Tag Archives: SSL

DynamoDB Accelerator (DAX) Now Generally Available

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

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

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

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

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

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

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

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

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

Jeff;

 

BPI Breaks Record After Sending 310 Million Google Takedowns

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

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

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

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

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

BPI takedown notices, as reported by Google

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Calibre 3.0 released

Post Syndicated from corbet original https://lwn.net/Articles/725588/rss

Version 3.0 of the
calibre electronic-book reader has been released. “It has been almost three years since calibre 2.0. In that time lots has happened. The biggest new feature, which was in development for almost that entire period, is a completely re-written calibre Content server.

The Content server allows you to wirelessly browse your calibre books on
any modern phone/tablet and even read the books right in your phone
browser.” Other additions include support for high-DPI screens and
support for multiple icon themes.

Pirate Bay Facilitates Piracy and Can be Blocked, Top EU Court Rules

Post Syndicated from Ernesto original https://torrentfreak.com/pirate-bay-facilitates-piracy-and-can-be-blocked-top-eu-court-rules-170614/

pirate bayIn 2014, The Court of The Hague handed down its decision in a long running case which had previously forced two Dutch ISPs, Ziggo and XS4ALL, to block The Pirate Bay.

The Court ruled against local anti-piracy outfit BREIN, concluding that the blockade was ineffective and restricted the ISPs’ entrepreneurial freedoms.

The Pirate Bay was unblocked by all local ISPs while BREIN took the matter to the Supreme Court, which subsequently referred the case to the EU Court of Justice, seeking further clarification.

After a careful review of the case, the Court of Justice today ruled that The Pirate Bay can indeed be blocked.

While the operators don’t share anything themselves, they knowingly provide users with a platform to share copyright-infringing links. This can be seen as “an act of communication” under the EU Copyright Directive, the Court concludes.

“Whilst it accepts that the works in question are placed online by the users, the Court highlights the fact that the operators of the platform play an essential role in making those works available,” the Court explains in a press release (pdf).

According to the ruling, The Pirate Bay indexes torrents in a way that makes it easy for users to find infringing content while the site makes a profit. The Pirate Bay is aware of the infringements, and although moderators sometimes remove “faulty” torrents, infringing links remain online.

“In addition, the same operators expressly display, on blogs and forums accessible on that platform, their intention of making protected works available to users, and encourage the latter to make copies of those works,” the Court writes.

The ruling means that there are no major obstacles for the Dutch Supreme Court to issue an ISP blockade, but a final decision in the underlying case will likely take a few more months.

A decision at the European level is important, as it may also affect court orders in other countries where The Pirate Bay and other torrent sites are already blocked, including Austria, Belgium, Finland, Italy, and its home turf Sweden.

Despite the negative outcome, the Pirate Bay team is not overly worried.

“Copyright holders will remain stubborn and fight to hold onto a dying model. Clueless and corrupt law makers will put corporate interests before the public’s. Their combined jackassery is what keeps TPB alive,” TPB’s plc365 tells TorrentFreak.

“The reality is that regardless of the ruling, nothing substantial will change. Maybe more ISPs will block TPB. More people will use one of the hundreds of existing proxies, and even more new ones will be created as a result.”

Pirate Bay moderator “Xe” notes that while it’s an extra barrier to access the site, blockades will eventually help people to get around censorship efforts, which are not restricted to TPB.

“They’re an issue for everyone in the sense that they’re an obstacle which has to be overcome. But learning how to work around them isn’t hard and knowing how to work around them is becoming a core skill for everyone who uses the Internet.

“Blockades are not a major issue for the site in the sense that they’re nothing new: we’ve long since adapted to them. We serve the needs of millions of people every day in spite of them,” Xe adds.

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

More notes on US-CERTs IOCs

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/06/more-notes-on-us-certs-iocs.html

Yet another Russian attack against the power grid, and yet more bad IOCs from the DHS US-CERT.

IOCs are “indicators of compromise“, things you can look for in order to order to see if you, too, have been hacked by the same perpetrators. There are several types of IOCs, ranging from the highly specific to the uselessly generic.

A uselessly generic IOC would be like trying to identify bank robbers by the fact that their getaway car was “white” in color. It’s worth documenting, so that if the police ever show up in a suspected cabin in the woods, they can note that there’s a “white” car parked in front.

But if you work bank security, that doesn’t mean you should be on the lookout for “white” cars. That would be silly.

This is what happens with US-CERT’s IOCs. They list some potentially useful things, but they also list a lot of junk that waste’s people’s times, with little ability to distinguish between the useful and the useless.

An example: a few months ago was the GRIZZLEYBEAR report published by US-CERT. Among other things, it listed IP addresses used by hackers. There was no description which would be useful IP addresses to watch for, and which would be useless.

Some of these IP addresses were useful, pointing to servers the group has been using a long time as command-and-control servers. Other IP addresses are more dubious, such as Tor exit nodes. You aren’t concerned about any specific Tor exit IP address, because it changes randomly, so has no relationship to the attackers. Instead, if you cared about those Tor IP addresses, what you should be looking for is a dynamically updated list of Tor nodes updated daily.

And finally, they listed IP addresses of Yahoo, because attackers passed data through Yahoo servers. No, it wasn’t because those Yahoo servers had been compromised, it’s just that everyone passes things though them, like email.

A Vermont power-plant blindly dumped all those IP addresses into their sensors. As a consequence, the next morning when an employee checked their Yahoo email, the sensors triggered. This resulted in national headlines about the Russians hacking the Vermont power grid.

Today, the US-CERT made similar mistakes with CRASHOVERRIDE. They took a report from Dragos Security, then mutilated it. Dragos’s own IOCs focused on things like hostile strings and file hashes of the hostile files. They also included filenames, but similar to the reason you’d noticed a white car — because it happened, not because you should be on the lookout for it. In context, there’s nothing wrong with noting the file name.

But the US-CERT pulled the filenames out of context. One of those filenames was, humorously, “svchost.exe”. It’s the name of an essential Windows service. Every Windows computer is running multiple copies of “svchost.exe”. It’s like saying “be on the lookout for Windows”.

Yes, it’s true that viruses use the same filenames as essential Windows files like “svchost.exe”. That’s, generally, something you should be aware of. But that CRASHOVERRIDE did this is wholly meaningless.

What Dragos Security was actually reporting was that a “svchost.exe” with the file hash of 79ca89711cdaedb16b0ccccfdcfbd6aa7e57120a was the virus — it’s the hash that’s the important IOC. Pulling the filename out of context is just silly.

Luckily, the DHS also provides some of the raw information provided by Dragos. But even then, there’s problems: they provide it in formatted form, for HTML, PDF, or Excel documents. This corrupts the original data so that it’s no longer machine readable. For example, from their webpage, they have the following:

import “pe”
import “hash”

Among the problems are the fact that the quote marks have been altered, probably by Word’s “smart quotes” feature. In other cases, I’ve seen PDF documents get confused by the number 0 and the letter O, as if the raw data had been scanned in from a printed document and OCRed.

If this were a “threat intel” company,  we’d call this snake oil. The US-CERT is using Dragos Security’s reports to promote itself, but ultimate providing negative value, mutilating the content.

This, ultimately, causes a lot of harm. The press trusted their content. So does the network of downstream entities, like municipal power grids. There are tens of thousands of such consumers of these reports, often with less expertise than even US-CERT. There are sprinklings of smart people in these organizations, I meet them at hacker cons, and am fascinated by their stories. But institutionally, they are dumbed down the same level as these US-CERT reports, with the smart people marginalized.

There are two solutions to this problem. The first is that when the stupidity of what you do causes everyone to laugh at you, stop doing it. The second is to value technical expertise, empowering those who know what they are doing. Examples of what not to do are giving power to people like Obama’s cyberczar, Michael Daniels, who once claimed his lack of technical knowledge was a bonus, because it allowed him to see the strategic picture instead of getting distracted by details.

An Open Letter To Microsoft: A 64-bit OS is Better Than a 32-bit OS

Post Syndicated from Brian Wilson original https://www.backblaze.com/blog/64-bit-os-vs-32-bit-os/

Windows 32 Bit vs. 64 Bit

Editor’s Note: Our co-founder & CTO, Brian Wilson, was working on a few minor performance enhancements and bug fixes (Inherit Backup State is a lot faster now). We got a version of this note from him late one night and thought it was worth sharing.

There are a few absolutes in life – death, taxes, and that a 64-bit OS is better than a 32-bit OS. Moving over to a 64-bit OS allows your laptop to run BOTH the old compatible 32-bit processes and also the new 64-bit processes. In other words, there is zero downside (and there are gigantic upsides).

32-Bit vs. 64-Bit

The main gigantic upside of a 64-bit process is the ability to support more than 2 GBytes of RAM (pedantic people will say “4 GBytes”… but there are technicalities I don’t want to get into here). Since only 1.6% of Backblaze customers have 2 GBytes or less of RAM, the other 98.4% desperately need 64-bit support, period, end of story. And remember, there is no downside.

Because there is zero downside, the first time it could, Apple shipped with 64-bit OS support. Apple did not give customers the option of “turning off all 64-bit programs.” Apple first shipped 64-bit support in OS X 10.6 Tiger in 2009 (which also had 32-bit support, so there was zero downside to the decision).

This was so successful that Apple shipped all future Operating Systems configured to support both 64-bit and 32-bit processes. All of them. Customers no longer had an option to turn off 64-bit support.

As a result, less than 2/10ths of 1% of Backblaze Mac customers are running a computer that is so old that it can only run 32-bit programs. Despite those microscopic numbers we still loyally support this segment of our customers by providing a 32-bit only version of Backblaze’s backup client.

Apple vs. Microsoft

But let’s contrast the Apple approach with that of Microsoft. Microsoft offers a 64-bit OS in Windows 10 that runs all 64-bit and all 32-bit programs. This is a valid choice of an Operating System. The problem is Microsoft ALSO gives customers the option to install 32-bit Windows 10 which will not run 64-bit programs. That’s crazy.

Another advantage of the 64-bit version of Windows is security. There are a variety of security features such as ASLR (Address Space Layout Randomization) that work best in 64-bits. The 32-bit version is inherently less secure.

By choosing 32-bit Windows 10 a customer is literally choosing a lower performance, LOWER SECURITY, Operating System that is artificially hobbled to not run all software.

When one of our customers running 32-bit Windows 10 contacts Backblaze support, it is almost always a customer that did not realize the choice they were making when they installed 32-bit Windows 10. They did not have the information to understand what they are giving up. For example, we have seen customers that have purchased 8 GB of RAM, yet they had installed 32-bit Windows 10. Simply by their OS “choice”, they disabled about 3/4ths of the RAM that they paid for!

Let’s put some numbers around it: Approximately 4.3% of Backblaze customers with Windows machines are running a 32-bit version of Windows compared with just 2/10ths of 1% of our Apple customers. The Apple customers did not choose incorrectly, they just have not upgraded their operating system in the last 9 years. If we assume the same rate of “legitimate older computers not upgraded yet” for Microsoft users that means 4.1% of the Microsoft users made a fairly large mistake when they choose their Microsoft Operating System version.

Now some people would blame the customer because after all they made the OS selection. Microsoft offers the correct choice, which is 64-bit Windows 10. In fact, 95.7% of Backblaze customers running Windows made the correct choice. My issue is that Microsoft shouldn’t offer the 32-bit version at all.

And again, for the fifth time, you will not lose any 32-bit capabilities as the 64-bit operating system runs BOTH 32-bit applications and 64-bit applications. You only lose capabilities if you choose the 32-bit only Operating System.

This is how bad it is -> When Microsoft released Windows Vista in 2007 it was 64-bit and also ran all 32-bit programs flawlessly. So at that time I was baffled why Microsoft ALSO released Windows Vista in 32-bit only mode – a version that refused to run any 64-bit binaries. Then, again in Windows 7, they did the same thing and I thought I was losing my mind. And again with Windows 8! By Windows 10, I realized Microsoft may never stop doing this. No matter how much damage they cause, no matter what happens.

You might be asking -> why do I care? Why does Brian want Microsoft to stop shipping an Operating System that is likely only chosen by mistake? My problem is this: Backblaze, like any good technology vendor, wants to be easy to use and friendly. In this case, that means we need to quietly, invisibly, continue to support BOTH the 32-bit and the 64-bit versions of every Microsoft OS they release. And we’ll probably need to do this for at least 5 years AFTER Microsoft officially retires the 32-bit only version of their operating system.

Supporting both versions is complicated. The more data our customers have, the more momentarily RAM intensive some functions (like inheriting backup state) can be. The more data you have the bigger the problem. Backblaze customers who accidentally chose to disable 64-bit operations are then going to have problems. It means we have to explain to some customers that their operating system is the root cause of many performance issues in their technical lives. This is never a pleasant conversation.

I know this will probably fall on deaf ears, but Microsoft, for the sake of your customers and third party application developers like Backblaze, please stop shipping Operating Systems that disable 64-bit support. It is causing all of us a bunch of headaches we do not need.

The post An Open Letter To Microsoft: A 64-bit OS is Better Than a 32-bit OS appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

Secure API Access with Amazon Cognito Federated Identities, Amazon Cognito User Pools, and Amazon API Gateway

Post Syndicated from Ed Lima original https://aws.amazon.com/blogs/compute/secure-api-access-with-amazon-cognito-federated-identities-amazon-cognito-user-pools-and-amazon-api-gateway/

Ed Lima, Solutions Architect

 

Our identities are what define us as human beings. Philosophical discussions aside, it also applies to our day-to-day lives. For instance, I need my work badge to get access to my office building or my passport to travel overseas. My identity in this case is attached to my work badge or passport. As part of the system that checks my access, these documents or objects help define whether I have access to get into the office building or travel internationally.

This exact same concept can also be applied to cloud applications and APIs. To provide secure access to your application users, you define who can access the application resources and what kind of access can be granted. Access is based on identity controls that can confirm authentication (AuthN) and authorization (AuthZ), which are different concepts. According to Wikipedia:

 

The process of authorization is distinct from that of authentication. Whereas authentication is the process of verifying that “you are who you say you are,” authorization is the process of verifying that “you are permitted to do what you are trying to do.” This does not mean authorization presupposes authentication; an anonymous agent could be authorized to a limited action set.

Amazon Cognito allows building, securing, and scaling a solution to handle user management and authentication, and to sync across platforms and devices. In this post, I discuss the different ways that you can use Amazon Cognito to authenticate API calls to Amazon API Gateway and secure access to your own API resources.

 

Amazon Cognito Concepts

 

It’s important to understand that Amazon Cognito provides three different services:

Today, I discuss the use of the first two. One service doesn’t need the other to work; however, they can be configured to work together.
 

Amazon Cognito Federated Identities

 
To use Amazon Cognito Federated Identities in your application, create an identity pool. An identity pool is a store of user data specific to your account. It can be configured to require an identity provider (IdP) for user authentication, after you enter details such as app IDs or keys related to that specific provider.

After the user is validated, the provider sends an identity token to Amazon Cognito Federated Identities. In turn, Amazon Cognito Federated Identities contacts the AWS Security Token Service (AWS STS) to retrieve temporary AWS credentials based on a configured, authenticated IAM role linked to the identity pool. The role has appropriate IAM policies attached to it and uses these policies to provide access to other AWS services.

Amazon Cognito Federated Identities currently supports the IdPs listed in the following graphic.

 



Continue reading Secure API Access with Amazon Cognito Federated Identities, Amazon Cognito User Pools, and Amazon API Gateway

Online Platforms Should Collaborate to Ban Piracy and Terrorism, Report Suggests

Post Syndicated from Andy original https://torrentfreak.com/online-platforms-collaborate-ban-piracy-terrorism-report-suggests-170608/

With deep ties to the content industries, the Digital Citizens Alliance periodically produces reports on Internet piracy. It has published reports on cyberlockers and tried to blame Cloudflare for the spread of malware, for example.

One of the key themes pursued by DCA is that Internet piracy is inextricably linked to a whole bunch of other online evils and that tackling the former could deliver a much-needed body blow to the latter.

Its new report, titled ‘Trouble in Our Digital Midst’, takes this notion and runs with it, bundling piracy with everything from fake news to hacking, to malware and brand protection, to the sextortion of “young girls and boys” via their computer cameras.

The premise of the report is that cybercrime as a whole is undermining America’s trust in the Internet, noting that 64% of US citizens say that their trust in digital platforms has dropped in the last year. Given the topics under the spotlight, it doesn’t take long to see where this is going – Internet platforms like Google, Facebook and YouTube must tackle the problem.

“When asked, ‘In your opinion, are digital platforms doing enough to keep the Internet safe and trustworthy, or are do they need to do more?’ a staggering 75 percent responded that they need to do more to keep the Internet safe,” the report notes.

It’s abundantly clear that the report is mostly about piracy but a lot of effort has been expended to ensure that people support its general call for the Internet to be cleaned up. By drawing attention to things that even most pirates might find offensive, it’s easy to find more people in agreement.

“Nearly three-quarters of respondents see the pairing of brand name advertising with offensive online content – like ISIS/terrorism recruiting videos – as a threat to the continued trust and integrity of the Internet,” the report notes.

Of course, this is an incredibly sensitive topic. When big brand ads turned up next to terrorist recruiting videos on YouTube, there was an almighty stink, and rightly so. However, at every turn, the DCA report manages to weave the issue of piracy into the equation, noting that the problem includes the “$200 million in advertising that shows up on illegal content theft websites often unbeknownst to the brands.”

The overriding theme is that platforms like Google, Facebook, and YouTube should be able to tackle all of these problems in the same way. Filtering out a terrorist video is the same as removing a pirate movie. And making sure that ads for big brands don’t appear alongside terrorist videos will be just as easy as starving pirates of revenue, the suggestion goes.

But if terrorism doesn’t grind your gears, what about fake news?

“64 percent of Americans say that the Fake News issue has made them less likely to trust the Internet as a source of information,” the report notes.

At this juncture, Facebook gets a gentle pat on the back for dealing with fake news and employing 3,000 people to monitor for violent videos being posted to the network. This shows that the company “takes seriously” the potential harm bad actors pose to Internet safety. But in keeping with the theme running throughout the report, it’s clear DCA are carefully easing in the thin end of the wedge.

“We are at only the beginning of thinking through other kinds of illicit and illegal activity happening on digital platforms right now that we must gain or re-gain control over,” DCA writes.

Quite. In the very next sentence, the group goes on to warn about the sale of drugs and stolen credit cards, adding that the sale of illicit streaming devices (modified Kodi boxes etc) is actually an “insidious yet effective delivery mechanism to infect computers with malware such as Remote Access Trojans.”

Both Amazon and Facebook receive praise in the report for their recent banning (1,2) of augmented Kodi devices but their actions are actually framed as the companies protecting their own reputations, rather than the interests of the media groups that have been putting them under pressure.

“And though this issue underscores the challenges faced by digital platforms – not all of which act with the same level of responsibility – it also highlights the fact digital platforms can and will step up when their own brands are at stake,” the report reads.

But pirate content and Remote Access Trojans through Kodi boxes are only the beginning. Pirate sites are playing a huge part as well, DCA claims, with one in three “content theft websites” exposing people to identify theft, ransomware, and sextortion via “the computer cameras of young girls and boys.”

Worst still, if that was possible, the lack of policing by online platforms means that people are able to “showcase live sexual assaults, murders, and other illegal conduct.”

DCA says that with all this in mind, Americans are looking for online digital platforms to help them. The group claims that citizens need proactive protection from these ills and want companies like Facebook to take similar steps to those taken when warning consumers about fake news and violent content.

So what can be done to stop this tsunami of illegality? According to DCA, platforms like Google, Facebook, YouTube, and Twitter need to up their game and tackle the problem together.

“While digital platforms collaborate on policy and technical issues, there is no evidence that they are sharing information about the bad actors themselves. That enables criminals and bad actors to move seamlessly from platform to platform,” DCA writes.

“There are numerous examples of industry working together to identify and share information about exploitive behavior. For example, casinos share information about card sharks and cheats, and for decades the retail industry has shared information about fraudulent credit cards. A similar model would enable digital platforms and law enforcement to more quickly identify and combat those seeking to leverage the platforms to harm consumers.”

How this kind of collaboration could take place in the real world is open to interpretation but the DCA has a few suggestions of its own. Again, it doesn’t shy away from pulling people on side with something extremely offensive (in this case child pornography) in order to push what is clearly an underlying anti-piracy agenda.

“With a little help from engineers, digital platforms could create fingerprints of unlawful conduct that is shared across platforms to proactively block such conduct, as is done in a limited capacity with child pornography,” DCA explains.

“If these and other newly developed measures were adopted, digital platforms would have the information to enable them to make decisions whether to de-list or demote websites offering illicit goods and services, and the ability to stop the spread of illegal behavior that victimizes its users.”

The careful framing of the DCA report means that there’s something for everyone. If you don’t agree with them on tackling piracy, then their malware, fake news, or child exploitation angles might do the trick. It’s quite a clever strategy but one that the likes of Google, Facebook, and YouTube will recognize immediately.

And they need to – because apparently, it’s their job to sort all of this out. Good luck with that.

The full report can be found here (pdf)

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

AWS Greengrass – Run AWS Lambda Functions on Connected Devices

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/aws-greengrass-run-aws-lambda-functions-on-connected-devices/

I first told you about AWS Greengrass in the post that I published during re:Invent (AWS Greengrass – Ubiquitous Real-World Computing). We launched a limited preview of Greengrass at that time and invited you to sign up if you were interested.

As I noted at the time, many AWS customers want to collect and process data out in the field, where connectivity is often slow and sometimes either intermittent or unreliable. Greengrass allows them to extend the AWS programming model to small, simple, field-based devices. It builds on AWS IoT and AWS Lambda, and supports access to the ever-increasing variety of services that are available in the AWS Cloud.

Greengrass gives you access to compute, messaging, data caching, and syncing services that run in the field, and that do not depend on constant, high-bandwidth connectivity to an AWS Region. You can write Lambda functions in Python 2.7 and deploy them to your Greengrass devices from the cloud while using device shadows to maintain state. Your devices and peripherals can talk to each other using local messaging that does not pass through the cloud.

Now Generally Available
Today we are making Greengrass generally available in the US East (Northern Virginia) and US West (Oregon) Regions. During the preview, AWS customers were able to get hands-on experience with Greengrass and to start building applications and businesses around it. I’ll share a few of these early successes later in this post.

The Greengrass Core code runs on each device. It allows you to deploy and run Lambda applications on the device, supports local MQTT messaging across a secure network, and also ensures that conversations between devices and the cloud are made across secure connections. The Greengrass Core also supports secure, over-the-air software updates, including Lambda functions. It includes a message broker, a Lambda runtime, a Thing Shadows implementation, and a deployment agent. Greengrass Core and (optionally) other devices make up a Greengrass Group. The group includes configuration data, the list of devices and the identity of the Greengrass Core, a list of Lambda functions, and a set of subscriptions that define where the messages should go. All of this information is copied to the Greengrass core devices during the deployment process.

Your Lambda functions can use APIs in three distinct SDKs:

AWS SDK for Python – This SDK allows your code to interact with Amazon Simple Storage Service (S3), Amazon DynamoDB, Amazon Simple Queue Service (SQS), and other AWS services.

AWS IoT Device SDK – This SDK (available for Node.js, Python, Java, and C++) helps you to connect your hardware devices to AWS IoT. The C++ SDK has a few extra features including access to the Greengrass Discovery Service and support for root CA downloads.

AWS Greengrass Core SDK – This SDK provides APIs that allow local invocation of other Lambda functions, publish messages, and work with thing shadows.

You can run the Greengrass Core on x86 and ARM devices that have version 4.4.11 (or newer) of the Linux kernel, with the OverlayFS and user namespace features enabled. While most deployments of Greengrass will be targeted at specialized, industrial-grade hardware, you can also run the Greengrass Core on a Raspberry Pi or an EC2 instance for development and test purposes.

For this post, I used a Raspberry Pi attached to a BrickPi, connected to my home network via WiFi:

The Raspberry Pi, the BrickPi, the case, and all of the other parts are available in the BrickPi 3 Starter Kit. You will need some Linux command-line expertise and a decent amount of manual dexterity to put all of this together, but if I did it then you surely can.

Greengrass in Action
I can access Greengrass from the Console, API, or CLI. I’ll use the Console. The intro page of the Greengrass Console lets me define groups, add Greengrass Cores, and add devices to my groups:

I click on Get Started and then on Use easy creation:

Then I name my group:

And name my first Greengrass Core:

I’m ready to go, so I click on Create Group and Core:

This runs for a few seconds and then offers up my security resources (two keys and a certificate) for downloading, along with the Greengrass Core:

I download the security resources and put them in a safe place, and select and download the desired version of the Greengrass Core software (ARMv7l for my Raspberry Pi), and click on Finish.

Now I power up my Pi, and copy the security resources and the software to it (I put them in an S3 bucket and pulled them down with wget). Here’s my shell history at that point:

Following the directions in the user guide, I create a new user and group, run the rpi-update script, and install several packages including sqlite3 and openssl. After a couple of reboots, I am ready to proceed!

Next, still following the directions, I untar the Greengrass Core software and move the security resources to their final destination (/greengrass/configuration/certs), giving them generic names along the way. Here’s what the directory looks like:

The next step is to associate the core with an AWS IoT thing. I return to the Console, click through the group and the Greengrass Core, and find the Thing ARN:

I insert the names of the certificates and the Thing ARN into the config.json file, and also fill in the missing sections of the iotHost and ggHost:

I start the Greengrass demon (this was my second attempt; I had a typo in one of my path names the first time around):

After all of this pleasant time at the command line (taking me back to my Unix v7 and BSD 4.2 days), it is time to go visual once again! I visit my AWS IoT dashboard and see that my Greengrass Core is making connections to IoT:

I go to the Lambda Console and create a Lambda function using the Python 2.7 runtime (the IAM role does not matter here):

I publish the function in the usual way and, hop over to the Greengrass Console, click on my group, and choose to add a Lambda function:

Then I choose the version to deploy:

I also configure the function to be long-lived instead of on-demand:

My code will publish messages to AWS IoT, so I create a subscription by specifying the source and destination:

I set up a topic filter (hello/world) on the subscription as well:

I confirm my settings and save my subscription and I am just about ready to deploy my code. I revisit my group, click on Deployments, and choose Deploy from the Actions menu:

I choose Automatic detection to move forward:

Since this is my first deployment, I need to create a service-level role that gives Greengrass permission to access other AWS services. I simply click on Grant permission:

I can see the status of each deployment:

The code is now running on my Pi! It publishes messages to topic hello/world; I can see them by going to the IoT Console, clicking on Test, and subscribing to the topic:

And here are the messages:

With all of the setup work taken care of, I can do iterative development by uploading, publishing, and deploying new versions of my code. I plan to use the BrickPi to control some LEGO Technic motors and to publish data collected from some sensors. Stay tuned for that post!

Greengrass Pricing
You can run the Greengrass Core on three devices free for one year as part of the AWS Free Tier. At the next level (3 to 10,000 devices) two options are available:

  • Pay as You Go – $0.16 per month per device.
  • Annual Commitment – $1.49 per year per device, a 17.5% savings.

If you want to run the Greengrass Core on more than 10,000 devices or make a longer commitment, please get in touch with us; details on all pricing models are on the Greengrass Pricing page.

Jeff;

Friday Squid Blogging: Squid as Prey

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/06/friday_squid_bl_579.html

There’s lots of video of squid as undersea predators. This is one of the few instances of squid as prey (from a deep submersible in the Pacific):

“We saw brittle stars capturing a squid from the water column while it was swimming. I didn’t know that was possible. And then there was a tussle among the brittle stars to see who got to have the squid,” says France.

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

Read my blog posting guidelines here.

Build a Serverless Architecture to Analyze Amazon CloudFront Access Logs Using AWS Lambda, Amazon Athena, and Amazon Kinesis Analytics

Post Syndicated from Rajeev Srinivasan original https://aws.amazon.com/blogs/big-data/build-a-serverless-architecture-to-analyze-amazon-cloudfront-access-logs-using-aws-lambda-amazon-athena-and-amazon-kinesis-analytics/

Nowadays, it’s common for a web server to be fronted by a global content delivery service, like Amazon CloudFront. This type of front end accelerates delivery of websites, APIs, media content, and other web assets to provide a better experience to users across the globe.

The insights gained by analysis of Amazon CloudFront access logs helps improve website availability through bot detection and mitigation, optimizing web content based on the devices and browser used to view your webpages, reducing perceived latency by caching of popular object closer to its viewer, and so on. This results in a significant improvement in the overall perceived experience for the user.

This blog post provides a way to build a serverless architecture to generate some of these insights. To do so, we analyze Amazon CloudFront access logs both at rest and in transit through the stream. This serverless architecture uses Amazon Athena to analyze large volumes of CloudFront access logs (on the scale of terabytes per day), and Amazon Kinesis Analytics for streaming analysis.

The analytic queries in this blog post focus on three common use cases:

  1. Detection of common bots using the user agent string
  2. Calculation of current bandwidth usage per Amazon CloudFront distribution per edge location
  3. Determination of the current top 50 viewers

However, you can easily extend the architecture described to power dashboards for monitoring, reporting, and trigger alarms based on deeper insights gained by processing and analyzing the logs. Some examples are dashboards for cache performance, usage and viewer patterns, and so on.

Following we show a diagram of this architecture.

Prerequisites

Before you set up this architecture, install the AWS Command Line Interface (AWS CLI) tool on your local machine, if you don’t have it already.

Setup summary

The following steps are involved in setting up the serverless architecture on the AWS platform:

  1. Create an Amazon S3 bucket for your Amazon CloudFront access logs to be delivered to and stored in.
  2. Create a second Amazon S3 bucket to receive processed logs and store the partitioned data for interactive analysis.
  3. Create an Amazon Kinesis Firehose delivery stream to batch, compress, and deliver the preprocessed logs for analysis.
  4. Create an AWS Lambda function to preprocess the logs for analysis.
  5. Configure Amazon S3 event notification on the CloudFront access logs bucket, which contains the raw logs, to trigger the Lambda preprocessing function.
  6. Create an Amazon DynamoDB table to look up partition details, such as partition specification and partition location.
  7. Create an Amazon Athena table for interactive analysis.
  8. Create a second AWS Lambda function to add new partitions to the Athena table based on the log delivered to the processed logs bucket.
  9. Configure Amazon S3 event notification on the processed logs bucket to trigger the Lambda partitioning function.
  10. Configure Amazon Kinesis Analytics application for analysis of the logs directly from the stream.

ETL and preprocessing

In this section, we parse the CloudFront access logs as they are delivered, which occurs multiple times in an hour. We filter out commented records and use the user agent string to decipher the browser name, the name of the operating system, and whether the request has been made by a bot. For more details on how to decipher the preceding information based on the user agent string, see user-agents 1.1.0 in the Python documentation.

We use the Lambda preprocessing function to perform these tasks on individual rows of the access log. On successful completion, the rows are pushed to an Amazon Kinesis Firehose delivery stream to be persistently stored in an Amazon S3 bucket, the processed logs bucket.

To create a Firehose delivery stream with a new or existing S3 bucket as the destination, follow the steps described in Create a Firehose Delivery Stream to Amazon S3 in the S3 documentation. Keep most of the default settings, but select an AWS Identity and Access Management (IAM) role that has write access to your S3 bucket and specify GZIP compression. Name the delivery stream CloudFrontLogsToS3.

Another pre-requisite for this setup is to create an IAM role that provides the necessary permissions our AWS Lambda function to get the data from S3, process it, and deliver it to the CloudFrontLogsToS3 delivery stream.

Let’s use the AWS CLI to create the IAM role using the following the steps:

  1. Create the IAM policy (lambda-exec-policy) for the Lambda execution role to use.
  2. Create the Lambda execution role (lambda-cflogs-exec-role) and assign the service to use this role.
  3. Attach the policy created in step 1 to the Lambda execution role.

To download the policy document to your local machine, type the following command.

aws s3 cp s3://aws-bigdata-blog/artifacts/Serverless-CF-Analysis/preprocessiong-lambda/lambda-exec-policy.json  <path_on_your_local_machine>

To download the assume policy document to your local machine, type the following command.

aws s3 cp s3://aws-bigdata-blog/artifacts/Serverless-CF-Analysis/preprocessiong-lambda/assume-lambda-policy.json  <path_on_your_local_machine>

Following is the lambda-exec-policy.json file, which is the IAM policy used by the Lambda execution role.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "CloudWatchAccess",
            "Effect": "Allow",
            "Action": [
                "logs:CreateLogGroup",
                "logs:CreateLogStream",
                "logs:PutLogEvents"
            ],
            "Resource": "arn:aws:logs:*:*:*"
        },
        {
            "Sid": "S3Access",
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:PutObject"
            ],
            "Resource": [
                "arn:aws:s3:::*"
            ]
        },
        {
            "Sid": "FirehoseAccess",
            "Effect": "Allow",
            "Action": [
                "firehose:ListDeliveryStreams",
                "firehose:PutRecord",
                "firehose:PutRecordBatch"
            ],
            "Resource": [
                "arn:aws:firehose:*:*:deliverystream/CloudFrontLogsToS3"
            ]
        }
    ]
}

To create the IAM policy used by Lambda execution role, type the following command.

aws iam create-policy --policy-name lambda-exec-policy --policy-document file://<path>/lambda-exec-policy.json

To create the AWS Lambda execution role and assign the service to use this role, type the following command.

aws iam create-role --role-name lambda-cflogs-exec-role --assume-role-policy-document file://<path>/assume-lambda-policy.json

Following is the assume-lambda-policy.json file, to grant Lambda permission to assume a role.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "Service": "lambda.amazonaws.com"
      },
      "Action": "sts:AssumeRole"
    }
  ]
}

To attach the policy (lambda-exec-policy) created to the AWS Lambda execution role (lambda-cflogs-exec-role), type the following command.

aws iam attach-role-policy --role-name lambda-cflogs-exec-role --policy-arn arn:aws:iam::<your-account-id>:policy/lambda-exec-policy

Now that we have created the CloudFrontLogsToS3 Firehose delivery stream and the lambda-cflogs-exec-role IAM role for Lambda, the next step is to create a Lambda preprocessing function.

This Lambda preprocessing function parses the CloudFront access logs delivered into the S3 bucket and performs a few transformation and mapping operations on the data. The Lambda function adds descriptive information, such as the browser and the operating system that were used to make this request based on the user agent string found in the logs. The Lambda function also adds information about the web distribution to support scenarios where CloudFront access logs are delivered to a centralized S3 bucket from multiple distributions. With the solution in this blog post, you can get insights across distributions and their edge locations.

Use the Lambda Management Console to create a new Lambda function with a Python 2.7 runtime and the s3-get-object-python blueprint. Open the console, and on the Configure triggers page, choose the name of the S3 bucket where the CloudFront access logs are delivered. Choose Put for Event type. For Prefix, type the name of the prefix, if any, for the folder where CloudFront access logs are delivered, for example cloudfront-logs/. To invoke Lambda to retrieve the logs from the S3 bucket as they are delivered, select Enable trigger.

Choose Next and provide a function name to identify this Lambda preprocessing function.

For Code entry type, choose Upload a file from Amazon S3. For S3 link URL, type https.amazonaws.com//preprocessing-lambda/pre-data.zip. In the section, also create an environment variable with the key KINESIS_FIREHOSE_STREAM and a value with the name of the Firehose delivery stream as CloudFrontLogsToS3.

Choose lambda-cflogs-exec-role as the IAM role for the Lambda function, and type prep-data.lambda_handler for the value for Handler.

Choose Next, and then choose Create Lambda.

Table creation in Amazon Athena

In this step, we will build the Athena table. Use the Athena console in the same region and create the table using the query editor.

CREATE EXTERNAL TABLE IF NOT EXISTS cf_logs (
  logdate date,
  logtime string,
  location string,
  bytes bigint,
  requestip string,
  method string,
  host string,
  uri string,
  status bigint,
  referrer string,
  useragent string,
  uriquery string,
  cookie string,
  resulttype string,
  requestid string,
  header string,
  csprotocol string,
  csbytes string,
  timetaken bigint,
  forwardedfor string,
  sslprotocol string,
  sslcipher string,
  responseresulttype string,
  protocolversion string,
  browserfamily string,
  osfamily string,
  isbot string,
  filename string,
  distribution string
)
PARTITIONED BY(year string, month string, day string, hour string)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
LOCATION 's3://<pre-processing-log-bucket>/prefix/';

Creation of the Athena partition

A popular website with millions of requests each day routed using Amazon CloudFront can generate a large volume of logs, on the order of a few terabytes a day. We strongly recommend that you partition your data to effectively restrict the amount of data scanned by each query. Partitioning significantly improves query performance and substantially reduces cost. The Lambda partitioning function adds the partition information to the Athena table for the data delivered to the preprocessed logs bucket.

Before delivering the preprocessed Amazon CloudFront logs file into the preprocessed logs bucket, Amazon Kinesis Firehose adds a UTC time prefix in the format YYYY/MM/DD/HH. This approach supports multilevel partitioning of the data by year, month, date, and hour. You can invoke the Lambda partitioning function every time a new processed Amazon CloudFront log is delivered to the preprocessed logs bucket. To do so, configure the Lambda partitioning function to be triggered by an S3 Put event.

For a website with millions of requests, a large number of preprocessed logs can be delivered multiple times in an hour—for example, at the interval of one each second. To avoid querying the Athena table for partition information every time a preprocessed log file is delivered, you can create an Amazon DynamoDB table for fast lookup.

Based on the year, month, data and hour in the prefix of the delivered log, the Lambda partitioning function checks if the partition specification exists in the Amazon DynamoDB table. If it doesn’t, it’s added to the table using an atomic operation, and then the Athena table is updated.

Type the following command to create the Amazon DynamoDB table.

aws dynamodb create-table --table-name athenapartitiondetails \
--attribute-definitions AttributeName=PartitionSpec,AttributeType=S \
--key-schema AttributeName=PartitionSpec,KeyType=HASH \
--provisioned-throughput ReadCapacityUnits=100,WriteCapacityUnits=100

Here the following is true:

  • PartitionSpec is the hash key and is a representation of the partition signature—for example, year=”2017”; month=”05”; day=”15”; hour=”10”.
  • Depending on the rate at which the processed log files are delivered to the processed log bucket, you might have to increase the ReadCapacityUnits and WriteCapacityUnits values, if these are throttled.

The other attributes besides PartitionSpec are the following:

  • PartitionPath – The S3 path associated with the partition.
  • PartitionType – The type of partition used (Hour, Month, Date, Year, or ALL). In this case, ALL is used.

Next step is to create the IAM role to provide permissions for the Lambda partitioning function. You require permissions to do the following:

  1. Look up and write partition information to DynamoDB.
  2. Alter the Athena table with new partition information.
  3. Perform Amazon CloudWatch logs operations.
  4. Perform Amazon S3 operations.

To download the policy document to your local machine, type following command.

aws s3 cp s3://aws-bigdata-blog/artifacts/Serverless-CF-Analysis/partitioning-lambda/lambda-partition-function-execution-policy.json  <path_on_your_local_machine>

To download the assume policy document to your local machine, type the following command.

aws s3 cp s3://aws-bigdata-blog/artifacts/Serverless-CF-Analysis/partitioning-lambda/assume-lambda-policy.json <path_on_your_local_machine>

To create the Lambda execution role and assign the service to use this role, type the following command.

aws iam create-role --role-name lambda-cflogs-exec-role --assume-role-policy-document file://<path>/assume-lambda-policy.json

Let’s use the AWS CLI to create the IAM role using the following three steps:

  1. Create the IAM policy(lambda-partition-exec-policy) used by the Lambda execution role.
  2. Create the Lambda execution role (lambda-partition-execution-role)and assign the service to use this role.
  3. Attach the policy created in step 1 to the Lambda execution role.

To create the IAM policy used by Lambda execution role, type the following command.

aws iam create-policy --policy-name lambda-partition-exec-policy --policy-document file://<path>/lambda-partition-function-execution-policy.json

To create the Lambda execution role and assign the service to use this role, type the following command.

aws iam create-role --role-name lambda-partition-execution-role --assume-role-policy-document file://<path>/assume-lambda-policy.json

To attach the policy (lambda-partition-exec-policy) created to the AWS Lambda execution role (lambda-partition-execution-role), type the following command.

aws iam attach-role-policy --role-name lambda-partition-execution-role --policy-arn arn:aws:iam::<your-account-id>:policy/lambda-partition-exec-policy

Following is the lambda-partition-function-execution-policy.json file, which is the IAM policy used by the Lambda execution role.

{
    "Version": "2012-10-17",
    "Statement": [
      	{
            	"Sid": "DDBTableAccess",
            	"Effect": "Allow",
            	"Action": "dynamodb:PutItem"
            	"Resource": "arn:aws:dynamodb*:*:table/athenapartitiondetails"
        	},
        	{
            	"Sid": "S3Access",
            	"Effect": "Allow",
            	"Action": [
                		"s3:GetBucketLocation",
                		"s3:GetObject",
                		"s3:ListBucket",
                		"s3:ListBucketMultipartUploads",
                		"s3:ListMultipartUploadParts",
                		"s3:AbortMultipartUpload",
                		"s3:PutObject"
            	],
          		"Resource":"arn:aws:s3:::*"
		},
	              {
		      "Sid": "AthenaAccess",
      		"Effect": "Allow",
      		"Action": [ "athena:*" ],
      		"Resource": [ "*" ]
	      },
        	{
            	"Sid": "CloudWatchLogsAccess",
            	"Effect": "Allow",
            	"Action": [
                		"logs:CreateLogGroup",
                		"logs:CreateLogStream",
             	   	"logs:PutLogEvents"
            	],
            	"Resource": "arn:aws:logs:*:*:*"
        	}
    ]
}

Download the .jar file containing the Java deployment package to your local machine.

aws s3 cp s3://aws-bigdata-blog/artifacts/Serverless-CF-Analysis/partitioning-lambda/aws-lambda-athena-1.0.0.jar <path_on_your_local_machine>

From the AWS Management Console, create a new Lambda function with Java8 as the runtime. Select the Blank Function blueprint.

On the Configure triggers page, choose the name of the S3 bucket where the preprocessed logs are delivered. Choose Put for the Event Type. For Prefix, type the name of the prefix folder, if any, where preprocessed logs are delivered by Firehose—for example, out/. For Suffix, type the name of the compression format that the Firehose stream (CloudFrontLogToS3) delivers the preprocessed logs —for example, gz. To invoke Lambda to retrieve the logs from the S3 bucket as they are delivered, select Enable Trigger.

Choose Next and provide a function name to identify this Lambda partitioning function.

Choose Java8 for Runtime for the AWS Lambda function. Choose Upload a .ZIP or .JAR file for the Code entry type, and choose Upload to upload the downloaded aws-lambda-athena-1.0.0.jar file.

Next, create the following environment variables for the Lambda function:

  • TABLE_NAME – The name of the Athena table (for example, cf_logs).
  • PARTITION_TYPE – The partition to be created based on the Athena table for the logs delivered to the sub folders in S3 bucket based on Year, Month, Date, Hour, or Set this to ALL to use Year, Month, Date, and Hour.
  • DDB_TABLE_NAME – The name of the DynamoDB table holding partition information (for example, athenapartitiondetails).
  • ATHENA_REGION – The current AWS Region for the Athena table to construct the JDBC connection string.
  • S3_STAGING_DIR – The Amazon S3 location where your query output is written. The JDBC driver asks Athena to read the results and provide rows of data back to the user (for example, s3://<bucketname>/<folder>/).

To configure the function handler and IAM, for Handler copy and paste the name of the handler: com.amazonaws.services.lambda.CreateAthenaPartitionsBasedOnS3EventWithDDB::handleRequest. Choose the existing IAM role, lambda-partition-execution-role.

Choose Next and then Create Lambda.

Interactive analysis using Amazon Athena

In this section, we analyze the historical data that’s been collected since we added the partitions to the Amazon Athena table for data delivered to the preprocessing logs bucket.

Scenario 1 is robot traffic by edge location.

SELECT COUNT(*) AS ct, requestip, location FROM cf_logs
WHERE isbot='True'
GROUP BY requestip, location
ORDER BY ct DESC;

Scenario 2 is total bytes transferred per distribution for each edge location for your website.

SELECT distribution, location, SUM(bytes) as totalBytes
FROM cf_logs
GROUP BY location, distribution;

Scenario 3 is the top 50 viewers of your website.

SELECT requestip, COUNT(*) AS ct  FROM cf_logs
GROUP BY requestip
ORDER BY ct DESC;

Streaming analysis using Amazon Kinesis Analytics

In this section, you deploy a stream processing application using Amazon Kinesis Analytics to analyze the preprocessed Amazon CloudFront log streams. This application analyzes directly from the Amazon Kinesis Stream as it is delivered to the preprocessing logs bucket. The stream queries in section are focused on gaining the following insights:

  • The IP address of the bot, identified by its Amazon CloudFront edge location, that is currently sending requests to your website. The query also includes the total bytes transferred as part of the response.
  • The total bytes served per distribution per population for your website.
  • The top 10 viewers of your website.

To download the firehose-access-policy.json file, type the following.

aws s3 cp s3://aws-bigdata-blog/artifacts/Serverless-CF-Analysis/kinesisanalytics/firehose-access-policy.json  <path_on_your_local_machine>

To download the kinesisanalytics-policy.json file, type the following.

aws s3 cp s3://aws-bigdata-blog/artifacts/Serverless-CF-Analysis/kinesisanalytics/assume-kinesisanalytics-policy.json <path_on_your_local_machine>

Before we create the Amazon Kinesis Analytics application, we need to create the IAM role to provide permission for the analytics application to access Amazon Kinesis Firehose stream.

Let’s use the AWS CLI to create the IAM role using the following three steps:

  1. Create the IAM policy(firehose-access-policy) for the Lambda execution role to use.
  2. Create the Lambda execution role (ka-execution-role) and assign the service to use this role.
  3. Attach the policy created in step 1 to the Lambda execution role.

Following is the firehose-access-policy.json file, which is the IAM policy used by Kinesis Analytics to read Firehose delivery stream.

{
    "Version": "2012-10-17",
    "Statement": [
      	{
    	"Sid": "AmazonFirehoseAccess",
    	"Effect": "Allow",
    	"Action": [
       	"firehose:DescribeDeliveryStream",
        	"firehose:Get*"
    	],
    	"Resource": [
              "arn:aws:firehose:*:*:deliverystream/CloudFrontLogsToS3”
       ]
     }
}

Following is the assume-kinesisanalytics-policy.json file, to grant Amazon Kinesis Analytics permissions to assume a role.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "Service": "kinesisanalytics.amazonaws.com"
      },
      "Action": "sts:AssumeRole"
    }
  ]
}

To create the IAM policy used by Analytics access role, type the following command.

aws iam create-policy --policy-name firehose-access-policy --policy-document file://<path>/firehose-access-policy.json

To create the Analytics execution role and assign the service to use this role, type the following command.

aws iam attach-role-policy --role-name ka-execution-role --policy-arn arn:aws:iam::<your-account-id>:policy/firehose-access-policy

To attach the policy (irehose-access-policy) created to the Analytics execution role (ka-execution-role), type the following command.

aws iam attach-role-policy --role-name ka-execution-role --policy-arn arn:aws:iam::<your-account-id>:policy/firehose-access-policy

To deploy the Analytics application, first download the configuration file and then modify ResourceARN and RoleARN for the Amazon Kinesis Firehose input configuration.

"KinesisFirehoseInput": { 
    "ResourceARN": "arn:aws:firehose:<region>:<account-id>:deliverystream/CloudFrontLogsToS3", 
    "RoleARN": "arn:aws:iam:<account-id>:role/ka-execution-role"
}

To download the Analytics application configuration file, type the following command.

aws s3 cp s3://aws-bigdata-blog/artifacts/Serverless-CF-Analysis//kinesisanalytics/kinesis-analytics-app-configuration.json <path_on_your_local_machine>

To deploy the application, type the following command.

aws kinesisanalytics create-application --application-name "cf-log-analysis" --cli-input-json file://<path>/kinesis-analytics-app-configuration.json

To start the application, type the following command.

aws kinesisanalytics start-application --application-name "cf-log-analysis" --input-configuration Id="1.1",InputStartingPositionConfiguration={InputStartingPosition="NOW"}

SQL queries using Amazon Kinesis Analytics

Scenario 1 is a query for detecting bots for sending request to your website detection for your website.

-- Create output stream, which can be used to send to a destination
CREATE OR REPLACE STREAM "BOT_DETECTION" (requesttime TIME, destribution VARCHAR(16), requestip VARCHAR(64), edgelocation VARCHAR(64), totalBytes BIGINT);
-- Create pump to insert into output 
CREATE OR REPLACE PUMP "BOT_DETECTION_PUMP" AS INSERT INTO "BOT_DETECTION"
--
SELECT STREAM 
    STEP("CF_LOG_STREAM_001"."request_time" BY INTERVAL '1' SECOND) as requesttime,
    "distribution_name" as distribution,
    "request_ip" as requestip, 
    "edge_location" as edgelocation, 
    SUM("bytes") as totalBytes
FROM "CF_LOG_STREAM_001"
WHERE "is_bot" = true
GROUP BY "request_ip", "edge_location", "distribution_name",
STEP("CF_LOG_STREAM_001"."request_time" BY INTERVAL '1' SECOND),
STEP("CF_LOG_STREAM_001".ROWTIME BY INTERVAL '1' SECOND);

Scenario 2 is a query for total bytes transferred per distribution for each edge location for your website.

-- Create output stream, which can be used to send to a destination
CREATE OR REPLACE STREAM "BYTES_TRANSFFERED" (requesttime TIME, destribution VARCHAR(16), edgelocation VARCHAR(64), totalBytes BIGINT);
-- Create pump to insert into output 
CREATE OR REPLACE PUMP "BYTES_TRANSFFERED_PUMP" AS INSERT INTO "BYTES_TRANSFFERED"
-- Bytes Transffered per second per web destribution by edge location
SELECT STREAM 
    STEP("CF_LOG_STREAM_001"."request_time" BY INTERVAL '1' SECOND) as requesttime,
    "distribution_name" as distribution,
    "edge_location" as edgelocation, 
    SUM("bytes") as totalBytes
FROM "CF_LOG_STREAM_001"
GROUP BY "distribution_name", "edge_location", "request_date",
STEP("CF_LOG_STREAM_001"."request_time" BY INTERVAL '1' SECOND),
STEP("CF_LOG_STREAM_001".ROWTIME BY INTERVAL '1' SECOND);

Scenario 3 is a query for the top 50 viewers for your website.

-- Create output stream, which can be used to send to a destination
CREATE OR REPLACE STREAM "TOP_TALKERS" (requestip VARCHAR(64), requestcount DOUBLE);
-- Create pump to insert into output 
CREATE OR REPLACE PUMP "TOP_TALKERS_PUMP" AS INSERT INTO "TOP_TALKERS"
-- Top Ten Talker
SELECT STREAM ITEM as requestip, ITEM_COUNT as requestcount FROM TABLE(TOP_K_ITEMS_TUMBLING(
  CURSOR(SELECT STREAM * FROM "CF_LOG_STREAM_001"),
  'request_ip', -- name of column in single quotes
  50, -- number of top items
  60 -- tumbling window size in seconds
  )
);

Conclusion

Following the steps in this blog post, you just built an end-to-end serverless architecture to analyze Amazon CloudFront access logs. You analyzed these both in interactive and streaming mode, using Amazon Athena and Amazon Kinesis Analytics respectively.

By creating a partition in Athena for the logs delivered to a centralized bucket, this architecture is optimized for performance and cost when analyzing large volumes of logs for popular websites that receive millions of requests. Here, we have focused on just three common use cases for analysis, sharing the analytic queries as part of the post. However, you can extend this architecture to gain deeper insights and generate usage reports to reduce latency and increase availability. This way, you can provide a better experience on your websites fronted with Amazon CloudFront.

In this blog post, we focused on building serverless architecture to analyze Amazon CloudFront access logs. Our plan is to extend the solution to provide rich visualization as part of our next blog post.


About the Authors

Rajeev Srinivasan is a Senior Solution Architect for AWS. He works very close with our customers to provide big data and NoSQL solution leveraging the AWS platform and enjoys coding . In his spare time he enjoys riding his motorcycle and reading books.

 

Sai Sriparasa is a consultant with AWS Professional Services. He works with our customers to provide strategic and tactical big data solutions with an emphasis on automation, operations & security on AWS. In his spare time, he follows sports and current affairs.

 

 


Related

Analyzing VPC Flow Logs with Amazon Kinesis Firehose, Amazon Athena, and Amazon QuickSight

DevOps Cafe Episode 71

Post Syndicated from DevOpsCafeAdmin original http://devopscafe.org/show/2017/5/25/devops-cafe-episode-71.html

Ordering Up Some Transformation

John and Damon pick Courtney Kissler’s brain on the techniques that enable her to be a hands-on technology leader with a track record for getting teams to find and fix what is getting in the way. 

 

 

 

  

Direct download

Follow John Willis on Twitter: @botchagalupe
Follow Damon Edwards on Twitter: @damonedwards 
Follow Courtney Kissler on Twitter: @ladyhock

Notes:

 

Please tweet or leave comments or questions below and we’ll read them on the show!

DevOps Cafe Episode 71 – Courtney Kissler

Post Syndicated from DevOpsCafeAdmin original http://devopscafe.org/show/2017/5/25/devops-cafe-episode-71-courtney-kissler.html

Ordering Up Some Transformation

John and Damon pick Courtney Kissler’s brain on the techniques that enable her to be a hands-on technology leader with a track record for getting teams to find and fix what is getting in the way. 

 

 

 

  

Direct download

Follow John Willis on Twitter: @botchagalupe
Follow Damon Edwards on Twitter: @damonedwards 
Follow Courtney Kissler on Twitter: @ladyhock

Notes:

 

Please tweet or leave comments or questions below and we’ll read them on the show!

Ransomware and the Internet of Things

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/05/ransomware_and_.html

As devastating as the latest widespread ransomware attacks have been, it’s a problem with a solution. If your copy of Windows is relatively current and you’ve kept it updated, your laptop is immune. It’s only older unpatched systems on your computer that are vulnerable.

Patching is how the computer industry maintains security in the face of rampant Internet insecurity. Microsoft, Apple and Google have teams of engineers who quickly write, test and distribute these patches, updates to the codes that fix vulnerabilities in software. Most people have set up their computers and phones to automatically apply these patches, and the whole thing works seamlessly. It isn’t a perfect system, but it’s the best we have.

But it is a system that’s going to fail in the “Internet of things”: everyday devices like smart speakers, household appliances, toys, lighting systems, even cars, that are connected to the web. Many of the embedded networked systems in these devices that will pervade our lives don’t have engineering teams on hand to write patches and may well last far longer than the companies that are supposed to keep the software safe from criminals. Some of them don’t even have the ability to be patched.

Fast forward five to 10 years, and the world is going to be filled with literally tens of billions of devices that hackers can attack. We’re going to see ransomware against our cars. Our digital video recorders and web cameras will be taken over by botnets. The data that these devices collect about us will be stolen and used to commit fraud. And we’re not going to be able to secure these devices.

Like every other instance of product safety, this problem will never be solved without considerable government involvement.

For years, I have been calling for more regulation to improve security in the face of this market failure. In the short term, the government can mandate that these devices have more secure default configurations and the ability to be patched. It can issue best-practice regulations for critical software and make software manufacturers liable for vulnerabilities. It’ll be expensive, but it will go a long way toward improved security.

But it won’t be enough to focus only on the devices, because these things are going to be around and on the Internet much longer than the two to three years we use our phones and computers before we upgrade them. I expect to keep my car for 15 years, and my refrigerator for at least 20 years. Cities will expect the networks they’re putting in place to last at least that long. I don’t want to replace my digital thermostat ever again. Nor, if I ever need one, do I want a surgeon to ever have to go back in to replace my computerized heart defibrillator in order to fix a software bug.

No amount of regulation can force companies to maintain old products, and it certainly can’t prevent companies from going out of business. The future will contain billions of orphaned devices connected to the web that simply have no engineers able to patch them.

Imagine this: The company that made your Internet-enabled door lock is long out of business. You have no way to secure yourself against the ransomware attack on that lock. Your only option, other than paying, and paying again when it’s reinfected, is to throw it away and buy a new one.

Ultimately, we will also need the network to block these attacks before they get to the devices, but there again the market will not fix the problem on its own. We need additional government intervention to mandate these sorts of solutions.

None of this is welcome news to a government that prides itself on minimal intervention and maximal market forces, but national security is often an exception to this rule. Last week’s cyberattacks have laid bare some fundamental vulnerabilities in our computer infrastructure and serve as a harbinger. There’s a lot of good research into robust solutions, but the economic incentives are all misaligned. As politically untenable as it is, we need government to step in to create the market forces that will get us out of this mess.

This essay previously appeared in the New York Times. Yes, I know I’m repeating myself.

How to Control TLS Ciphers in Your AWS Elastic Beanstalk Application by Using AWS CloudFormation

Post Syndicated from Paco Hope original https://aws.amazon.com/blogs/security/how-to-control-tls-ciphers-in-your-aws-elastic-beanstalk-application-by-using-aws-cloudformation/

Securing data in transit is critical to the integrity of transactions on the Internet. Whether you log in to an account with your user name and password or give your credit card details to a retailer, you want your data protected as it travels across the Internet from place to place. One of the protocols in widespread use to protect data in transit is Transport Layer Security (TLS). Every time you access a URL that begins with “https” instead of just “http”, you are using a TLS-secured connection to a website.

To demonstrate that your application has a strong TLS configuration, you can use services like the one provided by SSL Labs. There are also open source, command-line-oriented TLS testing programs such as testssl.sh (which I do not cover in this post) and sslscan (which I cover later in this post). The goal of testing your TLS configuration is to provide evidence that weak cryptographic ciphers are disabled in your TLS configuration and only strong ciphers are enabled. In this blog post, I show you how to control the TLS security options for your secure load balancer in AWS CloudFormation, pass the TLS certificate and host name for your secure AWS Elastic Beanstalk application to the CloudFormation script as parameters, and then confirm that only strong TLS ciphers are enabled on the launched application by testing it with SSLLabs.

Background

In some situations, it’s not enough to simply turn on TLS with its default settings and call it done. Over the years, a number of vulnerabilities have been discovered in the TLS protocol itself with codenames such as CRIME, POODLE, and Logjam. Though some vulnerabilities were in specific implementations, such as OpenSSL, others were vulnerabilities in the Secure Sockets Layer (SSL) or TLS protocol itself.

The only way to avoid some TLS vulnerabilities is to ensure your web server uses only the latest version of TLS. Some organizations want to limit their TLS configuration to the highest possible security levels to satisfy company policies, regulatory requirements, or other information security requirements. In practice, such limitations usually mean using TLS version 1.2 (at the time of this writing, TLS 1.3 is in the works) and using only strong cryptographic ciphers. Note that forcing a high-security TLS connection in this manner limits which types of devices can connect to your web server. I address this point at the end of this post.

The default TLS configuration in most web servers is compatible with the broadest set of clients (such as web browsers, mobile devices, and point-of-sale systems). As a result, older ciphers and protocol versions are usually enabled. This is true for the Elastic Load Balancing load balancer that is created in your Elastic Beanstalk application as well as for web server software such as Apache and nginx.  For example, TLS versions 1.0 and 1.1 are enabled in addition to 1.2. The RC4 cipher is permitted, even though that cipher is too weak for the most demanding security requirements. If your application needs to prioritize the security of connections over compatibility with legacy devices, you must adjust the TLS encryption settings on your application. The solution in this post helps you make those adjustments.

Prerequisites for the solution

Before you implement this solution, you must have a few prerequisites in place:

  1. You must have a hosted zone in Amazon Route 53 where the name of the secure application will be created. I use example.com as my domain name in this post and assume that I host example.com publicly in Route 53. To learn more about creating and hosting a zone publicly in Route 53, see Working with Public Hosted Zones.
  2. You must choose a name to be associated with the secure app. In this case, I use secure.example.com as the DNS name to be associated with the secure app. This means that I’m trying to create an Elastic Beanstalk application whose URL will be https://secure.example.com/.
  3. You must have a TLS certificate hosted in AWS Certificate Manager (ACM). This certificate must be issued with the name you decided in Step 2. If you are new to ACM, see Getting Started. If you are already familiar with ACM, request a certificate and get its Amazon Resource Name (ARN).Look up the ARN for the certificate that you created by opening the ACM console. The ARN looks something like: arn:aws:acm:eu-west-1:111122223333:certificate/12345678-abcd-1234-abcd-1234abcd1234.

Implementing the solution

You can use two approaches to control the TLS ciphers used by your load balancer: one is to use a predefined protocol policy from AWS, and the other is to write your own protocol policy that lists exactly which ciphers should be enabled. There are many ciphers and options that can be set, so the appropriate AWS predefined policy is often the simplest policy to use. If you have to comply with an information security policy that requires enabling or disabling specific ciphers, you will probably find it easiest to write a custom policy listing only the ciphers that are acceptable to your requirements.

AWS released two predefined TLS policies on March 10, 2017: ELBSecurityPolicy-TLS-1-1-2017-01 and ELBSecurityPolicy-TLS-1-2-2017-01. These policies restrict TLS negotiations to TLS 1.1 and 1.2, respectively. You can find a good comparison of the ciphers that these policies enable and disable in the HTTPS listener documentation for Elastic Load Balancing. If your requirements are simply “support TLS 1.1 and later” or “support TLS 1.2 and later,” those AWS predefined cipher policies are the best place to start. If you need to control your cipher choice with a custom policy, I show you in this post which lines of the CloudFormation template to change.

Download the predefined policy CloudFormation template

Many AWS customers rely on CloudFormation to launch their AWS resources, including their Elastic Beanstalk applications. To change the ciphers and protocol versions supported on your load balancer, you must put those options in a CloudFormation template. You can store your site’s TLS certificate in ACM and create the corresponding DNS alias record in the correct zone in Route 53.

To start, download the CloudFormation template that I have provided for this blog post, or deploy the template directly in your environment. This template creates a CloudFormation stack in your default VPC that contains two resources: an Elastic Beanstalk application that deploys a standard sample PHP application, and a Route 53 record in a hosted zone. This CloudFormation template selects the AWS predefined policy called ELBSecurityPolicy-TLS-1-2-2017-01 and deploys it.

Launching the sample application from the CloudFormation console

In the CloudFormation console, choose Create Stack. You can either upload the template through your browser, or load the template into an Amazon S3 bucket and type the S3 URL in the Specify an Amazon S3 template URL box.

After you click Next, you will see that there are three parameters defined: CertificateARN, ELBHostName, and HostedDomainName. Set the CertificateARN parameter to the ARN of the certificate you want to use for your application. Set the ELBHostName parameter to the hostname part of the URL. For example, if your URL were https://secure.example.com/, the HostedDomainName parameter would be example.com and the ELBHostName parameter would be secure.

For the sample application, choose Next and then choose Create, and the CloudFormation stack will be created. For your own applications, you might need to set other options such as a database, VPC options, or Amazon SNS notifications. For more details, see AWS Elastic Beanstalk Environment Configuration. To deploy an application other than our sample PHP application, create your own application source bundle.

Launching the sample application from the command line

In addition to launching the sample application from the console, you can specify the parameters from the command line. Because the template uses parameters, you can launch multiple copies of the application, specifying different parameters for each copy. To launch the application from a Linux command line with the AWS CLI, insert the correct values for your application, as shown in the following command.

aws cloudformation create-stack --stack-name "SecureSampleApplication" \
--template-url https://<URL of your CloudFormation template in S3> \
--parameters ParameterKey=CertificateARN,ParameterValue=<Your ARN> \
ParameterKey=ELBHostName,ParameterValue=<Your Host Name> \
ParameterKey=HostedDomainName,ParameterValue=<Your Domain Name>

When that command exits, it prints the StackID of the stack it created. Save that StackID for later so that you can fetch the stack’s outputs from the command line.

Using a custom cipher specification

If you want to specify your own cipher choices, you can use the same CloudFormation template and change two lines. Let’s assume your information security policies require you to disable any ciphers that use Cipher Block Chaining (CBC) mode encryption. These ciphers are enabled in the ELBSecurityPolicy-TLS-1-2-2017-01 managed policy, so to satisfy that security requirement, you have to modify the CloudFormation template to use your own protocol policy.

In the template, locate the three lines that define the TLSHighPolicy.

- Namespace:  aws:elb:policies:TLSHighPolicy
OptionName: SSLReferencePolicy
Value:      ELBSecurityPolicy-TLS-1-2-2017-01

Change the OptionName and Value for the TLSHighPolicy. Instead of referring to the AWS predefined policy by name, explicitly list all the ciphers you want to use. Change those three lines so they look like the following.

- Namespace: aws:elb:policies:TLSHighPolicy
OptionName: SSLProtocols
Value:  Protocol-TLSv1.2,Server-Defined-Cipher-Order,ECDHE-ECDSA-AES256-GCM-SHA384,ECDHE-ECDSA-AES128-GCM-SHA256,ECDHE-RSA-AES256-GCM-SHA384,ECDHE-RSA-AES128-GCM-SHA256

This protocol policy stipulates that the load balancer should:

  • Negotiate connections using only TLS 1.2.
  • Ignore any attempts by the client (for example, the web browser or mobile device) to negotiate a weaker cipher.
  • Accept four specific, strong combinations of cipher and key exchange—and nothing else.

The protocol policy enables only TLS 1.2, strong ciphers that do not use CBC mode encryption, and strong key exchange.

Connect to the secure application

When your CloudFormation stack is in the CREATE_COMPLETED state, you will find three outputs:

  1. The public DNS name of the load balancer
  2. The secure URL that was created
  3. TestOnSSLLabs output that contains a direct link for testing your configuration

You can either enter the secure URL in a web browser (for example, https://secure.example.com/), or click the link in the Outputs to open your sample application and see the demo page. Note that you must use HTTPS—this template has disabled HTTP on port 80 and only listens with HTTPS on port 443.

If you launched your application through the command line, you can view the CloudFormation outputs using the command line as well. You need to know the StackId of the stack you launched and insert it in the following stack-name parameter.

aws cloudformation describe-stacks --stack-name "<ARN of Your Stack>" \
--query 'Stacks[0].Outputs'

Test your application over the Internet with SSLLabs

The easiest way to confirm that the load balancer is using the secure ciphers that we chose is to enter the URL of the load balancer in the form on SSL Labs’ SSL Server Test page. If you do not want the name of your load balancer to be shared publicly on SSLLabs.com, select the Do not show the results on the boards check box. After a minute or two of testing, SSLLabs gives you a detailed report of every cipher it tried and how your load balancer responded. This test simulates many devices that might connect to your website, including mobile phones, desktop web browsers, and software libraries such as Java and OpenSSL. The report tells you whether these clients would be able to connect to your application successfully.

Assuming all went well, you should receive an A grade for the sample application. The biggest contributors to the A grade are:

  • Supporting only TLS 1.2, and not TLS 1.1, TLS 1.0, or SSL 3.0
  • Supporting only strong ciphers such as AES, and not weaker ciphers such as RC4
  • Having an X.509 public key certificate issued correctly by ACM

How to test your application privately with sslscan

You might not be able to reach your Elastic Beanstalk application from the Internet because it might be in a private subnet that is only accessible internally. If you want to test the security of your load balancer’s configuration privately, you can use one of the open source command-line tools such as sslscan. You can install and run the sslscan command on any Amazon EC2 Linux instance or even from your own laptop. Be sure that the Elastic Beanstalk application you want to test will accept an HTTPS connection from your Amazon Linux EC2 instance or from your laptop.

The easiest way to get sslscan on an Amazon Linux EC2 instance is to:

  1. Enable the Extra Packages for Enterprise Linux (EPEL) repository.
  2. Run sudo yum install sslscan.
  3. After the command runs successfully, run sslscan secure.example.com to scan your application for supported ciphers.

The results are similar to Qualys’ results at SSLLabs.com, but the sslscan tool does not summarize and evaluate the results to assign a grade. It just reports whether your application accepted a connection using the cipher that it tried. You must decide for yourself whether that set of accepted connections represents the right level of security for your application. If you have been asked to build a secure load balancer that meets specific security requirements, the output from sslscan helps to show how the security of your application is configured.

The following sample output shows a small subset of the total output of the sslscan tool.

Accepted TLS12 256 bits AES256-GCM-SHA384
Accepted TLS12 256 bits AES256-SHA256
Accepted TLS12 256 bits AES256-SHA
Rejected TLS12 256 bits CAMELLIA256-SHA
Failed TLS12 256 bits PSK-AES256-CBC-SHA
Rejected TLS12 128 bits ECDHE-RSA-AES128-GCM-SHA256
Rejected TLS12 128 bits ECDHE-ECDSA-AES128-GCM-SHA256
Rejected TLS12 128 bits ECDHE-RSA-AES128-SHA256

An Accepted connection is one that was successful: the load balancer and the client were both able to use the indicated cipher. Failed and Rejected connections are connections whose load balancer would not accept the level of security that the client was requesting. As a result, the load balancer closed the connection instead of communicating insecurely. The difference between Failed and Rejected is based one whether the TLS connection was closed cleanly.

Comparing the two policies

The main difference between our custom policy and the AWS predefined policy is whether or not CBC ciphers are accepted. The test results with both policies are identical except for the results shown in the following table. The only change in the policy, and therefore the only change in the results, is that the cipher suites using CBC ciphers have been disabled.

Cipher Suite Name Encryption Algorithm Key Size (bits) ELBSecurityPolicy-TLS-1-2-2017-01 Custom Policy
ECDHE-RSA-AES256-GCM-SHA384 AESGCM 256 Enabled Enabled
ECDHE-RSA-AES256-SHA384 AES 256 Enabled Disabled
AES256-GCM-SHA384 AESGCM 256 Enabled Disabled
AES256-SHA256 AES 256 Enabled Disabled
ECDHE-RSA-AES128-GCM-SHA256 AESGCM 128 Enabled Enabled
ECDHE-RSA-AES128-SHA256 AES 128 Enabled Disabled
AES128-GCM-SHA256 AESGCM 128 Enabled Disabled
AES128-SHA256 AES 128 Enabled Disabled

Strong ciphers and compatibility

The custom policy described in the previous section prevents legacy devices and older versions of software and web browsers from connecting. The output at SSLLabs provides a list of devices and applications (such as Internet Explorer 10 on Windows 7) that cannot connect to an application that uses the TLS policy. By design, the load balancer will refuse to connect to a device that is unable to negotiate a connection at the required levels of security. Users who use legacy software and devices will see different errors, depending on which device or software they use (for example, Internet Explorer on Windows, Chrome on Android, or a legacy mobile application). The error messages will be some variation of “connection failed” because the Elastic Load Balancer closes the connection without responding to the user’s request. This behavior can be problematic for websites that must be accessible to older desktop operating systems or older mobile devices.

If you need to support legacy devices, adjust the TLSHighPolicy in the CloudFormation template. For example, if you need to support web browsers on Windows 7 systems (and you cannot enable TLS 1.2 support on those systems), you can change the policy to enable TLS 1.1. To do this, change the value of SSLReferencePolicy to ELBSecurityPolicy-TLS-1-1-2017-01.

Enabling legacy protocol versions such as TLS version 1.1 will allow older devices to connect, but then the application may not be compliant with the information security policies or business requirements that require strong ciphers.

Conclusion

Using Elastic Beanstalk, Route 53, and ACM can help you launch secure applications that are designed to not only protect data but also meet regulatory compliance requirements and your information security policies. The TLS policy, either custom or predefined, allows you to control exactly which cryptographic ciphers are enabled on your Elastic Load Balancer. The TLS test results provide you with clear evidence you can use to demonstrate compliance with security policies or requirements. The parameters in this post’s CloudFormation template also make it adaptable and reusable for multiple applications. You can use the same template to launch different applications on different secure URLs by simply changing the parameters that you pass to the template.

If you have comments about this post, submit them in the “Comments” section below. If you have questions about or issues implementing this solution, start a new thread on the CloudFormation forum.

– Paco

How to Update AWS CloudHSM Devices and Client Instances to the Software and Firmware Versions Supported by AWS

Post Syndicated from Tracy Pierce original https://aws.amazon.com/blogs/security/how-to-update-aws-cloudhsm-devices-and-client-instances-to-the-software-and-firmware-versions-supported-by-aws/

As I explained in my previous Security Blog post, a hardware security module (HSM) is a hardware device designed with the security of your data and cryptographic key material in mind. It is tamper-resistant hardware that prevents unauthorized users from attempting to pry open the device, plug in any extra devices to access data or keys such as subtokens, or damage the outside housing. The HSM device AWS CloudHSM offers is the Luna SA 7000 (also called Safenet Network HSM 7000), which is created by Gemalto. Depending on the firmware version you install, many of the security properties of these HSMs will have been validated under Federal Information Processing Standard (FIPS) 140-2, a standard issued by the National Institute of Standards and Technology (NIST) for cryptography modules. These standards are in place to protect the integrity and confidentiality of the data stored on cryptographic modules.

To help ensure its continued use, functionality, and support from AWS, we suggest that you update your AWS CloudHSM device software and firmware as well as the client instance software to current versions offered by AWS. As of the publication of this blog post, the current non-FIPS-validated versions are 5.4.9/client, 5.3.13/software, and 6.20.2/firmware, and the current FIPS-validated versions are 5.4.9/client, 5.3.13/software, and 6.10.9/firmware. (The firmware version determines FIPS validation.) It is important to know your current versions before updating so that you can follow the correct update path.

In this post, I demonstrate how to update your current CloudHSM devices and client instances so that you are using the most current versions of software and firmware. If you contact AWS Support for CloudHSM hardware and application issues, you will be required to update to these supported versions before proceeding. Also, any newly provisioned CloudHSM devices will use these supported software and firmware versions only, and AWS does not offer “downgrade options.

Note: Before you perform any updates, check with your local CloudHSM administrator and application developer to verify that these updates will not conflict with your current applications or architecture.

Overview of the update process

To update your client and CloudHSM devices, you must use both update paths offered by AWS. The first path involves updating the software on your client instance, also known as a control instance. Following the second path updates the software first and then the firmware on your CloudHSM devices. The CloudHSM software must be updated before the firmware because of the firmware’s dependencies on the software in order to work appropriately.

As I demonstrate in this post, the correct update order is:

  1. Updating your client instance
  2. Updating your CloudHSM software
  3. Updating your CloudHSM firmware

To update your client instance, you must have the private SSH key you created when you first set up your client environment. This key is used to connect via SSH protocol on port 22 of your client instance. If you have more than one client instance, you must repeat this connection and update process on each of them. The following diagram shows the flow of an SSH connection from your local network to your client instances in the AWS Cloud.

Diagram that shows the flow of an SSH connection from your local network to your client instances in the AWS Cloud

After you update your client instance to the most recent software (5.3.13), you then must update the CloudHSM device software and firmware. First, you must initiate an SSH connection from any one client instance to each CloudHSM device, as illustrated in the following diagram. A successful SSH connection will have you land at the Luna shell, denoted by lunash:>. Second, you must be able to initiate a Secure Copy (SCP) of files to each device from the client instance. Because the software and firmware updates require an elevated level of privilege, you must have the Security Officer (SO) password that you created when you initialized your CloudHSM devices.

Diagram illustrating the initiation of an SSH connection from any one client instance to each CloudHSM device

After you have completed all updates, you can receive enhanced troubleshooting assistance from AWS, if you need it. When new versions of software and firmware are released, AWS performs extensive testing to ensure your smooth transition from version to version.

Detailed guidance for updating your client instance, CloudHSM software, and CloudHSM firmware

1.  Updating your client instance

Let’s start by updating your client instances. My client instance and CloudHSM devices are in the eu-west-1 region, but these steps work the same in any AWS region. Because Gemalto offers client instances in both Linux and Windows, I will cover steps to update both. I will start with Linux. Please note that all commands should be run as the “root” user.

Updating the Linux client

  1. SSH from your local network into the client instance. You can do this from Linux or Windows. Typically, you would do this from the directory where you have stored your private SSH key by using a command like the following command in a terminal or PuTTY This initiates the SSH connection by pointing to the path of your SSH key and denoting the user name and IP address of your client instance.
    ssh –i /Users/Bob/Keys/CloudHSM_SSH_Key.pem [email protected]

  1. After the SSH connection is established, you must stop all applications and services on the instance that are using the CloudHSM device. This is required because you are removing old software and installing new software in its place. After you have stopped all applications and services, you can move on to remove the existing version of the client software.
    /usr/safenet/lunaclient/bin/uninstall.sh

This command will remove the old client software, but will not remove your configuration file or certificates. These will be saved in the Chrystoki.conf file of your /etc directory and your usr/safenet/lunaclient/cert directory. Do not delete these files because you will lose the configuration of your CloudHSM devices and client connections.

  1. Download the new client software package: cloudhsm-safenet-client. Double-click it to extract the archive.
    SafeNet-Luna-client-5-4-9/linux/64/install.sh

    Make sure you choose the Luna SA option when presented with it. Because the directory where your certificates are installed is the same, you do not need to copy these certificates to another directory. You do, however, need to ensure that the Chrystoki.conf file, located at /etc/Chrystoki.conf, has the same path and name for the certificates as when you created them. (The path or names should not have changed, but you should still verify they are same as before the update.)

  1. Check to ensure that the PATH environment variable points to the directory, /usr/safenet/lunaclient/bin, to ensure no issues when you restart applications and services. The update process for your Linux client Instance is now complete.

Updating the Windows client

Use the following steps to update your Windows client instances:

  1. Use Remote Desktop Protocol (RDP) from your local network into the client instance. You can accomplish this with the RDP application of your choice.
  2. After you establish the RDP connection, stop all applications and services on the instance that are using the CloudHSM device. This is required because you will remove old software and install new software in its place or overwrite If your client software version is older than 5.4.1, you need to completely remove it and all patches by using Programs and Features in the Windows Control Panel. If your client software version is 5.4.1 or newer, proceed without removing the software. Your configuration file will remain intact in the crystoki.ini file of your C:\Program Files\SafeNet\Lunaclient\ directory. All certificates are preserved in the C:\Program Files\SafeNet\Lunaclient\cert\ directory. Again, do not delete these files, or you will lose all configuration and client connection data.
  3. After you have completed these steps, download the new client software: cloudhsm-safenet-client. Extract the archive from the downloaded file, and launch the SafeNet-Luna-client-5-4-9\win\64\Lunaclient.msi Choose the Luna SA option when it is presented to you. Because the directory where your certificates are installed is the same, you do not need to copy these certificates to another directory. You do, however, need to ensure that the crystoki.ini file, which is located at C:\Program Files\SafeNet\Lunaclient\crystoki.ini, has the same path and name for the certificates as when you created them. (The path and names should not have changed, but you should still verify they are same as before the update.)
  4. Make one last check to ensure the PATH environment variable points to the directory C:\Program Files\SafeNet\Lunaclient\ to help ensure no issues when you restart applications and services. The update process for your Windows client instance is now complete.

2.  Updating your CloudHSM software

Now that your clients are up to date with the most current software version, it’s time to move on to your CloudHSM devices. A few important notes:

  • Back up your data to a Luna SA Backup device. AWS does not sell or support the Luna SA Backup devices, but you can purchase them from Gemalto. We do, however, offer the steps to back up your data to a Luna SA Backup device. Do not update your CloudHSM devices without backing up your data first.
  • If the names of your clients used for Network Trust Link Service (NTLS) connections has a capital “T” as the eighth character, the client will not work after this update. This is because of a Gemalto naming convention. Before upgrading, ensure you modify your client names accordingly. The NTLS connection uses a two-way digital certificate authentication and SSL data encryption to protect sensitive data transmitted between your CloudHSM device and the client Instances.
  • The syslog configuration for the CloudHSM devices will be lost. After the update is complete, notify AWS Support and we will update the configuration for you.

Now on to updating the software versions. There are actually three different update paths to follow, and I will cover each. Depending on the current software versions on your CloudHSM devices, you might need to follow all three or just one.

Updating the software from version 5.1.x to 5.1.5

If you are running any version of the software older than 5.1.5, you must first update to version 5.1.5 before proceeding. To update to version 5.1.5:

  1. Stop all applications and services that access the CloudHSM device.
  2. Download the Luna SA software update package.
  3. Extract all files from the archive.
  4. Run the following command from your client instance to copy the lunasa_update-5.1.5-2.spkg file to the CloudHSM device.
    $ scp –I <private_key_file> lunasa_update-5.1.5-2.spkg manager@<hsm_ip_address>:

    <private_key_file> is the private portion of your SSH key pair and <hsm_ip_address> is the IP address of your CloudHSM elastic network interface (ENI). The ENI is the network endpoint that permits access to your CloudHSM device. The IP address was supplied to you when the CloudHSM device was provisioned.

  1. Use the following command to connect to your CloudHSM device and log in with your Security Officer (SO) password.
    $ ssh –I <private_key_file> manager@<hsm_ip_address>
    
    lunash:> hsm login

  1. Run the following commands to verify and then install the updated Luna SA software package.
    lunash:> package verify lunasa_update-5.1.5-2.spkg –authcode <auth_code>
    
    lunash:> package update lunasa_update-5.1.5-2.spkg –authcode <auth_code>

    The value you will use for <auth_code> is contained in the lunasa_update-5.1.5-2.auth file found in the 630-010165-018_reva.tar archive you downloaded in Step 2.

  1. Reboot the CloudHSM device by running the following command.
    lunash:> sysconf appliance reboot

When all the steps in this section are completed, you will have updated your CloudHSM software to version 5.1.5. You can now move on to update to version 5.3.10.

Updating the software to version 5.3.10

You can update to version 5.3.10 only if you are currently running version 5.1.5. To update to version 5.3.10:

  1. Stop all applications and services that access the CloudHSM device.
  2. Download the v 5.3.10 Luna SA software update package.
  3. Extract all files from the archive.
  4. Run the following command to copy the lunasa_update-5.3.10-7.spkg file to the CloudHSM device.
    $ scp –i <private_key_file> lunasa_update-5.3.10-7.spkg manager@<hsm_ip_address>:

    <private_key_file> is the private portion of your SSH key pair and <hsm_ip_address> is the IP address of your CloudHSM ENI.

  1. Run the following command to connect to your CloudHSM device and log in with your SO password.
    $ ssh –i <private_key_file> manager@<hsm_ip_address>
    
    lunash:> hsm login

  1. Run the following commands to verify and then install the updated Luna SA software package.
    lunash:> package verify lunasa_update-5.3.10-7.spkg –authcode <auth_code>
    
    lunash:> package update lunasa_update-5.3.10-7.spkg –authcode <auth_code>

The value you will use for <auth_code> is contained in the lunasa_update-5.3.10-7.auth file found in the SafeNet-Luna-SA-5-3-10.zip archive you downloaded in Step 2.

  1. Reboot the CloudHSM device by running the following command.
    lunash:> sysconf appliance reboot

When all the steps in this section are completed, you will have updated your CloudHSM software to version 5.3.10. You can now move on to update to version 5.3.13.

Note: Do not configure your applog settings at this point; you must first update the software to version 5.3.13 in the following step.

Updating the software to version 5.3.13

You can update to version 5.3.13 only if you are currently running version 5.3.10. If you are not already running version 5.3.10, follow the two update paths mentioned previously in this section.

To update to version 5.3.13:

  1. Stop all applications and services that access the CloudHSM device.
  2. Download the Luna SA software update package.
  3. Extract all files from the archive.
  4. Run the following command to copy the lunasa_update-5.3.13-1.spkg file to the CloudHSM device.
    $ scp –i <private_key_file> lunasa_update-5.3.13-1.spkg manager@<hsm_ip_address>

<private_key_file> is the private portion of your SSH key pair and <hsm_ip_address> is the IP address of your CloudHSM ENI.

  1. Run the following command to connect to your CloudHSM device and log in with your SO password.
    $ ssh –i <private_key_file> manager@<hsm_ip_address>
    
    lunash:> hsm login

  1. Run the following commands to verify and then install the updated Luna SA software package.
    lunash:> package verify lunasa_update-5.3.13-1.spkg –authcode <auth_code>
    
    lunash:> package update lunasa_update-5.3.13-1.spkg –authcode <auth_code>

The value you will use for <auth_code> is contained in the lunasa_update-5.3.13-1.auth file found in the SafeNet-Luna-SA-5-3-13.zip archive that you downloaded in Step 2.

  1. When updating to this software version, the option to update the firmware also is offered. If you do not require a version of the firmware validated under FIPS 140-2, accept the firmware update to version 6.20.2. If you do require a version of the firmware validated under FIPS 140-2, do not accept the firmware update and instead update by using the steps in the next section, “Updating your CloudHSM FIPS 140-2 validated firmware.”
  2. After updating the CloudHSM device, reboot it by running the following command.
    lunash:> sysconf appliance reboot

  1. Disable NTLS IP checking on the CloudHSM device so that it can operate within its VPC. To do this, run the following command.
    lunash:> ntls ipcheck disable

When all the steps in this section are completed, you will have updated your CloudHSM software to version 5.3.13. If you don’t need the FIPS 140-2 validated firmware, you will have also updated the firmware to version 6.20.2. If you do need the FIPS 140-2 validated firmware, proceed to the next section.

3.  Updating your CloudHSM FIPS 140-2 validated firmware

To update the FIPS 140-2 validated version of the firmware to 6.10.9, use the following steps:

  1. Download version 6.10.9 of the firmware package.
  2. Extract all files from the archive.
  3. Run the following command to copy the 630-010430-010_SPKG_LunaFW_6.10.9.spkg file to the CloudHSM device.
    $ scp –i <private_key_file> 630-010430-010_SPKG_LunaFW_6.10.9.spkg manager@<hsm_ip_address>:

<private_key_file> is the private portion of your SSH key pair, and <hsm_ip_address> is the IP address of your CloudHSM ENI.

  1. Run the following command to connect to your CloudHSM device and log in with your SO password.
    $ ssh –i <private_key_file> manager#<hsm_ip_address>
    
    lunash:> hsm login

  1. Run the following commands to verify and then install the updated Luna SA firmware package.
    lunash:> package verify 630-010430-010_SPKG_LunaFW_6.10.9.spkg –authcode <auth_code>
    
    lunash:> package update 630-010430-010_SPKG_LunaFW_6.10.9.spkg –authcode <auth_code>

The value you will use for <auth_code> is contained in the 630-010430-010_SPKG_LunaFW_6.10.9.auth file found in the 630-010430-010_SPKG_LunaFW_6.10.9.zip archive that you downloaded in Step 1.

  1. Run the following command to update the firmware of the CloudHSM devices.
    lunash:> hsm update firmware

  1. After you have updated the firmware, reboot the CloudHSM devices to complete the installation.
    lunash:> sysconf appliance reboot

Summary

In this blog post, I walked you through how to update your existing CloudHSM devices and clients so that they are using supported client, software, and firmware versions. Per AWS Support and CloudHSM Terms and Conditions, your devices and clients must use the most current supported software and firmware for continued troubleshooting assistance. Software and firmware versions regularly change based on customer use cases and requirements. Because AWS tests and validates all updates from Gemalto, you must install all updates for firmware and software by using our package links described in this post and elsewhere in our documentation.

If you have comments about this blog post, submit them in the “Comments” section below. If you have questions about implementing this solution, please start a new thread on the CloudHSM forum.

– Tracy