its ability to comprehensively and accurately scan all types of websites.

With v12 also comes a brand new scanning engine, re-engineered and re-written from the ground up, making Acunetix the fastest scanning engine in the industry.

Read the rest of Acunetix v12 – More Comprehensive More Accurate & 2x Faster now! Only available at Darknet.

The Benefits of Side Projects

Post Syndicated from Bozho original https://techblog.bozho.net/the-benefits-of-side-projects/

Side projects are the things you do at home, after work, for your own “entertainment”, or to satisfy your desire to learn new stuff, in case your workplace doesn’t give you that opportunity (or at least not enough of it). Side projects are also a way to build stuff that you think is valuable but not necessarily “commercialisable”. Many side projects are open-sourced sooner or later and some of them contribute to the pool of tools at other people’s disposal.

I’ve outlined one recommendation about side projects before – do them with technologies that are new to you, so that you learn important things that will keep you better positioned in the software world.

But there are more benefits than that – serendipitous benefits, for example. And I’d like to tell some personal stories about that. I’ll focus on a few examples from my list of side projects to show how, through a sort-of butterfly effect, they helped shape my career.

The computoser project, no matter how cool algorithmic music composition, didn’t manage to have much of a long term impact. But it did teach me something apart from niche musical theory – how to read a bulk of scientific papers (mostly computer science) and understand them without being formally trained in the particular field. We’ll see how that was useful later.

Then there was the “State alerts” project – a website that scraped content from public institutions in my country (legislation, legislation proposals, decisions by regulators, new tenders, etc.), made them searchable, and “subscribable” – so that you get notified when a keyword of interest is mentioned in newly proposed legislation, for example. (I obviously subscribed for “information technologies” and “electronic”).

And that project turned out to have a significant impact on the following years. First, I chose a new technology to write it with – Scala. Which turned out to be of great use when I started working at TomTom, and on the 3rd day I was transferred to a Scala project, which was way cooler and much more complex than the original one I was hired for. It was a bit ironic, as my colleagues had just read that “I don’t like Scala” a few weeks earlier, but nevertheless, that was one of the most interesting projects I’ve worked on, and it went on for two years. Had I not known Scala, I’d probably be gone from TomTom much earlier (as the other project was restructured a few times), and I would not have learned many of the scalability, architecture and AWS lessons that I did learn there.

But the very same project had an even more important follow-up. Because if its “civic hacking” flavour, I was invited to join an informal group of developers (later officiated as an NGO) who create tools that are useful for society (something like MySociety.org). That group gathered regularly, discussed both tools and policies, and at some point we put up a list of policy priorities that we wanted to lobby policy makers. One of them was open source for the government, the other one was open data. As a result of our interaction with an interim government, we donated the official open data portal of my country, functioning to this day.

As a result of that, a few months later we got a proposal from the deputy prime minister’s office to “elect” one of the group for an advisor to the cabinet. And we decided that could be me. So I went for it and became advisor to the deputy prime minister. The job has nothing to do with anything one could imagine, and it was challenging and fascinating. We managed to pass legislation, including one that requires open source for custom projects, eID and open data. And all of that would not have been possible without my little side project.

As for my latest side project, LogSentinel – it became my current startup company. And not without help from the previous two mentioned above – the computer science paper reading was of great use when I was navigating the crypto papers landscape, and from the government job I not only gained invaluable legal knowledge, but I also “got” a co-founder.

Some other side projects died without much fanfare, and that’s fine. But the ones above shaped my “story” in a way that would not have been possible otherwise.

And I agree that such serendipitous chain of events could have happened without side projects – I could’ve gotten these opportunities by meeting someone at a bar (unlikely, but who knows). But we, as software engineers, are capable of tilting chance towards us by utilizing our skills. Side projects are our “extracurricular activities”, and they often lead to unpredictable, but rather positive chains of events. They would rarely be the only factor, but they are certainly great at unlocking potential.

The post The Benefits of Side Projects appeared first on Bozho's tech blog.

The Practical Effects of GDPR at Backblaze

Post Syndicated from Andy Klein original https://www.backblaze.com/blog/the-practical-effects-of-gdpr-at-backblaze/


GDPR day, May 25, 2018, is nearly here. On that day, will your inbox explode with update notices, opt-in agreements, and offers from lawyers searching for GDPR violators? Perhaps all the companies on earth that are not GDPR ready will just dissolve into dust. More likely, there will be some changes, but business as usual will continue and we’ll all be more aware of data privacy. Let’s go with the last one.

What’s Different With GDPR at Backblaze

The biggest difference you’ll notice is a completely updated Privacy Policy. Last week we sent out a service email announcing the new Privacy Policy. Some people asked what was different. Basically everything. About 95% of the agreement was rewritten. In the agreement, we added in the appropriate provisions required by GDPR, and hopefully did a better job specifying the data we collect from you, why we collect it, and what we are going to do with it.

As a reminder, at Backblaze your data falls into two catagories. The first type of data is the data you store with us — stored data. These are the files and objects you upload and store, and as needed, restore. We do not share this data. We do not process this data, except as requested by you to store and restore the data. We do not analyze this data looking for keywords, tags, images, etc. No one outside of Backblaze has access to this data unless you explicitly shared the data by providing that person access to one or more files.

The second type of data is your account data. Some of your account data is considered personal data. This is the information we collect from you to provide our Personal Backup, Business Backup and B2 Cloud Storage services. Examples include your email address to provide access to your account, or the name of your computer so we can organize your files like they are arranged on your computer to make restoration easier. We have written a number of Help Articles covering the different ways this information is collected and processed. In addition, these help articles outline the various “rights” granted via GDPR. We will continue to add help articles over the coming weeks to assist in making it easy to work with us to understand and exercise your rights.

What’s New With GDPR at Backblaze

The most obvious addition is the Data Processing Addendum (DPA). This covers how we protect the data you store with us, i.e. stored data. As noted above, we don’t do anything with your data, except store it and keep it safe until you need it. Now we have a separate document saying that.

It is important to note the new Data Processing Addendum is now incorporated by reference into our Terms of Service, which everyone agrees to when they sign up for any of our services. Now all of our customers have a shiny new Data Processing Agreement to go along with the updated Privacy Policy. We promise they are not long or complicated, and we encourage you to read them. If you have any questions, stop by our GDPR help section on our website.

Patience, Please

Every company we have dealt with over the last few months is working hard to comply with GDPR. It has been a tough road whether you tried to do it yourself or like Backblaze, hired an EU-based law firm for advice. Over the coming weeks and months as you reach out to discover and assert your rights, please have a little patience. We are all going through a steep learning curve as GDPR gets put into practice. Along the way there are certain to be some growing pains — give us a chance, we all want to get it right.

Regardless, at Backblaze we’ve been diligently protecting our customers’ data for over 11 years and nothing that will happen on May 25th will change that.

The post The Practical Effects of GDPR at Backblaze appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

AWS GDPR Data Processing Addendum – Now Part of Service Terms

Post Syndicated from Chad Woolf original https://aws.amazon.com/blogs/security/aws-gdpr-data-processing-addendum/

Today, we’re happy to announce that the AWS GDPR Data Processing Addendum (GDPR DPA) is now part of our online Service Terms. This means all AWS customers globally can rely on the terms of the AWS GDPR DPA which will apply automatically from May 25, 2018, whenever they use AWS services to process personal data under the GDPR. The AWS GDPR DPA also includes EU Model Clauses, which were approved by the European Union (EU) data protection authorities, known as the Article 29 Working Party. This means that AWS customers wishing to transfer personal data from the European Economic Area (EEA) to other countries can do so with the knowledge that their personal data on AWS will be given the same high level of protection it receives in the EEA.

As we approach the GDPR enforcement date this week, this announcement is an important GDPR compliance component for us, our customers, and our partners. All customers which that are using cloud services to process personal data will need to have a data processing agreement in place between them and their cloud services provider if they are to comply with GDPR. As early as April 2017, AWS announced that AWS had a GDPR-ready DPA available for its customers. In this way, we started offering our GDPR DPA to customers over a year before the May 25, 2018 enforcement date. Now, with the DPA terms included in our online service terms, there is no extra engagement needed by our customers and partners to be compliant with the GDPR requirement for data processing terms.

The AWS GDPR DPA also provides our customers with a number of other important assurances, such as the following:

  • AWS will process customer data only in accordance with customer instructions.
  • AWS has implemented and will maintain robust technical and organizational measures for the AWS network.
  • AWS will notify its customers of a security incident without undue delay after becoming aware of the security incident.
  • AWS will make available certificates issued in relation to the ISO 27001 certification, the ISO 27017 certification, and the ISO 27018 certification to further help customers and partners in their own GDPR compliance activities.

Customers who have already signed an offline version of the AWS GDPR DPA can continue to rely on that GDPR DPA. By incorporating our GDPR DPA into the AWS Service Terms, we are simply extending the terms of our GDPR DPA to all customers globally who will require it under GDPR.

AWS GDPR DPA is only part of the story, however. We are continuing to work alongside our customers and partners to help them on their journey towards GDPR compliance.

If you have any questions about the GDPR or the AWS GDPR DPA, please contact your account representative, or visit the AWS GDPR Center at: https://aws.amazon.com/compliance/gdpr-center/

-Chad

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