Tag Archives: SAM

AWS Bill Simplification – Consolidated CloudWatch Charges

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/aws-bill-simplification-consolidated-cloudwatch-charges/

The bill that you receive for your use of AWS in July will include a change in the way that Amazon CloudWatch charges are presented. The CloudWatch team made this change in order to make your bill simpler and easier to understand.

Consolidating Charges
In the past, charges for your usage of CloudWatch were split between two sections of your bill. For historical reasons, the charges for CloudWatch Alarms, CloudWatch Metrics, and calls to the CloudWatch API were reported in the Elastic Compute Cloud (EC2) detail section, while charges for CloudWatch Logs and CloudWatch Dashboards were reported in the CloudWatch detail section, like this:

We have received feedback that splitting the charges across two sections of the bill made it difficult to locate and understand the entire set of monitoring charges. In order to address this issue, we are moving the charges that were formerly listed in the Elastic Compute Cloud (EC2) detail section to the CloudWatch detail section. We are making the same change to the detailed billing report, moving the affected charges from the AmazonEC2 product code to the AmazonCloudWatch product code and changing to the AmazonCloudWatch product name. This change does not affect your overall bill; it simply consolidates all of the charges for the use of CloudWatch in one section.

Billing Metric
The CloudWatch billing metric named Estimated Charges can be viewed as a Total Estimated Charge, or broken down By Service:

The total will not change. However, as noted above, the charges that formerly had AmazonEC2 as the ServiceName dimension will now have it set to AmazonCloudWatch:

You may need to adjust thresholds on your billing alarms as a result:

Once again, your total AWS bill will not change. You will begin to see the consolidated charges for CloudWatch in your AWS bill for July 2017.

Jeff;

 

NSA Insider Security Post-Snowden

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/06/nsa_insider_sec.html

According to a recently declassified report obtained under FOIA, the NSA’s attempts to protect itself against insider attacks aren’t going very well:

The N.S.A. failed to consistently lock racks of servers storing highly classified data and to secure data center machine rooms, according to the report, an investigation by the Defense Department’s inspector general completed in 2016.

[…]

The agency also failed to meaningfully reduce the number of officials and contractors who were empowered to download and transfer data classified as top secret, as well as the number of “privileged” users, who have greater power to access the N.S.A.’s most sensitive computer systems. And it did not fully implement software to monitor what those users were doing.

In all, the report concluded, while the post-Snowden initiative — called “Secure the Net” by the N.S.A. — had some successes, it “did not fully meet the intent of decreasing the risk of insider threats to N.S.A. operations and the ability of insiders to exfiltrate data.”

Marcy Wheeler comments:

The IG report examined seven of the most important out of 40 “Secure the Net” initiatives rolled out since Snowden began leaking classified information. Two of the initiatives aspired to reduce the number of people who had the kind of access Snowden did: those who have privileged access to maintain, configure, and operate the NSA’s computer systems (what the report calls PRIVACs), and those who are authorized to use removable media to transfer data to or from an NSA system (what the report calls DTAs).

But when DOD’s inspectors went to assess whether NSA had succeeded in doing this, they found something disturbing. In both cases, the NSA did not have solid documentation about how many such users existed at the time of the Snowden leak. With respect to PRIVACs, in June 2013 (the start of the Snowden leak), “NSA officials stated that they used a manually kept spreadsheet, which they no longer had, to identify the initial number of privileged users.” The report offered no explanation for how NSA came to no longer have that spreadsheet just as an investigation into the biggest breach thus far at NSA started. With respect to DTAs, “NSA did not know how many DTAs it had because the manually kept list was corrupted during the months leading up to the security breach.”

There seem to be two possible explanations for the fact that the NSA couldn’t track who had the same kind of access that Snowden exploited to steal so many documents. Either the dog ate their homework: Someone at NSA made the documents unavailable (or they never really existed). Or someone fed the dog their homework: Some adversary made these lists unusable. The former would suggest the NSA had something to hide as it prepared to explain why Snowden had been able to walk away with NSA’s crown jewels. The latter would suggest that someone deliberately obscured who else in the building might walk away with the crown jewels. Obscuring that list would be of particular value if you were a foreign adversary planning on walking away with a bunch of files, such as the set of hacking tools the Shadow Brokers have since released, which are believed to have originated at NSA.

Read the whole thing. Securing against insiders, especially those with technical access, is difficult, but I had assumed the NSA did more post-Snowden.

How to Create an AMI Builder with AWS CodeBuild and HashiCorp Packer – Part 2

Post Syndicated from Heitor Lessa original https://aws.amazon.com/blogs/devops/how-to-create-an-ami-builder-with-aws-codebuild-and-hashicorp-packer-part-2/

Written by AWS Solutions Architects Jason Barto and Heitor Lessa

 
In Part 1 of this post, we described how AWS CodeBuild, AWS CodeCommit, and HashiCorp Packer can be used to build an Amazon Machine Image (AMI) from the latest version of Amazon Linux. In this post, we show how to use AWS CodePipeline, AWS CloudFormation, and Amazon CloudWatch Events to continuously ship new AMIs. We use Ansible by Red Hat to harden the OS on the AMIs through a well-known set of security controls outlined by the Center for Internet Security in its CIS Amazon Linux Benchmark.

You’ll find the source code for this post in our GitHub repo.

At the end of this post, we will have the following architecture:

Requirements

 
To follow along, you will need Git and a text editor. Make sure Git is configured to work with AWS CodeCommit, as described in Part 1.

Technologies

 
In addition to the services and products used in Part 1 of this post, we also use these AWS services and third-party software:

AWS CloudFormation gives developers and systems administrators an easy way to create and manage a collection of related AWS resources, provisioning and updating them in an orderly and predictable fashion.

Amazon CloudWatch Events enables you to react selectively to events in the cloud and in your applications. Specifically, you can create CloudWatch Events rules that match event patterns, and take actions in response to those patterns.

AWS CodePipeline is a continuous integration and continuous delivery service for fast and reliable application and infrastructure updates. AWS CodePipeline builds, tests, and deploys your code every time there is a code change, based on release process models you define.

Amazon SNS is a fast, flexible, fully managed push notification service that lets you send individual messages or to fan out messages to large numbers of recipients. Amazon SNS makes it simple and cost-effective to send push notifications to mobile device users or email recipients. The service can even send messages to other distributed services.

Ansible is a simple IT automation system that handles configuration management, application deployment, cloud provisioning, ad-hoc task-execution, and multinode orchestration.

Getting Started

 
We use CloudFormation to bootstrap the following infrastructure:

Component Purpose
AWS CodeCommit repository Git repository where the AMI builder code is stored.
S3 bucket Build artifact repository used by AWS CodePipeline and AWS CodeBuild.
AWS CodeBuild project Executes the AWS CodeBuild instructions contained in the build specification file.
AWS CodePipeline pipeline Orchestrates the AMI build process, triggered by new changes in the AWS CodeCommit repository.
SNS topic Notifies subscribed email addresses when an AMI build is complete.
CloudWatch Events rule Defines how the AMI builder should send a custom event to notify an SNS topic.
Region AMI Builder Launch Template
N. Virginia (us-east-1)
Ireland (eu-west-1)

After launching the CloudFormation template linked here, we will have a pipeline in the AWS CodePipeline console. (Failed at this stage simply means we don’t have any data in our newly created AWS CodeCommit Git repository.)

Next, we will clone the newly created AWS CodeCommit repository.

If this is your first time connecting to a AWS CodeCommit repository, please see instructions in our documentation on Setup steps for HTTPS Connections to AWS CodeCommit Repositories.

To clone the AWS CodeCommit repository (console)

  1. From the AWS Management Console, open the AWS CloudFormation console.
  2. Choose the AMI-Builder-Blogpost stack, and then choose Output.
  3. Make a note of the Git repository URL.
  4. Use git to clone the repository.

For example: git clone https://git-codecommit.eu-west-1.amazonaws.com/v1/repos/AMI-Builder_repo

To clone the AWS CodeCommit repository (CLI)

# Retrieve CodeCommit repo URL
git_repo=$(aws cloudformation describe-stacks --query 'Stacks[0].Outputs[?OutputKey==`GitRepository`].OutputValue' --output text --stack-name "AMI-Builder-Blogpost")

# Clone repository locally
git clone ${git_repo}

Bootstrap the Repo with the AMI Builder Structure

 
Now that our infrastructure is ready, download all the files and templates required to build the AMI.

Your local Git repo should have the following structure:

.
├── ami_builder_event.json
├── ansible
├── buildspec.yml
├── cloudformation
├── packer_cis.json

Next, push these changes to AWS CodeCommit, and then let AWS CodePipeline orchestrate the creation of the AMI:

git add .
git commit -m "My first AMI"
git push origin master

AWS CodeBuild Implementation Details

 
While we wait for the AMI to be created, let’s see what’s changed in our AWS CodeBuild buildspec.yml file:

...
phases:
  ...
  build:
    commands:
      ...
      - ./packer build -color=false packer_cis.json | tee build.log
  post_build:
    commands:
      - egrep "${AWS_REGION}\:\sami\-" build.log | cut -d' ' -f2 > ami_id.txt
      # Packer doesn't return non-zero status; we must do that if Packer build failed
      - test -s ami_id.txt || exit 1
      - sed -i.bak "s/<<AMI-ID>>/$(cat ami_id.txt)/g" ami_builder_event.json
      - aws events put-events --entries file://ami_builder_event.json
      ...
artifacts:
  files:
    - ami_builder_event.json
    - build.log
  discard-paths: yes

In the build phase, we capture Packer output into a file named build.log. In the post_build phase, we take the following actions:

  1. Look up the AMI ID created by Packer and save its findings to a temporary file (ami_id.txt).
  2. Forcefully make AWS CodeBuild to fail if the AMI ID (ami_id.txt) is not found. This is required because Packer doesn’t fail if something goes wrong during the AMI creation process. We have to tell AWS CodeBuild to stop by informing it that an error occurred.
  3. If an AMI ID is found, we update the ami_builder_event.json file and then notify CloudWatch Events that the AMI creation process is complete.
  4. CloudWatch Events publishes a message to an SNS topic. Anyone subscribed to the topic will be notified in email that an AMI has been created.

Lastly, the new artifacts phase instructs AWS CodeBuild to upload files built during the build process (ami_builder_event.json and build.log) to the S3 bucket specified in the Outputs section of the CloudFormation template. These artifacts can then be used as an input artifact in any later stage in AWS CodePipeline.

For information about customizing the artifacts sequence of the buildspec.yml, see the Build Specification Reference for AWS CodeBuild.

CloudWatch Events Implementation Details

 
CloudWatch Events allow you to extend the AMI builder to not only send email after the AMI has been created, but to hook up any of the supported targets to react to the AMI builder event. This event publication means you can decouple from Packer actions you might take after AMI completion and plug in other actions, as you see fit.

For more information about targets in CloudWatch Events, see the CloudWatch Events API Reference.

In this case, CloudWatch Events should receive the following event, match it with a rule we created through CloudFormation, and publish a message to SNS so that you can receive an email.

Example CloudWatch custom event

[
        {
            "Source": "com.ami.builder",
            "DetailType": "AmiBuilder",
            "Detail": "{ \"AmiStatus\": \"Created\"}",
            "Resources": [ "ami-12cd5guf" ]
        }
]

Cloudwatch Events rule

{
  "detail-type": [
    "AmiBuilder"
  ],
  "source": [
    "com.ami.builder"
  ],
  "detail": {
    "AmiStatus": [
      "Created"
    ]
  }
}

Example SNS message sent in email

{
    "version": "0",
    "id": "f8bdede0-b9d7...",
    "detail-type": "AmiBuilder",
    "source": "com.ami.builder",
    "account": "<<aws_account_number>>",
    "time": "2017-04-28T17:56:40Z",
    "region": "eu-west-1",
    "resources": ["ami-112cd5guf "],
    "detail": {
        "AmiStatus": "Created"
    }
}

Packer Implementation Details

 
In addition to the build specification file, there are differences between the current version of the HashiCorp Packer template (packer_cis.json) and the one used in Part 1.

Variables

  "variables": {
    "vpc": "{{env `BUILD_VPC_ID`}}",
    "subnet": "{{env `BUILD_SUBNET_ID`}}",
         “ami_name”: “Prod-CIS-Latest-AMZN-{{isotime \”02-Jan-06 03_04_05\”}}”
  },
  • ami_name: Prefixes a name used by Packer to tag resources during the Builders sequence.
  • vpc and subnet: Environment variables defined by the CloudFormation stack parameters.

We no longer assume a default VPC is present and instead use the VPC and subnet specified in the CloudFormation parameters. CloudFormation configures the AWS CodeBuild project to use these values as environment variables. They are made available throughout the build process.

That allows for more flexibility should you need to change which VPC and subnet will be used by Packer to launch temporary resources.

Builders

  "builders": [{
    ...
    "ami_name": “{{user `ami_name`| clean_ami_name}}”,
    "tags": {
      "Name": “{{user `ami_name`}}”,
    },
    "run_tags": {
      "Name": “{{user `ami_name`}}",
    },
    "run_volume_tags": {
      "Name": “{{user `ami_name`}}",
    },
    "snapshot_tags": {
      "Name": “{{user `ami_name`}}",
    },
    ...
    "vpc_id": "{{user `vpc` }}",
    "subnet_id": "{{user `subnet` }}"
  }],

We now have new properties (*_tag) and a new function (clean_ami_name) and launch temporary resources in a VPC and subnet specified in the environment variables. AMI names can only contain a certain set of ASCII characters. If the input in project deviates from the expected characters (for example, includes whitespace or slashes), Packer’s clean_ami_name function will fix it.

For more information, see functions on the HashiCorp Packer website.

Provisioners

  "provisioners": [
    {
        "type": "shell",
        "inline": [
            "sudo pip install ansible"
        ]
    }, 
    {
        "type": "ansible-local",
        "playbook_file": "ansible/playbook.yaml",
        "role_paths": [
            "ansible/roles/common"
        ],
        "playbook_dir": "ansible",
        "galaxy_file": "ansible/requirements.yaml"
    },
    {
      "type": "shell",
      "inline": [
        "rm .ssh/authorized_keys ; sudo rm /root/.ssh/authorized_keys"
      ]
    }

We used shell provisioner to apply OS patches in Part 1. Now, we use shell to install Ansible on the target machine and ansible-local to import, install, and execute Ansible roles to make our target machine conform to our standards.

Packer uses shell to remove temporary keys before it creates an AMI from the target and temporary EC2 instance.

Ansible Implementation Details

 
Ansible provides OS patching through a custom Common role that can be easily customized for other tasks.

CIS Benchmark and Cloudwatch Logs are implemented through two Ansible third-party roles that are defined in ansible/requirements.yaml as seen in the Packer template.

The Ansible provisioner uses Ansible Galaxy to download these roles onto the target machine and execute them as instructed by ansible/playbook.yaml.

For information about how these components are organized, see the Playbook Roles and Include Statements in the Ansible documentation.

The following Ansible playbook (ansible</playbook.yaml) controls the execution order and custom properties:

---
- hosts: localhost
  connection: local
  gather_facts: true    # gather OS info that is made available for tasks/roles
  become: yes           # majority of CIS tasks require root
  vars:
    # CIS Controls whitepaper:  http://bit.ly/2mGAmUc
    # AWS CIS Whitepaper:       http://bit.ly/2m2Ovrh
    cis_level_1_exclusions:
    # 3.4.2 and 3.4.3 effectively blocks access to all ports to the machine
    ## This can break automation; ignoring it as there are stronger mechanisms than that
      - 3.4.2 
      - 3.4.3
    # CloudWatch Logs will be used instead of Rsyslog/Syslog-ng
    ## Same would be true if any other software doesn't support Rsyslog/Syslog-ng mechanisms
      - 4.2.1.4
      - 4.2.2.4
      - 4.2.2.5
    # Autofs is not installed in newer versions, let's ignore
      - 1.1.19
    # Cloudwatch Logs role configuration
    logs:
      - file: /var/log/messages
        group_name: "system_logs"
  roles:
    - common
    - anthcourtney.cis-amazon-linux
    - dharrisio.aws-cloudwatch-logs-agent

Both third-party Ansible roles can be easily configured through variables (vars). We use Ansible playbook variables to exclude CIS controls that don’t apply to our case and to instruct the CloudWatch Logs agent to stream the /var/log/messages log file to CloudWatch Logs.

If you need to add more OS or application logs, you can easily duplicate the playbook and make changes. The CloudWatch Logs agent will ship configured log messages to CloudWatch Logs.

For more information about parameters you can use to further customize third-party roles, download Ansible roles for the Cloudwatch Logs Agent and CIS Amazon Linux from the Galaxy website.

Committing Changes

 
Now that Ansible and CloudWatch Events are configured as a part of the build process, commiting any changes to the AWS CodeComit Git Repository will triger a new AMI build process that can be followed through the AWS CodePipeline console.

When the build is complete, an email will be sent to the email address you provided as a part of the CloudFormation stack deployment. The email serves as notification that an AMI has been built and is ready for use.

Summary

 
We used AWS CodeCommit, AWS CodePipeline, AWS CodeBuild, Packer, and Ansible to build a pipeline that continuously builds new, hardened CIS AMIs. We used Amazon SNS so that email addresses subscribed to a SNS topic are notified upon completion of the AMI build.

By treating our AMI creation process as code, we can iterate and track changes over time. In this way, it’s no different from a software development workflow. With that in mind, software patches, OS configuration, and logs that need to be shipped to a central location are only a git commit away.

Next Steps

 
Here are some ideas to extend this AMI builder:

  • Hook up a Lambda function in Cloudwatch Events to update EC2 Auto Scaling configuration upon completion of the AMI build.
  • Use AWS CodePipeline parallel steps to build multiple Packer images.
  • Add a commit ID as a tag for the AMI you created.
  • Create a scheduled Lambda function through Cloudwatch Events to clean up old AMIs based on timestamp (name or additional tag).
  • Implement Windows support for the AMI builder.
  • Create a cross-account or cross-region AMI build.

Cloudwatch Events allow the AMI builder to decouple AMI configuration and creation so that you can easily add your own logic using targets (AWS Lambda, Amazon SQS, Amazon SNS) to add events or recycle EC2 instances with the new AMI.

If you have questions or other feedback, feel free to leave it in the comments or contribute to the AMI Builder repo on GitHub.

Three Men Sentenced Following £2.5m Internet Piracy Case

Post Syndicated from Andy original https://torrentfreak.com/three-men-sentenced-following-2-5m-internet-piracy-case-170622/

While legal action against low-level individual file-sharers is extremely rare in the UK, the country continues to pose a risk for those engaged in larger-scale infringement.

That is largely due to the activities of the Police Intellectual Property Crime Unit and private anti-piracy outfits such as the Federation Against Copyright Theft (FACT). Investigations are often a joint effort which can take many years to complete, but the outcomes can often involve criminal sentences.

That was the profile of another Internet piracy case that concluded in London this week. It involved three men from the UK, Eric Brooks, 43, from Bolton, Mark Valentine, 44, from Manchester, and Craig Lloyd, 33, from Wolverhampton.

The case began when FACT became aware of potentially infringing activity back in February 2011. The anti-piracy group then investigated for more than a year before handing the case to police in March 2012.

On July 4, 2012, officers from City of London Police arrested Eric Brooks’ at his home in Bolton following a joint raid with FACT. Computer equipment was seized containing evidence that Brooks had been running a Netherlands-based server hosting more than £100,000 worth of pirated films, music, games, software and ebooks.

According to police, a spreadsheet on Brooks’ computer revealed he had hundreds of paying customers, all recruited from online forums. Using PayPal or utilizing bank transfers, each paid money to access the server. Police mentioned no group or site names in information released this week.

“Enquiries with PayPal later revealed that [Brooks] had made in excess of £500,000 in the last eight years from his criminal business and had in turn defrauded the film and TV industry alone of more than £2.5 million,” police said.

“As his criminal enterprise affected not only the film and TV but the wider entertainment industry including music, games, books and software it is thought that he cost the wider industry an amount much higher than £2.5 million.”

On the same day police arrested Brooks, Mark Valentine’s home in Manchester had a similar unwelcome visit. A day later, Craig Lloyd’s home in Wolverhampton become the third target for police.

Computer equipment was seized from both addresses which revealed that the pair had been paying for access to Brooks’ servers in order to service their own customers.

“They too had used PayPal as a means of taking payment and had earned thousands of pounds from their criminal actions; Valentine gaining £34,000 and Lloyd making over £70,000,” police revealed.

But after raiding the trio in 2012, it took more than four years to charge the men. In a feature common to many FACT cases, all three were charged with Conspiracy to Defraud rather than copyright infringement offenses. All three men pleaded guilty before trial.

On Monday, the men were sentenced at Inner London Crown Court. Brooks was sentenced to 24 months in prison, suspended for 12 months and ordered to complete 140 hours of unpaid work.

Valentine and Lloyd were each given 18 months in prison, suspended for 12 months. Each was ordered to complete 80 hours unpaid work.

Detective Constable Chris Glover, who led the investigation for the City of London Police, welcomed the sentencing.

“The success of this investigation is a result of co-ordinated joint working between the City of London Police and FACT. Brooks, Valentine and Lloyd all thought that they were operating under the radar and doing something which they thought was beyond the controls of law enforcement,” Glover said.

“Brooks, Valentine and Lloyd will now have time in prison to reflect on their actions and the result should act as deterrent for anyone else who is enticed by abusing the internet to the detriment of the entertainment industry.”

While even suspended sentences are a serious matter, none of the men will see the inside of a cell if they meet the conditions of their sentence for the next 12 months. For a case lasting four years involving such large sums of money, that is probably a disappointing result for FACT and the police.

Nevertheless, the men won’t be allowed to enjoy the financial proceeds of their piracy, if indeed any money is left. City of London Police say the trio will be subject to a future confiscation hearing to seize any proceeds of crime.

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

DynamoDB Accelerator (DAX) Now Generally Available

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/dynamodb-accelerator-dax-now-generally-available/

Earlier this year I told you about Amazon DynamoDB Accelerator (DAX), a fully-managed caching service that sits in front of (logically speaking) your Amazon DynamoDB tables. DAX returns cached responses in microseconds, making it a great fit for eventually-consistent read-intensive workloads. DAX supports the DynamoDB API, and is seamless and easy to use. As a managed service, you simply create your DAX cluster and use it as the target for your existing reads and writes. You don’t have to worry about patching, cluster maintenance, replication, or fault management.

Now Generally Available
Today I am pleased to announce that DAX is now generally available. We have expanded DAX into additional AWS Regions and used the preview time to fine-tune performance and availability:

Now in Five Regions – DAX is now available in the US East (Northern Virginia), EU (Ireland), US West (Oregon), Asia Pacific (Tokyo), and US West (Northern California) Regions.

In Production – Our preview customers are reporting that they are using DAX in production, that they loved how easy it was to add DAX to their application, and have told us that their apps are now running 10x faster.

Getting Started with DAX
As I outlined in my earlier post, it is easy to use DAX to accelerate your existing DynamoDB applications. You simply create a DAX cluster in the desired region, update your application to reference the DAX SDK for Java (the calls are the same; this is a drop-in replacement), and configure the SDK to use the endpoint to your cluster. As a read-through/write-through cache, DAX seamlessly handles all of the DynamoDB read/write APIs.

We are working on SDK support for other languages, and I will share additional information as it becomes available.

DAX Pricing
You pay for each node in the cluster (see the DynamoDB Pricing page for more information) on a per-hour basis, with prices starting at $0.269 per hour in the US East (Northern Virginia) and US West (Oregon) regions. With DAX, each of the nodes in your cluster serves as a read target and as a failover target for high availability. The DAX SDK is cluster aware and will issue round-robin requests to all nodes in the cluster so that you get to make full use of the cluster’s cache resources.

Because DAX can easily handle sudden spikes in read traffic, you may be able to reduce the amount of provisioned throughput for your tables, resulting in an overall cost savings while still returning results in microseconds.

Jeff;

 

Is Continuing to Patch Windows XP a Mistake?

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/06/is_continuing_t.html

Last week, Microsoft issued a security patch for Windows XP, a 16-year-old operating system that Microsoft officially no longer supports. Last month, Microsoft issued a Windows XP patch for the vulnerability used in WannaCry.

Is this a good idea? This 2014 essay argues that it’s not:

The zero-day flaw and its exploitation is unfortunate, and Microsoft is likely smarting from government calls for people to stop using Internet Explorer. The company had three ways it could respond. It could have done nothing­ — stuck to its guns, maintained that the end of support means the end of support, and encouraged people to move to a different platform. It could also have relented entirely, extended Windows XP’s support life cycle for another few years and waited for attrition to shrink Windows XP’s userbase to irrelevant levels. Or it could have claimed that this case is somehow “special,” releasing a patch while still claiming that Windows XP isn’t supported.

None of these options is perfect. A hard-line approach to the end-of-life means that there are people being exploited that Microsoft refuses to help. A complete about-turn means that Windows XP will take even longer to flush out of the market, making it a continued headache for developers and administrators alike.

But the option Microsoft took is the worst of all worlds. It undermines efforts by IT staff to ditch the ancient operating system and undermines Microsoft’s assertion that Windows XP isn’t supported, while doing nothing to meaningfully improve the security of Windows XP users. The upside? It buys those users at best a few extra days of improved security. It’s hard to say how that was possibly worth it.

This is a hard trade-off, and it’s going to get much worse with the Internet of Things. Here’s me:

The security of our computers and phones also comes from the fact that we replace them regularly. We buy new laptops every few years. We get new phones even more frequently. This isn’t true for all of the embedded IoT systems. They last for years, even decades. We might buy a new DVR every five or ten years. We replace our refrigerator every 25 years. We replace our thermostat approximately never. Already the banking industry is dealing with the security problems of Windows 95 embedded in ATMs. This same problem is going to occur all over the Internet of Things.

At least Microsoft has security engineers on staff that can write a patch for Windows XP. There will be no one able to write patches for your 16-year-old thermostat and refrigerator, even assuming those devices can accept security patches.

Protect Web Sites & Services Using Rate-Based Rules for AWS WAF

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/protect-web-sites-services-using-rate-based-rules-for-aws-waf/

AWS WAF (Web Application Firewall) helps to protect your application from many different types of application-layer attacks that involve requests that are malicious or malformed. As I showed you when I first wrote about this service (New – AWS WAF), you can define rules that match cross-site scripting, IP address, SQL injection, size, or content constraints:

When incoming requests match rules, actions are invoked. Actions can either allow, block, or simply count matches.

The existing rule model is powerful and gives you the ability to detect and respond to many different types of attacks. It does not, however, allow you to respond to attacks that simply consist of a large number of otherwise valid requests from a particular IP address. These requests might be a web-layer DDoS attack, a brute-force login attempt, or even a partner integration gone awry.

New Rate-Based Rules
Today we are adding Rate-based Rules to WAF, giving you control of when IP addresses are added to and removed from a blacklist, along with the flexibility to handle exceptions and special cases:

Blacklisting IP Addresses – You can blacklist IP addresses that make requests at a rate that exceeds a configured threshold rate.

IP Address Tracking– You can see which IP addresses are currently blacklisted.

IP Address Removal – IP addresses that have been blacklisted are automatically removed when they no longer make requests at a rate above the configured threshold.

IP Address Exemption – You can exempt certain IP addresses from blacklisting by using an IP address whitelist inside of the a rate-based rule. For example, you might want to allow trusted partners to access your site at a higher rate.

Monitoring & Alarming – You can watch and alarm on CloudWatch metrics that are published for each rule.

You can combine new Rate-based Rules with WAF Conditions to implement sophisticated rate-limiting strategies. For example, you could use a Rate-based Rule and a WAF Condition that matches your login pages. This would allow you to impose a modest threshold on your login pages (to avoid brute-force password attacks) and allow a more generous one on your marketing or system status pages.

Thresholds are defined in terms of the number of incoming requests from a single IP address within a 5 minute period. Once this threshold is breached, additional requests from the IP address are blocked until the request rate falls below the threshold.

Using Rate-Based Rules
Here’s how you would define a Rate-based Rule that protects the /login portion of your site. Start by defining a WAF condition that matches the desired string in the URI of the page:

Then use this condition to define a Rate-based Rule (the rate limit is expressed in terms of requests within a 5 minute interval, but the blacklisting goes in to effect as soon as the limit is breached):

With the condition and the rule in place, create a Web ACL (ProtectLoginACL) to bring it all together and to attach it to the AWS resource (a CloudFront distribution in this case):

Then attach the rule (ProtectLogin) to the Web ACL:

The resource is now protected in accord with the rule and the web ACL. You can monitor the associated CloudWatch metrics (ProtectLogin and ProtectLoginACL in this case). You could even create CloudWatch Alarms and use them to fire Lambda functions when a protection threshold is breached. The code could examine the offending IP address and make a complex, business-driven decision, perhaps adding a whitelisting rule that gives an extra-generous allowance to a trusted partner or to a user with a special payment plan.

Available Now
The new, Rate-based Rules are available now and you can start using them today! Rate-based rules are priced the same as Regular rules; see the WAF Pricing page for more info.

Jeff;

MPAA & RIAA Demand Tough Copyright Standards in NAFTA Negotiations

Post Syndicated from Andy original https://torrentfreak.com/mpaa-riaa-demand-tough-copyright-standards-in-nafta-negotiations-170621/

The North American Free Trade Agreement (NAFTA) between the United States, Canada, and Mexico was negotiated more than 25 years ago. With a quarter of a decade of developments to contend with, the United States wants to modernize.

“While our economy and U.S. businesses have changed considerably over that period, NAFTA has not,” the government says.

With this in mind, the US requested comments from interested parties seeking direction for negotiation points. With those comments now in, groups like the MPAA and RIAA have been making their positions known. It’s no surprise that intellectual property enforcement is high on the agenda.

“Copyright is the lifeblood of the U.S. motion picture and television industry. As such, MPAA places high priority on securing strong protection and enforcement disciplines in the intellectual property chapters of trade agreements,” the MPAA writes in its submission.

“Strong IPR protection and enforcement are critical trade priorities for the music industry. With IPR, we can create good jobs, make significant contributions to U.S. economic growth and security, invest in artists and their creativity, and drive technological innovation,” the RIAA notes.

While both groups have numerous demands, it’s clear that each seeks an environment where not only infringers can be held liable, but also Internet platforms and services.

For the RIAA, there is a big focus on the so-called ‘Value Gap’, a phenomenon found on user-uploaded content sites like YouTube that are able to offer infringing content while avoiding liability due to Section 512 of the DMCA.

“Today, user-uploaded content services, which have developed sophisticated on-demand music platforms, use this as a shield to avoid licensing music on fair terms like other digital services, claiming they are not legally responsible for the music they distribute on their site,” the RIAA writes.

“Services such as Apple Music, TIDAL, Amazon, and Spotify are forced to compete with services that claim they are not liable for the music they distribute.”

But if sites like YouTube are exercising their rights while acting legally under current US law, how can partners Canada and Mexico do any better? For the RIAA, that can be achieved by holding them to standards envisioned by the group when the DMCA was passed, not how things have panned out since.

Demanding that negotiators “protect the original intent” of safe harbor, the RIAA asks that a “high-level and high-standard service provider liability provision” is pursued. This, the music group says, should only be available to “passive intermediaries without requisite knowledge of the infringement on their platforms, and inapplicable to services actively engaged in communicating to the public.”

In other words, make sure that YouTube and similar sites won’t enjoy the same level of safe harbor protection as they do today.

The RIAA also requires any negotiated safe harbor provisions in NAFTA to be flexible in the event that the DMCA is tightened up in response to the ongoing safe harbor rules study.

In any event, NAFTA should not “support interpretations that no longer reflect today’s digital economy and threaten the future of legitimate and sustainable digital trade,” the RIAA states.

For the MPAA, Section 512 is also perceived as a problem. While noting that the original intent was to foster a system of shared responsibility between copyright owners and service providers, the MPAA says courts have subsequently let copyright holders down. Like the RIAA, the MPAA also suggests that Canada and Mexico can be held to higher standards.

“We recommend a new approach to this important trade policy provision by moving to high-level language that establishes intermediary liability and appropriate limitations on liability. This would be fully consistent with U.S. law and avoid the same misinterpretations by policymakers and courts overseas,” the MPAA writes.

“In so doing, a modernized NAFTA would be consistent with Trade Promotion Authority’s negotiating objective of ‘ensuring that standards of protection and enforcement keep pace with technological developments’.”

The MPAA also has some specific problems with Mexico, including unauthorized camcording. The Hollywood group says that 85 illicit audio and video recordings of films were linked to Mexican theaters in 2016. However, recording is not currently a criminal offense in Mexico.

Another issue for the MPAA is that criminal sanctions for commercial scale infringement are only available if the infringement is for profit.

“This has hampered enforcement against the above-discussed camcording problem but also against online infringement, such as peer-to-peer piracy, that may be on a scale that is immensely harmful to U.S. rightsholders but nonetheless occur without profit by the infringer,” the MPAA writes.

“The modernized NAFTA like other U.S. bilateral free trade agreements must provide for criminal sanctions against commercial scale infringements without proof of profit motive.”

Also of interest are the MPAA’s complaints against Mexico’s telecoms laws. Unlike in the US and many countries in Europe, Mexico’s ISPs are forbidden to hand out their customers’ personal details to rights holders looking to sue. This, the MPAA says, needs to change.

The submissions from the RIAA and MPAA can be found here and here (pdf)

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

Building Loosely Coupled, Scalable, C# Applications with Amazon SQS and Amazon SNS

Post Syndicated from Tara Van Unen original https://aws.amazon.com/blogs/compute/building-loosely-coupled-scalable-c-applications-with-amazon-sqs-and-amazon-sns/

 
Stephen Liedig, Solutions Architect

 

One of the many challenges professional software architects and developers face is how to make cloud-native applications scalable, fault-tolerant, and highly available.

Fundamental to your project success is understanding the importance of making systems highly cohesive and loosely coupled. That means considering the multi-dimensional facets of system coupling to support the distributed nature of the applications that you are building for the cloud.

By that, I mean addressing not only the application-level coupling (managing incoming and outgoing dependencies), but also considering the impacts of of platform, spatial, and temporal coupling of your systems. Platform coupling relates to the interoperability, or lack thereof, of heterogeneous systems components. Spatial coupling deals with managing components at a network topology level or protocol level. Temporal, or runtime coupling, refers to the ability of a component within your system to do any kind of meaningful work while it is performing a synchronous, blocking operation.

The AWS messaging services, Amazon SQS and Amazon SNS, help you deal with these forms of coupling by providing mechanisms for:

  • Reliable, durable, and fault-tolerant delivery of messages between application components
  • Logical decomposition of systems and increased autonomy of components
  • Creating unidirectional, non-blocking operations, temporarily decoupling system components at runtime
  • Decreasing the dependencies that components have on each other through standard communication and network channels

Following on the recent topic, Building Scalable Applications and Microservices: Adding Messaging to Your Toolbox, in this post, I look at some of the ways you can introduce SQS and SNS into your architectures to decouple your components, and show how you can implement them using C#.

Walkthrough

To illustrate some of these concepts, consider a web application that processes customer orders. As good architects and developers, you have followed best practices and made your application scalable and highly available. Your solution included implementing load balancing, dynamic scaling across multiple Availability Zones, and persisting orders in a Multi-AZ Amazon RDS database instance, as in the following diagram.


In this example, the application is responsible for handling and persisting the order data, as well as dealing with increases in traffic for popular items.

One potential point of vulnerability in the order processing workflow is in saving the order in the database. The business expects that every order has been persisted into the database. However, any potential deadlock, race condition, or network issue could cause the persistence of the order to fail. Then, the order is lost with no recourse to restore the order.

With good logging capability, you may be able to identify when an error occurred and which customer’s order failed. This wouldn’t allow you to “restore” the transaction, and by that stage, your customer is no longer your customer.

As illustrated in the following diagram, introducing an SQS queue helps improve your ordering application. Using the queue isolates the processing logic into its own component and runs it in a separate process from the web application. This, in turn, allows the system to be more resilient to spikes in traffic, while allowing work to be performed only as fast as necessary in order to manage costs.


In addition, you now have a mechanism for persisting orders as messages (with the queue acting as a temporary database), and have moved the scope of your transaction with your database further down the stack. In the event of an application exception or transaction failure, this ensures that the order processing can be retired or redirected to the Amazon SQS Dead Letter Queue (DLQ), for re-processing at a later stage. (See the recent post, Using Amazon SQS Dead-Letter Queues to Control Message Failure, for more information on dead-letter queues.)

Scaling the order processing nodes

This change allows you now to scale the web application frontend independently from the processing nodes. The frontend application can continue to scale based on metrics such as CPU usage, or the number of requests hitting the load balancer. Processing nodes can scale based on the number of orders in the queue. Here is an example of scale-in and scale-out alarms that you would associate with the scaling policy.

Scale-out Alarm

aws cloudwatch put-metric-alarm --alarm-name AddCapacityToCustomerOrderQueue --metric-name ApproximateNumberOfMessagesVisible --namespace "AWS/SQS" 
--statistic Average --period 300 --threshold 3 --comparison-operator GreaterThanOrEqualToThreshold --dimensions Name=QueueName,Value=customer-orders
--evaluation-periods 2 --alarm-actions <arn of the scale-out autoscaling policy>

Scale-in Alarm

aws cloudwatch put-metric-alarm --alarm-name RemoveCapacityFromCustomerOrderQueue --metric-name ApproximateNumberOfMessagesVisible --namespace "AWS/SQS" 
 --statistic Average --period 300 --threshold 1 --comparison-operator LessThanOrEqualToThreshold --dimensions Name=QueueName,Value=customer-orders
 --evaluation-periods 2 --alarm-actions <arn of the scale-in autoscaling policy>

In the above example, use the ApproximateNumberOfMessagesVisible metric to discover the queue length and drive the scaling policy of the Auto Scaling group. Another useful metric is ApproximateAgeOfOldestMessage, when applications have time-sensitive messages and developers need to ensure that messages are processed within a specific time period.

Scaling the order processing implementation

On top of scaling at an infrastructure level using Auto Scaling, make sure to take advantage of the processing power of your Amazon EC2 instances by using as many of the available threads as possible. There are several ways to implement this. In this post, we build a Windows service that uses the BackgroundWorker class to process the messages from the queue.

Here’s a closer look at the implementation. In the first section of the consuming application, use a loop to continually poll the queue for new messages, and construct a ReceiveMessageRequest variable.

public static void PollQueue()
{
    while (_running)
    {
        Task<ReceiveMessageResponse> receiveMessageResponse;

        // Pull messages off the queue
        using (var sqs = new AmazonSQSClient())
        {
            const int maxMessages = 10;  // 1-10

            //Receiving a message
            var receiveMessageRequest = new ReceiveMessageRequest
            {
                // Get URL from Configuration
                QueueUrl = _queueUrl, 
                // The maximum number of messages to return. 
                // Fewer messages might be returned. 
                MaxNumberOfMessages = maxMessages, 
                // A list of attributes that need to be returned with message.
                AttributeNames = new List<string> { "All" },
                // Enable long polling. 
                // Time to wait for message to arrive on queue.
                WaitTimeSeconds = 5 
            };

            receiveMessageResponse = sqs.ReceiveMessageAsync(receiveMessageRequest);
        }

The WaitTimeSeconds property of the ReceiveMessageRequest specifies the duration (in seconds) that the call waits for a message to arrive in the queue before returning a response to the calling application. There are a few benefits to using long polling:

  • It reduces the number of empty responses by allowing SQS to wait until a message is available in the queue before sending a response.
  • It eliminates false empty responses by querying all (rather than a limited number) of the servers.
  • It returns messages as soon any message becomes available.

For more information, see Amazon SQS Long Polling.

After you have returned messages from the queue, you can start to process them by looping through each message in the response and invoking a new BackgroundWorker thread.

// Process messages
if (receiveMessageResponse.Result.Messages != null)
{
    foreach (var message in receiveMessageResponse.Result.Messages)
    {
        Console.WriteLine("Received SQS message, starting worker thread");

        // Create background worker to process message
        BackgroundWorker worker = new BackgroundWorker();
        worker.DoWork += (obj, e) => ProcessMessage(message);
        worker.RunWorkerAsync();
    }
}
else
{
    Console.WriteLine("No messages on queue");
}

The event handler, ProcessMessage, is where you implement business logic for processing orders. It is important to have a good understanding of how long a typical transaction takes so you can set a message VisibilityTimeout that is long enough to complete your operation. If order processing takes longer than the specified timeout period, the message becomes visible on the queue. Other nodes may pick it and process the same order twice, leading to unintended consequences.

Handling Duplicate Messages

In order to manage duplicate messages, seek to make your processing application idempotent. In mathematics, idempotent describes a function that produces the same result if it is applied to itself:

f(x) = f(f(x))

No matter how many times you process the same message, the end result is the same (definition from Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions, Hohpe and Wolf, 2004).

There are several strategies you could apply to achieve this:

  • Create messages that have inherent idempotent characteristics. That is, they are non-transactional in nature and are unique at a specified point in time. Rather than saying “place new order for Customer A,” which adds a duplicate order to the customer, use “place order <orderid> on <timestamp> for Customer A,” which creates a single order no matter how often it is persisted.
  • Deliver your messages via an Amazon SQS FIFO queue, which provides the benefits of message sequencing, but also mechanisms for content-based deduplication. You can deduplicate using the MessageDeduplicationId property on the SendMessage request or by enabling content-based deduplication on the queue, which generates a hash for MessageDeduplicationId, based on the content of the message, not the attributes.
var sendMessageRequest = new SendMessageRequest
{
    QueueUrl = _queueUrl,
    MessageBody = JsonConvert.SerializeObject(order),
    MessageGroupId = Guid.NewGuid().ToString("N"),
    MessageDeduplicationId = Guid.NewGuid().ToString("N")
};
  • If using SQS FIFO queues is not an option, keep a message log of all messages attributes processed for a specified period of time, as an alternative to message deduplication on the receiving end. Verifying the existence of the message in the log before processing the message adds additional computational overhead to your processing. This can be minimized through low latency persistence solutions such as Amazon DynamoDB. Bear in mind that this solution is dependent on the successful, distributed transaction of the message and the message log.

Handling exceptions

Because of the distributed nature of SQS queues, it does not automatically delete the message. Therefore, you must explicitly delete the message from the queue after processing it, using the message ReceiptHandle property (see the following code example).

However, if at any stage you have an exception, avoid handling it as you normally would. The intention is to make sure that the message ends back on the queue, so that you can gracefully deal with intermittent failures. Instead, log the exception to capture diagnostic information, and swallow it.

By not explicitly deleting the message from the queue, you can take advantage of the VisibilityTimeout behavior described earlier. Gracefully handle the message processing failure and make the unprocessed message available to other nodes to process.

In the event that subsequent retries fail, SQS automatically moves the message to the configured DLQ after the configured number of receives has been reached. You can further investigate why the order process failed. Most importantly, the order has not been lost, and your customer is still your customer.

private static void ProcessMessage(Message message)
{
    using (var sqs = new AmazonSQSClient())
    {
        try
        {
            Console.WriteLine("Processing message id: {0}", message.MessageId);

            // Implement messaging processing here
            // Ensure no downstream resource contention (parallel processing)
            // <your order processing logic in here…>
            Console.WriteLine("{0} Thread {1}: {2}", DateTime.Now.ToString("s"), Thread.CurrentThread.ManagedThreadId, message.MessageId);
            
            // Delete the message off the queue. 
            // Receipt handle is the identifier you must provide 
            // when deleting the message.
            var deleteRequest = new DeleteMessageRequest(_queueName, message.ReceiptHandle);
            sqs.DeleteMessageAsync(deleteRequest);
            Console.WriteLine("Processed message id: {0}", message.MessageId);

        }
        catch (Exception ex)
        {
            // Do nothing.
            // Swallow exception, message will return to the queue when 
            // visibility timeout has been exceeded.
            Console.WriteLine("Could not process message due to error. Exception: {0}", ex.Message);
        }
    }
}

Using SQS to adapt to changing business requirements

One of the benefits of introducing a message queue is that you can accommodate new business requirements without dramatically affecting your application.

If, for example, the business decided that all orders placed over $5000 are to be handled as a priority, you could introduce a new “priority order” queue. The way the orders are processed does not change. The only significant change to the processing application is to ensure that messages from the “priority order” queue are processed before the “standard order” queue.

The following diagram shows how this logic could be isolated in an “order dispatcher,” whose only purpose is to route order messages to the appropriate queue based on whether the order exceeds $5000. Nothing on the web application or the processing nodes changes other than the target queue to which the order is sent. The rates at which orders are processed can be achieved by modifying the poll rates and scalability settings that I have already discussed.

Extending the design pattern with Amazon SNS

Amazon SNS supports reliable publish-subscribe (pub-sub) scenarios and push notifications to known endpoints across a wide variety of protocols. It eliminates the need to periodically check or poll for new information and updates. SNS supports:

  • Reliable storage of messages for immediate or delayed processing
  • Publish / subscribe – direct, broadcast, targeted “push” messaging
  • Multiple subscriber protocols
  • Amazon SQS, HTTP, HTTPS, email, SMS, mobile push, AWS Lambda

With these capabilities, you can provide parallel asynchronous processing of orders in the system and extend it to support any number of different business use cases without affecting the production environment. This is commonly referred to as a “fanout” scenario.

Rather than your web application pushing orders to a queue for processing, send a notification via SNS. The SNS messages are sent to a topic and then replicated and pushed to multiple SQS queues and Lambda functions for processing.

As the diagram above shows, you have the development team consuming “live” data as they work on the next version of the processing application, or potentially using the messages to troubleshoot issues in production.

Marketing is consuming all order information, via a Lambda function that has subscribed to the SNS topic, inserting the records into an Amazon Redshift warehouse for analysis.

All of this, of course, is happening without affecting your order processing application.

Summary

While I haven’t dived deep into the specifics of each service, I have discussed how these services can be applied at an architectural level to build loosely coupled systems that facilitate multiple business use cases. I’ve also shown you how to use infrastructure and application-level scaling techniques, so you can get the most out of your EC2 instances.

One of the many benefits of using these managed services is how quickly and easily you can implement powerful messaging capabilities in your systems, and lower the capital and operational costs of managing your own messaging middleware.

Using Amazon SQS and Amazon SNS together can provide you with a powerful mechanism for decoupling application components. This should be part of design considerations as you architect for the cloud.

For more information, see the Amazon SQS Developer Guide and Amazon SNS Developer Guide. You’ll find tutorials on all the concepts covered in this post, and more. To can get started using the AWS console or SDK of your choice visit:

Happy messaging!

Roku Sales Banned in Mexico Over Piracy Concerns

Post Syndicated from Ernesto original https://torrentfreak.com/roku-sales-banned-in-mexico-over-piracy-concerns-170619/

Online streaming piracy is on the rise and many people use dedicated media players to watch it through their regular TV.

While a lot of attention has been on Kodi, there are other players on the market that allow people to do the same. Roku, for example, has been doing very well too.

Like Kodi, Roku media players don’t offer any pirated content out of the box. In fact, they can be hooked up to a wide variety of legal streaming options including HBO Go, Hulu, and Netflix. Still, there is also a market for third-party pirate channels, outside the Roku Channel Store, which turn the boxes into pirate tools.

This pirate angle has now resulted in a ban on Roku sales in Mexico, according to a report in Milenio.

The ban was issued by the Superior Court of Justice of the City of Mexico, following a complaint from Cablevision. The order in question prohibits stores such as Amazon, Liverpool, El Palacio de Hierro, and Sears from importing and selling the devices.

In addition, the court also instructs banks including Banorte and BBVA Bancomer to stop processing payments from a long list of accounts linked to pirated services on Roku.

The main reason for the order is the availability of pirated content through Roku, but banning the device itself is utterly comprehensive. It would be similar to banning all Android-based devices because certain apps allow users to stream copyrighted content without permission.

Roku

Roku has yet to release an official statement on the court order. TorrentFreak reached out to the company but hadn’t heard back at the time of publication.

It’s clear, however, that streaming players are among the top concerns for copyright holders. Motion Picture Association boss Stan McCoy recently characterized the use of streaming players to access infringing content as “Piracy 3.0.

“If you think of old-fashioned peer-to-peer piracy as 1.0, and then online illegal streaming websites as 2.0, in the audio-visual sector, in particular, we now face challenge number 3.0, which is what I’ll call the challenge of illegal streaming devices,” McCoy said earlier this month.

Unlike the court order in Mexico, however, McCoy stressed that the devices themselves, and software such as Kodi, are ‘probably’ not illegal. However, copyright-infringing pirate add-ons have the capability to turn them into an unprecedented piracy threat.

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

BPI Breaks Record After Sending 310 Million Google Takedowns

Post Syndicated from Andy original https://torrentfreak.com/bpi-breaks-record-after-sending-310-million-google-takedowns-170619/

A little over a year ago during March 2016, music industry group BPI reached an important milestone. After years of sending takedown notices to Google, the group burst through the 200 million URL barrier.

The fact that it took BPI several years to reach its 200 million milestone made the surpassing of the quarter billion milestone a few months later even more remarkable. In October 2016, the group sent its 250 millionth takedown to Google, a figure that nearly doubled when accounting for notices sent to Microsoft’s Bing.

But despite the volumes, the battle hadn’t been won, let alone the war. The BPI’s takedown machine continued to run at a remarkable rate, churning out millions more notices per week.

As a result, yet another new milestone was reached this month when the BPI smashed through the 300 million URL barrier. Then, days later, a further 10 million were added, with the latter couple of million added during the time it took to put this piece together.

BPI takedown notices, as reported by Google

While demanding that Google places greater emphasis on its de-ranking of ‘pirate’ sites, the BPI has called again and again for a “notice and stay down” regime, to ensure that content taken down by the search engine doesn’t simply reappear under a new URL. It’s a position BPI maintains today.

“The battle would be a whole lot easier if intermediaries played fair,” a BPI spokesperson informs TF.

“They need to take more proactive responsibility to reduce infringing content that appears on their platform, and, where we expressly notify infringing content to them, to ensure that they do not only take it down, but also keep it down.”

The long-standing suggestion is that the volume of takedown notices sent would reduce if a “take down, stay down” regime was implemented. The BPI says it’s difficult to present a precise figure but infringing content has a tendency to reappear, both in search engines and on hosting sites.

“Google rejects repeat notices for the same URL. But illegal content reappears as it is re-indexed by Google. As to the sites that actually host the content, the vast majority of notices sent to them could be avoided if they implemented take-down & stay-down,” BPI says.

The fact that the BPI has added 60 million more takedowns since the quarter billion milestone a few months ago is quite remarkable, particularly since there appears to be little slowdown from month to month. However, the numbers have grown so huge that 310 billion now feels a lot like 250 million, with just a few added on top for good measure.

That an extra 60 million takedowns can almost be dismissed as a handful is an indication of just how massive the issue is online. While pirates always welcome an abundance of links to juicy content, it’s no surprise that groups like the BPI are seeking more comprehensive and sustainable solutions.

Previously, it was hoped that the Digital Economy Bill would provide some relief, hopefully via government intervention and the imposition of a search engine Code of Practice. In the event, however, all pressure on search engines was removed from the legislation after a separate voluntary agreement was reached.

All parties agreed that the voluntary code should come into effect two weeks ago on June 1 so it seems likely that some effects should be noticeable in the near future. But the BPI says it’s still early days and there’s more work to be done.

“BPI has been working productively with search engines since the voluntary code was agreed to understand how search engines approach the problem, but also what changes can and have been made and how results can be improved,” the group explains.

“The first stage is to benchmark where we are and to assess the impact of the changes search engines have made so far. This will hopefully be completed soon, then we will have better information of the current picture and from that we hope to work together to continue to improve search for rights owners and consumers.”

With more takedown notices in the pipeline not yet publicly reported by Google, the BPI informs TF that it has now notified the search giant of 315 million links to illegal content.

“That’s an astonishing number. More than 1 in 10 of the entire world’s notices to Google come from BPI. This year alone, one in every three notices sent to Google from BPI is for independent record label repertoire,” BPI concludes.

While it’s clear that groups like BPI have developed systems to cope with the huge numbers of takedown notices required in today’s environment, it’s clear that few rightsholders are happy with the status quo. With that in mind, the fight will continue, until search engines are forced into compromise. Considering the implications, that could only appear on a very distant horizon.

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

The Pirate Bay Isn’t Affected By Adverse Court Rulings – Everyone Else Is

Post Syndicated from Andy original https://torrentfreak.com/the-pirate-bay-isnt-affected-by-adverse-court-rulings-everyone-else-is-170618/

For more than a decade The Pirate Bay has been the world’s most controversial site. Delivering huge quantities of copyrighted content to the masses, the platform is revered and reviled across the copyright spectrum.

Its reputation is one of a defiant Internet swashbuckler, but due to changes in how the site has been run in more recent times, its current philosophy is more difficult to gauge. What has never been in doubt, however, is the site’s original intent to be as provocative as possible.

Through endless publicity stunts, some real, some just for the ‘lulz’, The Pirate Bay managed to attract a massive audience, all while incurring the wrath of every major copyright holder in the world.

Make no mistake, they all queued up to strike back, but every subsequent rightsholder action was met by a Pirate Bay middle finger, two fingers, or chin flick, depending on the mood of the day. This only served to further delight the masses, who happily spread the word while keeping their torrents flowing.

This vicious circle of being targeted by the entertainment industries, mocking them, and then reaping the traffic benefits, developed into the cheapest long-term marketing campaign the Internet had ever seen. But nothing is ever truly for free and there have been consequences.

After taunting Hollywood and the music industry with its refusals to capitulate, endless legal action that the site would have ordinarily been forced to participate in largely took place without The Pirate Bay being present. It doesn’t take a law degree to work out what happened in each and every one of those cases, whatever complex route they took through the legal system. No defense, no win.

For example, the web-blocking phenomenon across the UK, Europe, Asia and Australia was driven by the site’s absolute resilience and although there would clearly have been other scapegoats had The Pirate Bay disappeared, the site was the ideal bogeyman the copyright lobby required to move forward.

Filing blocking lawsuits while bringing hosts, advertisers, and ISPs on board for anti-piracy initiatives were also made easier with the ‘evil’ Pirate Bay still online. Immune from every anti-piracy technique under the sun, the existence of the platform in the face of all onslaughts only strengthened the cases of those arguing for even more drastic measures.

Over a decade, this has meant a significant tightening of the sharing and streaming climate. Without any big legislative changes but plenty of case law against The Pirate Bay, web-blocking is now a walk in the park, ad hoc domain seizures are a fairly regular occurrence, and few companies want to host sharing sites. Advertisers and brands are also hesitant over where they place their ads. It’s a very different world to the one of 10 years ago.

While it would be wrong to attribute every tightening of the noose to the actions of The Pirate Bay, there’s little doubt that the site and its chaotic image played a huge role in where copyright enforcement is today. The platform set out to provoke and succeeded in every way possible, gaining supporters in their millions. It could also be argued it kicked a hole in a hornets’ nest, releasing the hell inside.

But perhaps the site’s most amazing achievement is the way it has managed to stay online, despite all the turmoil.

This week yet another ruling, this time from the powerful European Court of Justice, found that by offering links in the manner it does, The Pirate Bay and other sites are liable for communicating copyright works to the public. Of course, this prompted the usual swathe of articles claiming that this could be the final nail in the site’s coffin.

Wrong.

In common with every ruling, legal defeat, and legislative restriction put in place due to the site’s activities, this week’s decision from the ECJ will have zero effect on the Pirate Bay’s availability. For right or wrong, the site was breaking the law long before this ruling and will continue to do so until it decides otherwise.

What we have instead is a further tightened legal landscape that will have a lasting effect on everything BUT the site, including weaker torrent sites, Internet users, and user-uploaded content sites such as YouTube.

With The Pirate Bay carrying on regardless, that is nothing short of remarkable.

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

Digital painter rundown

Post Syndicated from Eevee original https://eev.ee/blog/2017/06/17/digital-painter-rundown/

Another patron post! IndustrialRobot asks:

You should totally write about drawing/image manipulation programs! (Inspired by https://eev.ee/blog/2015/05/31/text-editor-rundown/)

This is a little trickier than a text editor comparison — while most text editors are cross-platform, quite a few digital art programs are not. So I’m effectively unable to even try a decent chunk of the offerings. I’m also still a relatively new artist, and image editors are much harder to briefly compare than text editors…

Right, now that your expectations have been suitably lowered:

Krita

I do all of my digital art in Krita. It’s pretty alright.

Okay so Krita grew out of Calligra, which used to be KOffice, which was an office suite designed for KDE (a Linux desktop environment). I bring this up because KDE has a certain… reputation. With KDE, there are at least three completely different ways to do anything, each of those ways has ludicrous amounts of customization and settings, and somehow it still can’t do what you want.

Krita inherits this aesthetic by attempting to do literally everything. It has 17 different brush engines, more than 70 layer blending modes, seven color picker dockers, and an ungodly number of colorspaces. It’s clearly intended primarily for drawing, but it also supports animation and vector layers and a pretty decent spread of raster editing tools. I just right now discovered that it has Photoshop-like “layer styles” (e.g. drop shadow), after a year and a half of using it.

In fairness, Krita manages all of this stuff well enough, and (apparently!) it manages to stay out of your way if you’re not using it. In less fairness, they managed to break erasing with a Wacom tablet pen for three months?

I don’t want to rag on it too hard; it’s an impressive piece of work, and I enjoy using it! The emotion it evokes isn’t so much frustration as… mystified bewilderment.

I once filed a ticket suggesting the addition of a brush size palette — a panel showing a grid of fixed brush sizes that makes it easy to switch between known sizes with a tablet pen (and increases the chances that you’ll be able to get a brush back to the right size again). It’s a prominent feature of Paint Tool SAI and Clip Studio Paint, and while I’ve never used either of those myself, I’ve seen a good few artists swear by it.

The developer response was that I could emulate the behavior by creating brush presets. But that’s flat-out wrong: getting the same effect would require creating a ton of brush presets for every brush I have, plus giving them all distinct icons so the size is obvious at a glance. Even then, it would be much more tedious to use and fill my presets with junk.

And that sort of response is what’s so mysterious to me. I’ve never even been able to use this feature myself, but a year of amateur painting with Krita has convinced me that it would be pretty useful. But a developer didn’t see the use and suggested an incredibly tedious alternative that only half-solves the problem and creates new ones. Meanwhile, of the 28 existing dockable panels, a quarter of them are different ways to choose colors.

What is Krita trying to be, then? What does Krita think it is? Who precisely is the target audience? I have no idea.


Anyway, I enjoy drawing in Krita well enough. It ships with a respectable set of brushes, and there are plenty more floating around. It has canvas rotation, canvas mirroring, perspective guide tools, and other art goodies. It doesn’t colordrop on right click by default, which is arguably a grave sin (it shows a customizable radial menu instead), but that’s easy to rebind. It understands having a background color beneath a bottom transparent layer, which is very nice. You can also toggle any brush between painting and erasing with the press of a button, and that turns out to be very useful.

It doesn’t support infinite canvases, though it does offer a one-click button to extend the canvas in a given direction. I’ve never used it (and didn’t even know what it did until just now), but would totally use an infinite canvas.

I haven’t used the animation support too much, but it’s pretty nice to have. Granted, the only other animation software I’ve used is Aseprite, so I don’t have many points of reference here. It’s a relatively new addition, too, so I assume it’ll improve over time.

The one annoyance I remember with animation was really an interaction with a larger annoyance, which is: working with selections kind of sucks. You can’t drag a selection around with the selection tool; you have to switch to the move tool. That would be fine if you could at least drag the selection ring around with the selection tool, but you can’t do that either; dragging just creates a new selection.

If you want to copy a selection, you have to explicitly copy it to the clipboard and paste it, which creates a new layer. Ctrl-drag with the move tool doesn’t work. So then you have to merge that layer down, which I think is where the problem with animation comes in: a new layer is non-animated by default, meaning it effectively appears in any frame, so simply merging it down with merge it onto every single frame of the layer below. And you won’t even notice until you switch frames or play back the animation. Not ideal.

This is another thing that makes me wonder about Krita’s sense of identity. It has a lot of fancy general-purpose raster editing features that even GIMP is still struggling to implement, like high color depth support and non-destructive filters, yet something as basic as working with selections is clumsy. (In fairness, GIMP is a bit clumsy here too, but it has a consistent notion of “floating selection” that’s easy enough to work with.)

I don’t know how well Krita would work as a general-purpose raster editor; I’ve never tried to use it that way. I can’t think of anything obvious that’s missing. The only real gotcha is that some things you might expect to be tools, like smudge or clone, are just types of brush in Krita.

GIMP

Ah, GIMP — open source’s answer to Photoshop.

It’s very obviously intended for raster editing, and I’m pretty familiar with it after half a lifetime of only using Linux. I even wrote a little Scheme script for it ages ago to automate some simple edits to a couple hundred files, back before I was aware of ImageMagick. I don’t know what to say about it, specifically; it’s fairly powerful and does a wide variety of things.

In fact I’d say it’s almost frustratingly intended for raster editing. I used GIMP in my first attempts at digital painting, before I’d heard of Krita. It was okay, but so much of it felt clunky and awkward. Painting is split between a pencil tool, a paintbrush tool, and an airbrush tool; I don’t really know why. The default brushes are largely uninteresting. Instead of brush presets, there are tool presets that can be saved for any tool; it’s a neat idea, but doesn’t feel like a real substitute for brush presets.

Much of the same functionality as Krita is there, but it’s all somehow more clunky. I’m sure it’s possible to fiddle with the interface to get something friendlier for painting, but I never really figured out how.

And then there’s the surprising stuff that’s missing. There’s no canvas rotation, for example. There’s only one type of brush, and it just stamps the same pattern along a path. I don’t think it’s possible to smear or blend or pick up color while painting. The only way to change the brush size is via the very sensitive slider on the tool options panel, which I remember being a little annoying with a tablet pen. Also, you have to specifically enable tablet support? It’s not difficult or anything, but I have no idea why the default is to ignore tablet pressure and treat it like a regular mouse cursor.

As I mentioned above, there’s also no support for high color depth or non-destructive editing, which is honestly a little embarrassing. Those are the major things Serious Professionals™ have been asking for for ages, and GIMP has been trying to provide them, but it’s taking a very long time. The first signs of GEGL, a new library intended to provide these features, appeared in GIMP 2.6… in 2008. The last major release was in 2012. GIMP has been working on this new plumbing for almost as long as Krita’s entire development history. (To be fair, Krita has also raised almost €90,000 from three Kickstarters to fund its development; I don’t know that GIMP is funded at all.)

I don’t know what’s up with GIMP nowadays. It’s still under active development, but the exact status and roadmap are a little unclear. I still use it for some general-purpose editing, but I don’t see any reason to use it to draw.

I do know that canvas rotation will be in the next release, and there was some experimentation with embedding MyPaint’s brush engine (though when I tried it it was basically unusable), so maybe GIMP is interested in wooing artists? I guess we’ll see.

MyPaint

Ah, MyPaint. I gave it a try once. Once.

It’s a shame, really. It sounds pretty great: specifically built for drawing, has very powerful brushes, supports an infinite canvas, supports canvas rotation, has a simple UI that gets out of your way. Perfect.

Or so it seems. But in MyPaint’s eagerness to shed unnecessary raster editing tools, it forgot a few of the more useful ones. Like selections.

MyPaint has no notion of a selection, nor of copy/paste. If you want to move a head to align better to a body, for example, the sanctioned approach is to duplicate the layer, erase the head from the old layer, erase everything but the head from the new layer, then move the new layer.

I can’t find anything that resembles HSL adjustment, either. I guess the workaround for that is to create H/S/L layers and floodfill them with different colors until you get what you want.

I can’t work seriously without these basic editing tools. I could see myself doodling in MyPaint, but Krita works just as well for doodling as for serious painting, so I’ve never gone back to it.

Drawpile

Drawpile is the modern equivalent to OpenCanvas, I suppose? It lets multiple people draw on the same canvas simultaneously. (I would not recommend it as a general-purpose raster editor.)

It’s a little clunky in places — I sometimes have bugs where keyboard focus gets stuck in the chat, or my tablet cursor becomes invisible — but the collaborative part works surprisingly well. It’s not a brush powerhouse or anything, and I don’t think it allows textured brushes, but it supports tablet pressure and canvas rotation and locked alpha and selections and whatnot.

I’ve used it a couple times, and it’s worked well enough that… well, other people made pretty decent drawings with it? I’m not sure I’ve managed yet. And I wouldn’t use it single-player. Still, it’s fun.

Aseprite

Aseprite is for pixel art so it doesn’t really belong here at all. But it’s very good at that and I like it a lot.

That’s all

I can’t name any other serious contender that exists for Linux.

I’m dimly aware of a thing called “Photo Shop” that’s more intended for photos but functions as a passable painter. More artists seem to swear by Paint Tool SAI and Clip Studio Paint. Also there’s Paint.NET, but I have no idea how well it’s actually suited for painting.

And that’s it! That’s all I’ve got. Krita for drawing, GIMP for editing, Drawpile for collaborative doodling.

Konecny: Anaconda modularisation

Post Syndicated from jake original https://lwn.net/Articles/725623/rss

On his blog, Jiri Konecny writes about plans for modularizing Anaconda, which is the installer for Fedora and other Linux distributions. Anaconda is written in Python 3, but is all contained in one monolithic program.
The current Anaconda has one significant problem: all of the code is in one place–the monolith. It is more difficult to trace bugs and to a have a stable API. Implementing new features or modifying existing code in Anaconda is also more challenging. Modularisation should help with these things mainly because of isolation between the modules. It will be much easier to create tests for modules or to add new functionality.

Modularisation also opens up new possibilities to developers. They should be able to create a new user interface easily. Since developers can rely on the existing API documentation, it should not be necessary to browse the source code tree very often. Another benefit is that an addon is like another module, communicating with other modules, so it has the same capabilities. Developers can use the public API to write their addons in their favourite programming language which supports DBus.”

ISP Doesn’t Have to Expose Alleged BitTorrent Pirates, Finnish Court Rules

Post Syndicated from Ernesto original https://torrentfreak.com/isp-doesnt-have-to-expose-alleged-bittorrent-pirates-finnish-court-rules-170615/

finlandStarting three years ago, copyright holders began sending out thousands of settlement letters to alleged pirates in Finland, a practice often described as copyright trolling.

This week, however, the local Market Court has put the brakes on these efforts, with a rather significant ruling.

In the case in question, filmmakers requested the personal information of hundreds of alleged BitTorrent users from Internet provider DNA. However, after a careful review by a panel of seven judges, the Court decided not to grant the request.

The rightsholders provided a detailed log from a BitTorrent monitoring tool as evidence. While the Court didn’t doubt that the pirated material had been shared, it questioned how significant the infringements were.

The provided list of IP-addresses and timestamps don’t show how much data was shared, or for how long.

The evidence included an overview of the total number of users sharing the same file in a single BitTorrent swarm. However, the fact that thousands of people were sharing the same file says nothing about the significance of individual infringements.

“[T]he applicant has not claimed or provided any explanation that would indicate that the distribution of its work, by an IP address in the application, would have repeatedly occurred or for a longer period of time,” the Market Court writes.

The verdict, first reported by Iltalethi, refers to a recent case in the European Court of Justice, and stressed that the significance of an infringement must be weighed against the defendants’ privacy rights. In this case, the court decided that the evidence doesn’t warrant the exposure of the alleged pirates.

“Since the applicant has not provided sufficient proof of compliance with the conditions set out in Article 60a of the Copyright Act to adoption of an application, the application must be dismissed,” the Market Court writes.

The outcome is a clear victory for the accused BitTorrent users. Time will tell whether rightsholders will adapt their evidence to the ruling, or whether they will test their luck elsewhere. The current ruling can still be appealed.

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

Notes on open-sourcing abandoned code

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/06/notes-on-open-sourcing-abandoned-code.html

Some people want a law that compels companies to release their source code for “abandoned software”, in the name of cybersecurity, so that customers who bought it can continue to patch bugs long after the seller has stopped supporting the product. This is a bad policy, for a number of reasons.

Code is Speech

First of all, code is speech. That was the argument why Phil Zimmerman could print the source code to PGP in a book, ship it overseas, and then have somebody scan the code back into a computer. Compelled speech is a violation of free speech. That was one of the arguments in the Apple vs. FBI case, where the FBI demanded that Apple write code for them, compelling speech.

Compelling the opening of previously closed source is compelled speech.

There might still be legal arguments that get away with it. After all state already compels some speech, such as warning labels, where is services a narrow, legitimate government interest. So the courts may allow it. Also, like many free-speech issues (e.g. the legality of hate-speech), people may legitimately disagree with the courts about what “is” legal and what “should” be legal.

But here’s the thing. What rights “should” be protected changes depending on what side you are on. Whether something deserves the protection of “free speech” depends upon whether the speaker is “us” or the speaker is “them”. If it’s “them”, then you’ll find all sorts of reasons why their speech is a special case, and what it doesn’t deserve protection.

That’s what’s happening here. The legitimate government purpose of “product safety” looms large, the “code is speech” doesn’t, because they hate closed-source code, and hate Microsoft in particular. The open-source community has been strong on “code is speech” when it applies to them, but weak when it applies to closed-source.

Define abandoned

What, precisely, does ‘abandoned’ mean? Consider Windows 3.1. Microsoft hasn’t sold it for decades. Yet, it’s not precisely abandoned either, because they still sell modern versions of Windows. Being forced to show even 30 year old source code would give competitors a significant advantage in creating Windows-compatible code like WINE.

When code is truly abandoned, such as when the vendor has gone out of business, chances are good they don’t have the original source code anyway. Thus, in order for this policy to have any effect, you’d have to force vendors to give a third-party escrow service a copy of their code whenever they release a new version of their product.

All the source code

And that is surprisingly hard and costly. Most companies do not precisely know what source code their products are based upon. Yes, technically, all the code is in that ZIP file they gave to the escrow service, but it doesn’t build. Essential build steps are missing, so that source code won’t compile. It’s like the dependency hell that many open-source products experience, such as downloading and installing two different versions of Python at different times during the build. Except, it’s a hundred times worse.

Often times building closed-source requires itself an obscure version of a closed-source tool that itself has been abandoned by its original vendor. You often times can’t even define which is the source code. For example, engine control units (ECUs) are Matlab code that compiles down to C, which is then integrated with other C code, all of which is (using a special compiler) is translated to C. Unless you have all these closed source products, some of which are no longer sold, the source-code to the ECU will not help you in patch bugs.

For small startups running fast, such as off Kickstarter, forcing them to escrow code that actually builds would force upon them an undue burden, harming innovation.

Binary patch and reversing

Then there is the issue of why you need the source code in the first place. Here’s the deal with binary exploits like buffer-overflows: if you know enough to exploit it, you know enough to patch it. Just add some binary code onto the end of the function the program that verifies the input, then replace where the vulnerability happens to a jump instruction to the new code.

I know this is possible and fairly trivial because I’ve done it myself. Indeed, one of the reason Microsoft has signed kernel components is specifically because they got tired of me patching the live kernel this way (and, almost sued me for reverse engineering their code in violation of their EULA).

Given the aforementioned difficulties in building software, this would be the easier option for third parties trying to fix bugs. The only reason closed-source companies don’t do this already is because they need to fix their products permanently anyway, which involves checking in the change into their source control systems and rebuilding.

Conclusion

So what we see here is that there is no compelling benefit to forcing vendors to release code for “abandoned” products, while at the same time, there are significant costs involved, not the least of which is a violation of the principle that “code is speech”.

It doesn’t exist as a serious proposal. It only exists as a way to support open-source advocacy and security advocacy. Both would gladly stomp on your rights and drive up costs in order to achieve their higher moral goal.


Bonus: so let’s say you decide that “Window XP” has been abandoned, which is exactly the intent of proponents. You think what would happen is that we (the open-source community) would then be able to continue to support WinXP and patch bugs.

But what we’d see instead is a lot more copies of WinXP floating around, with vulnerabilities, as people decided to use it instead of paying hundreds of dollars for a new Windows 10 license.

Indeed, part of the reason for Micrsoft abandoning WinXP is because it’s riddled with flaws that can’t practically be fixed, whereas the new features of Win10 fundamentally fixes them. Getting rid of SMBv1 is just one of many examples.

Manage Instances at Scale without SSH Access Using EC2 Run Command

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/manage-instances-at-scale-without-ssh-access-using-ec2-run-command/

The guest post below, written by Ananth Vaidyanathan (Senior Product Manager for EC2 Systems Manager) and Rich Urmston (Senior Director of Cloud Architecture at Pegasystems) shows you how to use EC2 Run Command to manage a large collection of EC2 instances without having to resort to SSH.

Jeff;


Enterprises often have several managed environments and thousands of Amazon EC2 instances. It’s important to manage systems securely, without the headaches of Secure Shell (SSH). Run Command, part of Amazon EC2 Systems Manager, allows you to run remote commands on instances (or groups of instances using tags) in a controlled and auditable manner. It’s been a nice added productivity boost for Pega Cloud operations, which rely daily on Run Command services.

You can control Run Command access through standard IAM roles and policies, define documents to take input parameters, control the S3 bucket used to return command output. You can also share your documents with other AWS accounts, or with the public. All in all, Run Command provides a nice set of remote management features.

Better than SSH
Here’s why Run Command is a better option than SSH and why Pegasystems has adopted it as their primary remote management tool:

Run Command Takes Less Time –  Securely connecting to an instance requires a few steps e.g. jumpboxes to connect to or IP addresses to whitelist etc. With Run Command, cloud ops engineers can invoke commands directly from their laptop, and never have to find keys or even instance IDs. Instead, system security relies on AWS auth, IAM roles and policies.

Run Command Operations are Fully Audited – With SSH, there is no real control over what they can do, nor is there an audit trail. With Run Command, every invoked operation is audited in CloudTrail, including information on the invoking user, instances on which command was run, parameters, and operation status. You have full control and ability to restrict what functions engineers can perform on a system.

Run Command has no SSH keys to Manage – Run Command leverages standard AWS credentials, API keys, and IAM policies. Through integration with a corporate auth system, engineers can interact with systems based on their corporate credentials and identity.

Run Command can Manage Multiple Systems at the Same Time – Simple tasks such as looking at the status of a Linux service or retrieving a log file across a fleet of managed instances is cumbersome using SSH. Run Command allows you to specify a list of instances by IDs or tags, and invokes your command, in parallel, across the specified fleet. This provides great leverage when troubleshooting or managing more than the smallest Pega clusters.

Run Command Makes Automating Complex Tasks Easier – Standardizing operational tasks requires detailed procedure documents or scripts describing the exact commands. Managing or deploying these scripts across the fleet is cumbersome. Run Command documents provide an easy way to encapsulate complex functions, and handle document management and access controls. When combined with AWS Lambda, documents provide a powerful automation platform to handle any complex task.

Example – Restarting a Docker Container
Here is an example of a simple document used to restart a Docker container. It takes one parameter; the name of the Docker container to restart. It uses the AWS-RunShellScript method to invoke the command. The output is collected automatically by the service and returned to the caller. For an example of the latest document schema, see Creating Systems Manager Documents.

{
  "schemaVersion":"1.2",
  "description":"Restart the specified docker container.",
  "parameters":{
    "param":{
      "type":"String",
      "description":"(Required) name of the container to restart.",
      "maxChars":1024
    }
  },
  "runtimeConfig":{
    "aws:runShellScript":{
      "properties":[
        {
          "id":"0.aws:runShellScript",
          "runCommand":[
            "docker restart {{param}}"
          ]
        }
      ]
    }
  }
}

Putting Run Command into practice at Pegasystems
The Pegasystems provisioning system sits on AWS CloudFormation, which is used to deploy and update Pega Cloud resources. Layered on top of it is the Pega Provisioning Engine, a serverless, Lambda-based service that manages a library of CloudFormation templates and Ansible playbooks.

A Configuration Management Database (CMDB) tracks all the configurations details and history of every deployment and update, and lays out its data using a hierarchical directory naming convention. The following diagram shows how the various systems are integrated:

For cloud system management, Pega operations uses a command line version called cuttysh and a graphical version based on the Pega 7 platform, called the Pega Operations Portal. Both tools allow you to browse the CMDB of deployed environments, view configuration settings, and interact with deployed EC2 instances through Run Command.

CLI Walkthrough
Here is a CLI walkthrough for looking into a customer deployment and interacting with instances using Run Command.

Launching the cuttysh tool brings you to the root of the CMDB and a list of the provisioned customers:

% cuttysh
d CUSTA
d CUSTB
d CUSTC
d CUSTD

You interact with the CMDB using standard Linux shell commands, such as cd, ls, cat, and grep. Items prefixed with s are services that have viewable properties. Items prefixed with d are navigable subdirectories in the CMDB hierarchy.

In this example, change directories into customer CUSTB’s portion of the CMDB hierarchy, and then further into a provisioned Pega environment called env1, under the Dev network. The tool displays the artifacts that are provisioned for that environment. These entries map to provisioned CloudFormation templates.

> cd CUSTB
/ROOT/CUSTB/us-east-1 > cd DEV/env1

The ls –l command shows the version of the provisioned resources. These version numbers map back to source control–managed artifacts for the CloudFormation, Ansible, and other components that compose a version of the Pega Cloud.

/ROOT/CUSTB/us-east-1/DEV/env1 > ls -l
s 1.2.5 RDSDatabase 
s 1.2.5 PegaAppTier 
s 7.2.1 Pega7 

Now, use Run Command to interact with the deployed environments. To do this, use the attach command and specify the service with which to interact. In the following example, you attach to the Pega Web Tier. Using the information in the CMDB and instance tags, the CLI finds the corresponding EC2 instances and displays some basic information about them. This deployment has three instances.

/ROOT/CUSTB/us-east-1/DEV/env1 > attach PegaWebTier
 # ID         State  Public Ip    Private Ip  Launch Time
 0 i-0cf0e84 running 52.63.216.42 10.96.15.70 2017-01-16 
 1 i-0043c1d running 53.47.191.22 10.96.15.43 2017-01-16 
 2 i-09b879e running 55.93.118.27 10.96.15.19 2017-01-16 

From here, you can use the run command to invoke Run Command documents. In the following example, you run the docker-ps document against instance 0 (the first one on the list). EC2 executes the command and returns the output to the CLI, which in turn shows it.

/ROOT/CUSTB/us-east-1/DEV/env1 > run 0 docker-ps
. . 
CONTAINER ID IMAGE             CREATED      STATUS        NAMES
2f187cc38c1  pega-7.2         10 weeks ago  Up 8 weeks    pega-web

Using the same command and some of the other documents that have been defined, you can restart a Docker container or even pull back the contents of a file to your local system. When you get a file, Run Command also leaves a copy in an S3 bucket in case you want to pass the link along to a colleague.

/ROOT/CUSTB/us-east-1/DEV/env1 > run 0 docker-restart pega-web
..
pega-web

/ROOT/CUSTB/us-east-1/DEV/env1 > run 0 get-file /var/log/cfn-init-cmd.log
. . . . . 
get-file

Data has been copied locally to: /tmp/get-file/i-0563c9e/data
Data is also available in S3 at: s3://my-bucket/CUSTB/cuttysh/get-file/data

Now, leverage the Run Command ability to do more than one thing at a time. In the following example, you attach to a deployment with three running instances and want to see the uptime for each instance. Using the par (parallel) option for run, the CLI tells Run Command to execute the uptime document on all instances in parallel.

/ROOT/CUSTB/us-east-1/DEV/env1 > run par uptime
 …
Output for: i-006bdc991385c33
 20:39:12 up 15 days, 3:54, 0 users, load average: 0.42, 0.32, 0.30

Output for: i-09390dbff062618
 20:39:12 up 15 days, 3:54, 0 users, load average: 0.08, 0.19, 0.22

Output for: i-08367d0114c94f1
 20:39:12 up 15 days, 3:54, 0 users, load average: 0.36, 0.40, 0.40

Commands are complete.
/ROOT/PEGACLOUD/CUSTB/us-east-1/PROD/prod1 > 

Summary
Run Command improves productivity by giving you faster access to systems and the ability to run operations across a group of instances. Pega Cloud operations has integrated Run Command with other operational tools to provide a clean and secure method for managing systems. This greatly improves operational efficiency, and gives greater control over who can do what in managed deployments. The Pega continual improvement process regularly assesses why operators need access, and turns those operations into new Run Command documents to be added to the library. In fact, their long-term goal is to stop deploying cloud systems with SSH enabled.

If you have any questions or suggestions, please leave a comment for us!

— Ananth and Rich