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How to Patch Linux Workloads on AWS

Post Syndicated from Koen van Blijderveen original https://aws.amazon.com/blogs/security/how-to-patch-linux-workloads-on-aws/

Most malware tries to compromise your systems by using a known vulnerability that the operating system maker has already patched. As best practices to help prevent malware from affecting your systems, you should apply all operating system patches and actively monitor your systems for missing patches.

In this blog post, I show you how to patch Linux workloads using AWS Systems Manager. To accomplish this, I will show you how to use the AWS Command Line Interface (AWS CLI) to:

  1. Launch an Amazon EC2 instance for use with Systems Manager.
  2. Configure Systems Manager to patch your Amazon EC2 Linux instances.

In two previous blog posts (Part 1 and Part 2), I showed how to use the AWS Management Console to perform the necessary steps to patch, inspect, and protect Microsoft Windows workloads. You can implement those same processes for your Linux instances running in AWS by changing the instance tags and types shown in the previous blog posts.

Because most Linux system administrators are more familiar with using a command line, I show how to patch Linux workloads by using the AWS CLI in this blog post. The steps to use the Amazon EBS Snapshot Scheduler and Amazon Inspector are identical for both Microsoft Windows and Linux.

What you should know first

To follow along with the solution in this post, you need one or more Amazon EC2 instances. You may use existing instances or create new instances. For this post, I assume this is an Amazon EC2 for Amazon Linux instance installed from Amazon Machine Images (AMIs).

Systems Manager is a collection of capabilities that helps you automate management tasks for AWS-hosted instances on Amazon EC2 and your on-premises servers. In this post, I use Systems Manager for two purposes: to run remote commands and apply operating system patches. To learn about the full capabilities of Systems Manager, see What Is AWS Systems Manager?

As of Amazon Linux 2017.09, the AMI comes preinstalled with the Systems Manager agent. Systems Manager Patch Manager also supports Red Hat and Ubuntu. To install the agent on these Linux distributions or an older version of Amazon Linux, see Installing and Configuring SSM Agent on Linux Instances.

If you are not familiar with how to launch an Amazon EC2 instance, see Launching an Instance. I also assume you launched or will launch your instance in a private subnet. You must make sure that the Amazon EC2 instance can connect to the internet using a network address translation (NAT) instance or NAT gateway to communicate with Systems Manager. The following diagram shows how you should structure your VPC.

Diagram showing how to structure your VPC

Later in this post, you will assign tasks to a maintenance window to patch your instances with Systems Manager. To do this, the IAM user you are using for this post must have the iam:PassRole permission. This permission allows the IAM user assigning tasks to pass his own IAM permissions to the AWS service. In this example, when you assign a task to a maintenance window, IAM passes your credentials to Systems Manager. You also should authorize your IAM user to use Amazon EC2 and Systems Manager. As mentioned before, you will be using the AWS CLI for most of the steps in this blog post. Our documentation shows you how to get started with the AWS CLI. Make sure you have the AWS CLI installed and configured with an AWS access key and secret access key that belong to an IAM user that have the following AWS managed policies attached to the IAM user you are using for this example: AmazonEC2FullAccess and AmazonSSMFullAccess.

Step 1: Launch an Amazon EC2 Linux instance

In this section, I show you how to launch an Amazon EC2 instance so that you can use Systems Manager with the instance. This step requires you to do three things:

  1. Create an IAM role for Systems Manager before launching your Amazon EC2 instance.
  2. Launch your Amazon EC2 instance with Amazon EBS and the IAM role for Systems Manager.
  3. Add tags to the instances so that you can add your instances to a Systems Manager maintenance window based on tags.

A. Create an IAM role for Systems Manager

Before launching an Amazon EC2 instance, I recommend that you first create an IAM role for Systems Manager, which you will use to update the Amazon EC2 instance. AWS already provides a preconfigured policy that you can use for the new role and it is called AmazonEC2RoleforSSM.

  1. Create a JSON file named trustpolicy-ec2ssm.json that contains the following trust policy. This policy describes which principal (an entity that can take action on an AWS resource) is allowed to assume the role we are going to create. In this example, the principal is the Amazon EC2 service.
      "Version": "2012-10-17",
      "Statement": {
        "Effect": "Allow",
        "Principal": {"Service": "ec2.amazonaws.com"},
        "Action": "sts:AssumeRole"

  1. Use the following command to create a role named EC2SSM that has the AWS managed policy AmazonEC2RoleforSSM attached to it. This generates JSON-based output that describes the role and its parameters, if the command is successful.
    $ aws iam create-role --role-name EC2SSM --assume-role-policy-document file://trustpolicy-ec2ssm.json

  1. Use the following command to attach the AWS managed IAM policy (AmazonEC2RoleforSSM) to your newly created role.
    $ aws iam attach-role-policy --role-name EC2SSM --policy-arn arn:aws:iam::aws:policy/service-role/AmazonEC2RoleforSSM

  1. Use the following commands to create the IAM instance profile and add the role to the instance profile. The instance profile is needed to attach the role we created earlier to your Amazon EC2 instance.
    $ aws iam create-instance-profile --instance-profile-name EC2SSM-IP
    $ aws iam add-role-to-instance-profile --instance-profile-name EC2SSM-IP --role-name EC2SSM

B. Launch your Amazon EC2 instance

To follow along, you need an Amazon EC2 instance that is running Amazon Linux. You can use any existing instance you may have or create a new instance.

When launching a new Amazon EC2 instance, be sure that:

  1. Use the following command to launch a new Amazon EC2 instance using an Amazon Linux AMI available in the US East (N. Virginia) Region (also known as us-east-1). Replace YourKeyPair and YourSubnetId with your information. For more information about creating a key pair, see the create-key-pair documentation. Write down the InstanceId that is in the output because you will need it later in this post.
    $ aws ec2 run-instances --image-id ami-cb9ec1b1 --instance-type t2.micro --key-name YourKeyPair --subnet-id YourSubnetId --iam-instance-profile Name=EC2SSM-IP

  1. If you are using an existing Amazon EC2 instance, you can use the following command to attach the instance profile you created earlier to your instance.
    $ aws ec2 associate-iam-instance-profile --instance-id YourInstanceId --iam-instance-profile Name=EC2SSM-IP

C. Add tags

The final step of configuring your Amazon EC2 instances is to add tags. You will use these tags to configure Systems Manager in Step 2 of this post. For this example, I add a tag named Patch Group and set the value to Linux Servers. I could have other groups of Amazon EC2 instances that I treat differently by having the same tag name but a different tag value. For example, I might have a collection of other servers with the tag name Patch Group with a value of Web Servers.

  • Use the following command to add the Patch Group tag to your Amazon EC2 instance.
    $ aws ec2 create-tags --resources YourInstanceId --tags --tags Key="Patch Group",Value="Linux Servers"

Note: You must wait a few minutes until the Amazon EC2 instance is available before you can proceed to the next section. To make sure your Amazon EC2 instance is online and ready, you can use the following AWS CLI command:

$ aws ec2 describe-instance-status --instance-ids YourInstanceId

At this point, you now have at least one Amazon EC2 instance you can use to configure Systems Manager.

Step 2: Configure Systems Manager

In this section, I show you how to configure and use Systems Manager to apply operating system patches to your Amazon EC2 instances, and how to manage patch compliance.

To start, I provide some background information about Systems Manager. Then, I cover how to:

  1. Create the Systems Manager IAM role so that Systems Manager is able to perform patch operations.
  2. Create a Systems Manager patch baseline and associate it with your instance to define which patches Systems Manager should apply.
  3. Define a maintenance window to make sure Systems Manager patches your instance when you tell it to.
  4. Monitor patch compliance to verify the patch state of your instances.

You must meet two prerequisites to use Systems Manager to apply operating system patches. First, you must attach the IAM role you created in the previous section, EC2SSM, to your Amazon EC2 instance. Second, you must install the Systems Manager agent on your Amazon EC2 instance. If you have used a recent Amazon Linux AMI, Amazon has already installed the Systems Manager agent on your Amazon EC2 instance. You can confirm this by logging in to an Amazon EC2 instance and checking the Systems Manager agent log files that are located at /var/log/amazon/ssm/.

To install the Systems Manager agent on an instance that does not have the agent preinstalled or if you want to use the Systems Manager agent on your on-premises servers, see Installing and Configuring the Systems Manager Agent on Linux Instances. If you forgot to attach the newly created role when launching your Amazon EC2 instance or if you want to attach the role to already running Amazon EC2 instances, see Attach an AWS IAM Role to an Existing Amazon EC2 Instance by Using the AWS CLI or use the AWS Management Console.

A. Create the Systems Manager IAM role

For a maintenance window to be able to run any tasks, you must create a new role for Systems Manager. This role is a different kind of role than the one you created earlier: this role will be used by Systems Manager instead of Amazon EC2. Earlier, you created the role, EC2SSM, with the policy, AmazonEC2RoleforSSM, which allowed the Systems Manager agent on your instance to communicate with Systems Manager. In this section, you need a new role with the policy, AmazonSSMMaintenanceWindowRole, so that the Systems Manager service can execute commands on your instance.

To create the new IAM role for Systems Manager:

  1. Create a JSON file named trustpolicy-maintenancewindowrole.json that contains the following trust policy. This policy describes which principal is allowed to assume the role you are going to create. This trust policy allows not only Amazon EC2 to assume this role, but also Systems Manager.

  1. Use the following command to create a role named MaintenanceWindowRole that has the AWS managed policy, AmazonSSMMaintenanceWindowRole, attached to it. This command generates JSON-based output that describes the role and its parameters, if the command is successful.
    $ aws iam create-role --role-name MaintenanceWindowRole --assume-role-policy-document file://trustpolicy-maintenancewindowrole.json

  1. Use the following command to attach the AWS managed IAM policy (AmazonEC2RoleforSSM) to your newly created role.
    $ aws iam attach-role-policy --role-name MaintenanceWindowRole --policy-arn arn:aws:iam::aws:policy/service-role/AmazonSSMMaintenanceWindowRole

B. Create a Systems Manager patch baseline and associate it with your instance

Next, you will create a Systems Manager patch baseline and associate it with your Amazon EC2 instance. A patch baseline defines which patches Systems Manager should apply to your instance. Before you can associate the patch baseline with your instance, though, you must determine if Systems Manager recognizes your Amazon EC2 instance. Use the following command to list all instances managed by Systems Manager. The --filters option ensures you look only for your newly created Amazon EC2 instance.

$ aws ssm describe-instance-information --filters Key=InstanceIds,Values= YourInstanceId

    "InstanceInformationList": [
            "IsLatestVersion": true,
            "ComputerName": "ip-10-50-2-245",
            "PingStatus": "Online",
            "InstanceId": "YourInstanceId",
            "IPAddress": "",
            "ResourceType": "EC2Instance",
            "AgentVersion": "",
            "PlatformVersion": "2017.09",
            "PlatformName": "Amazon Linux AMI",
            "PlatformType": "Linux",
            "LastPingDateTime": 1515759143.826

If your instance is missing from the list, verify that:

  1. Your instance is running.
  2. You attached the Systems Manager IAM role, EC2SSM.
  3. You deployed a NAT gateway in your public subnet to ensure your VPC reflects the diagram shown earlier in this post so that the Systems Manager agent can connect to the Systems Manager internet endpoint.
  4. The Systems Manager agent logs don’t include any unaddressed errors.

Now that you have checked that Systems Manager can manage your Amazon EC2 instance, it is time to create a patch baseline. With a patch baseline, you define which patches are approved to be installed on all Amazon EC2 instances associated with the patch baseline. The Patch Group resource tag you defined earlier will determine to which patch group an instance belongs. If you do not specifically define a patch baseline, the default AWS-managed patch baseline is used.

To create a patch baseline:

  1. Use the following command to create a patch baseline named AmazonLinuxServers. With approval rules, you can determine the approved patches that will be included in your patch baseline. In this example, you add all Critical severity patches to the patch baseline as soon as they are released, by setting the Auto approval delay to 0 days. By setting the Auto approval delay to 2 days, you add to this patch baseline the Important, Medium, and Low severity patches two days after they are released.
    $ aws ssm create-patch-baseline --name "AmazonLinuxServers" --description "Baseline containing all updates for Amazon Linux" --operating-system AMAZON_LINUX --approval-rules "PatchRules=[{PatchFilterGroup={PatchFilters=[{Values=[Critical],Key=SEVERITY}]},ApproveAfterDays=0,ComplianceLevel=CRITICAL},{PatchFilterGroup={PatchFilters=[{Values=[Important,Medium,Low],Key=SEVERITY}]},ApproveAfterDays=2,ComplianceLevel=HIGH}]"
        "BaselineId": "YourBaselineId"

  1. Use the following command to register the patch baseline you created with your instance. To do so, you use the Patch Group tag that you added to your Amazon EC2 instance.
    $ aws ssm register-patch-baseline-for-patch-group --baseline-id YourPatchBaselineId --patch-group "Linux Servers"
        "PatchGroup": "Linux Servers",
        "BaselineId": "YourBaselineId"

C.  Define a maintenance window

Now that you have successfully set up a role, created a patch baseline, and registered your Amazon EC2 instance with your patch baseline, you will define a maintenance window so that you can control when your Amazon EC2 instances will receive patches. By creating multiple maintenance windows and assigning them to different patch groups, you can make sure your Amazon EC2 instances do not all reboot at the same time.

To define a maintenance window:

  1. Use the following command to define a maintenance window. In this example command, the maintenance window will start every Saturday at 10:00 P.M. UTC. It will have a duration of 4 hours and will not start any new tasks 1 hour before the end of the maintenance window.
    $ aws ssm create-maintenance-window --name SaturdayNight --schedule "cron(0 0 22 ? * SAT *)" --duration 4 --cutoff 1 --allow-unassociated-targets
        "WindowId": "YourMaintenanceWindowId"

For more information about defining a cron-based schedule for maintenance windows, see Cron and Rate Expressions for Maintenance Windows.

  1. After defining the maintenance window, you must register the Amazon EC2 instance with the maintenance window so that Systems Manager knows which Amazon EC2 instance it should patch in this maintenance window. You can register the instance by using the same Patch Group tag you used to associate the Amazon EC2 instance with the AWS-provided patch baseline, as shown in the following command.
    $ aws ssm register-target-with-maintenance-window --window-id YourMaintenanceWindowId --resource-type INSTANCE --targets "Key=tag:Patch Group,Values=Linux Servers"
        "WindowTargetId": "YourWindowTargetId"

  1. Assign a task to the maintenance window that will install the operating system patches on your Amazon EC2 instance. The following command includes the following options.
    1. name is the name of your task and is optional. I named mine Patching.
    2. task-arn is the name of the task document you want to run.
    3. max-concurrency allows you to specify how many of your Amazon EC2 instances Systems Manager should patch at the same time. max-errors determines when Systems Manager should abort the task. For patching, this number should not be too low, because you do not want your entire patch task to stop on all instances if one instance fails. You can set this, for example, to 20%.
    4. service-role-arn is the Amazon Resource Name (ARN) of the AmazonSSMMaintenanceWindowRole role you created earlier in this blog post.
    5. task-invocation-parameters defines the parameters that are specific to the AWS-RunPatchBaseline task document and tells Systems Manager that you want to install patches with a timeout of 600 seconds (10 minutes).
      $ aws ssm register-task-with-maintenance-window --name "Patching" --window-id "YourMaintenanceWindowId" --targets "Key=WindowTargetIds,Values=YourWindowTargetId" --task-arn AWS-RunPatchBaseline --service-role-arn "arn:aws:iam::123456789012:role/MaintenanceWindowRole" --task-type "RUN_COMMAND" --task-invocation-parameters "RunCommand={Comment=,TimeoutSeconds=600,Parameters={SnapshotId=[''],Operation=[Install]}}" --max-concurrency "500" --max-errors "20%"
          "WindowTaskId": "YourWindowTaskId"

Now, you must wait for the maintenance window to run at least once according to the schedule you defined earlier. If your maintenance window has expired, you can check the status of any maintenance tasks Systems Manager has performed by using the following command.

$ aws ssm describe-maintenance-window-executions --window-id "YourMaintenanceWindowId"

    "WindowExecutions": [
            "Status": "SUCCESS",
            "WindowId": "YourMaintenanceWindowId",
            "WindowExecutionId": "b594984b-430e-4ffa-a44c-a2e171de9dd3",
            "EndTime": 1515766467.487,
            "StartTime": 1515766457.691

D.  Monitor patch compliance

You also can see the overall patch compliance of all Amazon EC2 instances using the following command in the AWS CLI.

$ aws ssm list-compliance-summaries

This command shows you the number of instances that are compliant with each category and the number of instances that are not in JSON format.

You also can see overall patch compliance by choosing Compliance under Insights in the navigation pane of the Systems Manager console. You will see a visual representation of how many Amazon EC2 instances are up to date, how many Amazon EC2 instances are noncompliant, and how many Amazon EC2 instances are compliant in relation to the earlier defined patch baseline.

Screenshot of the Compliance page of the Systems Manager console

In this section, you have set everything up for patch management on your instance. Now you know how to patch your Amazon EC2 instance in a controlled manner and how to check if your Amazon EC2 instance is compliant with the patch baseline you have defined. Of course, I recommend that you apply these steps to all Amazon EC2 instances you manage.


In this blog post, I showed how to use Systems Manager to create a patch baseline and maintenance window to keep your Amazon EC2 Linux instances up to date with the latest security patches. Remember that by creating multiple maintenance windows and assigning them to different patch groups, you can make sure your Amazon EC2 instances do not all reboot at the same time.

If you have comments about this post, submit them in the “Comments” section below. If you have questions about or issues implementing any part of this solution, start a new thread on the Amazon EC2 forum or contact AWS Support.

– Koen

HackSpace magazine 4: the wearables issue

Post Syndicated from Andrew Gregory original https://www.raspberrypi.org/blog/hackspace-4-wearables/

Big things are afoot in the world of HackSpace magazine! This month we’re running our first special issue, with wearables projects throughout the magazine. Moreover, we’re giving away our first subscription gift free to all 12-month print subscribers. Lastly, and most importantly, we’ve made the cover EXTRA SHINY!

HackSpace magazine issue 4 cover

Prepare your eyeballs — it’s HackSpace magazine issue 4!


In this issue, we’re taking an in-depth look at wearable tech. Not Fitbits or Apple Watches — we’re talking stuff you can make yourself, from projects that take a couple of hours to put together, to the huge, inspiring builds that are bringing technology to the runway. If you like wearing clothes and you like using your brain to make things better, then you’ll love this feature.

We’re continuing our obsession with Nixie tubes, with the brilliant Time-To-Go-Clock – Trump edition. This ingenious bit of kit uses obsolete Russian electronics to count down the time until the end of the 45th president’s term in office. However, you can also program it to tell the time left to any predictable event, such as the deadline for your tax return or essay submission, or the date England gets knocked out of the World Cup.

HackSpace magazine page 08
HackSpace magazine page 70
HackSpace magazine issue 4 page 98

We’re also talking to Dr Lucy Rogers — NASA alumna, Robot Wars judge, and fellow of the Institution of Mechanical Engineers — about the difference between making as a hobby and as a job, and about why we need the Guild of Makers. Plus, issue 4 has a teeny boat, the most beautiful Raspberry Pi cases you’ve ever seen, and it explores the results of what happens when you put a bunch of hardware hackers together in a French chateau — sacré bleu!


As always, we’ve got more how-tos than you can shake a soldering iron at. Fittingly for the current climate here in the UK, there’s a hot water monitor, which shows you how long you have before your morning shower turns cold, and an Internet of Tea project to summon a cuppa from your kettle via the web. Perhaps not so fittingly, there’s also an ESP8266 project for monitoring a solar power station online. Readers in the southern hemisphere, we’ll leave that one for you — we haven’t seen the sun here for months!

And there’s more!

We’re super happy to say that all our 12-month print subscribers have been sent an Adafruit Circuit Playground Express with this new issue:

Adafruit Circuit Playground Express HackSpace

This gadget was developed primarily with wearables in mind and comes with all sorts of in-built functionality, so subscribers can get cracking with their latest wearable project today! If you’re not a 12-month print subscriber, you’ll miss out, so subscribe here to get your magazine and your device,  and let us know what you’ll make.

The post HackSpace magazine 4: the wearables issue appeared first on Raspberry Pi.

Court Dismisses Playboy’s Copyright Claims Against Boing Boing

Post Syndicated from Ernesto original https://torrentfreak.com/court-dismisses-playboys-copyright-claims-against-boing-boing-180215/

Early 2016, Boing Boing co-editor Xeni Jardin published an article in which she linked to an archive of every Playboy centerfold image till then.

“Kind of amazing to see how our standards of hotness, and the art of commercial erotic photography, have changed over time,” Jardin commented.

While the linked material undoubtedly appealed to many readers, Playboy itself took offense to the fact that infringing copies of their work were being shared in public. While Boing Boing didn’t upload or store the images in question, the publisher filed a lawsuit late last year.

The blog’s parent company Happy Mutants was accused of various counts of copyright infringement, with Playboy claiming that it exploited their playmates’ images for commercial purposes.

Boing Boing saw things differently. With help from the Electronic Frontier Foundation (EFF) it filed a motion to dismiss, arguing that hyperlinking is not copyright infringement. If Playboy would’ve had their way, millions of other Internet users could be sued for linking too.

“This case merely has to survive a motion to dismiss to launch a thousand more expensive lawsuits, chilling a broad variety of lawful expression and reporting that merely adopts the common practice of linking to the material that is the subject of the report,” they wrote.

The article in question

Yesterday US District Court Judge Fernando Olguin ruled on the matter. In a brief order, he concluded that an oral argument is not needed and that based on the arguments from both sides, the case should be dismissed with leave.

This effectively means that Playboy’s complaint has been thrown out. However, the company is offered a lifeline and is allowed to submit a new one if they can properly back up their copyright infringement allegations.

“The court will grant defendant’s Motion and dismiss plaintiff’s First Amended Complaint with leave to amend. In preparing the Second Amended Complaint, plaintiff shall carefully evaluate the contentions set forth in defendant’s Motion.

“For example, the court is skeptical that plaintiff has sufficiently alleged facts to support either its inducement or material contribution theories of copyright infringement,” Judge Olguin adds.

According to the order, it is not sufficient to argue that Boing Boing merely ‘provided the means’ to carry out copyright infringing activity. There also has to be a personal action that ‘assists’ the infringing activity.

Playboy has until the end of the month to submit a new complaint and if it chooses not to do so, the case will be thrown out.

The order is clearly a win for Boing Boing, which vehemently opposed Playboy’s claims. While the order is clear, it must come as a surprise to the magazine publisher, which won a similar ‘hyperlinking’ lawsuit in the European Court of Justice last year.

EFF, who defend Boing Boing, is happy with the order and hopes that Playboy will leave it at this.

“From the outset of this lawsuit, we have been puzzled as to why Playboy, once a staunch defender of the First Amendment, would attack a small news and commentary website,” EFF comments

“Today’s decision leaves Playboy with a choice: it can try again with a new complaint or it can leave this lawsuit behind. We don’t believe there’s anything Playboy could add to its complaint that would meet the legal standard. We hope that it will choose not to continue with its misguided suit.”

A copy of US District Court Judge Fernando Olguin’s order is available here (pdf).

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN discounts, offers and coupons

Top 10 Most Pirated Movies of The Week on BitTorrent – 02/12/18

Post Syndicated from Ernesto original https://torrentfreak.com/top-10-pirated-movies-week-bittorrent-021218/

This week we have three newcomers in our chart.

Coco is the most downloaded movie.

The data for our weekly download chart is estimated by TorrentFreak, and is for informational and educational reference only. All the movies in the list are Web-DL/Webrip/HDRip/BDrip/DVDrip unless stated otherwise.

RSS feed for the weekly movie download chart.

This week’s most downloaded movies are:
Movie Rank Rank last week Movie name IMDb Rating / Trailer
Most downloaded movies via torrents
1 (6) Coco 8.9 / trailer
2 (1) Thor Ragnarok 8.1 / trailer
3 (…) Daddy’s Home 2 6.0 / trailer
4 (3) The Shape of Water (DVDScr) 8.0 / trailer
5 (…) Murder on The Orient Express 6.7 / trailer
6 (2) Jumanji: Welcome to the Jungle (HDTS) 7.3 / trailer
7 (9) Justice League (Subbed HDRip) 7.1 / trailer
8 (5) Blade Runner 2049 8.9 / trailer
9 (7) Braven 5.6 / trailer
10 (…) The Cloverfield Paradox 5.8 / trailer

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN discounts, offers and coupons

BootStomp – Find Android Bootloader Vulnerabilities

Post Syndicated from Darknet original https://www.darknet.org.uk/2018/02/bootstomp-find-android-bootloader-vulnerabilities/?utm_source=rss&utm_medium=social&utm_campaign=darknetfeed

BootStomp – Find Android Bootloader Vulnerabilities

BootStomp is a Python-based tool, with Docker support that helps you find two different classes of Android bootloader vulnerabilities and bugs. It looks for memory corruption and state storage vulnerabilities.

Note that BootStomp works with boot-loaders compiled for ARM architectures (32 and 64 bits both) and that results might slightly vary depending on angr and Z3’s versions. This is because of the time angr takes to analyze basic blocks and to Z3’s expression concretization results.

Read the rest of BootStomp – Find Android Bootloader Vulnerabilities now! Only available at Darknet.

Playboy’s Copyright Lawsuit Threatens Online Expression, Boing Boing Argues

Post Syndicated from Ernesto original https://torrentfreak.com/playboys-copyright-lawsuit-threatens-online-expression-boing-boing-argues-180202/

Early 2016, Boing Boing co-editor Xeni Jardin published an article in which she linked to an archive of every Playboy centerfold image till then.

“Kind of amazing to see how our standards of hotness, and the art of commercial erotic photography, have changed over time,” Jardin commented.

While the linked material undoubtedly appealed to many readers, Playboy itself took offense to the fact that infringing copies of their work were being shared in public. While Boing Boing didn’t upload or store the images in question, the publisher filed a complaint.

Playboy accused the blog’s parent company Happy Mutants of various counts of copyright infringement, claiming that it exploited their playmates’ images for commercial purposes.

Last month Boing Boing responded to the allegations with a motion to dismiss. The case should be thrown out, it argued, noting that linking to infringing material for the purpose of reporting and commentary, is not against the law.

This prompted Playboy to fire back, branding Boing Boing a “clickbait” site. Playboy informed the court that the popular blog profits off the work of others and has no fair use defense.

Before the California District Court decides on the matter, Boing Boing took the opportunity to reply to Playboy’s latest response. According to the defense, Playboy’s case is an attack on people’s freedom of expression.

“Playboy claims this is an important case. It is partially correct: if the Court allows this case to go forward, it will send a dangerous message to everyone engaged in ordinary online commentary,” Boing Boing’s reply reads.

Referencing a previous Supreme Court decision, the blog says that the Internet democratizes access to speech, with websites as a form of modern-day pamphlets.

Links to source materials posted by third parties give these “pamphlets” more weight as they allow readers to form their own opinion on the matter, Boing Boing argues. If the court upholds Playboy’s arguments, however, this will become a risky endeavor.

“Playboy, however, would apparently prefer a world in which the ‘pamphleteer’ must ask for permission before linking to primary sources, on pain of expensive litigation,” the defense writes.

“This case merely has to survive a motion to dismiss to launch a thousand more expensive lawsuits, chilling a broad variety of lawful expression and reporting that merely adopts the common practice of linking to the material that is the subject of the report.”

The defense says that there are several problems with Playboy’s arguments. Among other things, Boing Boing argues that did nothing to cause the unauthorized posting of Playboy’s work on Imgur and YouTube.

Another key argument is that linking to copyright-infringing material should be considered fair use, since it was for purposes of criticism, commentary, and news reporting.

“Settled precedent requires dismissal, both because Boing Boing did not induce or materially contribute to any copyright infringement and, in the alternative, because Boing Boing engaged in fair use,” the defense writes.

Instead of going after Boing Boing for contributory infringement, Playboy could actually try to uncover the people who shared the infringing material, they argue. There is nothing that prevents them from doing so.

After hearing the arguments from both sides it is now up to the court to decide how to proceed. Given what’s at stake, the eventual outcome in this case is bound to set a crucial precedent.

A copy of Boing Boing’s reply is available here (pdf).

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN discounts, offers and coupons

Addressing Data Residency with AWS

Post Syndicated from Min Hyun original https://aws.amazon.com/blogs/security/addressing-data-residency-with-aws/

Whitepaper image

AWS has released a new whitepaper that has been requested by many AWS customers: AWS Policy Perspectives: Data Residency. Data residency is the requirement that all customer content processed and stored in an IT system must remain within a specific country’s borders, and it is one of the foremost concerns of governments that want to use commercial cloud services. General cybersecurity concerns and concerns about government requests for data have contributed to a continued focus on keeping data within countries’ borders. In fact, some governments have determined that mandating data residency provides an extra layer of security.

This approach, however, is counterproductive to the data protection objectives and the IT modernization and global economic growth goals that many governments have set as milestones. This new whitepaper addresses the real and perceived security risks expressed by governments when they demand in-country data residency by identifying the most likely and prevalent IT vulnerabilities and security risks, explaining the native security embedded in cloud services, and highlighting the roles and responsibilities of cloud service providers (CSPs), governments, and customers in protecting data.

Large-scale, multinational CSPs, often called hyperscale CSPs, represent a transformational disruption in technology because of how they support their customers with high degrees of efficiency, agility, and innovation as part of world-class security offerings. The whitepaper explains how hyperscale CSPs, such as AWS, that might be located out of country provide their customers the ability to achieve high levels of data protection through safeguards on their own platform and with turnkey tooling for their customers. They do this while at the same time preserving nation-state regulatory sovereignty.

The whitepaper also considers the commercial, public-sector, and economic effects of data residency policies and offers considerations for governments to evaluate before enforcing requirements that can unintentionally limit public-sector digital transformation goals, in turn possibly leading to increased cybersecurity risk.

AWS continues to engage with governments around the world to hear and address their top-of-mind security concerns. We take seriously our commitment to advocate for our customers’ interests and enforce security from “ground zero.” This means that when customers use AWS, they can have the confidence that their data is protected with a level of assurance that meets, if not exceeds, their needs, regardless of where the data resides.

– Min Hyun, Cloud Security Policy Strategist

Four days of STEAM at Bett 2018

Post Syndicated from Dan Fisher original https://www.raspberrypi.org/blog/bett-2018/

If you’re an educator from the UK, chances are you’ve heard of Bett. For everyone else: Bett stands for British Education Technology Tradeshow. It’s the El Dorado of edtech, where every street is adorned with interactive whiteboards, VR headsets, and new technologies for the classroom. Every year since 2014, the Raspberry Pi Foundation has been going to the event hosted in the ExCeL London to chat to thousands of lovely educators about our free programmes and resources.

Raspberry Pi Bett 2018

On a mission

Our setup this year consisted of four pods (imagine tables on steroids) in the STEAM village, and the mission of our highly trained team of education agents was to establish a new world record for Highest number of teachers talked to in a four-day period. I’m only half-joking.

Bett 2018 Raspberry Pi

Educators with a mission

Meeting educators

The best thing about being at Bett is meeting the educators who use our free content and training materials. It’s easy to get wrapped up in the everyday tasks of the office without stopping to ask: “Hey, have we asked our users what they want recently?” Events like Bett help us to connect with our audience, creating some lovely moments for both sides. We had plenty of Hello World authors visit us, including Gary Stager, co-author of Invent to Learn, a must-read for any computing educator. More than 700 people signed up for a digital subscription, we had numerous lovely conversations about our content and about ideas for new articles, and we met many new authors expressing an interest in writing for us in the future.

BETT 2018 Hello World Raspberry Pi
BETT 2018 Hello World Raspberry Pi
BETT 2018 Hello World Raspberry Pi

We also talked to lots of Raspberry Pi Certified Educators who we’d trained in our free Picademy programme — new dates in Belfast and Dublin now! — and who are now doing exciting and innovative things in their local areas. For example, Chris Snowden came to tell us about the great digital making outreach work he has been doing with the Eureka! museum in Yorkshire.

Bett 2018 Raspberry Pi

Raspberry Pi Certified Educator Chris Snowden

Digital making for kids

The other best thing about being at Bett is running workshops for young learners and seeing the delight on their faces when they accomplish something they believed to be impossible only five minutes ago. On the Saturday, we ran a massive Raspberry Jam/Code Club where over 250 children, parents, and curious onlookers got stuck into some of our computing activities. We were super happy to find out that we’d won the Bett Kids’ Choice Award for Best Hands-on Experience — a fantastic end to a busy four days. With Bett over for another year, our tired and happy ‘rebel alliance’ from across the Foundation still had the energy to pose for a group photo.

Bett 2018 Raspberry Pi

Celebrating our ‘Best Hands-on Experience’ award

More events

You can find out more about starting a Code Club here, and if you’re running a Jam, why not get involved with our global Raspberry Jam Big Birthday Weekend celebrations in March?

Raspberry Pi Big Birthday Weekend 2018. GIF with confetti and bopping JAM balloons

We’ll be at quite a few events in 2018, including the Big Bang Fair in March — do come and say hi.

The post Four days of STEAM at Bett 2018 appeared first on Raspberry Pi.

New Anti-Piracy Coalition Calls For Canadian Website Blocking

Post Syndicated from Ernesto original https://torrentfreak.com/new-anti-piracy-coalition-calls-for-canadian-website-blocking-180130/

In recent years pirate sites have been blocked around the world, from Europe, through Asia, and even Down Under.

While many of the large corporations backing these blockades have their roots in North America, blocking efforts have been noticeably absent there. This should change, according to a new anti-piracy coalition that was launched in Canada this week.

Fairplay Canada, which consists of a broad range of organizations with ties to the entertainment industry, calls on the local telecom regulator CRTC to institute a national website blocking program.

The coalition’s members include Bell, Cineplex, Directors Guild of Canada, Maple Leaf Sports and Entertainment, Movie Theatre Association of Canada, and Rogers Media, which all share the goal of addressing the country’s rampant piracy problem.

The Canadian blocklist should be maintained by a yet to be established non-profit organization called “Independent Piracy Review Agency” (IPRA) and both IPRA and the CRTC would be overseen by the Federal Court of Appeal, the organizations propose.

“What we are proposing has been effective in countries like the UK, France, and Australia,” says Dr. Shan Chandrasekar, President and CEO of Asian Television Network International Limited (ATN), who is filing Fairplay Canada’s application.

“We are ardent supporters of this incredible coalition that has been formed to propose a new tool to empower the CRTC to address online piracy in Canada. We have great faith in Canadian regulators to modernize the tools available to help creators protect the content they make for Canadians’ enjoyment.”

The proposal is unique in the sense that it’s the first of its kind in North America and also has support from major players in the Telco industry. Since most large ISPs also have ties to media companies of their own, the latter is less surprising as it may seem at first glance.

Bell, for example, is not only the largest Internet provider in Canada but also owns the television broadcasting and production company Bell Media, which applauds the new plan.

“Bell is pleased to work with our partners across the industry and the CRTC on this important step in ensuring the long-term viability of the Canadian creative sector,” says Randy Lennox, President of Bell Media.

“Digital rights holders need up-to-date tools to combat piracy where it’s happening, on the Internet, and the process proposed by the coalition will provide just that, fairly, openly and effectively,” he adds.

Thus far the Government’s response to the plan has been rather reserved. When an early version of the plans leaked last month, Canadaland quoted a spokesperson who said that the Government is committed to opening doors instead of building walls.

Digital rights group OpenMedia goes a step further and brands the proposal a censorship plan which will violate net neutrality and limit people’s right to freedom of expression.

“Everybody agrees that content creators deserved to be paid for their work. But the proposal from this censorship coalition goes too far,” Executive Director Laura Tribe says.

“FairPlay Canada’s proposal is like using a machine gun to kill a mosquito. It will undoubtedly lead to legitimate content and speech being censored online violating our right to free expression and the principles of net neutrality, which the federal government has consistently pledged support for.”

While CTRC is reviewing FairPlay Canada’s plans, OpenMedia has launched a petition to stop the effort in its tracks, which has been signed by more than 45,000 Canadians to date.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN discounts, offers and coupons

Udemy Targets ‘Pirate’ Site Giving Away its Paid Courses For Free

Post Syndicated from Andy original https://torrentfreak.com/udemy-targets-pirate-site-giving-away-its-paid-courses-for-free-180129/

While there’s no shortage of people who advocate free sharing of movies and music, passions are often raised when it comes to the availability of educational information.

Significant numbers of people believe that learning should be open to all and that texts and associated materials shouldn’t be locked away by copyright holders trying to monetize knowledge. Of course, people who make a living creating learning materials see the position rather differently.

A clash of these ideals is brewing in the United States where online learning platform Udemy has been trying to have some of its courses taken down from FreeTutorials.us, a site that makes available premium tutorials and other learning materials for free.

Early December 2017, counsel acting for Udemy and a number of its individual and corporate instructors (Maximilian Schwarzmüller, Academind GmbH, Peter Dalmaris, Futureshock Enterprises, Jose Marcial Portilla, and Pierian Data) wrote to FreeTutorials.us with DMCA takedown notice.

“Pursuant to 17 U.S.C. § 512(c)(3)(A) of the Digital Millennium Copyright Act (‘DMCA’), this communication serves as a notice of infringement and request for removal of certain web content available on freetutorials.us,” the letter reads.

“I hereby request that you remove or disable access to the material listed in Exhibit A in as expedient a fashion as possible. This communication does not constitute a waiver of any right to recover damages incurred by virtue of any such unauthorized activities, and such rights as well as claims for other relief are expressly retained.”

A small sample of Exhibit A

On January 10, 2018, the same law firm wrote to Cloudflare, which provides services to FreeTutorials. The DMCA notice asked Cloudflare to disable access to the same set of infringing content listed above.

It seems likely that whatever happened next wasn’t to Udemy’s satisfaction. On January 16, an attorney from the same law firm filed a DMCA subpoena at a district court in California. A DMCA subpoena can enable a copyright holder to obtain the identity of an alleged infringer without having to file a lawsuit and without needing a signature from a judge.

The subpoena was directed at Cloudflare, which provides services to FreeTutorials. The company was ordered to hand over “all identifying information identifying the owner, operator and/or contact person(s) associated with the domain www.freetutorials.us, including but not limited to name(s), address(es), telephone number(s), email address(es), Internet protocol connection records, administrative records and billing records from the time the account was established to the present.”

On January 26, the date by which Cloudflare was ordered to hand over the information, Cloudflare wrote to FreeTutorials with a somewhat late-in-the-day notification.

“We received the attached subpoena regarding freetutorials.us, a domain managed through your Cloudflare account. The subpoena requires us to provide information in our systems related to this website,” the company wrote.

“We have determined that this is a valid subpoena, and we are required to provide the requested information. In accordance with our Privacy Policy, we are informing you before we provide any of the requested subscriber information. We plan to turn over documents in response to the subpoena on January 26th, 2018, unless you intervene in the case.”

With that deadline passing last Friday, it’s safe to say that Cloudflare has complied with the subpoena as the law requires. However, TorrentFreak spoke with FreeTutorials who told us that the company doesn’t hold anything useful on them.

“No, they have nothing,” the team explained.

Noting that they’ll soon dispense with the services of Cloudflare, the team confirmed that they had received emails from Udemy and its instructors but hadn’t done a lot in response.

“How about a ‘NO’? was our answer to all the DMCA takedown requests from Udemy and its Instructors,” they added.

FreeTutorials (FTU) are affiliated with FreeCoursesOnline (FCO) and seem passionate about what they do. In common with others who distribute learning materials online, they express a belief in free education for all, irrespective of financial resources.

“We, FTU and FCO, are a group of seven members assorted as a team from different countries and cities. We are JN, SRZ aka SunRiseZone, Letap, Lihua Google Drive, Kaya, Zinnia, Faiz MeemBazooka,” a spokesperson revealed.

“We’re all members and colleagues and we also have our own daily work and business stuff to do. We have been through that phase of life when we didn’t have enough money to buy books and get tuition or even apply for a good course that we always wanted to have, so FTU & FCO are just our vision to provide Free Education For Everyone.

“We would love to change our priorities towards our current and future projects, only if we manage to get some faithful FTU’ers to join in and help us to grow together and make FTU a place it should be.”

TorrentFreak requested comment from Udemy but at the time of publication, we were yet to hear back. However, we did manage to get in touch with Jonathan Levi, an Udemy instructor who sent this takedown notice to the site in October 2017:

“I’m writing to you on behalf of SuperHuman Enterprises, LLC. You are in violation of our copyright, using our images, and linking to pirated copies of our courses. Remove them IMMEDIATELY or face severe legal action….You have 48 hours to comply,” he wrote, adding:

“And in case you’re going to say I don’t have evidence that I own the files, it’s my fucking face in the videos.”

Levi says that the site had been non-responsive so now things are being taken to the next level.

“They don’t reply to takedowns, so we’ve joined a class action lawsuit against FTU lead by Udemy and a law firm specializing in this type of thing,” Levi concludes.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN discounts, offers and coupons

Top 10 Most Pirated Movies of The Week on BitTorrent – 01/29/18

Post Syndicated from Ernesto original https://torrentfreak.com/top-10-pirated-movies-week-bittorrent-012918/

This week we have three newcomers in our chart.

Thor Ragnarok is the most downloaded movie.

The data for our weekly download chart is estimated by TorrentFreak, and is for informational and educational reference only. All the movies in the list are Web-DL/Webrip/HDRip/BDrip/DVDrip unless stated otherwise.

RSS feed for the weekly movie download chart.

This week’s most downloaded movies are:
Movie Rank Rank last week Movie name IMDb Rating / Trailer
Most downloaded movies via torrents
1 (2) Thor Ragnarok 8.1 / trailer
2 (1) The Shape of Water (DVDScr) 8.0 / trailer
3 (3) Jumanji: Welcome to the Jungle (HDTS) 7.3 / trailer
4 (…) Bright 6.5 / trailer
5 (4) Blade Runner 2049 8.9 / trailer
6 (…) Murder on the Orient Express (Subbed HDrip) 6.7 / trailer
7 (…) Downsizing (Subbed HDrip) 5.8 / trailer
8 (5) Geostorm 5.4 / trailer
9 (8) Justice League (Subbed HDRip) 7.1 / trailer
10 (7) Coco (DVDscr) 8.9 / trailer

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN discounts, offers and coupons

Court Orders Hosting Provider to Stop Pirate Premier League Streams

Post Syndicated from Ernesto original https://torrentfreak.com/court-orders-hosting-provider-to-stop-pirate-premier-league-streams-180126/

In many parts of the world football, or soccer as some would call it, is the number one spectator sport.

The English Premier League, widely regarded as one the top competitions, draws hundreds of millions of viewers per year. Many of these pay for access to the matches, but there’s also a massive circuit of unauthorized streams.

The Football Association Premier League (FAPL) has been clamping down on these pirate sources for years. In the UK, for example, it obtained a unique High Court injunction last year, which requires local Internet providers to block streams as they go live.

In addition, the organization has also filed legal action against a hosting provider through which several live sports streaming sites are operating. The case in question was filed in the Netherlands where Ecatel LTD, a UK company, operated several servers.

According to the complaint, Ecatel hosted sites such as cast247.tv, streamlive.to and iguide.to, which allowed visitors to watch live Premier League streams without paying.

As the streaming platforms themselves were not responsive to takedown requests, the Premier League demanded action from their hosting provider. Specifically, they wanted the company to disconnect live streams on their end, by null-routing the servers of the offending customer.

This week the Court of The Hague issued its judgment, which is a clear win for the football association.

The Court ruled that, after the hosting company receives a takedown notice from FAPL or one of its agents, Ecatel must disconnect pirate Premier League streams within 30 minutes.

“[The Court] recommends that, after 24 hours of service of this judgment, Ecatel cease and discontinue any service used by third parties to infringe the copyright to FAPL by promptly but no later than 30 minutes after receipt of a request to that end,” the verdict reads.

The ban can be lifted after the game has ended, making it a temporary measure similar to the UK Internet provider blockades. If Ecatel fails to comply, it faces a penalty of €5,000 for each illegal stream, to a maximum of € 1,500,000.

While the order is good news for the Premier League, it will be hard to enforce, since Ecatel LTD was dissolved last year. Another hosting company called Novogara was previously linked with Ecatel and is still active, but that is not mentioned in the court order.

This means that the order will mostly be valuable as a precedent. Especially since it goes against an earlier order from 2015, which Emerce pointed out. This warrants a closer look at how the Court reached its decision.

In its defense, Ecatel had argued that an obligation to disconnect customers based on a takedown notice would be disproportionate and violate its entrepreneurial freedoms. The latter is protected by the EU Charter of Fundamental Rights.

The Court, however, highlights that there is a clash between the entrepreneurial rights of Ecatel and the copyrights of FAPL in this case. This requires the Court to weigh these rights to see which prevails over the other.

According to the verdict, the measures Ecatel would have to take to comply are not overly costly. The company already null-routed customers who failed to pay, so the technical capabilities are there.

Ecatel also argued that disconnecting a server could affect legal content that’s provided by its customers. However, according to the Court, Ecatel is partly to blame for this, as it does business with customers who seemingly don’t have a proper takedown process themselves. This is something the company could have included in their contracts.

As a result, the Court put the copyrights of FAPL above the entrepreneurial freedom rights of the hosting provider.

The second right that has to be weighed is the public’s right to freedom of expression and information. While the Court rules that this right is limited by the measures, it argues that the rights of copyright holders weigh stronger.

“Admittedly, this freedom [of expression and information] is restricted, but according to the order, this will only apply for the duration of the offending streams. Furthermore, as said, this will only take place if the stream has not already been blocked in another way,” the Court writes.

If any legal content is affected by the measures then the offending streaming platform itself will experience more pressure from users to deal with the problem, and offer a suitable takedown procedure to prevent similar problems in the future, the Court notes.

TorrentFreak reached out to FAPL and Ecatel’s lawyers for a comment on the verdict but at the time of writing we haven’t heard back.

The verdict appears to be a powerful precedent for copyright holders. Kim Kuik, director of local anti-piracy group BREIN, is pleased with the outcome. While BREIN was not involved in this lawsuit, it previously sued Ecatel in another case.

“It is a good precedent. An intermediary like Ecatel has its accountability and must have an effective notice and take down procedure,” Kuik tells TorrentFreak.

“Too bad it wasn’t also against the people behind Ecatel, who now can continue using another vehicle. The judge thinks this verdict serves a warning to them. Time will tell if that is so.”

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN discounts, offers and coupons

Grumpy Cat Wins $710,000 From Copyright Infringing Coffee Maker

Post Syndicated from Ernesto original https://torrentfreak.com/grumpy-cat-wins-710000-copyright-infringing-coffee-maker-180125/

grumpcatThere are dozens of celebrity cats on the Internet, but Grumpy Cat probably tops them all.

The cat’s owners have made millions thanks to their pet’s unique facial expression, which turned her into an overnight Internet star.

Part of this revenue comes from successful merchandise lines, including the Grumpy Cat “Grumppuccino” iced coffee beverage, sold by the California company Grenade Beverage.

The company licensed the copyright and trademarks to sell the iced coffee but is otherwise not affiliated with the cat and its owners. Initially, this partnership went well, but after the coffee maker started to sell other “Grumpy Cat” products, things turned bad.

The cat’s owners, incorporated as Grumpy Cat LLC, took the matter to court with demands for the coffee maker to stop infringing associated copyrights and trademarks.

“Without authorization, Defendants […] have extensively and repeatedly exploited the Grumpy Cat Copyrights and the Grumpy Cat Trademarks,” the complaint read.

Pirate coffee..


After two years the case went before a jury this week where, Courthouse News reports, the cat itself also made an appearance.

The eight-person jury in Santa Ana, California sided with the cat’s owner and awarded the company $710,000 in copyright and trademark infringement damages, as well as a symbolic $1 for contract breach.

According to court documents, the majority of the damages have to be paid by Grumpy Beverage, but the company’s owner Paul Sandford is also held personally liable for $60,000.

The verdict is good news for Grumpy Cat and its owner, and according to their attorney, they are happy with the outcome.

“Grumpy Cat feels vindicated and feels the jury reached a just verdict,” Grumpy Cat’s lawyer David Jonelis said, describing it as “a complete victory.”

A copy of the verdict form is available here (pdf).

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN discounts, offers and coupons

Planned Piracy Upload Filters are ‘Censorship Machines,’ MEPs Warn

Post Syndicated from Ernesto original https://torrentfreak.com/planned-piracy-upload-filters-are-censorship-machines-meps-warn-180122/

Through a series of new proposals, the European Commission is working hard to modernize EU copyright law. Among other things, it will require online services to do more to fight piracy.

These proposals have not been without controversy. Article 13 of the proposed Copyright Directive, for example, has been widely criticized as it would require online services to monitor and filter uploaded content.

This means that online services, which deal with large volumes of user-uploaded content, must use fingerprinting or other detection mechanisms – similar to YouTube’s Content-ID system – to block copyright infringing files.

The Commission believes that more stringent control is needed to support copyright holders. However, many legal scholars, digital activists, and members of the public worry that they will violate the rights of regular Internet users.

In the European Parliament, there is fierce opposition as well. Today, six Members of Parliament (MEPs) from across the political spectrum released a new campaign video warning their fellow colleagues and the public at large.

The MEPs warn that such upload filters would act as “censorship machines,” something they’ve made clear to the Council’s working group on intellectual property, where the controversial proposal was discussed today.

“Imagine if every time you opened your mouth, computers controlled by big companies would check what you were about to say, and have the power to prevent you from saying it,” Greens/EFA MEP Julia Reda says.

“A new legal proposal would make this a reality when it comes to expressing yourself online: Every clip and every photo would have to be pre-screened by some automated ‘robocop’ before it could be uploaded and seen online,” ALDE MEP Marietje Schaake adds.

Stop censorship machines!

Schaake notes that she has dealt with the consequences of upload filters herself. When she uploaded a recording of a political speech to YouTube, the site took it down without explanation. Until this day, the MEP still doesn’t know on what grounds it was removed.

These broad upload filters are completely disproportionate and a danger for freedom of speech, the MEPs warn. The automated systems make mistakes and can’t properly detect whether something’s fair use, for example.

Another problem is that the measures will be relatively costly for smaller companies ,which puts them at a competitive disadvantage. “Only the biggest platforms can afford them – European competitors and small businesses will struggle,” ECR MEP Dan Dalton says.

The plans can still be stopped, the MEPs say. They are currently scheduled for a vote in the Legal Affairs Committee at the end of March, and the video encourages members of the public to raise their voices.

“Speak out …while you can still do so unfiltered!” S&D MEP Catherine Stihler says.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN discounts, offers and coupons

China Seriously Doubts Objectivity of US ‘Pirate Site’ List

Post Syndicated from Ernesto original https://torrentfreak.com/china-seriously-doubts-objectivity-of-us-pirate-site-list-180120/

Late last week, the Office of the US Trade Representative (USTR) released an updated version of its “Out-of-Cycle Review of Notorious Markets,” identifying some of the worst IP-offenders worldwide.

The overview is largely based on input from major copyright holders and related industry groups. While the US Government admits that it doesn’t make any judgments, the list carries a lot of weight and can hurt the image of companies that are singled out.

For some of the ‘classic’ pirate sites such as The Pirate Bay, this doesn’t really matter. On the contrary, they may see it as a badge of honor. However, for billion-dollar businesses such as Alibaba and VK, it’s a different story.

They are not at risk of being the target of a criminal prosecution, as some classic pirate sites are, but the listing will make them a hot topic on the political agenda.

Interestingly, it seems that not all countries are happy with seeing some of their top companies being singled out. When China’s commerce ministry spokesman Gao Feng was confronted with the fact that Alibaba and its Taobao.com site were listed, he made some noteworthy observations.

“In the report, the U.S. frequently discusses the relevant Chinese businesses with the words like ‘reportedly,’ ‘according to authoritative sources’ and the like,” Feng told the local press.

In its report, the US Government stressed that Alibaba should do more to combat counterfeiting and piracy on Taobao.com and other platforms, but China’s officials don’t seem convinced.

“It lacked conclusive evidence and had no relevant figures to back up its points. We have no choice but to express our doubts about the objectivity and reliability of the department that issued the report,” Feng added.

China’s commerce ministry has a point. The USTR report is compiled from comments that are provided by copyright holders. These are not thoroughly vetted, as far as we know, which doesn’t seem very objective.

Even more concerning, copyright holders often cite the USTR’s notorious markets list in legal and lobbying efforts, even though they are in essence their own findings in a rewritten form. While that may be very convenient, it can also be misleading.

Alibaba itself went a step further than the commerce ministry and noted that the company is being used as a “scapegoat” in a geopolitical game. In a detailed ten-page rebuttal, the marketplace responded to the allegations point by point.

“As a result of the rise of trade protectionism, Alibaba has been turned into a scapegoat by the USTR to win points in a highly-politicized environment and their actions should be recognized for what they are,” the company commented.

“The USTR’s actions made it clear that the Notorious Markets List, which only targets non-US marketplaces, is not about intellectual property protection, but just another instrument to achieve the US Government’s geopolitical objectives.”

Critique on the USTR’s Special 301 reports, which the Notorious Markets lists are part of, is not new. Earlier this year Canada’s Government described the process as flawed as it’s mainly driven by one-sided copyright industry claims.

“Canada does not recognize the validity of the Special 301 and considers the process and the Report to be flawed,” a Government memo read.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN discounts, offers and coupons

Graphite 1.1: Teaching an Old Dog New Tricks

Post Syndicated from Blogs on Grafana Labs Blog original https://grafana.com/blog/2018/01/11/graphite-1.1-teaching-an-old-dog-new-tricks/

The Road to Graphite 1.1

I started working on Graphite just over a year ago, when @obfuscurity asked me to help out with some issues blocking the Graphite 1.0 release. Little did I know that a year later, that would have resulted in 262 commits (and counting), and that with the help of the other Graphite maintainers (especially @deniszh, @iksaif & @cbowman0) we would have added a huge amount of new functionality to Graphite.

There are a huge number of new additions and updates in this release, in this post I’ll give a tour of some of the highlights including tag support, syntax and function updates, custom function plugins, and python 3.x support.


The single biggest feature in this release is the addition of tag support, which brings the ability to describe metrics in a much richer way and to write more flexible and expressive queries.

Traditionally series in Graphite are identified using a hierarchical naming scheme based on dot-separated segments called nodes. This works very well and is simple to map into a hierarchical structure like the whisper filesystem tree, but it means that the user has to know what each segment represents, and makes it very difficult to modify or extend the naming scheme since everything is based on the positions of the segments within the hierarchy.

The tagging system gives users the ability to encode information about the series in a collection of tag=value pairs which are used together with the series name to uniquely identify each series, and the ability to query series by specifying tag-based matching expressions rather than constructing glob-style selectors based on the positions of specific segments within the hierarchy. This is broadly similar to the system used by Prometheus and makes it possible to use Graphite as a long-term storage backend for metrics gathered by Prometheus with full tag support.

When using tags, series names are specified using the new tagged carbon format: name;tag1=value1;tag2=value2. This format is backward compatible with most existing carbon tooling, and makes it easy to adapt existing tools to produce tagged metrics simply by changing the metric names. The OpenMetrics format is also supported for ingestion, and is normalized into the standard Graphite format internally.

At its core, the tagging system is implemented as a tag database (TagDB) alongside the metrics that allows them to be efficiently queried by individual tag values rather than having to traverse the metrics tree looking for series that match the specified query. Internally the tag index is stored in one of a number of pluggable tag databases, currently supported options are the internal graphite-web database, redis, or an external system that implements the Graphite tagging HTTP API. Carbon automatically keeps the index up to date with any tagged series seen.

The new seriesByTag function is used to query the TagDB and will return a list of all the series that match the expressions passed to it. seriesByTag supports both exact and regular expression matches, and can be used anywhere you would previously have specified a metric name or glob expression.

There are new dedicated functions for grouping and aliasing series by tag (groupByTags and aliasByTags), and you can also use tags interchangeably with node numbers in the standard Graphite functions like aliasByNode, groupByNodes, asPercent, mapSeries, etc.

Piping Syntax & Function Updates

One of the huge strengths of the Graphite render API is the ability to chain together multiple functions to process data, but until now (unless you were using a tool like Grafana) writing chained queries could be painful as each function had to be wrapped around the previous one. With this release it is now possible to “pipe” the output of one processing function into the next, and to combine piped and nested functions.

For example:


Can now be written as:




Another source of frustration with the old function API was the inconsistent implementation of aggregations, with different functions being used in different parts of the API, and some functions simply not being available. In 1.1 all functions that perform aggregation (whether across series or across time intervals) now support a consistent set of aggregations; average, median, sum, min, max, diff, stddev, count, range, multiply and last. This is part of a new approach to implementing functions that emphasises using shared building blocks to ensure consistency across the API and solve the problem of a particular function not working with the aggregation needed for a given task.

To that end a number of new functions have been added that each provide the same functionality as an entire family of “old” functions; aggregate, aggregateWithWildcards, movingWindow, filterSeries, highest, lowest and sortBy.

Each of these functions accepts an aggregation method parameter, for example aggregate(some.metric.*, 'sum') implements the same functionality as sumSeries(some.metric.*).

It can also be used with different aggregation methods to replace averageSeries, stddevSeries, multiplySeries, diffSeries, rangeOfSeries, minSeries, maxSeries and countSeries. All those functions are now implemented as aliases for aggregate, and it supports the previously-missing median and last aggregations.

The same is true for the other functions, and the summarize, smartSummarize, groupByNode, groupByNodes and the new groupByTags functions now all support the standard set of aggregations. Gone are the days of wishing that sortByMedian or highestRange were available!

For more information on the functions available check the function documentation.

Custom Functions

No matter how many functions are available there are always going to be specific use-cases where a custom function can perform analysis that wouldn’t otherwise be possible, or provide a convenient alias for a complicated function chain or specific set of parameters.

In Graphite 1.1 we added support for easily adding one-off custom functions, as well as for creating and sharing plugins that can provide one or more functions.

Each function plugin is packaged as a simple python module, and will be automatically loaded by Graphite when placed into the functions/custom folder.

An example of a simple function plugin that translates the name of every series passed to it into UPPERCASE:

from graphite.functions.params import Param, ParamTypes

def toUpperCase(requestContext, seriesList):
  """Custom function that changes series names to UPPERCASE"""
  for series in seriesList:
    series.name = series.name.upper()
  return seriesList

toUpperCase.group = 'Custom'
toUpperCase.params = [
  Param('seriesList', ParamTypes.seriesList, required=True),

SeriesFunctions = {
  'upper': toUpperCase,

Once installed the function is not only available for use within Grpahite, but is also exposed via the new Function API which allows the function definition and documentation to be automatically loaded by tools like Grafana. This means that users will be able to select and use the new function in exactly the same way as the internal functions.

More information on writing and using custom functions is available in the documentation.

Clustering Updates

One of the biggest changes from the 0.9 to 1.0 releases was the overhaul of the clustering code, and with 1.1.1 that process has been taken even further to optimize performance when using Graphite in a clustered deployment. In the past it was common for a request to require the frontend node to make multiple requests to the backend nodes to identify matching series and to fetch data, and the code for handling remote vs local series was overly complicated. In 1.1.1 we took a new approach where all render data requests pass through the same path internally, and multiple backend nodes are handled individually rather than grouped together into a single finder. This has greatly simplified the codebase, making it much easier to understand and reason about, while allowing much more flexibility in design of the finders. After these changes, render requests can now be answered with a single internal request to each backend node, and all requests for both remote and local data are executed in parallel.

To maintain the ability of graphite to scale out horizontally, the tagging system works seamlessly within a clustered environment, with each node responsible for the series stored on that node. Calls to load tagged series via seriesByTag are fanned out to the backend nodes and results are merged on the query node just like they are for non-tagged series.

Python 3 & Django 1.11 Support

Graphite 1.1 finally brings support for Python 3.x, both graphite-web and carbon are now tested against Python 2.7, 3.4, 3.5, 3.6 and PyPy. Django releases 1.8 through 1.11 are also supported. The work involved in sorting out the compatibility issues between Python 2.x and 3.x was quite involved, but it is a huge step forward for the long term support of the project! With the new Django 2.x series supporting only Python 3.x we will need to evaluate our long-term support for Python 2.x, but the Django 1.11 series is supported through 2020 so there is time to consider the options there.

Watch This Space

Efforts are underway to add support for the new functionality across the ecosystem of tools that work with Graphite, adding collectd tagging support, prometheus remote read & write with tags (and native Prometheus remote read/write support in Graphite) and last but not least Graphite tag support in Grafana.

We’re excited about the possibilities that the new capabilities in 1.1.x open up, and can’t wait to see how the community puts them to work.

Download the 1.1.1 release and check out the release notes here.

Random with care

Post Syndicated from Eevee original https://eev.ee/blog/2018/01/02/random-with-care/

Hi! Here are a few loose thoughts about picking random numbers.

A word about crypto


This is all aimed at frivolous pursuits like video games. Hell, even video games where money is at stake should be deferring to someone who knows way more than I do. Otherwise you might find out that your deck shuffles in your poker game are woefully inadequate and some smartass is cheating you out of millions. (If your random number generator has fewer than 226 bits of state, it can’t even generate every possible shuffling of a deck of cards!)

Use the right distribution

Most languages have a random number primitive that spits out a number uniformly in the range [0, 1), and you can go pretty far with just that. But beware a few traps!

Random pitches

Say you want to pitch up a sound by a random amount, perhaps up to an octave. Your audio API probably has a way to do this that takes a pitch multiplier, where I say “probably” because that’s how the only audio API I’ve used works.

Easy peasy. If 1 is unchanged and 2 is pitched up by an octave, then all you need is rand() + 1. Right?

No! Pitch is exponential — within the same octave, the “gap” between C and C♯ is about half as big as the gap between B and the following C. If you pick a pitch multiplier uniformly, you’ll have a noticeable bias towards the higher pitches.

One octave corresponds to a doubling of pitch, so if you want to pick a random note, you want 2 ** rand().

Random directions

For two dimensions, you can just pick a random angle with rand() * TAU.

If you want a vector rather than an angle, or if you want a random direction in three dimensions, it’s a little trickier. You might be tempted to just pick a random point where each component is rand() * 2 - 1 (ranging from −1 to 1), but that’s not quite right. A direction is a point on the surface (or, equivalently, within the volume) of a sphere, and picking each component independently produces a point within the volume of a cube; the result will be a bias towards the corners of the cube, where there’s much more extra volume beyond the sphere.

No? Well, just trust me. I don’t know how to make a diagram for this.

Anyway, you could use the Pythagorean theorem a few times and make a huge mess of things, or it turns out there’s a really easy way that even works for two or four or any number of dimensions. You pick each coordinate from a Gaussian (normal) distribution, then normalize the resulting vector. In other words, using Python’s random module:

def random_direction():
    x = random.gauss(0, 1)
    y = random.gauss(0, 1)
    z = random.gauss(0, 1)
    r = math.sqrt(x*x + y*y + z*z)
    return x/r, y/r, z/r

Why does this work? I have no idea!

Note that it is possible to get zero (or close to it) for every component, in which case the result is nonsense. You can re-roll all the components if necessary; just check that the magnitude (or its square) is less than some epsilon, which is equivalent to throwing away a tiny sphere at the center and shouldn’t affect the distribution.

Beware Gauss

Since I brought it up: the Gaussian distribution is a pretty nice one for choosing things in some range, where the middle is the common case and should appear more frequently.

That said, I never use it, because it has one annoying drawback: the Gaussian distribution has no minimum or maximum value, so you can’t really scale it down to the range you want. In theory, you might get any value out of it, with no limit on scale.

In practice, it’s astronomically rare to actually get such a value out. I did a hundred million trials just to see what would happen, and the largest value produced was 5.8.

But, still, I’d rather not knowingly put extremely rare corner cases in my code if I can at all avoid it. I could clamp the ends, but that would cause unnatural bunching at the endpoints. I could reroll if I got a value outside some desired range, but I prefer to avoid rerolling when I can, too; after all, it’s still (astronomically) possible to have to reroll for an indefinite amount of time. (Okay, it’s really not, since you’ll eventually hit the period of your PRNG. Still, though.) I don’t bend over backwards here — I did just say to reroll when picking a random direction, after all — but when there’s a nicer alternative I’ll gladly use it.

And lo, there is a nicer alternative! Enter the beta distribution. It always spits out a number in [0, 1], so you can easily swap it in for the standard normal function, but it takes two “shape” parameters α and β that alter its behavior fairly dramatically.

With α = β = 1, the beta distribution is uniform, i.e. no different from rand(). As α increases, the distribution skews towards the right, and as β increases, the distribution skews towards the left. If α = β, the whole thing is symmetric with a hump in the middle. The higher either one gets, the more extreme the hump (meaning that value is far more common than any other). With a little fiddling, you can get a number of interesting curves.

Screenshots don’t really do it justice, so here’s a little Wolfram widget that lets you play with α and β live:

Note that if α = 1, then 1 is a possible value; if β = 1, then 0 is a possible value. You probably want them both greater than 1, which clamps the endpoints to zero.

Also, it’s possible to have either α or β or both be less than 1, but this creates very different behavior: the corresponding endpoints become poles.

Anyway, something like α = β = 3 is probably close enough to normal for most purposes but already clamped for you. And you could easily replicate something like, say, NetHack’s incredibly bizarre rnz function.

Random frequency

Say you want some event to have an 80% chance to happen every second. You (who am I kidding, I) might be tempted to do something like this:

if random() < 0.8 * dt:

In an ideal world, dt is always the same and is equal to 1 / f, where f is the framerate. Replace that 80% with a variable, say P, and every tic you have a P / f chance to do the… whatever it is.

Each second, f tics pass, so you’ll make this check f times. The chance that any check succeeds is the inverse of the chance that every check fails, which is \(1 – \left(1 – \frac{P}{f}\right)^f\).

For P of 80% and a framerate of 60, that’s a total probability of 55.3%. Wait, what?

Consider what happens if the framerate is 2. On the first tic, you roll 0.4 twice — but probabilities are combined by multiplying, and splitting work up by dt only works for additive quantities. You lose some accuracy along the way. If you’re dealing with something that multiplies, you need an exponent somewhere.

But in this case, maybe you don’t want that at all. Each separate roll you make might independently succeed, so it’s possible (but very unlikely) that the event will happen 60 times within a single second! Or 200 times, if that’s someone’s framerate.

If you explicitly want something to have a chance to happen on a specific interval, you have to check on that interval. If you don’t have a gizmo handy to run code on an interval, it’s easy to do yourself with a time buffer:

timer += dt
# here, 1 is the "every 1 seconds"
while timer > 1:
    timer -= 1
    if random() < 0.8:

Using while means rolls still happen even if you somehow skipped over an entire second.

(For the curious, and the nerds who already noticed: the expression \(1 – \left(1 – \frac{P}{f}\right)^f\) converges to a specific value! As the framerate increases, it becomes a better and better approximation for \(1 – e^{-P}\), which for the example above is 0.551. Hey, 60 fps is pretty accurate — it’s just accurately representing something nowhere near what I wanted. Er, you wanted.)

Rolling your own

Of course, you can fuss with the classic [0, 1] uniform value however you want. If I want a bias towards zero, I’ll often just square it, or multiply two of them together. If I want a bias towards one, I’ll take a square root. If I want something like a Gaussian/normal distribution, but with clearly-defined endpoints, I might add together n rolls and divide by n. (The normal distribution is just what you get if you roll infinite dice and divide by infinity!)

It’d be nice to be able to understand exactly what this will do to the distribution. Unfortunately, that requires some calculus, which this post is too small to contain, and which I didn’t even know much about myself until I went down a deep rabbit hole while writing, and which in many cases is straight up impossible to express directly.

Here’s the non-calculus bit. A source of randomness is often graphed as a PDF — a probability density function. You’ve almost certainly seen a bell curve graphed, and that’s a PDF. They’re pretty nice, since they do exactly what they look like: they show the relative chance that any given value will pop out. On a bog standard bell curve, there’s a peak at zero, and of course zero is the most common result from a normal distribution.

(Okay, actually, since the results are continuous, it’s vanishingly unlikely that you’ll get exactly zero — but you’re much more likely to get a value near zero than near any other number.)

For the uniform distribution, which is what a classic rand() gives you, the PDF is just a straight horizontal line — every result is equally likely.

If there were a calculus bit, it would go here! Instead, we can cheat. Sometimes. Mathematica knows how to work with probability distributions in the abstract, and there’s a free web version you can use. For the example of squaring a uniform variable, try this out:

PDF[TransformedDistribution[u^2, u \[Distributed] UniformDistribution[{0, 1}]], u]

(The \[Distributed] is a funny tilde that doesn’t exist in Unicode, but which Mathematica uses as a first-class operator. Also, press shiftEnter to evaluate the line.)

This will tell you that the distribution is… \(\frac{1}{2\sqrt{u}}\). Weird! You can plot it:

Plot[%, {u, 0, 1}]

(The % refers to the result of the last thing you did, so if you want to try several of these, you can just do Plot[PDF[…], u] directly.)

The resulting graph shows that numbers around zero are, in fact, vastly — infinitely — more likely than anything else.

What about multiplying two together? I can’t figure out how to get Mathematica to understand this, but a great amount of digging revealed that the answer is -ln x, and from there you can plot them both on Wolfram Alpha. They’re similar, though squaring has a much better chance of giving you high numbers than multiplying two separate rolls — which makes some sense, since if either of two rolls is a low number, the product will be even lower.

What if you know the graph you want, and you want to figure out how to play with a uniform roll to get it? Good news! That’s a whole thing called inverse transform sampling. All you have to do is take an integral. Good luck!

This is all extremely ridiculous. New tactic: Just Simulate The Damn Thing. You already have the code; run it a million times, make a histogram, and tada, there’s your PDF. That’s one of the great things about computers! Brute-force numerical answers are easy to come by, so there’s no excuse for producing something like rnz. (Though, be sure your histogram has sufficiently narrow buckets — I tried plotting one for rnz once and the weird stuff on the left side didn’t show up at all!)

By the way, I learned something from futzing with Mathematica here! Taking the square root (to bias towards 1) gives a PDF that’s a straight diagonal line, nothing like the hyperbola you get from squaring (to bias towards 0). How do you get a straight line the other way? Surprise: \(1 – \sqrt{1 – u}\).

Okay, okay, here’s the actual math

I don’t claim to have a very firm grasp on this, but I had a hell of a time finding it written out clearly, so I might as well write it down as best I can. This was a great excuse to finally set up MathJax, too.

Say \(u(x)\) is the PDF of the original distribution and \(u\) is a representative number you plucked from that distribution. For the uniform distribution, \(u(x) = 1\). Or, more accurately,

u(x) = \begin{cases}
1 & \text{ if } 0 \le x \lt 1 \\
0 & \text{ otherwise }

Remember that \(x\) here is a possible outcome you want to know about, and the PDF tells you the relative probability that a roll will be near it. This PDF spits out 1 for every \(x\), meaning every number between 0 and 1 is equally likely to appear.

We want to do something to that PDF, which creates a new distribution, whose PDF we want to know. I’ll use my original example of \(f(u) = u^2\), which creates a new PDF \(v(x)\).

The trick is that we need to work in terms of the cumulative distribution function for \(u\). Where the PDF gives the relative chance that a roll will be (“near”) a specific value, the CDF gives the relative chance that a roll will be less than a specific value.

The conventions for this seem to be a bit fuzzy, and nobody bothers to explain which ones they’re using, which makes this all the more confusing to read about… but let’s write the CDF with a capital letter, so we have \(U(x)\). In this case, \(U(x) = x\), a straight 45° line (at least between 0 and 1). With the definition I gave, this should make sense. At some arbitrary point like 0.4, the value of the PDF is 1 (0.4 is just as likely as anything else), and the value of the CDF is 0.4 (you have a 40% chance of getting a number from 0 to 0.4).

Calculus ahoy: the PDF is the derivative of the CDF, which means it measures the slope of the CDF at any point. For \(U(x) = x\), the slope is always 1, and indeed \(u(x) = 1\). See, calculus is easy.

Okay, so, now we’re getting somewhere. What we want is the CDF of our new distribution, \(V(x)\). The CDF is defined as the probability that a roll \(v\) will be less than \(x\), so we can literally write:

$$V(x) = P(v \le x)$$

(This is why we have to work with CDFs, rather than PDFs — a PDF gives the chance that a roll will be “nearby,” whatever that means. A CDF is much more concrete.)

What is \(v\), exactly? We defined it ourselves; it’s the do something applied to a roll from the original distribution, or \(f(u)\).

$$V(x) = P\!\left(f(u) \le x\right)$$

Now the first tricky part: we have to solve that inequality for \(u\), which means we have to do something, backwards to \(x\).

$$V(x) = P\!\left(u \le f^{-1}(x)\right)$$

Almost there! We now have a probability that \(u\) is less than some value, and that’s the definition of a CDF!

$$V(x) = U\!\left(f^{-1}(x)\right)$$

Hooray! Now to turn these CDFs back into PDFs, all we need to do is differentiate both sides and use the chain rule. If you never took calculus, don’t worry too much about what that means!

$$v(x) = u\!\left(f^{-1}(x)\right)\left|\frac{d}{dx}f^{-1}(x)\right|$$

Wait! Where did that absolute value come from? It takes care of whether \(f(x)\) increases or decreases. It’s the least interesting part here by far, so, whatever.

There’s one more magical part here when using the uniform distribution — \(u(\dots)\) is always equal to 1, so that entire term disappears! (Note that this only works for a uniform distribution with a width of 1; PDFs are scaled so the entire area under them sums to 1, so if you had a rand() that could spit out a number between 0 and 2, the PDF would be \(u(x) = \frac{1}{2}\).)

$$v(x) = \left|\frac{d}{dx}f^{-1}(x)\right|$$

So for the specific case of modifying the output of rand(), all we have to do is invert, then differentiate. The inverse of \(f(u) = u^2\) is \(f^{-1}(x) = \sqrt{x}\) (no need for a ± since we’re only dealing with positive numbers), and differentiating that gives \(v(x) = \frac{1}{2\sqrt{x}}\). Done! This is also why square root comes out nicer; inverting it gives \(x^2\), and differentiating that gives \(2x\), a straight line.

Incidentally, that method for turning a uniform distribution into any distribution — inverse transform sampling — is pretty much the same thing in reverse: integrate, then invert. For example, when I saw that taking the square root gave \(v(x) = 2x\), I naturally wondered how to get a straight line going the other way, \(v(x) = 2 – 2x\). Integrating that gives \(2x – x^2\), and then you can use the quadratic formula (or just ask Wolfram Alpha) to solve \(2x – x^2 = u\) for \(x\) and get \(f(u) = 1 – \sqrt{1 – u}\).

Multiply two rolls is a bit more complicated; you have to write out the CDF as an integral and you end up doing a double integral and wow it’s a mess. The only thing I’ve retained is that you do a division somewhere, which then gets integrated, and that’s why it ends up as \(-\ln x\).

And that’s quite enough of that! (Okay but having math in my blog is pretty cool and I will definitely be doing more of this, sorry, not sorry.)

Random vs varied

Sometimes, random isn’t actually what you want. We tend to use the word “random” casually to mean something more like chaotic, i.e., with no discernible pattern. But that’s not really random. In fact, given how good humans can be at finding incidental patterns, they aren’t all that unlikely! Consider that when you roll two dice, they’ll come up either the same or only one apart almost half the time. Coincidence? Well, yes.

If you ask for randomness, you’re saying that any outcome — or series of outcomes — is acceptable, including five heads in a row or five tails in a row. Most of the time, that’s fine. Some of the time, it’s less fine, and what you really want is variety. Here are a couple examples and some fairly easy workarounds.

NPC quips

The nature of games is such that NPCs will eventually run out of things to say, at which point further conversation will give the player a short brush-off quip — a slight nod from the designer to the player that, hey, you hit the end of the script.

Some NPCs have multiple possible quips and will give one at random. The trouble with this is that it’s very possible for an NPC to repeat the same quip several times in a row before abruptly switching to another one. With only a few options to choose from, getting the same option twice or thrice (especially across an entire game, which may have numerous NPCs) isn’t all that unlikely. The notion of an NPC quip isn’t very realistic to start with, but having someone repeat themselves and then abruptly switch to something else is especially jarring.

The easy fix is to show the quips in order! Paradoxically, this is more consistently varied than choosing at random — the original “order” is likely to be meaningless anyway, and it already has the property that the same quip can never appear twice in a row.

If you like, you can shuffle the list of quips every time you reach the end, but take care here — it’s possible that the last quip in the old order will be the same as the first quip in the new order, so you may still get a repeat. (Of course, you can just check for this case and swap the first quip somewhere else if it bothers you.)

That last behavior is, in fact, the canonical way that Tetris chooses pieces — the game simply shuffles a list of all 7 pieces, gives those to you in shuffled order, then shuffles them again to make a new list once it’s exhausted. There’s no avoidance of duplicates, though, so you can still get two S blocks in a row, or even two S and two Z all clumped together, but no more than that. Some Tetris variants take other approaches, such as actively avoiding repeats even several pieces apart or deliberately giving you the worst piece possible.

Random drops

Random drops are often implemented as a flat chance each time. Maybe enemies have a 5% chance to drop health when they die. Legally speaking, over the long term, a player will see health drops for about 5% of enemy kills.

Over the short term, they may be desperate for health and not survive to see the long term. So you may want to put a thumb on the scale sometimes. Games in the Metroid series, for example, have a somewhat infamous bias towards whatever kind of drop they think you need — health if your health is low, missiles if your missiles are low.

I can’t give you an exact approach to use, since it depends on the game and the feeling you’re going for and the variables at your disposal. In extreme cases, you might want to guarantee a health drop from a tough enemy when the player is critically low on health. (Or if you’re feeling particularly evil, you could go the other way and deny the player health when they most need it…)

The problem becomes a little different, and worse, when the event that triggers the drop is relatively rare. The pathological case here would be something like a raid boss in World of Warcraft, which requires hours of effort from a coordinated group of people to defeat, and which has some tiny chance of dropping a good item that will go to only one of those people. This is why I stopped playing World of Warcraft at 60.

Dialing it back a little bit gives us Enter the Gungeon, a roguelike where each room is a set of encounters and each floor only has a dozen or so rooms. Initially, you have a 1% chance of getting a reward after completing a room — but every time you complete a room and don’t get a reward, the chance increases by 9%, up to a cap of 80%. Once you get a reward, the chance resets to 1%.

The natural question is: how frequently, exactly, can a player expect to get a reward? We could do math, or we could Just Simulate The Damn Thing.

from collections import Counter
import random

histogram = Counter()

TRIALS = 1000000
chance = 1
rooms_cleared = 0
rewards_found = 0
while rewards_found < TRIALS:
    rooms_cleared += 1
    if random.random() * 100 < chance:
        # Reward!
        rewards_found += 1
        histogram[rooms_cleared] += 1
        rooms_cleared = 0
        chance = 1
        chance = min(80, chance + 9)

for gaps, count in sorted(histogram.items()):
    print(f"{gaps:3d} | {count / TRIALS * 100:6.2f}%", '#' * (count // (TRIALS // 100)))
  1 |   0.98%
  2 |   9.91% #########
  3 |  17.00% ################
  4 |  20.23% ####################
  5 |  19.21% ###################
  6 |  15.05% ###############
  7 |   9.69% #########
  8 |   5.07% #####
  9 |   2.09% ##
 10 |   0.63%
 11 |   0.12%
 12 |   0.03%
 13 |   0.00%
 14 |   0.00%
 15 |   0.00%

We’ve got kind of a hilly distribution, skewed to the left, which is up in this histogram. Most of the time, a player should see a reward every three to six rooms, which is maybe twice per floor. It’s vanishingly unlikely to go through a dozen rooms without ever seeing a reward, so a player should see at least one per floor.

Of course, this simulated a single continuous playthrough; when starting the game from scratch, your chance at a reward always starts fresh at 1%, the worst it can be. If you want to know about how many rewards a player will get on the first floor, hey, Just Simulate The Damn Thing.

  0 |   0.01%
  1 |  13.01% #############
  2 |  56.28% ########################################################
  3 |  27.49% ###########################
  4 |   3.10% ###
  5 |   0.11%
  6 |   0.00%

Cool. Though, that’s assuming exactly 12 rooms; it might be worth changing that to pick at random in a way that matches the level generator.

(Enter the Gungeon does some other things to skew probability, which is very nice in a roguelike where blind luck can make or break you. For example, if you kill a boss without having gotten a new gun anywhere else on the floor, the boss is guaranteed to drop a gun.)

Critical hits

I suppose this is the same problem as random drops, but backwards.

Say you have a battle sim where every attack has a 6% chance to land a devastating critical hit. Presumably the same rules apply to both the player and the AI opponents.

Consider, then, that the AI opponents have exactly the same 6% chance to ruin the player’s day. Consider also that this gives them an 0.4% chance to critical hit twice in a row. 0.4% doesn’t sound like much, but across an entire playthrough, it’s not unlikely that a player might see it happen and find it incredibly annoying.

Perhaps it would be worthwhile to explicitly forbid AI opponents from getting consecutive critical hits.

In conclusion

An emerging theme here has been to Just Simulate The Damn Thing. So consider Just Simulating The Damn Thing. Even a simple change to a random value can do surprising things to the resulting distribution, so unless you feel like differentiating the inverse function of your code, maybe test out any non-trivial behavior and make sure it’s what you wanted. Probability is hard to reason about.

Instrumenting Web Apps Using AWS X-Ray

Post Syndicated from Bharath Kumar original https://aws.amazon.com/blogs/devops/instrumenting-web-apps-using-aws-x-ray/

This post was written by James Bowman, Software Development Engineer, AWS X-Ray

AWS X-Ray helps developers analyze and debug distributed applications and underlying services in production. You can identify and analyze root-causes of performance issues and errors, understand customer impact, and extract statistical aggregations (such as histograms) for optimization.

In this blog post, I will provide a step-by-step walkthrough for enabling X-Ray tracing in the Go programming language. You can use these steps to add X-Ray tracing to any distributed application.

Revel: A web framework for the Go language

This section will assist you with designing a guestbook application. Skip to “Instrumenting with AWS X-Ray” section below if you already have a Go language application.

Revel is a web framework for the Go language. It facilitates the rapid development of web applications by providing a predefined framework for controllers, views, routes, filters, and more.

To get started with Revel, run revel new github.com/jamesdbowman/guestbook. A project base is then copied to $GOPATH/src/github.com/jamesdbowman/guestbook.

$ tree -L 2
├── README.md
├── app
│ ├── controllers
│ ├── init.go
│ ├── routes
│ ├── tmp
│ └── views
├── conf
│ ├── app.conf
│ └── routes
├── messages
│ └── sample.en
├── public
│ ├── css
│ ├── fonts
│ ├── img
│ └── js
└── tests
└── apptest.go

Writing a guestbook application

A basic guestbook application can consist of just two routes: one to sign the guestbook and another to list all entries.
Let’s set up these routes by adding a Book controller, which can be routed to by modifying ./conf/routes.

package controllers

import (


const TABLE_NAME = "guestbook"
const SUCCESS = "Success.\n"
const DAY = 86400


func init() {

// randString returns a random string of len n, used for DynamoDB Hash key.
func randString(n int) string {
    b := make([]rune, n)
    for i := range b {
        b[i] = letters[rand.Intn(len(letters))]
    return string(b)

// Book controls interactions with the guestbook.
type Book struct {
    ddbClient *dynamodb.DynamoDB

// Signature represents a user's signature.
type Signature struct {
    Message string
    Epoch   int64
    ID      string

// ddb returns the controller's DynamoDB client, instatiating a new client if necessary.
func (c Book) ddb() *dynamodb.DynamoDB {
    if c.ddbClient == nil {
        sess := session.Must(session.NewSession(&aws.Config{
            Region: aws.String(endpoints.UsWest2RegionID),
        c.ddbClient = dynamodb.New(sess)
    return c.ddbClient

// Sign allows users to sign the book.
// The message is to be passed as application/json typed content, listed under the "message" top level key.
func (c Book) Sign() revel.Result {
    var s Signature

    err := c.Params.BindJSON(&s)
    if err != nil {
        return c.RenderError(err)
    now := time.Now()
    s.Epoch = now.Unix()
    s.ID = randString(20)

    item, err := dynamodbattribute.MarshalMap(s)
    if err != nil {
        return c.RenderError(err)

    putItemInput := &dynamodb.PutItemInput{
        TableName: aws.String(TABLE_NAME),
        Item:      item,
    _, err = c.ddb().PutItem(putItemInput)
    if err != nil {
        return c.RenderError(err)

    return c.RenderText(SUCCESS)

// List allows users to list all signatures in the book.
func (c Book) List() revel.Result {
    scanInput := &dynamodb.ScanInput{
        TableName: aws.String(TABLE_NAME),
        Limit:     aws.Int64(100),
    res, err := c.ddb().Scan(scanInput)
    if err != nil {
        return c.RenderError(err)

    messages := make([]string, 0)
    for _, v := range res.Items {
        messages = append(messages, *(v["Message"].S))
    return c.RenderJSON(messages)

POST /sign Book.Sign
GET /list Book.List

Creating the resources and testing

For the purposes of this blog post, the application will be run and tested locally. We will store and retrieve messages from an Amazon DynamoDB table. Use the following AWS CLI command to create the guestbook table:

aws dynamodb create-table --region us-west-2 --table-name "guestbook" --attribute-definitions AttributeName=ID,AttributeType=S AttributeName=Epoch,AttributeType=N --key-schema AttributeName=ID,KeyType=HASH AttributeName=Epoch,KeyType=RANGE --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5

Now, let’s test our sign and list routes. If everything is working correctly, the following result appears:

$ curl -d '{"message":"Hello from cURL!"}' -H "Content-Type: application/json" http://localhost:9000/book/sign
$ curl http://localhost:9000/book/list
  "Hello from cURL!"

Integrating with AWS X-Ray

Download and run the AWS X-Ray daemon

The AWS SDKs emit trace segments over UDP on port 2000. (This port can be configured.) In order for the trace segments to make it to the X-Ray service, the daemon must listen on this port and batch the segments in calls to the PutTraceSegments API.
For information about downloading and running the X-Ray daemon, see the AWS X-Ray Developer Guide.

Installing the AWS X-Ray SDK for Go

To download the SDK from GitHub, run go get -u github.com/aws/aws-xray-sdk-go/... The SDK will appear in the $GOPATH.

Enabling the incoming request filter

The first step to instrumenting an application with AWS X-Ray is to enable the generation of trace segments on incoming requests. The SDK conveniently provides an implementation of http.Handler which does exactly that. To ensure incoming web requests travel through this handler, we can modify app/init.go, adding a custom function to be run on application start.

import (


func init() {

func installXRayHandler() {
    revel.Server.Handler = xray.Handler(xray.NewFixedSegmentNamer("GuestbookApp"), revel.Server.Handler)

The application will now emit a segment for each incoming web request. The service graph appears:

You can customize the name of the segment to make it more descriptive by providing an alternate implementation of SegmentNamer to xray.Handler. For example, you can use xray.NewDynamicSegmentNamer(fallback, pattern) in place of the fixed namer. This namer will use the host name from the incoming web request (if it matches pattern) as the segment name. This is often useful when you are trying to separate different instances of the same application.

In addition, HTTP-centric information such as method and URL is collected in the segment’s http subsection:

"http": {
    "request": {
        "url": "/book/list",
        "method": "GET",
        "user_agent": "curl/7.54.0",
        "client_ip": "::1"
    "response": {
        "status": 200

Instrumenting outbound calls

To provide detailed performance metrics for distributed applications, the AWS X-Ray SDK needs to measure the time it takes to make outbound requests. Trace context is passed to downstream services using the X-Amzn-Trace-Id header. To draw a detailed and accurate representation of a distributed application, outbound call instrumentation is required.

AWS SDK calls

The AWS X-Ray SDK for Go provides a one-line AWS client wrapper that enables the collection of detailed per-call metrics for any AWS client. We can modify the DynamoDB client instantiation to include this line:

// ddb returns the controller's DynamoDB client, instatiating a new client if necessary.
func (c Book) ddb() *dynamodb.DynamoDB {
    if c.ddbClient == nil {
        sess := session.Must(session.NewSession(&aws.Config{
            Region: aws.String(endpoints.UsWest2RegionID),
        c.ddbClient = dynamodb.New(sess)
        xray.AWS(c.ddbClient.Client) // add subsegment-generating X-Ray handlers to this client
    return c.ddbClient

We also need to ensure that the segment generated by our xray.Handler is passed to these AWS calls so that the X-Ray SDK knows to which segment these generated subsegments belong. In Go, the context.Context object is passed throughout the call path to achieve this goal. (In most other languages, some variant of ThreadLocal is used.) AWS clients provide a *WithContext method variant for each AWS operation, which we need to switch to:

_, err = c.ddb().PutItemWithContext(c.Request.Context(), putItemInput)
    res, err := c.ddb().ScanWithContext(c.Request.Context(), scanInput)

We now see much more detail in the Timeline view of the trace for the sign and list operations:

We can use this detail to help diagnose throttling on our DynamoDB table. In the following screenshot, the purple in the DynamoDB service graph node indicates that our table is underprovisioned. The red in the GuestbookApp node indicates that the application is throwing faults due to this throttling.

HTTP calls

Although the guestbook application does not make any non-AWS outbound HTTP calls in its current state, there is a similar one-liner to wrap HTTP clients that make outbound requests. xray.Client(c *http.Client) wraps an existing http.Client (or nil if you want to use a default HTTP client). For example:

resp, err := ctxhttp.Get(ctx, xray.Client(nil), "https://aws.amazon.com/")

Instrumenting local operations

X-Ray can also assist in measuring the performance of local compute operations. To see this in action, let’s create a custom subsegment inside the randString method:

// randString returns a random string of len n, used for DynamoDB Hash key.
func randString(ctx context.Context, n int) string {
    xray.Capture(ctx, "randString", func(innerCtx context.Context) {
        b := make([]rune, n)
        for i := range b {
            b[i] = letters[rand.Intn(len(letters))]
        s := string(b)
    return s

// we'll also need to change the callsite

s.ID = randString(c.Request.Context(), 20)


By now, you are an expert on how to instrument X-Ray for your Go applications. Instrumenting X-Ray with your applications is an easy way to analyze and debug performance issues and understand customer impact. Please feel free to give any feedback or comments below.

For more information about advanced configuration of the AWS X-Ray SDK for Go, see the AWS X-Ray SDK for Go in the AWS X-Ray Developer Guide and the aws/aws-xray-sdk-go GitHub repository.

For more information about some of the advanced X-Ray features such as histograms, annotations, and filter expressions, see the Analyzing Performance for Amazon Rekognition Apps Written on AWS Lambda Using AWS X-Ray blog post.