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Running ActiveMQ in a Hybrid Cloud Environment with Amazon MQ

Post Syndicated from Tara Van Unen original https://aws.amazon.com/blogs/compute/running-activemq-in-a-hybrid-cloud-environment-with-amazon-mq/

This post courtesy of Greg Share, AWS Solutions Architect

Many organizations, particularly enterprises, rely on message brokers to connect and coordinate different systems. Message brokers enable distributed applications to communicate with one another, serving as the technological backbone for their IT environment, and ultimately their business services. Applications depend on messaging to work.

In many cases, those organizations have started to build new or “lift and shift” applications to AWS. In some cases, there are applications, such as mainframe systems, too costly to migrate. In these scenarios, those on-premises applications still need to interact with cloud-based components.

Amazon MQ is a managed message broker service for ActiveMQ that enables organizations to send messages between applications in the cloud and on-premises to enable hybrid environments and application modernization. For example, you can invoke AWS Lambda from queues and topics managed by Amazon MQ brokers to integrate legacy systems with serverless architectures. ActiveMQ is an open-source message broker written in Java that is packaged with clients in multiple languages, Java Message Server (JMS) client being one example.

This post shows you can use Amazon MQ to integrate on-premises and cloud environments using the network of brokers feature of ActiveMQ. It provides configuration parameters for a one-way duplex connection for the flow of messages from an on-premises ActiveMQ message broker to Amazon MQ.

ActiveMQ and the network of brokers

First, look at queues within ActiveMQ and then at the network of brokers as a mechanism to distribute messages.

The network of brokers behaves differently from models such as physical networks. The key consideration is that the production (sending) of a message is disconnected from the consumption of that message. Think of the delivery of a parcel: The parcel is sent by the supplier (producer) to the end customer (consumer). The path it took to get there is of little concern to the customer, as long as it receives the package.

The same logic can be applied to the network of brokers. Here’s how you build the flow from a simple message to a queue and build toward a network of brokers. Before you look at setting up a hybrid connection, I discuss how a broker processes messages in a simple scenario.

When a message is sent from a producer to a queue on a broker, the following steps occur:

  1. A message is sent to a queue from the producer.
  2. The broker persists this in its store or journal.
  3. At this point, an acknowledgement (ACK) is sent to the producer from the broker.

When a consumer looks to consume the message from that same queue, the following steps occur:

  1. The message listener (consumer) calls the broker, which creates a subscription to the queue.
  2. Messages are fetched from the message store and sent to the consumer.
  3. The consumer acknowledges that the message has been received before processing it.
  4. Upon receiving the ACK, the broker sets the message as having been consumed. By default, this deletes it from the queue.
    • You can set the consumer to ACK after processing by setting up transaction management or handle it manually using Session.CLIENT_ACKNOWLEDGE.

Static propagation

I now introduce the concept of static propagation with the network of brokers as the mechanism for message transfer from on-premises brokers to Amazon MQ.  Static propagation refers to message propagation that occurs in the absence of subscription information. In this case, the objective is to transfer messages arriving at your selected on-premises broker to the Amazon MQ broker for consumption within the cloud environment.

After you configure static propagation with a network of brokers, the following occurs:

  1. The on-premises broker receives a message from a producer for a specific queue.
  2. The on-premises broker sends (statically propagates) the message to the Amazon MQ broker.
  3. The Amazon MQ broker sends an acknowledgement to the on-premises broker, which marks the message as having been consumed.
  4. Amazon MQ holds the message in its queue ready for consumption.
  5. A consumer connects to Amazon MQ broker, subscribes to the queue in which the message resides, and receives the message.
  6. Amazon MQ broker marks the message as having been consumed.

Getting started

The first step is creating an Amazon MQ broker.

  1. Sign in to the Amazon MQ console and launch a new Amazon MQ broker.
  2. Name your broker and choose Next step.
  3. For Broker instance type, choose your instance size:
    mq.t2.micro
    mq.m4.large
  4. For Deployment mode, enter one of the following:
    Single-instance broker for development and test implementations (recommended)
    Active/standby broker for high availability in production environments
  5. Scroll down and enter your user name and password.
  6. Expand Advanced Settings.
  7. For VPC, Subnet, and Security Group, pick the values for the resources in which your broker will reside.
  8. For Public Accessibility, choose Yes, as connectivity is internet-based. Another option would be to use private connectivity between your on-premises network and the VPC, an example being an AWS Direct Connect or VPN connection. In that case, you could set Public Accessibility to No.
  9. For Maintenance, leave the default value, No preference.
  10. Choose Create Broker. Wait several minutes for the broker to be created.

After creation is complete, you see your broker listed.

For connectivity to work, you must configure the security group where Amazon MQ resides. For this post, I focus on the OpenWire protocol.

For Openwire connectivity, allow port 61617 access for Amazon MQ from your on-premises ActiveMQ broker source IP address. For alternate protocols, see the Amazon MQ broker configuration information for the ports required:

OpenWire – ssl://xxxxxxx.xxx.com:61617
AMQP – amqp+ssl:// xxxxxxx.xxx.com:5671
STOMP – stomp+ssl:// xxxxxxx.xxx.com:61614
MQTT – mqtt+ssl:// xxxxxxx.xxx.com:8883
WSS – wss:// xxxxxxx.xxx.com:61619

Configuring the network of brokers

Configuring the network of brokers with static propagation occurs on the on-premises broker by applying changes to the following file:
<activemq install directory>/conf activemq.xml

Network connector

This is the first configuration item required to enable a network of brokers. It is only required on the on-premises broker, which initiates and creates the connection with Amazon MQ. This connection, after it’s established, enables the flow of messages in either direction between the on-premises broker and Amazon MQ. The focus of this post is the uni-directional flow of messages from the on-premises broker to Amazon MQ.

The default activemq.xml file does not include the network connector configuration. Add this with the networkConnector element. In this scenario, edit the on-premises broker activemq.xml file to include the following information between <systemUsage> and <transportConnectors>:

<networkConnectors>
             <networkConnector 
                name="Q:source broker name->target broker name"
                duplex="false" 
                uri="static:(ssl:// aws mq endpoint:61617)" 
                userName="username"
                password="password" 
                networkTTL="2" 
                dynamicOnly="false">
                <staticallyIncludedDestinations>
                    <queue physicalName="queuename"/>
                </staticallyIncludedDestinations> 
                <excludedDestinations>
                      <queue physicalName=">" />
                </excludedDestinations>
             </networkConnector> 
     <networkConnectors>

The highlighted components are the most important elements when configuring your on-premises broker.

  • name – Name of the network bridge. In this case, it specifies two things:
    • That this connection relates to an ActiveMQ queue (Q) as opposed to a topic (T), for reference purposes.
    • The source broker and target broker.
  • duplex –Setting this to false ensures that messages traverse uni-directionally from the on-premises broker to Amazon MQ.
  • uri –Specifies the remote endpoint to which to connect for message transfer. In this case, it is an Openwire endpoint on your Amazon MQ broker. This information could be obtained from the Amazon MQ console or via the API.
  • username and password – The same username and password configured when creating the Amazon MQ broker, and used to access the Amazon MQ ActiveMQ console.
  • networkTTL – Number of brokers in the network through which messages and subscriptions can pass. Leave this setting at the current value, if it is already included in your broker connection.
  • staticallyIncludedDestinations > queue physicalName – The destination ActiveMQ queue for which messages are destined. This is the queue that is propagated from the on-premises broker to the Amazon MQ broker for message consumption.

After the network connector is configured, you must restart the ActiveMQ service on the on-premises broker for the changes to be applied.

Verify the configuration

There are a number of places within the ActiveMQ console of your on-premises and Amazon MQ brokers to browse to verify that the configuration is correct and the connection has been established.

On-premises broker

Launch the ActiveMQ console of your on-premises broker and navigate to Network. You should see an active network bridge similar to the following:

This identifies that the connection between your on-premises broker and your Amazon MQ broker is up and running.

Now navigate to Connections and scroll to the bottom of the page. Under the Network Connectors subsection, you should see a connector labeled with the name: value that you provided within the ActiveMQ.xml configuration file. You should see an entry similar to:

Amazon MQ broker

Launch the ActiveMQ console of your Amazon MQ broker and navigate to Connections. Scroll to the Connections openwire subsection and you should see a connection specified that references the name: value that you provided within the ActiveMQ.xml configuration file. You should see an entry similar to:

If you configured the uri: for AMQP, STOMP, MQTT, or WSS as opposed to Openwire, you would see this connection under the corresponding section of the Connections page.

Testing your message flow

The setup described outlines a way for messages produced on premises to be propagated to the cloud for consumption in the cloud. This section provides steps on verifying the message flow.

Verify that the queue has been created

After you specify this queue name as staticallyIncludedDestinations > queue physicalName: and your ActiveMQ service starts, you see the following on your on-premises ActiveMQ console Queues page.

As you can see, no messages have been sent but you have one consumer listed. If you then choose Active Consumers under the Views column, you see Active Consumers for TestingQ.

This is telling you that your Amazon MQ broker is a consumer of your on-premises broker for the testing queue.

Produce and send a message to the on-premises broker

Now, produce a message on an on-premises producer and send it to your on-premises broker to a queue named TestingQ. If you navigate back to the queues page of your on-premises ActiveMQ console, you see that the messages enqueued and messages dequeued column count for your TestingQ queue have changed:

What this means is that the message originating from the on-premises producer has traversed the on-premises broker and propagated immediately to the Amazon MQ broker. At this point, the message is no longer available for consumption from the on-premises broker.

If you access the ActiveMQ console of your Amazon MQ broker and navigate to the Queues page, you see the following for the TestingQ queue:

This means that the message originally sent to your on-premises broker has traversed the network of brokers unidirectional network bridge, and is ready to be consumed from your Amazon MQ broker. The indicator is the Number of Pending Messages column.

Consume the message from an Amazon MQ broker

Connect to the Amazon MQ TestingQ queue from a consumer within the AWS Cloud environment for message consumption. Log on to the ActiveMQ console of your Amazon MQ broker and navigate to the Queue page:

As you can see, the Number of Pending Messages column figure has changed to 0 as that message has been consumed.

This diagram outlines the message lifecycle from the on-premises producer to the on-premises broker, traversing the hybrid connection between the on-premises broker and Amazon MQ, and finally consumption within the AWS Cloud.

Conclusion

This post focused on an ActiveMQ-specific scenario for transferring messages within an ActiveMQ queue from an on-premises broker to Amazon MQ.

For other on-premises brokers, such as IBM MQ, another approach would be to run ActiveMQ on-premises broker and use JMS bridging to IBM MQ, while using the approach in this post to forward to Amazon MQ. Yet another approach would be to use Apache Camel for more sophisticated routing.

I hope that you have found this example of hybrid messaging between an on-premises environment in the AWS Cloud to be useful. Many customers are already using on-premises ActiveMQ brokers, and this is a great use case to enable hybrid cloud scenarios.

To learn more, see the Amazon MQ website and Developer Guide. You can try Amazon MQ for free with the AWS Free Tier, which includes up to 750 hours of a single-instance mq.t2.micro broker and up to 1 GB of storage per month for one year.

 

Flight Sim Company Embeds Malware to Steal Pirates’ Passwords

Post Syndicated from Andy original https://torrentfreak.com/flight-sim-company-embeds-malware-to-steal-pirates-passwords-180219/

Anti-piracy systems and DRM come in all shapes and sizes, none of them particularly popular, but one deployed by flight sim company FlightSimLabs is likely to go down in history as one of the most outrageous.

It all started yesterday on Reddit when Flight Sim user ‘crankyrecursion’ reported a little extra something in his download of FlightSimLabs’ A320X module.

“Using file ‘FSLabs_A320X_P3D_v2.0.1.231.exe’ there seems to be a file called ‘test.exe’ included,” crankyrecursion wrote.

“This .exe file is from http://securityxploded.com and is touted as a ‘Chrome Password Dump’ tool, which seems to work – particularly as the installer would typically run with Administrative rights (UAC prompts) on Windows Vista and above. Can anyone shed light on why this tool is included in a supposedly trusted installer?”

The existence of a Chrome password dumping tool is certainly cause for alarm, especially if the software had been obtained from a less-than-official source, such as a torrent or similar site, given the potential for third-party pollution.

However, with the possibility of a nefarious third-party dumping something nasty in a pirate release still lurking on the horizon, things took an unexpected turn. FlightSimLabs chief Lefteris Kalamaras made a statement basically admitting that his company was behind the malware installation.

“We were made aware there is a Reddit thread started tonight regarding our latest installer and how a tool is included in it, that indiscriminately dumps Chrome passwords. That is not correct information – in fact, the Reddit thread was posted by a person who is not our customer and has somehow obtained our installer without purchasing,” Kalamaras wrote.

“[T]here are no tools used to reveal any sensitive information of any customer who has legitimately purchased our products. We all realize that you put a lot of trust in our products and this would be contrary to what we believe.

“There is a specific method used against specific serial numbers that have been identified as pirate copies and have been making the rounds on ThePirateBay, RuTracker and other such malicious sites,” he added.

In a nutshell, FlightSimLabs installed a password dumper onto ALL users’ machines, whether they were pirates or not, but then only activated the password-stealing module when it determined that specific ‘pirate’ serial numbers had been used which matched those on FlightSimLabs’ servers.

“Test.exe is part of the DRM and is only targeted against specific pirate copies of copyrighted software obtained illegally. That program is only extracted temporarily and is never under any circumstances used in legitimate copies of the product,” Kalamaras added.

That didn’t impress Luke Gorman, who published an analysis slamming the flight sim company for knowingly installing password-stealing malware on users machines, even those who purchased the title legitimately.

Password stealer in action (credit: Luke Gorman)

Making matters even worse, the FlightSimLabs chief went on to say that information being obtained from pirates’ machines in this manner is likely to be used in court or other legal processes.

“This method has already successfully provided information that we’re going to use in our ongoing legal battles against such criminals,” Kalamaras revealed.

While the use of the extracted passwords and usernames elsewhere will remain to be seen, it appears that FlightSimLabs has had a change of heart. With immediate effect, the company is pointing customers to a new installer that doesn’t include code for stealing their most sensitive data.

“I want to reiterate and reaffirm that we as a company and as flight simmers would never do anything to knowingly violate the trust that you have placed in us by not only buying our products but supporting them and FlightSimLabs,” Kalamaras said in an update.

“While the majority of our customers understand that the fight against piracy is a difficult and ongoing battle that sometimes requires drastic measures, we realize that a few of you were uncomfortable with this particular method which might be considered to be a bit heavy handed on our part. It is for this reason we have uploaded an updated installer that does not include the DRM check file in question.”

To be continued………

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Epic Games Uses Private Investigators to Locate Cheaters

Post Syndicated from Ernesto original https://torrentfreak.com/epic-games-uses-private-investigators-to-locate-cheaters-180218/

Last fall, Epic Games released Fortnite’s free-to-play “Battle Royale” game mode for the PC and other platforms, generating massive interest among gamers.

This also included thousands of cheaters, many of whom were subsequently banned. Epic Games then went a step further by taking several cheaters to court for copyright infringement.

In the months that have passed several cases have been settled with undisclosed terms, but it appears that not all defendants are easy to track down. In at least two cases, Epic had to retain the services of private investigators to locate their targets.

In a case filed in North Carolina, the games company was unable to serve the defendant (now identified as B.B) so they called in the help of Klatt Investigations, with success.

“[A]fter having previously engaged two other process servers that were unable to locate and successfully serve B.B., Epic engaged Klatt Investigations, a Canadian firm that provides various services related to the private service of process in civil matters.

“In this case, we engaged Klatt Investigations to locate and effect service of process by personal service on Defendant,” Epic informs the court.

As Epic Games didn’t know the age of the defendant beforehand they chose to approach the person as a minor, which turned out to be a wise choice. The alleged cheater indeed appears to be a minor, so both the Defendant and Defendant’s mother were served.

Based on this new information, Epic Games asked the court to redact any court documents that reveal personal information of the defendant, which includes his or her full name.

Epic’s request to seal

This is not the first time Epic Games has used a private investigator to locate a defendant. It hired S&H Investigative Services in another widely reported case, where the defendant also turned out to be a minor.

In that case, the mother of the alleged cheater wrote a letter to the court in her son’s defense, but after that, things went quiet.

This lack of response prompted Epic Games to ask the court to enter a default in this case, which means that the defendant risks a default judgment for copyright infringement.

Epic’s declaration for the motion to seal the personal details of minor B.B. is available here (pdf). The request to enter a default in the separate C.R case can be found (here pdf).

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Game Companies Oppose DMCA Exemption for ‘Abandoned’ Online Games

Post Syndicated from Ernesto original https://torrentfreak.com/game-companies-oppose-dmca-exemption-for-abandoned-online-games-180217/

There are a lot of things people are not allowed to do under US copyright law, but perhaps just as importantly there are exemptions.

The U.S. Copyright Office is currently considering whether or not to loosen the DMCA’s anti-circumvention provisions, which prevent the public from ‘tinkering’ with DRM-protected content and devices.

These provisions are renewed every three years after the Office hears various arguments from the public. One of the major topics on the agenda this year is the preservation of abandoned games.

The Copyright Office previously included game preservation exemptions to keep these games accessible. This means that libraries, archives, and museums can use emulators and other circumvention tools to make old classics playable.

Late last year several gaming fans including the Museum of Art and Digital Entertainment (the MADE), a nonprofit organization operating in California, argued for an expansion of this exemption to also cover online games. This includes games in the widely popular multiplayer genre, which require a connection to an online server.

“Although the Current Exemption does not cover it, preservation of online video games is now critical,” MADE wrote in its comment to the Copyright Office.

“Online games have become ubiquitous and are only growing in popularity. For example, an estimated fifty-three percent of gamers play multiplayer games at least once a week, and spend, on average, six hours a week playing with others online.”

This week, the Entertainment Software Association (ESA), which acts on behalf of prominent members including Electonic Arts, Nintendo and Ubisoft, opposed the request.

While they are fine with the current game-preservation exemption, expanding it to online games goes too far, they say. This would allow outsiders to recreate online game environments using server code that was never published in public.

It would also allow a broad category of “affiliates” to help with this which, according to the ESA, could include members of the public

“The proponents characterize these as ‘slight modifications’ to the existing exemption. However they are nothing of the sort. The proponents request permission to engage in forms of circumvention that will enable the complete recreation of a hosted video game-service environment and make the video game available for play by a public audience.”

“Worse yet, proponents seek permission to deputize a legion of ‘affiliates’ to assist in their activities,” ESA adds.

The proposed changes would enable and facilitate infringing use, the game companies warn. They fear that outsiders such as MADE will replicate the game servers and allow the public to play these abandoned games, something games companies would generally charge for. This could be seen as direct competition.

MADE, for example, already charges the public to access its museum so they can play games. This can be seen as commercial use under the DMCA, ESA points out.

“Public performance and display of online games within a museum likewise is a commercial use within the meaning of Section 107. MADE charges an admission fee – ‘$10 to play games all day’.

“Under the authority summarized above, public performance and display of copyrighted works to generate entrance fee revenue is a commercial use, even if undertaken by a nonprofit museum,” the ESA adds.

The ESA also stresses that their members already make efforts to revive older games themselves. There is a vibrant and growing market for “retro” games, which games companies are motivated to serve, they say.

The games companies, therefore, urge the Copyright Office to keep the status quo and reject any exemptions for online games.

“In sum, expansion of the video game preservation exemption as contemplated by Class 8 is not a ‘modest’ proposal. Eliminating the important limitations that the Register provided when adopting the current exemption risks the possibility of wide-scale infringement and substantial market harm,” they write.

The Copyright Office will take all arguments into consideration before it makes a final decision. It’s clear that the wishes of game preservation advocates, such as MADE, are hard to unite with the interests of the game companies, so one side will clearly be disappointed with the outcome.

A copy of ESA’s submissionavailablelble here (pdf).

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Embedding a Tweet Can be Copyright Infringement, Court Rules

Post Syndicated from Ernesto original https://torrentfreak.com/embedding-a-tweet-can-be-copyright-infringement-court-rules-180216/

Nowadays it’s fairly common for blogs and news sites to embed content posted by third parties, ranging from YouTube videos to tweets.

Although these publications don’t host the content themselves, they can be held liable for copyright infringement, a New York federal court has ruled.

The case in question was filed by Justin Goldman whose photo of Tom Brady went viral after he posted it on Snapchat. After being reposted on Reddit, it also made its way onto Twitter from where various news organizations picked it up.

Several of these news sites reported on the photo by embedding tweets from others. However, since Goldman never gave permission to display his photo, he went on to sue the likes of Breitbart, Time, Vox and Yahoo, for copyright infringement.

In their defense, the news organizations argued that they did nothing wrong as no content was hosted on their servers. They referred to the so-called “server test” that was applied in several related cases in the past, which determined that liability rests on the party that hosts the infringing content.

In an order that was just issued, US District Court Judge Katherine Forrest disagrees. She rejects the “server test” argument and rules that the news organizations are liable.

“[W]hen defendants caused the embedded Tweets to appear on their websites, their actions violated plaintiff’s exclusive display right; the fact that the image was hosted on a server owned and operated by an unrelated third party (Twitter) does not shield them from this result,” Judge Forrest writes.

Judge Forrest argues that the server test was established in the ‘Perfect 10 v. Amazon’ case, which dealt with the ‘distribution’ of content. This case is about ‘displaying’ an infringing work instead, an area where the jurisprudence is not as clear.

“The Court agrees with plaintiff. The plain language of the Copyright Act, the legislative history undergirding its enactment, and subsequent Supreme Court jurisprudence provide no basis for a rule that allows the physical location or possession of an image to determine who may or may not have “displayed” a work within the meaning of the Copyright Act.”

As a result, summary judgment was granted in favor of Goldman.

Rightsholders, including Getty Images which supported Goldman, are happy with the result. However, not everyone is pleased. The Electronic Frontier Foundation (EFF) says that if the current verdict stands it will put millions of regular Internet users at risk.

“Rejecting years of settled precedent, a federal court in New York has ruled that you could infringe copyright simply by embedding a tweet in a web page,” EFF comments.

“Even worse, the logic of the ruling applies to all in-line linking, not just embedding tweets. If adopted by other courts, this legally and technically misguided decision would threaten millions of ordinary Internet users with infringement liability.”

Given what’s at stake, it’s likely that the news organization will appeal this week’s order.

Interestingly, earlier this week a California district court dismissed Playboy’s copyright infringement complaint against Boing Boing, which embedded a YouTube video that contained infringing content.

A copy of Judge Forrest’s opinion can be found here (pdf).

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Pirates Crack Microsoft’s UWP Protection, Five Layers of DRM Defeated

Post Syndicated from Andy original https://torrentfreak.com/pirates-crack-microsofts-uwp-protection-five-layers-of-drm-defeated-180215/

As the image on the right shows, Microsoft’s Universal Windows Platform (UWP) is a system that enables software developers to create applications that can run across many devices.

“The Universal Windows Platform (UWP) is the app platform for Windows 10. You can develop apps for UWP with just one API set, one app package, and one store to reach all Windows 10 devices – PC, tablet, phone, Xbox, HoloLens, Surface Hub and more,” Microsoft explains.

While the benefits of such a system are immediately apparent, critics say that UWP gives Microsoft an awful lot of control, not least since UWP software must be distributed via the Windows Store with Microsoft taking a cut.

Or that was the plan, at least.

Last evening it became clear that the UWP system, previously believed to be uncrackable, had fallen to pirates. After being released on October 31, 2017, the somewhat underwhelming Zoo Tycoon Ultimate Animal Collection became the first victim at the hands of popular scene group, CODEX.

“This is the first scene release of a UWP (Universal Windows Platform) game. Therefore we would like to point out that it will of course only work on Windows 10. This particular game requires Windows 10 version 1607 or newer,” the group said in its release notes.

CODEX release notes

CODEX says it’s important that the game isn’t allowed to communicate with the Internet so the group advises users to block the game’s executable in their firewall.

While that’s not a particularly unusual instruction, CODEX did reveal that various layers of protection had to be bypassed to make the game work. They’re listed by the group as MSStore, UWP, EAppX, XBLive, and Arxan, the latter being an anti-tamper system.

“It’s the equivalent of Denuvo (without the DRM License part),” cracker Voksi previously explained. “It’s still bloats the executable with useless virtual machines that only slow down your game.”

Arxan features

Arxan’s marketing comes off as extremely confident but may need amending in light of yesterday’s developments.

“Arxan uses code protection against reverse-engineering, key and data protection to secure servers and fortification of game logic to stop the bad guys from tampering. Sorry hackers, game over,” the company’s marketing reads.

What is unclear at this stage is whether Zoo Tycoon Ultimate Animal Collection represents a typical UWP release or if some particular flaw allowed CODEX to take it apart. The possibility of additional releases is certainly a tantalizing one for pirates but how long they will have to wait is unknown.

Whatever the outcome, Arxan calling “game over” is perhaps a little premature under the circumstances but in this continuing arms race, they probably have another version of their anti-tamper tech up their sleeves…..

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How to Patch Linux Workloads on AWS

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

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

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

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

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

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

What you should know first

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

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

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

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

Diagram showing how to structure your VPC

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

Step 1: Launch an Amazon EC2 Linux instance

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

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

A. Create an IAM role for Systems Manager

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

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

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

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

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

B. Launch your Amazon EC2 instance

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

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

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

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

C. Add tags

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

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

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

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

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

Step 2: Configure Systems Manager

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

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

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

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

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

A. Create the Systems Manager IAM role

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

To create the new IAM role for Systems Manager:

  1. Create a JSON file named trustpolicy-maintenancewindowrole.json that contains the following trust policy. This policy describes which principal is allowed to assume the role you are going to create. This trust policy allows not only Amazon EC2 to assume this role, but also Systems Manager.
    {
       "Version":"2012-10-17",
       "Statement":[
          {
             "Sid":"",
             "Effect":"Allow",
             "Principal":{
                "Service":[
                   "ec2.amazonaws.com",
                   "ssm.amazonaws.com"
               ]
             },
             "Action":"sts:AssumeRole"
          }
       ]
    }

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

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

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

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

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

{
    "InstanceInformationList": [
        {
            "IsLatestVersion": true,
            "ComputerName": "ip-10-50-2-245",
            "PingStatus": "Online",
            "InstanceId": "YourInstanceId",
            "IPAddress": "10.50.2.245",
            "ResourceType": "EC2Instance",
            "AgentVersion": "2.2.120.0",
            "PlatformVersion": "2017.09",
            "PlatformName": "Amazon Linux AMI",
            "PlatformType": "Linux",
            "LastPingDateTime": 1515759143.826
        }
    ]
}

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

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

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

To create a patch baseline:

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

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

C.  Define a maintenance window

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

To define a maintenance window:

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

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

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

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

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

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

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

D.  Monitor patch compliance

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

$ aws ssm list-compliance-summaries

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

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

Screenshot of the Compliance page of the Systems Manager console

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

Summary

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

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

– Koen

N-O-D-E’s always-on networked Pi Plug

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/node-pi-plug/

N-O-D-E’s Pi Plug is a simple approach to using a Raspberry Pi Zero W as an always-on networked device without a tangle of wires.

Pi Plug 2: Turn The Pi Zero Into A Mini Server

Today I’m back with an update on the Pi Plug I made a while back. This prototype is still in the works, and is much more modular than the previous version. https://N-O-D-E.net/piplug2.html https://github.com/N-O-D-E/piplug —————- Shop: http://N-O-D-E.net/shop/ Patreon: http://patreon.com/N_O_D_E_ BTC: 17HqC7ZzmpE7E8Liuyb5WRbpwswBUgKRGZ Newsletter: http://eepurl.com/ceA-nL Music: https://archive.org/details/Fwawn-FromManToGod

The Pi Zero Power Case

In a video early last year, YouTuber N-O-D-E revealed his Pi Zero Power Case, an all-in-one always-on networked computer that fits snugly against a wall power socket.

NODE Plug Raspberry Pi Plug

The project uses an official Raspberry Pi power supply, a Zero4U USB hub, and a Raspberry Pi Zero W, and it allows completely wireless connection to a network. N-O-D-E cut the power cord and soldered its wires directly to the power input of the USB hub. The hub powers the Zero via pogo pins that connect directly to the test pads beneath.

The Power Case is a neat project, but it may be a little daunting for anyone not keen on cutting and soldering the power supply wires.

Pi Plug 2

In his overhaul of the design, N-O-D-E has created a modular reimagining of the previous always-on networked computer that fits more streamlined to the wall socket and requires absolutely no soldering or hacking of physical hardware.

Pi Plug

The Pi Plug 2 uses a USB power supply alongside two custom PCBs and a Zero W. While one PCB houses a USB connector that slots directly into the power supply, two blobs of solder on the second PCB press against the test pads beneath the Zero W. When connected, the PCBs run power directly from the wall socket to the Raspberry Pi Zero W. Neat!

NODE Plug Raspberry Pi
NODE Plug Raspberry Pi
NODE Plug Raspberry Pi
NODE Plug Raspberry Pi

While N-O-D-E isn’t currently selling these PCBs in his online store, all files are available on GitHub, so have a look if you want to recreate the Pi Plug.

Uses

In another video — and seriously, if you haven’t checked out N-O-D-E’s YouTube channel yet, you really should — he demonstrates a few changes that can turn your Zero into a USB dongle computer. This is a great hack if you don’t want to carry a power supply around in your pocket. As N-O-D-E explains:

Besides simply SSH’ing into the Pi, you could also easily install a remote desktop client and use the GUI. You can share your computer’s internet connection with the Pi and use it just like you would normally, but now without the need for a monitor, chargers, adapters, cables, or peripherals.

We’re keen to see how our community is hacking their Zeros and Zero Ws in order to take full advantage of the small footprint of the computer, so be sure to share your projects and ideas with us, either in the comments below or via social media.

The post N-O-D-E’s always-on networked Pi Plug appeared first on Raspberry Pi.

Pirate Streaming Search Engine Exploits Crunchyroll Vulnerability

Post Syndicated from Ernesto original https://torrentfreak.com/pirate-streaming-search-engine-exploits-crunchyroll-vulnerability-180213/

With 20 million members around the world, Crunchyroll is one of the largest on-demand streaming platforms for anime and manga content.

Much like Hollywood, the site has competition from pirate streaming sites which offer their content without permission. These usually stream pirated videos which are hosted on external sites.

However, this week Crunchyroll is facing a more direct attack. The people behind the new streaming meta-search engine StreamCR say they’ve found a way to stream the site’s content from its own servers, without paying.

“This works due to a vulnerability in the Crunchyroll system,” StreamCR’s operators tell TorrentFreak.

Simply put, StreamCR uses an active Crunchyroll account to locate the video streams and embeds this on its own website. This allows people to access Crunchyroll videos in the best quality without paying.

“This gives access to the full library in the region of our server, retrieving it as long as we’re not bound by the regular regional restriction. For this, we pick a US server as American Crunchyroll has the most library of content.

Stream in various qualities

The exploit was developed in-house, the StreamCR team informs us. While it works fine at the moment the team realizes that this may not last forever, as Crunchyroll might eventually patch the vulnerability.

However, the meta-search engine will have made its point by then.

“We expect them to fix this, Why wouldn’t they? In the meantime, this can demonstrate how vulnerable Crunchyroll is at the moment,” they tell us.

The site’s ultimate plan is to become the go-to search engine for people looking to stream all kinds of pirated videos. In addition to Crunchyroll, StreamCR also indexes various pirate sites, including YesMovies, Gomovies, and 9anime.

“StreamCR’s goal is to let people access streams with ease from a universal site, we’re trying to have a Google-like experience for finding online streams,” they say.

TorrentFreak reached out to Crunchyroll asking for a comment on the issue, but at the time of publication, we have yet to hear back.

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

Pirate Site Blockades Enter Germany With Kinox.to as First Target

Post Syndicated from Ernesto original https://torrentfreak.com/pirate-site-blockades-enter-germany-with-kinox-to-as-first-target-180213/

Website blocking has become one of the leading anti-piracy mechanisms of recent years.

It is particularly prevalent across Europe, where thousands of sites are blocked by ISPs following court orders.

This week, these blocking efforts also reached Germany. Following a provisional injunction issued by the federal court in Munich, Internet provider Vodafone must block access to the popular streaming portal Kinox.to.

The injunction was issued on behalf of the German film production and distribution company Constantin Film. The company complained that Kinox facilitates copyright infringement and cited a recent order from the European Court of Justice in its defense, Golem reports.

While these types of blockades are common in Europe, they’re a new sight in Germany. Vodafone users who attempt to access the Kinox site will now be welcomed with a blocking notification instead.

“This portal is temporarily unavailable due to a copyright claim,” it reads, translated from German.

Blocked

The Kinox streaming site has been a thorn in the side of German authorities and copyright holders for a long time. Last year, one of the site’s admins was detained in Kosovo after a three-year manhunt, but despite these and other actions, the site remains online.

With the blocking efforts, Constantin Film hopes to make it harder for people to access the site, although this measure is also limited.

For now, it seems to be a simple DNS blockade, which means that people can bypass it relatively easily by switching to a free alternative DNS provider such as Google DNS or OpenDNS.

And there are other workarounds as well, as operators of Kinox point out in a message on their homepage.

“Vodafone User: Use the public Google DNS server: 8.8.8.8, that goes the .TO domain again! Otherwise, a VPN or the free Tor Browser can be used!” they write.

While the measure may not be foolproof, the current order is certainly significant. Previously, all German courts have denied similar blocking orders based on different arguments. This means that more blocking efforts may be on the horizon.

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

Amazon Relational Database Service – Looking Back at 2017

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/amazon-relational-database-service-looking-back-at-2017/

The Amazon RDS team launched nearly 80 features in 2017. Some of them were covered in this blog, others on the AWS Database Blog, and the rest in What’s New or Forum posts. To wrap up my week, I thought it would be worthwhile to give you an organized recap. So here we go!

Certification & Security

Features

Engine Versions & Features

Regional Support

Instance Support

Price Reductions

And That’s a Wrap
I’m pretty sure that’s everything. As you can see, 2017 was quite the year! I can’t wait to see what the team delivers in 2018.

Jeff;

 

Hosting Provider Steadfast Maintains DMCA Safe Harbor Defense For Trial

Post Syndicated from Ernesto original https://torrentfreak.com/hosting-provider-steadfast-maintains-dmca-safe-harbor-defense-for-trial-180212/

Two years ago, adult entertainment publisher ALS Scan dragged several third-party Internet services to court.

The company targeted several companies including CDN provider CloudFlare and the Chicago-based hosting company Steadfast, accusing them of copyright infringement because they offered services to pirate sites.

The case against Steadfast is getting close to trial and to start with an advantage, ALS Scan recently asked the court for partial summary judgment, determining that the hosting company contributed to copyright infringement and that it has no safe harbor protection.

ALS argued that Steadfast refused to shut down the servers of the image sharing platform Imagebam.com, which was operated by its client Flixya. ALS Scan described the site as a repeat offender, as it had been targeted with dozens of DMCA notices, and accused Steadfast of turning a blind eye to the situation.

Steadfast, for its part, fiercely denied the allegations. The hosting provider admitted that it leased servers to Flixya for ten years but said that it forwarded all notices to its client. The hosting company could not address individual infringements, other than shutting down the entire site, which would have been disproportionate in their view.

A few days ago California District Court Judge George Wu ruled on the matter, denying ALS’s motion for summary judgment.

Both sides made sensible arguments on the contributory infringement issue, but it is by no means undisputed that the hosting provider ‘contributed’ to the infringing activities. The court, therefore, left this question open for the jury to determine at trial.

“Ultimately, both sides have raised triable issues of fact with respect to material contribution. As a result, the Court would deny Plaintiff’s Motion,” Judge Wu writes.

ALS also sought summary judgment on the DMCA safe harbor protection issue, but the court denied this request as well. While it’s clear that the hosting company never terminated a customer for repeat infringements, it’s not clear whether it was ever in a situation where it needed to.

The DMCA requires Internet services to implement a meaningful repeat infringer policy, but in this case, Steadfast’s client Imagebam reportedly had a takedown policy of its own, which complicates the issue.

“While the fact Steadfast has never terminated one of its own customers for infringement is potentially damaging to its ability to fit the safe harbor, Plaintiff has not established that Steadfast faced a situation requiring it to terminate one of its users,” Judge Wu writes.

“Even in the present case it is unclear that Steadfast needed to terminate Flixya’s account given Flixya itself had a policy that was arguably successful at removing infringing images from imagebam.com.”

Judge Wu adds that safe harbor defenses are generally left to the jury, and this is what he decided as well.

As a result, ALS’s entire motion for summary judgment is denied. This is good news for Steadfast, who will have their safe harbor defense available at the upcoming trial. However, they will likely celebrate this win with caution, as the jury makes its ultimate decision.

A copy of the court’s order is available here (pdf).

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

How I built a data warehouse using Amazon Redshift and AWS services in record time

Post Syndicated from Stephen Borg original https://aws.amazon.com/blogs/big-data/how-i-built-a-data-warehouse-using-amazon-redshift-and-aws-services-in-record-time/

This is a customer post by Stephen Borg, the Head of Big Data and BI at Cerberus Technologies.

Cerberus Technologies, in their own words: Cerberus is a company founded in 2017 by a team of visionary iGaming veterans. Our mission is simple – to offer the best tech solutions through a data-driven and a customer-first approach, delivering innovative solutions that go against traditional forms of working and process. This mission is based on the solid foundations of reliability, flexibility and security, and we intend to fundamentally change the way iGaming and other industries interact with technology.

Over the years, I have developed and created a number of data warehouses from scratch. Recently, I built a data warehouse for the iGaming industry single-handedly. To do it, I used the power and flexibility of Amazon Redshift and the wider AWS data management ecosystem. In this post, I explain how I was able to build a robust and scalable data warehouse without the large team of experts typically needed.

In two of my recent projects, I ran into challenges when scaling our data warehouse using on-premises infrastructure. Data was growing at many tens of gigabytes per day, and query performance was suffering. Scaling required major capital investment for hardware and software licenses, and also significant operational costs for maintenance and technical staff to keep it running and performing well. Unfortunately, I couldn’t get the resources needed to scale the infrastructure with data growth, and these projects were abandoned. Thanks to cloud data warehousing, the bottleneck of infrastructure resources, capital expense, and operational costs have been significantly reduced or have totally gone away. There is no more excuse for allowing obstacles of the past to delay delivering timely insights to decision makers, no matter how much data you have.

With Amazon Redshift and AWS, I delivered a cloud data warehouse to the business very quickly, and with a small team: me. I didn’t have to order hardware or software, and I no longer needed to install, configure, tune, or keep up with patches and version updates. Instead, I easily set up a robust data processing pipeline and we were quickly ingesting and analyzing data. Now, my data warehouse team can be extremely lean, and focus more time on bringing in new data and delivering insights. In this post, I show you the AWS services and the architecture that I used.

Handling data feeds

I have several different data sources that provide everything needed to run the business. The data includes activity from our iGaming platform, social media posts, clickstream data, marketing and campaign performance, and customer support engagements.

To handle the diversity of data feeds, I developed abstract integration applications using Docker that run on Amazon EC2 Container Service (Amazon ECS) and feed data to Amazon Kinesis Data Streams. These data streams can be used for real time analytics. In my system, each record in Kinesis is preprocessed by an AWS Lambda function to cleanse and aggregate information. My system then routes it to be stored where I need on Amazon S3 by Amazon Kinesis Data Firehose. Suppose that you used an on-premises architecture to accomplish the same task. A team of data engineers would be required to maintain and monitor a Kafka cluster, develop applications to stream data, and maintain a Hadoop cluster and the infrastructure underneath it for data storage. With my stream processing architecture, there are no servers to manage, no disk drives to replace, and no service monitoring to write.

Setting up a Kinesis stream can be done with a few clicks, and the same for Kinesis Firehose. Firehose can be configured to automatically consume data from a Kinesis Data Stream, and then write compressed data every N minutes to Amazon S3. When I want to process a Kinesis data stream, it’s very easy to set up a Lambda function to be executed on each message received. I can just set a trigger from the AWS Lambda Management Console, as shown following.

I also monitor the duration of function execution using Amazon CloudWatch and AWS X-Ray.

Regardless of the format I receive the data from our partners, I can send it to Kinesis as JSON data using my own formatters. After Firehose writes this to Amazon S3, I have everything in nearly the same structure I received but compressed, encrypted, and optimized for reading.

This data is automatically crawled by AWS Glue and placed into the AWS Glue Data Catalog. This means that I can immediately query the data directly on S3 using Amazon Athena or through Amazon Redshift Spectrum. Previously, I used Amazon EMR and an Amazon RDS–based metastore in Apache Hive for catalog management. Now I can avoid the complexity of maintaining Hive Metastore catalogs. Glue takes care of high availability and the operations side so that I know that end users can always be productive.

Working with Amazon Athena and Amazon Redshift for analysis

I found Amazon Athena extremely useful out of the box for ad hoc analysis. Our engineers (me) use Athena to understand new datasets that we receive and to understand what transformations will be needed for long-term query efficiency.

For our data analysts and data scientists, we’ve selected Amazon Redshift. Amazon Redshift has proven to be the right tool for us over and over again. It easily processes 20+ million transactions per day, regardless of the footprint of the tables and the type of analytics required by the business. Latency is low and query performance expectations have been more than met. We use Redshift Spectrum for long-term data retention, which enables me to extend the analytic power of Amazon Redshift beyond local data to anything stored in S3, and without requiring me to load any data. Redshift Spectrum gives me the freedom to store data where I want, in the format I want, and have it available for processing when I need it.

To load data directly into Amazon Redshift, I use AWS Data Pipeline to orchestrate data workflows. I create Amazon EMR clusters on an intra-day basis, which I can easily adjust to run more or less frequently as needed throughout the day. EMR clusters are used together with Amazon RDS, Apache Spark 2.0, and S3 storage. The data pipeline application loads ETL configurations from Spring RESTful services hosted on AWS Elastic Beanstalk. The application then loads data from S3 into memory, aggregates and cleans the data, and then writes the final version of the data to Amazon Redshift. This data is then ready to use for analysis. Spark on EMR also helps with recommendations and personalization use cases for various business users, and I find this easy to set up and deliver what users want. Finally, business users use Amazon QuickSight for self-service BI to slice, dice, and visualize the data depending on their requirements.

Each AWS service in this architecture plays its part in saving precious time that’s crucial for delivery and getting different departments in the business on board. I found the services easy to set up and use, and all have proven to be highly reliable for our use as our production environments. When the architecture was in place, scaling out was either completely handled by the service, or a matter of a simple API call, and crucially doesn’t require me to change one line of code. Increasing shards for Kinesis can be done in a minute by editing a stream. Increasing capacity for Lambda functions can be accomplished by editing the megabytes allocated for processing, and concurrency is handled automatically. EMR cluster capacity can easily be increased by changing the master and slave node types in Data Pipeline, or by using Auto Scaling. Lastly, RDS and Amazon Redshift can be easily upgraded without any major tasks to be performed by our team (again, me).

In the end, using AWS services including Kinesis, Lambda, Data Pipeline, and Amazon Redshift allows me to keep my team lean and highly productive. I eliminated the cost and delays of capital infrastructure, as well as the late night and weekend calls for support. I can now give maximum value to the business while keeping operational costs down. My team pushed out an agile and highly responsive data warehouse solution in record time and we can handle changing business requirements rapidly, and quickly adapt to new data and new user requests.


Additional Reading

If you found this post useful, be sure to check out Deploy a Data Warehouse Quickly with Amazon Redshift, Amazon RDS for PostgreSQL and Tableau Server and Top 8 Best Practices for High-Performance ETL Processing Using Amazon Redshift.


About the Author

Stephen Borg is the Head of Big Data and BI at Cerberus Technologies. He has a background in platform software engineering, and first became involved in data warehousing using the typical RDBMS, SQL, ETL, and BI tools. He quickly became passionate about providing insight to help others optimize the business and add personalization to products. He is now the Head of Big Data and BI at Cerberus Technologies.

 

 

 

Cloudflare Hit With Piracy Lawsuit After Abuse Form ‘Fails’

Post Syndicated from Ernesto original https://torrentfreak.com/cloudflare-hit-with-piracy-lawsuit-after-abuse-form-fails-180210/

Seattle-based artist Christopher Boffoli is no stranger when it comes to suing tech companies for aiding copyright infringement of his work.

Boffoli has filed lawsuits against Imgur, Twitter, Pinterest, Google, and others, which were dismissed and/or settled out of court under undisclosed terms.

This month he filed a new case against another intermediary, Cloudflare, which has had its fair share of piracy allegations in recent years.

In common with other companies, Cloudflare is accused of contributing to copyright infringements of Boffoli’s “Big Appetites” miniatures series. In this case, several Cloudflare customers allegedly posted these photos on their sites which were then reproduced on the servers of the CDN provider.

The lawsuit mentions that the infringing copies were posted on unique-landscape.com and baklol.com. This was also pointed out to Cloudflare by Boffoli, who sent the company DMCA takedown notices in October and November of last year.

While the photographer received an automated response, the photos in question remained online. Through the lawsuit, Boffoli hopes this will change.

“CloudFlare induced, caused, or materially contributed to the Infringing Websites’ publication,” the complaint reads. “CloudFlare had actual knowledge of the Infringing Content. Boffoli provided notice to CloudFlare in compliance with the DMCA, and CloudFlare failed to disable access to or remove the Infringing Websites.”

The photographer is asking the court to order an injunction preventing Cloudflare from making his work available. In addition, the complaint asks for actual and statutory damages for willful copyright infringement. With at least four photos in the lawsuit, the potential damages are more than half a million dollars.

While it’s not mentioned in the complaint, the email communication between Boffoli and Cloudflare goes further than just an automated response. Court records show that the photographer initially didn’t ask Cloudflare to remove the infringing photos. Instead, he asked the CDN provider to forward them to the ISP or site owner.

“I would be grateful if you would forward this DMCA takedown request to the website owner and ISP so these infringing links can immediately be removed,” it read.

Part of the email communication

From then on things escalated a bit. The emails reveal that Boffoli had trouble reporting the infringing photos through the required form.

When the photographer pointed this out in a direct email, Cloudflare urged him to try the form again as that was the only way to send the DMCA request to the designated copyright agent.

“The DMCA doesn’t require us to process reports not sent to our registered agent as per our registration with the US Copyright Office. Our registered copyright agent is the form located at cloudflare.com/abuse/form and you may proceed via that avenue,” Cloudflare wrote.

If the case moves forward, Cloudflare may use this to argue that it never received a proper DMCA takedown notice. However, Boffoli wasn’t planning on trying again and instead threatened a lawsuit, unless Cloudflare took immediate action.

“As I have said, your form did not work for me despite repeated attempts to use it. And it is insulting for you to suggest that it’s working fine when it is not. So again, this is absolutely my last attempt to get you to respond to this infringement for which you are impeding the removal,” Boffoli wrote.

“If you take no action now I will forward this to my legal team this week. It is more than enough of a burden to have to waste countless hours policing my own copyrights without organizations like Cloudflare running interference for copyright infringers. I am not averse to asking a federal judge to compel you to deal with these copyright infringements. And I will seek statutory damages for contributory infringement at that time.”

As it turns out, that was not an idle threat.

—-

A copy of the complaint is available here (pdf) and the email exhibits can be found here (pdf).

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

Voksi Releases Detailed Denuvo-Cracking Video Tutorial

Post Syndicated from Andy original https://torrentfreak.com/voksi-releases-detailed-denuvo-cracking-video-tutorial-180210/

Earlier this week, version 4.9 of the Denuvo anti-tamper system, which had protected Assassins Creed Origin for the past several months, was defeated by Italian cracking group CPY.

While Denuvo would probably paint four months of protection as a success, the company would certainly have preferred for things to have gone on a bit longer, not least following publisher Ubisoft’s decision to use VMProtect technology on top.

But while CPY do their thing in Italy there’s another rival whittling away at whatever the giants at Denuvo (and new owner Irdeto) can come up with. The cracker – known only as Voksi – hails from Bulgaria and this week he took the unusual step of releasing a 90-minute video (embedded below) in which he details how to defeat Denuvo’s V4 anti-tamper technology.

The video is not for the faint-hearted so those with an aversion to issues of a highly technical nature might feel the urge to look away. However, it may surprise readers to learn that not so long ago, Voksi knew absolutely nothing about coding.

“You will find this very funny and unbelievable,” Voksi says, recalling the events of 2012.

“There was one game called Sanctum and on one free [play] weekend [on Steam], I and my best friend played through it and saw how great the cooperative action was. When the free weekend was over, we wanted to keep playing, but we didn’t have any money to buy the game.

“So, I started to look for alternative ways, LAN emulators, anything! Then I decided I need to crack it. That’s how I got into reverse engineering. I started watching some shitty YouTube videos with bad quality and doing some tutorials. Then I found about Steam exploits and that’s how I got into making Steamworks fixes, allowing cracked multiplayer between players.”

Voksi says his entire cracking career began with this one indie game and his desire to play it with his best friend. Prior to that, he had absolutely no experience at all. He says he’s taken no university courses or any course at all for that matter. Everything he knows has come from material he’s found online. But the intrigue doesn’t stop there.

“I don’t even know how to code properly in high-level language like C#, C++, etc. But I understand assembly [language] perfectly fine,” he explains.

For those who code, that’s generally a little bit back to front, with low-level languages usually posing the most difficulties. But Voksi says that with assembly, everything “just clicked.”

Of course, it’s been six years since the 21-year-old was first motivated to crack a game due to lack of funds. In the more than half decade since, have his motivations changed at all? Is it the thrill of solving the puzzle or are there other factors at play?

“I just developed an urge to provide paid stuff for free for people who can’t afford it and specifically, co-op and multiplayer cracks. Of course, i’m not saying don’t support the developers if you have the money and like the game. You should do that,” he says.

“The challenge of cracking also motivates me, especially with an abomination like Denuvo. It is pure cancer for the gaming industry, it doesn’t help and it only causes issues for the paying customers.”

Those who follow Voksi online will know that as well as being known in his own right, he’s part of the REVOLT group, a collective that has Voksi’s core interests and goals as their own.

“REVOLT started as a group with one and only goal – to provide multiplayer support for cracked games. No other group was doing it until that day. It was founded by several members, from which I’m currently the only one active, still releasing cracks.

“Our great achievements are in first place, of course, cracking Denuvo V4, making us one of the four groups/people who were able to break the protection. In second place are our online fixes for several AAA games, allowing you to play on legit servers with legit players. In third place, our ordinary Steamworks fixes allowing you to play multiplayer between cracked users.”

In communities like /r/crackwatch on Reddit and those less accessible, Voksi and others doing similar work are often held up as Internet heroes, cracking games in order to give the masses access to something that might’ve been otherwise inaccessible. But how does this fame sit with him?

“Well, I don’t see myself as a hero, just another ordinary person doing what he loves. I love seeing people happy because of my work, that’s also a big motivation, but nothing more than that,” he says.

Finally, what’s up next for Voksi and what are his hopes for the rest of the year?

“In an ideal world, Denuvo would die. As for me, I don’t know, time will tell,” he concludes.

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

Sharing Secrets with AWS Lambda Using AWS Systems Manager Parameter Store

Post Syndicated from Chris Munns original https://aws.amazon.com/blogs/compute/sharing-secrets-with-aws-lambda-using-aws-systems-manager-parameter-store/

This post courtesy of Roberto Iturralde, Sr. Application Developer- AWS Professional Services

Application architects are faced with key decisions throughout the process of designing and implementing their systems. One decision common to nearly all solutions is how to manage the storage and access rights of application configuration. Shared configuration should be stored centrally and securely with each system component having access only to the properties that it needs for functioning.

With AWS Systems Manager Parameter Store, developers have access to central, secure, durable, and highly available storage for application configuration and secrets. Parameter Store also integrates with AWS Identity and Access Management (IAM), allowing fine-grained access control to individual parameters or branches of a hierarchical tree.

This post demonstrates how to create and access shared configurations in Parameter Store from AWS Lambda. Both encrypted and plaintext parameter values are stored with only the Lambda function having permissions to decrypt the secrets. You also use AWS X-Ray to profile the function.

Solution overview

This example is made up of the following components:

  • An AWS SAM template that defines:
    • A Lambda function and its permissions
    • An unencrypted Parameter Store parameter that the Lambda function loads
    • A KMS key that only the Lambda function can access. You use this key to create an encrypted parameter later.
  • Lambda function code in Python 3.6 that demonstrates how to load values from Parameter Store at function initialization for reuse across invocations.

Launch the AWS SAM template

To create the resources shown in this post, you can download the SAM template or choose the button to launch the stack. The template requires one parameter, an IAM user name, which is the name of the IAM user to be the admin of the KMS key that you create. In order to perform the steps listed in this post, this IAM user will need permissions to execute Lambda functions, create Parameter Store parameters, administer keys in KMS, and view the X-Ray console. If you have these privileges in your IAM user account you can use your own account to complete the walkthrough. You can not use the root user to administer the KMS keys.

SAM template resources

The following sections show the code for the resources defined in the template.
Lambda function

ParameterStoreBlogFunctionDev:
    Type: 'AWS::Serverless::Function'
    Properties:
      FunctionName: 'ParameterStoreBlogFunctionDev'
      Description: 'Integrating lambda with Parameter Store'
      Handler: 'lambda_function.lambda_handler'
      Role: !GetAtt ParameterStoreBlogFunctionRoleDev.Arn
      CodeUri: './code'
      Environment:
        Variables:
          ENV: 'dev'
          APP_CONFIG_PATH: 'parameterStoreBlog'
          AWS_XRAY_TRACING_NAME: 'ParameterStoreBlogFunctionDev'
      Runtime: 'python3.6'
      Timeout: 5
      Tracing: 'Active'

  ParameterStoreBlogFunctionRoleDev:
    Type: AWS::IAM::Role
    Properties:
      AssumeRolePolicyDocument:
        Version: '2012-10-17'
        Statement:
          -
            Effect: Allow
            Principal:
              Service:
                - 'lambda.amazonaws.com'
            Action:
              - 'sts:AssumeRole'
      ManagedPolicyArns:
        - 'arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole'
      Policies:
        -
          PolicyName: 'ParameterStoreBlogDevParameterAccess'
          PolicyDocument:
            Version: '2012-10-17'
            Statement:
              -
                Effect: Allow
                Action:
                  - 'ssm:GetParameter*'
                Resource: !Sub 'arn:aws:ssm:${AWS::Region}:${AWS::AccountId}:parameter/dev/parameterStoreBlog*'
        -
          PolicyName: 'ParameterStoreBlogDevXRayAccess'
          PolicyDocument:
            Version: '2012-10-17'
            Statement:
              -
                Effect: Allow
                Action:
                  - 'xray:PutTraceSegments'
                  - 'xray:PutTelemetryRecords'
                Resource: '*'

In this YAML code, you define a Lambda function named ParameterStoreBlogFunctionDev using the SAM AWS::Serverless::Function type. The environment variables for this function include the ENV (dev) and the APP_CONFIG_PATH where you find the configuration for this app in Parameter Store. X-Ray tracing is also enabled for profiling later.

The IAM role for this function extends the AWSLambdaBasicExecutionRole by adding IAM policies that grant the function permissions to write to X-Ray and get parameters from Parameter Store, limited to paths under /dev/parameterStoreBlog*.
Parameter Store parameter

SimpleParameter:
    Type: AWS::SSM::Parameter
    Properties:
      Name: '/dev/parameterStoreBlog/appConfig'
      Description: 'Sample dev config values for my app'
      Type: String
      Value: '{"key1": "value1","key2": "value2","key3": "value3"}'

This YAML code creates a plaintext string parameter in Parameter Store in a path that your Lambda function can access.
KMS encryption key

ParameterStoreBlogDevEncryptionKeyAlias:
    Type: AWS::KMS::Alias
    Properties:
      AliasName: 'alias/ParameterStoreBlogKeyDev'
      TargetKeyId: !Ref ParameterStoreBlogDevEncryptionKey

  ParameterStoreBlogDevEncryptionKey:
    Type: AWS::KMS::Key
    Properties:
      Description: 'Encryption key for secret config values for the Parameter Store blog post'
      Enabled: True
      EnableKeyRotation: False
      KeyPolicy:
        Version: '2012-10-17'
        Id: 'key-default-1'
        Statement:
          -
            Sid: 'Allow administration of the key & encryption of new values'
            Effect: Allow
            Principal:
              AWS:
                - !Sub 'arn:aws:iam::${AWS::AccountId}:user/${IAMUsername}'
            Action:
              - 'kms:Create*'
              - 'kms:Encrypt'
              - 'kms:Describe*'
              - 'kms:Enable*'
              - 'kms:List*'
              - 'kms:Put*'
              - 'kms:Update*'
              - 'kms:Revoke*'
              - 'kms:Disable*'
              - 'kms:Get*'
              - 'kms:Delete*'
              - 'kms:ScheduleKeyDeletion'
              - 'kms:CancelKeyDeletion'
            Resource: '*'
          -
            Sid: 'Allow use of the key'
            Effect: Allow
            Principal:
              AWS: !GetAtt ParameterStoreBlogFunctionRoleDev.Arn
            Action:
              - 'kms:Encrypt'
              - 'kms:Decrypt'
              - 'kms:ReEncrypt*'
              - 'kms:GenerateDataKey*'
              - 'kms:DescribeKey'
            Resource: '*'

This YAML code creates an encryption key with a key policy with two statements.

The first statement allows a given user (${IAMUsername}) to administer the key. Importantly, this includes the ability to encrypt values using this key and disable or delete this key, but does not allow the administrator to decrypt values that were encrypted with this key.

The second statement grants your Lambda function permission to encrypt and decrypt values using this key. The alias for this key in KMS is ParameterStoreBlogKeyDev, which is how you reference it later.

Lambda function

Here I walk you through the Lambda function code.

import os, traceback, json, configparser, boto3
from aws_xray_sdk.core import patch_all
patch_all()

# Initialize boto3 client at global scope for connection reuse
client = boto3.client('ssm')
env = os.environ['ENV']
app_config_path = os.environ['APP_CONFIG_PATH']
full_config_path = '/' + env + '/' + app_config_path
# Initialize app at global scope for reuse across invocations
app = None

class MyApp:
    def __init__(self, config):
        """
        Construct new MyApp with configuration
        :param config: application configuration
        """
        self.config = config

    def get_config(self):
        return self.config

def load_config(ssm_parameter_path):
    """
    Load configparser from config stored in SSM Parameter Store
    :param ssm_parameter_path: Path to app config in SSM Parameter Store
    :return: ConfigParser holding loaded config
    """
    configuration = configparser.ConfigParser()
    try:
        # Get all parameters for this app
        param_details = client.get_parameters_by_path(
            Path=ssm_parameter_path,
            Recursive=False,
            WithDecryption=True
        )

        # Loop through the returned parameters and populate the ConfigParser
        if 'Parameters' in param_details and len(param_details.get('Parameters')) > 0:
            for param in param_details.get('Parameters'):
                param_path_array = param.get('Name').split("/")
                section_position = len(param_path_array) - 1
                section_name = param_path_array[section_position]
                config_values = json.loads(param.get('Value'))
                config_dict = {section_name: config_values}
                print("Found configuration: " + str(config_dict))
                configuration.read_dict(config_dict)

    except:
        print("Encountered an error loading config from SSM.")
        traceback.print_exc()
    finally:
        return configuration

def lambda_handler(event, context):
    global app
    # Initialize app if it doesn't yet exist
    if app is None:
        print("Loading config and creating new MyApp...")
        config = load_config(full_config_path)
        app = MyApp(config)

    return "MyApp config is " + str(app.get_config()._sections)

Beneath the import statements, you import the patch_all function from the AWS X-Ray library, which you use to patch boto3 to create X-Ray segments for all your boto3 operations.

Next, you create a boto3 SSM client at the global scope for reuse across function invocations, following Lambda best practices. Using the function environment variables, you assemble the path where you expect to find your configuration in Parameter Store. The class MyApp is meant to serve as an example of an application that would need its configuration injected at construction. In this example, you create an instance of ConfigParser, a class in Python’s standard library for handling basic configurations, to give to MyApp.

The load_config function loads the all the parameters from Parameter Store at the level immediately beneath the path provided in the Lambda function environment variables. Each parameter found is put into a new section in ConfigParser. The name of the section is the name of the parameter, less the base path. In this example, the full parameter name is /dev/parameterStoreBlog/appConfig, which is put in a section named appConfig.

Finally, the lambda_handler function initializes an instance of MyApp if it doesn’t already exist, constructing it with the loaded configuration from Parameter Store. Then it simply returns the currently loaded configuration in MyApp. The impact of this design is that the configuration is only loaded from Parameter Store the first time that the Lambda function execution environment is initialized. Subsequent invocations reuse the existing instance of MyApp, resulting in improved performance. You see this in the X-Ray traces later in this post. For more advanced use cases where configuration changes need to be received immediately, you could implement an expiry policy for your configuration entries or push notifications to your function.

To confirm that everything was created successfully, test the function in the Lambda console.

  1. Open the Lambda console.
  2. In the navigation pane, choose Functions.
  3. In the Functions pane, filter to ParameterStoreBlogFunctionDev to find the function created by the SAM template earlier. Open the function name to view its details.
  4. On the top right of the function detail page, choose Test. You may need to create a new test event. The input JSON doesn’t matter as this function ignores the input.

After running the test, you should see output similar to the following. This demonstrates that the function successfully fetched the unencrypted configuration from Parameter Store.

Create an encrypted parameter

You currently have a simple, unencrypted parameter and a Lambda function that can access it.

Next, you create an encrypted parameter that only your Lambda function has permission to use for decryption. This limits read access for this parameter to only this Lambda function.

To follow along with this section, deploy the SAM template for this post in your account and make your IAM user name the KMS key admin mentioned earlier.

  1. In the Systems Manager console, under Shared Resources, choose Parameter Store.
  2. Choose Create Parameter.
    • For Name, enter /dev/parameterStoreBlog/appSecrets.
    • For Type, select Secure String.
    • For KMS Key ID, choose alias/ParameterStoreBlogKeyDev, which is the key that your SAM template created.
    • For Value, enter {"secretKey": "secretValue"}.
    • Choose Create Parameter.
  3. If you now try to view the value of this parameter by choosing the name of the parameter in the parameters list and then choosing Show next to the Value field, you won’t see the value appear. This is because, even though you have permission to encrypt values using this KMS key, you do not have permissions to decrypt values.
  4. In the Lambda console, run another test of your function. You now also see the secret parameter that you created and its decrypted value.

If you do not see the new parameter in the Lambda output, this may be because the Lambda execution environment is still warm from the previous test. Because the parameters are loaded at Lambda startup, you need a fresh execution environment to refresh the values.

Adjust the function timeout to a different value in the Advanced Settings at the bottom of the Lambda Configuration tab. Choose Save and test to trigger the creation of a new Lambda execution environment.

Profiling the impact of querying Parameter Store using AWS X-Ray

By using the AWS X-Ray SDK to patch boto3 in your Lambda function code, each invocation of the function creates traces in X-Ray. In this example, you can use these traces to validate the performance impact of your design decision to only load configuration from Parameter Store on the first invocation of the function in a new execution environment.

From the Lambda function details page where you tested the function earlier, under the function name, choose Monitoring. Choose View traces in X-Ray.

This opens the X-Ray console in a new window filtered to your function. Be aware of the time range field next to the search bar if you don’t see any search results.
In this screenshot, I’ve invoked the Lambda function twice, one time 10.3 minutes ago with a response time of 1.1 seconds and again 9.8 minutes ago with a response time of 8 milliseconds.

Looking at the details of the longer running trace by clicking the trace ID, you can see that the Lambda function spent the first ~350 ms of the full 1.1 sec routing the request through Lambda and creating a new execution environment for this function, as this was the first invocation with this code. This is the portion of time before the initialization subsegment.

Next, it took 725 ms to initialize the function, which includes executing the code at the global scope (including creating the boto3 client). This is also a one-time cost for a fresh execution environment.

Finally, the function executed for 65 ms, of which 63.5 ms was the GetParametersByPath call to Parameter Store.

Looking at the trace for the second, much faster function invocation, you see that the majority of the 8 ms execution time was Lambda routing the request to the function and returning the response. Only 1 ms of the overall execution time was attributed to the execution of the function, which makes sense given that after the first invocation you’re simply returning the config stored in MyApp.

While the Traces screen allows you to view the details of individual traces, the X-Ray Service Map screen allows you to view aggregate performance data for all traced services over a period of time.

In the X-Ray console navigation pane, choose Service map. Selecting a service node shows the metrics for node-specific requests. Selecting an edge between two nodes shows the metrics for requests that traveled that connection. Again, be aware of the time range field next to the search bar if you don’t see any search results.

After invoking your Lambda function several more times by testing it from the Lambda console, you can view some aggregate performance metrics. Look at the following:

  • From the client perspective, requests to the Lambda service for the function are taking an average of 50 ms to respond. The function is generating ~1 trace per minute.
  • The function itself is responding in an average of 3 ms. In the following screenshot, I’ve clicked on this node, which reveals a latency histogram of the traced requests showing that over 95% of requests return in under 5 ms.
  • Parameter Store is responding to requests in an average of 64 ms, but note the much lower trace rate in the node. This is because you only fetch data from Parameter Store on the initialization of the Lambda execution environment.

Conclusion

Deduplication, encryption, and restricted access to shared configuration and secrets is a key component to any mature architecture. Serverless architectures designed using event-driven, on-demand, compute services like Lambda are no different.

In this post, I walked you through a sample application accessing unencrypted and encrypted values in Parameter Store. These values were created in a hierarchy by application environment and component name, with the permissions to decrypt secret values restricted to only the function needing access. The techniques used here can become the foundation of secure, robust configuration management in your enterprise serverless applications.

Server vs Endpoint Backup — Which is Best?

Post Syndicated from Roderick Bauer original https://www.backblaze.com/blog/endpoint-backup-for-distributed-computing/

server and computer backup to the cloud

How common are these statements in your organization?

  • I know I saved that file. The application must have put it somewhere outside of my documents folder.” — Mike in Marketing
  • I was on the road and couldn’t get a reliable VPN connection. I guess that’s why my laptop wasn’t backed up.” — Sally in Sales
  • I try to follow file policies, but I had a deadline this week and didn’t have time to copy my files to the server.” — Felicia in Finance
  • I just did a commit of my code changes and that was when the coffee mug was knocked over onto the laptop.” — Erin in Engineering
  • If you need a file restored from backup, contact the help desk at [email protected] The IT department will get back to you.” — XYZ corporate intranet
  • Why don’t employees save files on the network drive like they’re supposed to?” — Isaac in IT

If these statements are familiar, most likely you rely on file server backups to safeguard your valuable endpoint data.

The problem is, the workplace has changed. Where server backups might have fit how offices worked at one time in the past, relying solely on server backups today means you could be missing valuable endpoint data from your backups. On top of that, you likely are unnecessarily expending valuable user and IT time in attempting to secure and restore endpoint data.

Times Have Changed, and so have Effective Enterprise Backup Strategies

The ways we use computers and handle files today are vastly different from just five or ten years ago. Employees are mobile, and we no longer are limited to monolithic PC and Mac-based office suites. Cloud applications are everywhere. Company-mandated network drive policies are difficult to enforce as office practices change, devices proliferate, and organizational culture evolves. Besides, your IT staff has other things to do than babysit your employees to make sure they follow your organization’s policies for managing files.

Server Backup has its Place, but Does it Support How People Work Today?

Many organizations still rely on server backup. If your organization works primarily in centralized offices with all endpoints — likely desktops — connected directly to your network, and you maintain tight control of how employees manage their files, it still might work for you.

Your IT department probably has set network drive policies that require employees to save files in standard places that are regularly backed up to your file server. Turns out, though, that even standard applications don’t always save files where IT would like them to be. They could be in a directory or folder that’s not regularly backed up.

As employees have become more mobile, they have adopted practices that enable them to access files from different places, but these practices might not fit in with your organization’s server policies. An employee saving a file to Dropbox might be planning to copy it to an “official” location later, but whether that ever happens could be doubtful. Often people don’t realize until it’s too late that accidentally deleting a file in one sync service directory means that all copies in all locations — even the cloud — are also deleted.

Employees are under increasing demands to produce, which means that network drive policies aren’t always followed; time constraints and deadlines can cause best practices to go out the window. Users will attempt to comply with policies as best they can — and you might get 70% or even 75% effective compliance — but getting even to that level requires training, monitoring, and repeatedly reminding employees of policies they need to follow — none of which leads to a good work environment.

Even if you get to 75% compliance with network file policies, what happens if the critical file needed to close out an end-of-year financial summary isn’t one of the files backed up? The effort required for IT to get from 70% to 80% or 90% of an endpoint’s files effectively backed up could require multiple hours from your IT department, and you still might not have backed up the one critical file you need later.

Your Organization Operates on its Data — And Today That Data Exists in Multiple Locations

Users are no longer tied to one endpoint, and may use different computers in the office, at home, or traveling. The greater the number of endpoints used, the greater the chance of an accidental or malicious device loss or data corruption. The loss of the Sales VP’s laptop at the airport on her way back from meeting with major customers can affect an entire organization and require weeks to resolve.

Even with the best intentions and efforts, following policies when out of the office can be difficult or impossible. Connecting to your private network when remote most likely requires a VPN, and VPN connectivity can be challenging from the lobby Wi-Fi at the Radisson. Server restores require time from the IT staff, which can mean taking resources away from other IT priorities and a growing backlog of requests from users to need their files as soon as possible. When users are dependent on IT to get back files critical to their work, employee productivity and often deadlines are affected.

Managing Finite Server Storage Is an Ongoing Challenge

Network drive backup usually requires on-premises data storage for endpoint backups. Since it is a finite resource, allocating that storage is another burden on your IT staff. To make sure that storage isn’t exceeded, IT departments often ration storage by department and/or user — another oversight duty for IT, and even more choices required by your IT department and department heads who have to decide which files to prioritize for backing up.

Adding Backblaze Endpoint Backup Improves Business Continuity and Productivity

Having an endpoint backup strategy in place can mitigate these problems and improve user productivity, as well. A good endpoint backup service, such as Backblaze Cloud Backup, will ensure that all devices are backed up securely, automatically, without requiring any action by the user or by your IT department.

For 99% of users, no configuration is required for Backblaze Backup. Everything on the endpoint is encrypted and securely backed up to the cloud, including program configuration files and files outside of standard document folders. Even temp files are backed up, which can prove invaluable when recovering a file after a crash or other program interruption. Cloud storage is unlimited with Backblaze Backup, so there are no worries about running out of storage or rationing file backups.

The Backblaze client can be silently and remotely installed to both Macintosh and Windows clients with no user interaction. And, with Backblaze Groups, your IT staff has complete visibility into when files were last backed up. IT staff can recover any backed up file, folder, or entire computer from the admin panel, and even give file restore capability to the user, if desired, which reduces dependency on IT and time spent waiting for restores.

With over 500 petabytes of customer data stored and one million files restored every hour of every day by Backblaze customers, you know that Backblaze Backup works for its users.

You Need Data Security That Matches the Way People Work Today

Both file server and endpoint backup have their places in an organization’s data security plan, but their use and value differ. If you already are using file server backup, adding endpoint backup will make a valuable contribution to your organization by reducing workload, improving productivity, and increasing confidence that all critical files are backed up.

By guaranteeing fast and automatic backup of all endpoint data, and matching the current way organizations and people work with data, Backblaze Backup will enable you to effectively and affordably meet the data security demands of your organization.

The post Server vs Endpoint Backup — Which is Best? appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

New – Encryption at Rest for DynamoDB

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/new-encryption-at-rest-for-dynamodb/

At AWS re:Invent 2017, Werner encouraged his audience to “Dance like nobody is watching, and to encrypt like everyone is:

The AWS team is always eager to add features that make it easier for you to protect your sensitive data and to help you to achieve your compliance objectives. For example, in 2017 we launched encryption at rest for SQS and EFS, additional encryption options for S3, and server-side encryption of Kinesis Data Streams.

Today we are giving you another data protection option with the introduction of encryption at rest for Amazon DynamoDB. You simply enable encryption when you create a new table and DynamoDB takes care of the rest. Your data (tables, local secondary indexes, and global secondary indexes) will be encrypted using AES-256 and a service-default AWS Key Management Service (KMS) key. The encryption adds no storage overhead and is completely transparent; you can insert, query, scan, and delete items as before. The team did not observe any changes in latency after enabling encryption and running several different workloads on an encrypted DynamoDB table.

Creating an Encrypted Table
You can create an encrypted table from the AWS Management Console, API (CreateTable), or CLI (create-table). I’ll use the console! I enter the name and set up the primary key as usual:

Before proceeding, I uncheck Use default settings, scroll down to the Encrypytion section, and check Enable encryption. Then I click Create and my table is created in encrypted form:

I can see the encryption setting for the table at a glance:

When my compliance team asks me to show them how DynamoDB uses the key to encrypt the data, I can create a AWS CloudTrail trail, insert an item, and then scan the table to see the calls to the AWS KMS API. Here’s an extract from the trail:

{
  "eventTime": "2018-01-24T00:06:34Z",
  "eventSource": "kms.amazonaws.com",
  "eventName": "Decrypt",
  "awsRegion": "us-west-2",
  "sourceIPAddress": "dynamodb.amazonaws.com",
  "userAgent": "dynamodb.amazonaws.com",
  "requestParameters": {
    "encryptionContext": {
      "aws:dynamodb:tableName": "reg-users",
      "aws:dynamodb:subscriberId": "1234567890"
    }
  },
  "responseElements": null,
  "requestID": "7072def1-009a-11e8-9ab9-4504c26bd391",
  "eventID": "3698678a-d04e-48c7-96f2-3d734c5c7903",
  "readOnly": true,
  "resources": [
    {
      "ARN": "arn:aws:kms:us-west-2:1234567890:key/e7bd721d-37f3-4acd-bec5-4d08c765f9f5",
      "accountId": "1234567890",
      "type": "AWS::KMS::Key"
    }
  ]
}

Available Now
This feature is available now in the US East (N. Virginia), US East (Ohio), US West (Oregon), and EU (Ireland) Regions and you can start using it today.

There’s no charge for the encryption; you will be charged for the calls that DynamoDB makes to AWS KMS on your behalf.

Jeff;