Tag Archives: firewall

Another Chinese Developer Arrested For Selling VPN Access

Post Syndicated from Andy original https://torrentfreak.com/another-chinese-developer-arrested-for-selling-vpn-access-170920/

Early 2017, China’s Ministry of Industry and Information Technology said that due to Internet technologies and services expanding in a “disorderly” fashion, regulation would be needed to restore order.

Announcing measures to strengthen network information security management, the government said it would begin a “nationwide Internet network access services clean-up.”

Months later, it became evident that authorities were taking an even more aggressive stance towards Virtual Private Networks, since these allow citizens to evade the so-called Great Firewall of China. The government said that in future, operating such a service without a corresponding telecommunications license would constitute an offense.

Now, according to local news reports, a citizen who apparently failed to heed the government’s warnings has fallen foul of the new rules.

The Nanjinger reports that a software developer, named as Mr. Zhao from Nanjing, was arrested August 21 for contravening the new laws on VPN licensing.

Zhao reportedly told authorities he’d initially set up the VPN for his own use in order to access content hosted abroad, which presumably involved circumventing China’s firewall. However, once he recognized there was a demand, the developer decided to let others use the service for a small fee.

The prices he asked were indeed small – just $1.50 per month or around $18 for two years’ service. Based on reported total revenues of just $164 for the entire business, it’s possible he had around 100 customers, or indeed far fewer.

What will happen to the man isn’t clear but he’ll be keen to avoid the fate of Deng Jiewei, who previously ran a small website through which he’d sold around $2,100 worth of VPN software.

Early September it was reported that the 26-year-old had been sentenced to nine months in prison for offering tools that enable people to “visit foreign websites that cannot be accessed via a domestic (mainland) IP address.”

These cases are part of an emerging pattern in China centered around the supply and sale of VPN products and services. Back in July, Apple began banning VPN applications from its iOS store in China. The company reported that the apps contained content that is illegal locally, thereby violating the company’s policies.

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

New Network Load Balancer – Effortless Scaling to Millions of Requests per Second

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/new-network-load-balancer-effortless-scaling-to-millions-of-requests-per-second/

Elastic Load Balancing (ELB)) has been an important part of AWS since 2009, when it was launched as part of a three-pack that also included Auto Scaling and Amazon CloudWatch. Since that time we have added many features, and also introduced the Application Load Balancer. Designed to support application-level, content-based routing to applications that run in containers, Application Load Balancers pair well with microservices, streaming, and real-time workloads.

Over the years, our customers have used ELB to support web sites and applications that run at almost any scale — from simple sites running on a T2 instance or two, all the way up to complex applications that run on large fleets of higher-end instances and handle massive amounts of traffic. Behind the scenes, ELB monitors traffic and automatically scales to meet demand. This process, which includes a generous buffer of headroom, has become quicker and more responsive over the years and works well even for our customers who use ELB to support live broadcasts, “flash” sales, and holidays. However, in some situations such as instantaneous fail-over between regions, or extremely spiky workloads, we have worked with our customers to pre-provision ELBs in anticipation of a traffic surge.

New Network Load Balancer
Today we are introducing the new Network Load Balancer (NLB). It is designed to handle tens of millions of requests per second while maintaining high throughput at ultra low latency, with no effort on your part. The Network Load Balancer is API-compatible with the Application Load Balancer, including full programmatic control of Target Groups and Targets. Here are some of the most important features:

Static IP Addresses – Each Network Load Balancer provides a single IP address for each VPC subnet in its purview. If you have targets in a subnet in us-west-2a and other targets in a subnet in us-west-2c, NLB will create and manage two IP addresses (one per subnet); connections to that IP address will spread traffic across the instances in the subnet. You can also specify an existing Elastic IP for each subnet for even greater control. With full control over your IP addresses, Network Load Balancer can be used in situations where IP addresses need to be hard-coded into DNS records, customer firewall rules, and so forth.

Zonality – The IP-per-subnet feature reduces latency with improved performance, improves availability through isolation and fault tolerance and makes the use of Network Load Balancers transparent to your client applications. Network Load Balancers also attempt to route a series of requests from a particular source to targets in a single subnet while still allowing automatic failover.

Source Address Preservation – With Network Load Balancer, the original source IP address and source ports for the incoming connections remain unmodified, so application software need not support X-Forwarded-For, proxy protocol, or other workarounds. This also means that normal firewall rules, including VPC Security Groups, can be used on targets.

Long-running Connections – NLB handles connections with built-in fault tolerance, and can handle connections that are open for months or years, making them a great fit for IoT, gaming, and messaging applications.

Failover – Powered by Route 53 health checks, NLB supports failover between IP addresses within and across regions.

Creating a Network Load Balancer
I can create a Network Load Balancer opening up the EC2 Console, selecting Load Balancers, and clicking on Create Load Balancer:

I choose Network Load Balancer and click on Create, then enter the details. I can choose an Elastic IP address for each subnet in the target VPC and I can tag the Network Load Balancer:

Then I click on Configure Routing and create a new target group. I enter a name, and then choose the protocol and port. I can also set up health checks that go to the traffic port or to the alternate of my choice:

Then I click on Register Targets and the EC2 instances that will receive traffic, and click on Add to registered:

I make sure that everything looks good and then click on Create:

The state of my new Load Balancer is provisioning, switching to active within a minute or so:

For testing purposes, I simply grab the DNS name of the Load Balancer from the console (in practice I would use Amazon Route 53 and a more friendly name):

Then I sent it a ton of traffic (I intended to let it run for just a second or two but got distracted and it created a huge number of processes, so this was a happy accident):

$ while true;
> do
>   wget http://nlb-1-6386cc6bf24701af.elb.us-west-2.amazonaws.com/phpinfo2.php &
> done

A more disciplined test would use a tool like Bees with Machine Guns, of course!

I took a quick break to let some traffic flow and then checked the CloudWatch metrics for my Load Balancer, finding that it was able to handle the sudden onslaught of traffic with ease:

I also looked at my EC2 instances to see how they were faring under the load (really well, it turns out):

It turns out that my colleagues did run a more disciplined test than I did. They set up a Network Load Balancer and backed it with an Auto Scaled fleet of EC2 instances. They set up a second fleet composed of hundreds of EC2 instances, each running Bees with Machine Guns and configured to generate traffic with highly variable request and response sizes. Beginning at 1.5 million requests per second, they quickly turned the dial all the way up, reaching over 3 million requests per second and 30 Gbps of aggregate bandwidth before maxing out their test resources.

Choosing a Load Balancer
As always, you should consider the needs of your application when you choose a load balancer. Here are some guidelines:

Network Load Balancer (NLB) – Ideal for load balancing of TCP traffic, NLB is capable of handling millions of requests per second while maintaining ultra-low latencies. NLB is optimized to handle sudden and volatile traffic patterns while using a single static IP address per Availability Zone.

Application Load Balancer (ALB) – Ideal for advanced load balancing of HTTP and HTTPS traffic, ALB provides advanced request routing that supports modern application architectures, including microservices and container-based applications.

Classic Load Balancer (CLB) – Ideal for applications that were built within the EC2-Classic network.

For a side-by-side feature comparison, see the Elastic Load Balancer Details table.

If you are currently using a Classic Load Balancer and would like to migrate to a Network Load Balancer, take a look at our new Load Balancer Copy Utility. This Python tool will help you to create a Network Load Balancer with the same configuration as an existing Classic Load Balancer. It can also register your existing EC2 instances with the new load balancer.

Pricing & Availability
Like the Application Load Balancer, pricing is based on Load Balancer Capacity Units, or LCUs. Billing is $0.006 per LCU, based on the highest value seen across the following dimensions:

  • Bandwidth – 1 GB per LCU.
  • New Connections – 800 per LCU.
  • Active Connections – 100,000 per LCU.

Most applications are bandwidth-bound and should see a cost reduction (for load balancing) of about 25% when compared to Application or Classic Load Balancers.

Network Load Balancers are available today in all AWS commercial regions except China (Beijing), supported by AWS CloudFormation, Auto Scaling, and Amazon ECS.

Jeff;

 

Chinese Man Jailed For Nine Months For Selling VPN Software

Post Syndicated from Andy original https://torrentfreak.com/chinese-man-jailed-for-nine-months-for-selling-vpn-software-170904/

Back in January, China’s Ministry of Industry and Information Technology announced that due to Internet technologies and services expanding in a “disorderly” fashion, regulation would be needed to restore order.

The government said that it would take measures to “strengthen network information security management” and would embark on a “nationwide Internet network access services clean-up.”

One of the initial targets was reported as censorship-busting VPNs, which allow citizens to evade the so-called Great Firewall of China. Operating such a service without a corresponding telecommunications business license would constitute an offense, the government said.

The news was met with hostility, with media and citizens alike bemoaning Chinese censorship. Then early July, a further report suggested that the government would go a step further by ordering ISPs to block VPNs altogether. This elicited an immediate response from local authorities, who quickly denied the reports, blaming “foreign media” for false reporting.

But it was clear something was amiss in China. Later that month, it was revealed that Apple had banned VPN software and services from its app store.

“We are writing to notify you that your application will be removed from the China App Store because it includes content that is illegal in China, which is not in compliance with the App Store Review Guidelines,” Apple informed developers.

With an effort clearly underway to target VPNs, news today from China suggests that the government is indeed determined to tackle the anti-censorship threat presented by such tools. According to local media, Chinese man Deng Mouwei who ran a small website through which he sold VPN software, has been sentenced to prison.

The 26-year-old, from the city of Dongguan in the Guangdong province, was first arrested in October 2016 after setting up a website to sell VPNs. Just two products were on offer but this was enough to spring authorities into action.

A prosecution notice, published by Chinese publication Whatsonweibo, reveals the university educated man was arrested “on suspicion of providing tools for illegal control of a computer information system.”

It’s alleged that the man used several phrases to market the VPNs including “VPN over the wall” and “Shadow shuttle cloud”. The business wasn’t particularly profitable though, generating just 13957 yuan ($2,133) since October 2015.

“The court held that the defendant Deng Mouwei disregarded state law, by providing tools specifically for the invasion and illegal control of computer information systems procedures,” the Guandong Province’s First People’s Court said in its ruling, handed down earlier this year but only just made public.

“The circumstances are serious and the behavior violated the ‘Criminal Law of the People’s Republic of China Article 285.”

Article 285 – don’t interfere with the state

“The facts of the crime are clear, the evidence is true and sufficient. In accordance with the provisions of Article 172 of the Criminal Procedure Law of the People’s Republic of China, the defendant shall be sentenced according to law.”

Under Chinese law, Article 172 references stolen goods, noting that people who “conceal or act as distributors” shall be sentenced to not more than three years of fixed-term imprisonment, or fined, depending on circumstances. Where VPNs fit into that isn’t clear, but things didn’t end well for the defendant.

For offering tools that enable people to “visit foreign websites that can not be accessed via a domestic (mainland) IP address,” Deng Mouwei received a nine-month prison sentence.

News of the sentencing appeared on Chinese social media over the weekend, prompting fear and confusion among local users. While many struggled to see the sense of the prosecution, some expressed fear that people who even use VPN software to evade China’s Great Firewall could be subjected to prosecution in the future.

Whatever the outcome, it’s now abundantly clear that China is the midst of a VPN crackdown across the board and is serious about stamping out efforts to bypass its censorship. With the Internet’s ability to treat censorship as damage and route round it, it’s a battle that won’t be easily won.

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

VMware Cloud on AWS – Now Available

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/vmware-cloud-on-aws-now-available/

Last year I told you about the work that we are doing with our friends at VMware to build the VMware Cloud on AWS. As I shared at the time, this is a native, fully-managed offering that runs the VMware SDDC stack directly on bare-metal AWS infrastructure that maintains the elasticity and security customers have come to expect. This allows you to benefit from the scalability and resiliency of AWS, along with the networking and system-level hardware features that are fundamental parts of our security-first architecture.

VMware Cloud on AWS allows you take advantage of what you already know and own. Your existing skills, your investment in training, your operational practices, and your investment in software licenses remain relevant and applicable when you move to the public cloud. As part of that move you can forget about building & running data centers, modernizing hardware, and scaling to meet transient or short-term demand. You can also take advantage of a long list of AWS compute, database, analytics, IoT, AI, security, mobile, deployment and application services.

Initial Availability
After incorporating feedback from many customers and partners in our Early Access beta program, today at VMworld, VMware and Amazon announced the initial availability of VMware Cloud on AWS. This service is initially available in the US West (Oregon) region through VMware and members of the VMware Partner Network. It is designed to support popular use cases such as data center extension, application development & testing, and application migration.

This offering is sold, delivered, supported, and billed by VMware. It supports custom-sized VMs, runs any OS that is supported by VMware, and makes use of single-tenant bare-metal AWS infrastructure so that you can bring your Windows Server licenses to the cloud. Each SDDC (Software-Defined Data Center) consists of 4 to 16 instances, each with 36 cores, 512 GB of memory, and 15.2 TB of NVMe storage. Clusters currently run in a single AWS Availability Zone (AZ) with support in the works for clusters that span AZs. You can spin up an entire VMware SDDC in a couple of hours, and scale host capacity up and down in minutes.

The NSX networking platform (powered by the AWS Elastic Networking Adapter running at up to 25 Gbps) supports multicast traffic, separate networks for management and compute, and IPSec VPN tunnels to on-premises firewalls, routers, and so forth.

Here’s an overview to show you how all of the parts fit together:

The VMware and third-party management tools (vCenter Server, PowerCLI, the vRealize Suite, and code that calls the vSphere API) that you use today will work just fine when you build a hybrid VMware environment that combines your existing on-premises resources and those that you launch in AWS. This hybrid environment will use a new VMware Hybrid Linked Mode to create a single, unified view of your on-premises and cloud resources. You can use familiar VMware tools to manage your applications, without having to purchase any new or custom hardware, rewrite applications, or modify your operating model.

Your applications and your code can access the full range of AWS services (the database, analytical, and AI services are a good place to start). Use for these services is billed separately and you’ll need to create an AWS account.

Learn More at VMworld
If you are attending VMworld in Las Vegas, please be sure to check out some of the 90+ AWS sessions:

Also, be sure to stop by booth #300 and say hello to my colleagues from the AWS team.

In the Works
Our teams have come a long way since last year, but things are just getting revved up!

VMware and AWS are continuing to invest to enable support for new capabilities and use cases, such as application migration, data center expansion, and application test and development. Work is under way to add additional AWS regions, support more use cases such as disaster recovery and data center consolidation, add certifications, and enable even deeper integration with AWS services.

Jeff;

 

ROI is not a cybersecurity concept

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/08/roi-is-not-cybersecurity-concept.html

In the cybersecurity community, much time is spent trying to speak the language of business, in order to communicate to business leaders our problems. One way we do this is trying to adapt the concept of “return on investment” or “ROI” to explain why they need to spend more money. Stop doing this. It’s nonsense. ROI is a concept pushed by vendors in order to justify why you should pay money for their snake oil security products. Don’t play the vendor’s game.

The correct concept is simply “risk analysis”. Here’s how it works.

List out all the risks. For each risk, calculate:

  • How often it occurs.
  • How much damage it does.
  • How to mitigate it.
  • How effective the mitigation is (reduces chance and/or cost).
  • How much the mitigation costs.

If you have risk of something that’ll happen once-per-day on average, costing $1000 each time, then a mitigation costing $500/day that reduces likelihood to once-per-week is a clear win for investment.

Now, ROI should in theory fit directly into this model. If you are paying $500/day to reduce that risk, I could use ROI to show you hypothetical products that will …

  • …reduce the remaining risk to once-per-month for an additional $10/day.
  • …replace that $500/day mitigation with a $400/day mitigation.

But this is never done. Companies don’t have a sophisticated enough risk matrix in order to plug in some ROI numbers to reduce cost/risk. Instead, ROI is a calculation is done standalone by a vendor pimping product, or a security engineer building empires within the company.

If you haven’t done risk analysis to begin with (and almost none of you have), then ROI calculations are pointless.

But there are further problems. This is risk analysis as done in industries like oil and gas, which have inanimate risk. Almost all their risks are due to accidental failures, like in the Deep Water Horizon incident. In our industry, cybersecurity, risks are animate — by hackers. Our risk models are based on trying to guess what hackers might do.

An example of this problem is when our drug company jacks up the price of an HIV drug, Anonymous hackers will break in and dump all our financial data, and our CFO will go to jail. A lot of our risks come now from the technical side, but the whims and fads of the hacker community.

Another example is when some Google researcher finds a vuln in WordPress, and our website gets hacked by that three months from now. We have to forecast not only what hackers can do now, but what they might be able to do in the future.

Finally, there is this problem with cybersecurity that we really can’t distinguish between pesky and existential threats. Take ransomware. A lot of large organizations have just gotten accustomed to just wiping a few worker’s machines every day and restoring from backups. It’s a small, pesky problem of little consequence. Then one day a ransomware gets domain admin privileges and takes down the entire business for several weeks, as happened after #nPetya. Inevitably our risk models always come down on the high side of estimates, with us claiming that all threats are existential, when in fact, most companies continue to survive major breaches.

These difficulties with risk analysis leads us to punting on the problem altogether, but that’s not the right answer. No matter how faulty our risk analysis is, we still have to go through the exercise.

One model of how to do this calculation is architecture. We know we need a certain number of toilets per building, even without doing ROI on the value of such toilets. The same is true for a lot of security engineering. We know we need firewalls, encryption, and OWASP hardening, even without specifically doing a calculation. Passwords and session cookies need to go across SSL. That’s the starting point from which we start to analysis risks and mitigations — what we need beyond SSL, for example.

So stop using “ROI”, or worse, the abomination “ROSI”. Start doing risk analysis.

Top 10 Most Obvious Hacks of All Time (v0.9)

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/07/top-10-most-obvious-hacks-of-all-time.html

For teaching hacking/cybersecurity, I thought I’d create of the most obvious hacks of all time. Not the best hacks, the most sophisticated hacks, or the hacks with the biggest impact, but the most obvious hacks — ones that even the least knowledgeable among us should be able to understand. Below I propose some hacks that fit this bill, though in no particular order.

The reason I’m writing this is that my niece wants me to teach her some hacking. I thought I’d start with the obvious stuff first.

Shared Passwords

If you use the same password for every website, and one of those websites gets hacked, then the hacker has your password for all your websites. The reason your Facebook account got hacked wasn’t because of anything Facebook did, but because you used the same email-address and password when creating an account on “beagleforums.com”, which got hacked last year.

I’ve heard people say “I’m sure, because I choose a complex password and use it everywhere”. No, this is the very worst thing you can do. Sure, you can the use the same password on all sites you don’t care much about, but for Facebook, your email account, and your bank, you should have a unique password, so that when other sites get hacked, your important sites are secure.

And yes, it’s okay to write down your passwords on paper.

Tools: HaveIBeenPwned.com

PIN encrypted PDFs

My accountant emails PDF statements encrypted with the last 4 digits of my Social Security Number. This is not encryption — a 4 digit number has only 10,000 combinations, and a hacker can guess all of them in seconds.
PIN numbers for ATM cards work because ATM machines are online, and the machine can reject your card after four guesses. PIN numbers don’t work for documents, because they are offline — the hacker has a copy of the document on their own machine, disconnected from the Internet, and can continue making bad guesses with no restrictions.
Passwords protecting documents must be long enough that even trillion upon trillion guesses are insufficient to guess.

Tools: Hashcat, John the Ripper

SQL and other injection

The lazy way of combining websites with databases is to combine user input with an SQL statement. This combines code with data, so the obvious consequence is that hackers can craft data to mess with the code.
No, this isn’t obvious to the general public, but it should be obvious to programmers. The moment you write code that adds unfiltered user-input to an SQL statement, the consequence should be obvious. Yet, “SQL injection” has remained one of the most effective hacks for the last 15 years because somehow programmers don’t understand the consequence.
CGI shell injection is a similar issue. Back in early days, when “CGI scripts” were a thing, it was really important, but these days, not so much, so I just included it with SQL. The consequence of executing shell code should’ve been obvious, but weirdly, it wasn’t. The IT guy at the company I worked for back in the late 1990s came to me and asked “this guy says we have a vulnerability, is he full of shit?”, and I had to answer “no, he’s right — obviously so”.

XSS (“Cross Site Scripting”) [*] is another injection issue, but this time at somebody’s web browser rather than a server. It works because websites will echo back what is sent to them. For example, if you search for Cross Site Scripting with the URL https://www.google.com/search?q=cross+site+scripting, then you’ll get a page back from the server that contains that string. If the string is JavaScript code rather than text, then some servers (thought not Google) send back the code in the page in a way that it’ll be executed. This is most often used to hack somebody’s account: you send them an email or tweet a link, and when they click on it, the JavaScript gives control of the account to the hacker.

Cross site injection issues like this should probably be their own category, but I’m including it here for now.

More: Wikipedia on SQL injection, Wikipedia on cross site scripting.
Tools: Burpsuite, SQLmap

Buffer overflows

In the C programming language, programmers first create a buffer, then read input into it. If input is long than the buffer, then it overflows. The extra bytes overwrite other parts of the program, letting the hacker run code.
Again, it’s not a thing the general public is expected to know about, but is instead something C programmers should be expected to understand. They should know that it’s up to them to check the length and stop reading input before it overflows the buffer, that there’s no language feature that takes care of this for them.
We are three decades after the first major buffer overflow exploits, so there is no excuse for C programmers not to understand this issue.

What makes particular obvious is the way they are wrapped in exploits, like in Metasploit. While the bug itself is obvious that it’s a bug, actually exploiting it can take some very non-obvious skill. However, once that exploit is written, any trained monkey can press a button and run the exploit. That’s where we get the insult “script kiddie” from — referring to wannabe-hackers who never learn enough to write their own exploits, but who spend a lot of time running the exploit scripts written by better hackers than they.

More: Wikipedia on buffer overflow, Wikipedia on script kiddie,  “Smashing The Stack For Fun And Profit” — Phrack (1996)
Tools: bash, Metasploit

SendMail DEBUG command (historical)

The first popular email server in the 1980s was called “SendMail”. It had a feature whereby if you send a “DEBUG” command to it, it would execute any code following the command. The consequence of this was obvious — hackers could (and did) upload code to take control of the server. This was used in the Morris Worm of 1988. Most Internet machines of the day ran SendMail, so the worm spread fast infecting most machines.
This bug was mostly ignored at the time. It was thought of as a theoretical problem, that might only rarely be used to hack a system. Part of the motivation of the Morris Worm was to demonstrate that such problems was to demonstrate the consequences — consequences that should’ve been obvious but somehow were rejected by everyone.

More: Wikipedia on Morris Worm

Email Attachments/Links

I’m conflicted whether I should add this or not, because here’s the deal: you are supposed to click on attachments and links within emails. That’s what they are there for. The difference between good and bad attachments/links is not obvious. Indeed, easy-to-use email systems makes detecting the difference harder.
On the other hand, the consequences of bad attachments/links is obvious. That worms like ILOVEYOU spread so easily is because people trusted attachments coming from their friends, and ran them.
We have no solution to the problem of bad email attachments and links. Viruses and phishing are pervasive problems. Yet, we know why they exist.

Default and backdoor passwords

The Mirai botnet was caused by surveillance-cameras having default and backdoor passwords, and being exposed to the Internet without a firewall. The consequence should be obvious: people will discover the passwords and use them to take control of the bots.
Surveillance-cameras have the problem that they are usually exposed to the public, and can’t be reached without a ladder — often a really tall ladder. Therefore, you don’t want a button consumers can press to reset to factory defaults. You want a remote way to reset them. Therefore, they put backdoor passwords to do the reset. Such passwords are easy for hackers to reverse-engineer, and hence, take control of millions of cameras across the Internet.
The same reasoning applies to “default” passwords. Many users will not change the defaults, leaving a ton of devices hackers can hack.

Masscan and background radiation of the Internet

I’ve written a tool that can easily scan the entire Internet in a short period of time. It surprises people that this possible, but it obvious from the numbers. Internet addresses are only 32-bits long, or roughly 4 billion combinations. A fast Internet link can easily handle 1 million packets-per-second, so the entire Internet can be scanned in 4000 seconds, little more than an hour. It’s basic math.
Because it’s so easy, many people do it. If you monitor your Internet link, you’ll see a steady trickle of packets coming in from all over the Internet, especially Russia and China, from hackers scanning the Internet for things they can hack.
People’s reaction to this scanning is weirdly emotional, taking is personally, such as:
  1. Why are they hacking me? What did I do to them?
  2. Great! They are hacking me! That must mean I’m important!
  3. Grrr! How dare they?! How can I hack them back for some retribution!?

I find this odd, because obviously such scanning isn’t personal, the hackers have no idea who you are.

Tools: masscan, firewalls

Packet-sniffing, sidejacking

If you connect to the Starbucks WiFi, a hacker nearby can easily eavesdrop on your network traffic, because it’s not encrypted. Windows even warns you about this, in case you weren’t sure.

At DefCon, they have a “Wall of Sheep”, where they show passwords from people who logged onto stuff using the insecure “DefCon-Open” network. Calling them “sheep” for not grasping this basic fact that unencrypted traffic is unencrypted.

To be fair, it’s actually non-obvious to many people. Even if the WiFi itself is not encrypted, SSL traffic is. They expect their services to be encrypted, without them having to worry about it. And in fact, most are, especially Google, Facebook, Twitter, Apple, and other major services that won’t allow you to log in anymore without encryption.

But many services (especially old ones) may not be encrypted. Unless users check and verify them carefully, they’ll happily expose passwords.

What’s interesting about this was 10 years ago, when most services which only used SSL to encrypt the passwords, but then used unencrypted connections after that, using “cookies”. This allowed the cookies to be sniffed and stolen, allowing other people to share the login session. I used this on stage at BlackHat to connect to somebody’s GMail session. Google, and other major websites, fixed this soon after. But it should never have been a problem — because the sidejacking of cookies should have been obvious.

Tools: Wireshark, dsniff

Stuxnet LNK vulnerability

Again, this issue isn’t obvious to the public, but it should’ve been obvious to anybody who knew how Windows works.
When Windows loads a .dll, it first calls the function DllMain(). A Windows link file (.lnk) can load icons/graphics from the resources in a .dll file. It does this by loading the .dll file, thus calling DllMain. Thus, a hacker could put on a USB drive a .lnk file pointing to a .dll file, and thus, cause arbitrary code execution as soon as a user inserted a drive.
I say this is obvious because I did this, created .lnks that pointed to .dlls, but without hostile DllMain code. The consequence should’ve been obvious to me, but I totally missed the connection. We all missed the connection, for decades.

Social Engineering and Tech Support [* * *]

After posting this, many people have pointed out “social engineering”, especially of “tech support”. This probably should be up near #1 in terms of obviousness.

The classic example of social engineering is when you call tech support and tell them you’ve lost your password, and they reset it for you with minimum of questions proving who you are. For example, you set the volume on your computer really loud and play the sound of a crying baby in the background and appear to be a bit frazzled and incoherent, which explains why you aren’t answering the questions they are asking. They, understanding your predicament as a new parent, will go the extra mile in helping you, resetting “your” password.

One of the interesting consequences is how it affects domain names (DNS). It’s quite easy in many cases to call up the registrar and convince them to transfer a domain name. This has been used in lots of hacks. It’s really hard to defend against. If a registrar charges only $9/year for a domain name, then it really can’t afford to provide very good tech support — or very secure tech support — to prevent this sort of hack.

Social engineering is such a huge problem, and obvious problem, that it’s outside the scope of this document. Just google it to find example after example.

A related issue that perhaps deserves it’s own section is OSINT [*], or “open-source intelligence”, where you gather public information about a target. For example, on the day the bank manager is out on vacation (which you got from their Facebook post) you show up and claim to be a bank auditor, and are shown into their office where you grab their backup tapes. (We’ve actually done this).

More: Wikipedia on Social Engineering, Wikipedia on OSINT, “How I Won the Defcon Social Engineering CTF” — blogpost (2011), “Questioning 42: Where’s the Engineering in Social Engineering of Namespace Compromises” — BSidesLV talk (2016)

Blue-boxes (historical) [*]

Telephones historically used what we call “in-band signaling”. That’s why when you dial on an old phone, it makes sounds — those sounds are sent no differently than the way your voice is sent. Thus, it was possible to make tone generators to do things other than simply dial calls. Early hackers (in the 1970s) would make tone-generators called “blue-boxes” and “black-boxes” to make free long distance calls, for example.

These days, “signaling” and “voice” are digitized, then sent as separate channels or “bands”. This is call “out-of-band signaling”. You can’t trick the phone system by generating tones. When your iPhone makes sounds when you dial, it’s entirely for you benefit and has nothing to do with how it signals the cell tower to make a call.

Early hackers, like the founders of Apple, are famous for having started their careers making such “boxes” for tricking the phone system. The problem was obvious back in the day, which is why as the phone system moves from analog to digital, the problem was fixed.

More: Wikipedia on blue box, Wikipedia article on Steve Wozniak.

Thumb drives in parking lots [*]

A simple trick is to put a virus on a USB flash drive, and drop it in a parking lot. Somebody is bound to notice it, stick it in their computer, and open the file.

This can be extended with tricks. For example, you can put a file labeled “third-quarter-salaries.xlsx” on the drive that required macros to be run in order to open. It’s irresistible to other employees who want to know what their peers are being paid, so they’ll bypass any warning prompts in order to see the data.

Another example is to go online and get custom USB sticks made printed with the logo of the target company, making them seem more trustworthy.

We also did a trick of taking an Adobe Flash game “Punch the Monkey” and replaced the monkey with a logo of a competitor of our target. They now only played the game (infecting themselves with our virus), but gave to others inside the company to play, infecting others, including the CEO.

Thumb drives like this have been used in many incidents, such as Russians hacking military headquarters in Afghanistan. It’s really hard to defend against.

More: “Computer Virus Hits U.S. Military Base in Afghanistan” — USNews (2008), “The Return of the Worm That Ate The Pentagon” — Wired (2011), DoD Bans Flash Drives — Stripes (2008)

Googling [*]

Search engines like Google will index your website — your entire website. Frequently companies put things on their website without much protection because they are nearly impossible for users to find. But Google finds them, then indexes them, causing them to pop up with innocent searches.
There are books written on “Google hacking” explaining what search terms to look for, like “not for public release”, in order to find such documents.

More: Wikipedia entry on Google Hacking, “Google Hacking” book.

URL editing [*]

At the top of every browser is what’s called the “URL”. You can change it. Thus, if you see a URL that looks like this:

http://www.example.com/documents?id=138493

Then you can edit it to see the next document on the server:

http://www.example.com/documents?id=138494

The owner of the website may think they are secure, because nothing points to this document, so the Google search won’t find it. But that doesn’t stop a user from manually editing the URL.
An example of this is a big Fortune 500 company that posts the quarterly results to the website an hour before the official announcement. Simply editing the URL from previous financial announcements allows hackers to find the document, then buy/sell the stock as appropriate in order to make a lot of money.
Another example is the classic case of Andrew “Weev” Auernheimer who did this trick in order to download the account email addresses of early owners of the iPad, including movie stars and members of the Obama administration. It’s an interesting legal case because on one hand, techies consider this so obvious as to not be “hacking”. On the other hand, non-techies, especially judges and prosecutors, believe this to be obviously “hacking”.

DDoS, spoofing, and amplification [*]

For decades now, online gamers have figured out an easy way to win: just flood the opponent with Internet traffic, slowing their network connection. This is called a DoS, which stands for “Denial of Service”. DoSing game competitors is often a teenager’s first foray into hacking.
A variant of this is when you hack a bunch of other machines on the Internet, then command them to flood your target. (The hacked machines are often called a “botnet”, a network of robot computers). This is called DDoS, or “Distributed DoS”. At this point, it gets quite serious, as instead of competitive gamers hackers can take down entire businesses. Extortion scams, DDoSing websites then demanding payment to stop, is a common way hackers earn money.
Another form of DDoS is “amplification”. Sometimes when you send a packet to a machine on the Internet it’ll respond with a much larger response, either a very large packet or many packets. The hacker can then send a packet to many of these sites, “spoofing” or forging the IP address of the victim. This causes all those sites to then flood the victim with traffic. Thus, with a small amount of outbound traffic, the hacker can flood the inbound traffic of the victim.
This is one of those things that has worked for 20 years, because it’s so obvious teenagers can do it, yet there is no obvious solution. President Trump’s executive order of cyberspace specifically demanded that his government come up with a report on how to address this, but it’s unlikely that they’ll come up with any useful strategy.

More: Wikipedia on DDoS, Wikipedia on Spoofing

Conclusion

Tweet me (@ErrataRob) your obvious hacks, so I can add them to the list.

Apple Bans VPNs From App Store in China

Post Syndicated from Ernesto original https://torrentfreak.com/apple-bans-vpns-from-app-store-in-china-170729/

Apple is known to have a rigorous app-review policy.

Over the past several years, dozens of apps have been rejected from the App Store because they mention the word BitTorrent, for example.

The mere association with piracy is good enough to warrant a ban. This policy is now expanding to the privacy-sphere as well, at least in China.

It is no secret that the Chinese Government is preventing users from accessing certain sites and services. The so-called ‘Great Firewall’ works reasonably well, but can be circumvented through VPN services and other encryption tools.

These tools are a thorn in the side of Chinese authorities, which are now receiving help from Apple to limit their availability.

Over the past few hours, Apple has removed many of the most-used VPN applications from the Chinese app store. In a short email, VPN providers are informed that VPN applications are considered illegal in China.

“We are writing to notify you that your application will be removed from the China App Store because it includes content that is illegal in China, which is not in compliance with the App Store Review Guidelines,” Apple informed the affected VPNs.

Apple’s email to VPN providers

VPN providers and users are complaining bitterly about the rigorous action. However, it doesn’t come as a complete surprise. Over the past few months there have been various signals that the Chinese Government would crack down on non-authorized VPN providers.

In January, a notice published by China’s Ministry of Industry and Information Technology said that the government had launched a 14-month campaign to crack down on local ‘unauthorized’ Internet platforms.

This essentially means that all VPN services have to be pre-approved by the Government if they want to operate there.

Earlier this month Bloomberg broke the news that China’s Government had ordered telecommunications carriers to block individuals’ access to VPNs. The Chinese Government denied that this was the case, but it’s clear that these services remain a high-profile target.

Thanks to Apple, China’s Government no longer has to worry about iOS users having easy access to the most popular VPN applications. Those users who search the local app store for “VPN” still see plenty of results, but, ironically, many of these applications are fake.

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

China Denies User VPN Crackdown, Blames False “Foreign Media” Reports

Post Syndicated from Andy original https://torrentfreak.com/china-denies-user-vpn-crackdown-blames-false-foreign-media-reports-170713/

A notice published by China’s Ministry of Industry and Information Technology in January said that the government had launched a 14-month campaign to crack down on local ‘unauthorized’ Internet platforms.

The idea is that all Internet services such as data centers, ISPs, CDNs, and VPNs, will eventually need pre-approval from the government to operate. Operating such a service without a corresponding telecommunications business license will constitute an offense.

After the news broke, a source with contacts at a high-level telecoms company in the region told TF that, in his opinion, user-based VPNs were not the target and that MPLS VPNs were. These types of VPN (pdf) allow businesses, including those in China, to connect their geographically separated business locations, such as those in Hong Kong, Singapore, and Indonesia, for example.

This week, however, Bloomberg broke the news that China’s Government had ordered telecommunications carriers to block individuals’ access to Virtual Private Networks. This, the publication said, would stop citizens from accessing the global Internet.

According to the report, the government ordered at least three state-run telecommunications firms, including China Mobile, China Unicom and China Telecom, to stop people from using VPNs which allow people to circumvent censorship restrictions, otherwise known as the Great Firewall, by February next year.

Jake Parker, Beijing-based vice president of the US-China Business Council, agreed that the move “seems to impact individuals,” but last evening the Chinese authorities were attempting to pour cold water on the report.

In comments to China-based media outlet The Paper, the Ministry of Industry and Information Technology denied issuing a notice to the telecoms companies requiring them to block user VPNs. It said that “foreign media reports” were inaccurate.

“Our subordinate Secretary did not issue the relevant notice, what foreign media reported was false,” the Ministry said.

The local media report then has the Ministry citing news that previously broke in January, detailing the new government measures that require cross-border enterprise-level VPN systems to be authorized and licensed.

“Foreign trade enterprises and multinational companies, due to office for personal use and other reasons, need to access cross-border networking,” the Ministry said, adding that licensing is available and won’t have a detrimental effect on normal operations.

Given this statement, the announcement in January, and the comments made to TF regarding the government targeting enterprise-level VPNs, it raises the question whether the term ‘VPN’ has perhaps been interpreted too widely, to include user-based services.

Nevertheless, in a follow-up report last evening, Bloomberg repeated its claims that Beijing had ordered state-run telecoms firms to stop people from using VPNs that route traffic overseas to avoid censorship.

“The clampdown will shutter one of the main ways in which people both local and foreign still manage to access the global, unfiltered web on a daily basis,” the report said.

Only time will tell how the landscape will pan out, but it’s safe to say that China would like a tighter hold on the web than it has now and that VPNs of all kinds will continue to undermine that control, unless something is done.

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

Perform Near Real-time Analytics on Streaming Data with Amazon Kinesis and Amazon Elasticsearch Service

Post Syndicated from Tristan Li original https://aws.amazon.com/blogs/big-data/perform-near-real-time-analytics-on-streaming-data-with-amazon-kinesis-and-amazon-elasticsearch-service/

Nowadays, streaming data is seen and used everywhere—from social networks, to mobile and web applications, IoT devices, instrumentation in data centers, and many other sources. As the speed and volume of this type of data increases, the need to perform data analysis in real time with machine learning algorithms and extract a deeper understanding from the data becomes ever more important. For example, you might want a continuous monitoring system to detect sentiment changes in a social media feed so that you can react to the sentiment in near real time.

In this post, we use Amazon Kinesis Streams to collect and store streaming data. We then use Amazon Kinesis Analytics to process and analyze the streaming data continuously. Specifically, we use the Kinesis Analytics built-in RANDOM_CUT_FOREST function, a machine learning algorithm, to detect anomalies in the streaming data. Finally, we use Amazon Kinesis Firehose to export the anomalies data to Amazon Elasticsearch Service (Amazon ES). We then build a simple dashboard in the open source tool Kibana to visualize the result.

Solution overview

The following diagram depicts a high-level overview of this solution.

Amazon Kinesis Streams

You can use Amazon Kinesis Streams to build your own streaming application. This application can process and analyze streaming data by continuously capturing and storing terabytes of data per hour from hundreds of thousands of sources.

Amazon Kinesis Analytics

Kinesis Analytics provides an easy and familiar standard SQL language to analyze streaming data in real time. One of its most powerful features is that there are no new languages, processing frameworks, or complex machine learning algorithms that you need to learn.

Amazon Kinesis Firehose

Kinesis Firehose is the easiest way to load streaming data into AWS. It can capture, transform, and load streaming data into Amazon S3, Amazon Redshift, and Amazon Elasticsearch Service.

Amazon Elasticsearch Service

Amazon ES is a fully managed service that makes it easy to deploy, operate, and scale Elasticsearch for log analytics, full text search, application monitoring, and more.

Solution summary

The following is a quick walkthrough of the solution that’s presented in the diagram:

  1. IoT sensors send streaming data into Kinesis Streams. In this post, you use a Python script to simulate an IoT temperature sensor device that sends the streaming data.
  2. By using the built-in RANDOM_CUT_FOREST function in Kinesis Analytics, you can detect anomalies in real time with the sensor data that is stored in Kinesis Streams. RANDOM_CUT_FOREST is also an appropriate algorithm for many other kinds of anomaly-detection use cases—for example, the media sentiment example mentioned earlier in this post.
  3. The processed anomaly data is then loaded into the Kinesis Firehose delivery stream.
  4. By using the built-in integration that Kinesis Firehose has with Amazon ES, you can easily export the processed anomaly data into the service and visualize it with Kibana.

Implementation steps

The following sections walk through the implementation steps in detail.

Creating the delivery stream

  1. Open the Amazon Kinesis Streams console.
  2. Create a new Kinesis stream. Give it a name that indicates it’s for raw incoming stream data—for example, RawStreamData. For Number of shards, type 1.
  3. The Python code provided below simulates a streaming application, such as an IoT device, and generates random data and anomalies into a Kinesis stream. The code generates two temperature ranges, where the first range is the hypothetical sensor’s normal operating temperature range (10–20), and the second is the anomaly temperature range (100–120).Make sure to change the stream name on line 16 and 20 and the Region on line 6 to match your configuration. Alternatively, you can download the Amazon Kinesis Data Generator from this repository and use it to generate the data.
    import json
    import datetime
    import random
    import testdata
    from boto import kinesis
    
    kinesis = kinesis.connect_to_region("us-east-1")
    
    def getData(iotName, lowVal, highVal):
       data = {}
       data["iotName"] = iotName
       data["iotValue"] = random.randint(lowVal, highVal) 
       return data
    
    while 1:
       rnd = random.random()
       if (rnd < 0.01):
          data = json.dumps(getData("DemoSensor", 100, 120))  
          kinesis.put_record("RawStreamData", data, "DemoSensor")
          print '***************************** anomaly ************************* ' + data
       else:
          data = json.dumps(getData("DemoSensor", 10, 20))  
          kinesis.put_record("RawStreamData", data, "DemoSensor")
          print data

  4. Open the Amazon Elasticsearch Service console and create a new domain.
    1. Give the domain a unique name. In the Configure cluster screen, use the default settings.
    2. In the Set up access policy screen, in the Set the domain access policy list, choose Allow access to the domain from specific IP(s).
    3. Enter the public IP address of your computer.
      Note: If you’re working behind a proxy or firewall, see the “Use a proxy to simplify request signing” section in this AWS Database blog post to learn how to work with a proxy. For additional information about securing access to your Amazon ES domain, see How to Control Access to Your Amazon Elasticsearch Domain in the AWS Security Blog.
  5. After the Amazon ES domain is up and running, you can set up and configure Kinesis Firehose to export results to Amazon ES:
    1. Open the Amazon Kinesis Firehose console and choose Create Delivery Stream.
    2. In the Destination dropdown list, choose Amazon Elasticsearch Service.
    3. Type a stream name, and choose the Amazon ES domain that you created in Step 4.
    4. Provide an index name and ES type. In the S3 bucket dropdown list, choose Create New S3 bucket. Choose Next.
    5. In the configuration, change the Elasticsearch Buffer size to 1 MB and the Buffer interval to 60s. Use the default settings for all other fields. This shortens the time for the data to reach the ES cluster.
    6. Under IAM Role, choose Create/Update existing IAM role.
      The best practice is to create a new role every time. Otherwise, the console keeps adding policy documents to the same role. Eventually the size of the attached policies causes IAM to reject the role, but it does it in a non-obvious way, where the console basically quits functioning.
    7. Choose Next to move to the Review page.
  6. Review the configuration, and then choose Create Delivery Stream.
  7. Run the Python file for 1–2 minutes, and then press Ctrl+C to stop the execution. This loads some data into the stream for you to visualize in the next step.

Analyzing the data

Now it’s time to analyze the IoT streaming data using Amazon Kinesis Analytics.

  1. Open the Amazon Kinesis Analytics console and create a new application. Give the application a name, and then choose Create Application.
  2. On the next screen, choose Connect to a source. Choose the raw incoming data stream that you created earlier. (Note the stream name Source_SQL_STREAM_001 because you will need it later.)
  3. Use the default settings for everything else. When the schema discovery process is complete, it displays a success message with the formatted stream sample in a table as shown in the following screenshot. Review the data, and then choose Save and continue.
  4. Next, choose Go to SQL editor. When prompted, choose Yes, start application.
  5. Copy the following SQL code and paste it into the SQL editor window.
    CREATE OR REPLACE STREAM "TEMP_STREAM" (
       "iotName"        varchar (40),
       "iotValue"   integer,
       "ANOMALY_SCORE"  DOUBLE);
    -- Creates an output stream and defines a schema
    CREATE OR REPLACE STREAM "DESTINATION_SQL_STREAM" (
       "iotName"       varchar(40),
       "iotValue"       integer,
       "ANOMALY_SCORE"  DOUBLE,
       "created" TimeStamp);
     
    -- Compute an anomaly score for each record in the source stream
    -- using Random Cut Forest
    CREATE OR REPLACE PUMP "STREAM_PUMP_1" AS INSERT INTO "TEMP_STREAM"
    SELECT STREAM "iotName", "iotValue", ANOMALY_SCORE FROM
      TABLE(RANDOM_CUT_FOREST(
        CURSOR(SELECT STREAM * FROM "SOURCE_SQL_STREAM_001")
      )
    );
    
    -- Sort records by descending anomaly score, insert into output stream
    CREATE OR REPLACE PUMP "OUTPUT_PUMP" AS INSERT INTO "DESTINATION_SQL_STREAM"
    SELECT STREAM "iotName", "iotValue", ANOMALY_SCORE, ROWTIME FROM "TEMP_STREAM"
    ORDER BY FLOOR("TEMP_STREAM".ROWTIME TO SECOND), ANOMALY_SCORE DESC;

 

  1. Choose Save and run SQL.
    As the application is running, it displays the results as stream data arrives. If you don’t see any data coming in, run the Python script again to generate some fresh data. When there is data, it appears in a grid as shown in the following screenshot.Note that you are selecting data from the source stream name Source_SQL_STREAM_001 that you created previously. Also note the ANOMALY_SCORE column. This is the value that the Random_Cut_Forest function calculates based on the temperature ranges provided by the Python script. Higher (anomaly) temperature ranges have a higher score.Looking at the SQL code, note that the first two blocks of code create two new streams to store temporary data and the final result. The third block of code analyzes the raw source data (Stream_Pump_1) using the Random_Cut_Forest function. It calculates an anomaly score (ANOMALY_SCORE) and inserts it into the TEMP_STREAM stream. The final code block loads the result stored in the TEMP_STREAM into DESTINATION_SQL_STREAM.
  2. Choose Exit (done editing) next to the Save and run SQL button to return to the application configuration page.

Load processed data into the Kinesis Firehose delivery stream

Now, you can export the result from DESTINATION_SQL_STREAM into the Amazon Kinesis Firehose stream that you created previously.

  1. On the application configuration page, choose Connect to a destination.
  2. Choose the stream name that you created earlier, and use the default settings for everything else. Then choose Save and Continue.
  3. On the application configuration page, choose Exit to Kinesis Analytics applications to return to the Amazon Kinesis Analytics console.
  4. Run the Python script again for 4–5 minutes to generate enough data to flow through Amazon Kinesis Streams, Kinesis Analytics, Kinesis Firehose, and finally into the Amazon ES domain.
  5. Open the Kinesis Firehose console, choose the stream, and then choose the Monitoring
  6. As the processed data flows into Kinesis Firehose and Amazon ES, the metrics appear on the Delivery Stream metrics page. Keep in mind that the metrics page takes a few minutes to refresh with the latest data.
  7. Open the Amazon Elasticsearch Service dashboard in the AWS Management Console. The count in the Searchable documents column increases as shown in the following screenshot. In addition, the domain shows a cluster health of Yellow. This is because, by default, it needs two instances to deploy redundant copies of the index. To fix this, you can deploy two instances instead of one.

Visualize the data using Kibana

Now it’s time to launch Kibana and visualize the data.

  1. Use the ES domain link to go to the cluster detail page, and then choose the Kibana link as shown in the following screenshot.

    If you’re working behind a proxy or firewall, see the “Use a proxy to simplify request signing” section in this blog post to learn how to work with a proxy.
  2. In the Kibana dashboard, choose the Discover tab to perform a query.
  3. You can also visualize the data using the different types of charts offered by Kibana. For example, by going to the Visualize tab, you can quickly create a split bar chart that aggregates by ANOMALY_SCORE per minute.


Conclusion

In this post, you learned how to use Amazon Kinesis to collect, process, and analyze real-time streaming data, and then export the results to Amazon ES for analysis and visualization with Kibana. If you have comments about this post, add them to the “Comments” section below. If you have questions or issues with implementing this solution, please open a new thread on the Amazon Kinesis or Amazon ES discussion forums.


Next Steps

Take your skills to the next level. Learn real-time clickstream anomaly detection with Amazon Kinesis Analytics.

 


About the Author

Tristan Li is a Solutions Architect with Amazon Web Services. He works with enterprise customers in the US, helping them adopt cloud technology to build scalable and secure solutions on AWS.

 

 

 

 

Prepare for the OWASP Top 10 Web Application Vulnerabilities Using AWS WAF and Our New White Paper

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/prepare-for-the-owasp-top-10-web-application-vulnerabilities-using-aws-waf-and-our-new-white-paper/

Are you aware of the Open Web Application Security Project (OWASP) and the work that they do to improve the security of web applications? Among many other things, they publish a list of the 10 most critical application security flaws, known as the OWASP Top 10. The release candidate for the 2017 version contains a consensus view of common vulnerabilities often found in web sites and web applications.

AWS WAF, as I described in my blog post, New – AWS WAF, helps to protect your application from application-layer attacks such as SQL injection and cross-site scripting. You can create custom rules to define the types of traffic that are accepted or rejected.

Our new white paper, Use AWS WAF to Mitigate OWASP’s Top 10 Web Application Vulnerabilities, shows you how to put AWS WAF to use. Going far beyond a simple recommendation to “use WAF,” it includes detailed, concrete mitigation strategies and implementation details for the most important items in the OWASP Top 10 (formally known as A1 through A10):

Download Today
The white paper provides background and context for each vulnerability, and then shows you how to create WAF rules to identify and block them. It also provides some defense-in-depth recommendations, including a very cool suggestion to use [email protected] to prevalidate the parameters supplied to HTTP requests.

The white paper links to a companion AWS CloudFormation template that creates a Web ACL, along with the recommended condition types and rules. You can use this template as a starting point for your own work, adding more condition types and rules as desired.

AWSTemplateFormatVersion: '2010-09-09'
Description: AWS WAF Basic OWASP Example Rule Set

## ::PARAMETERS::
## Template parameters to be configured by user
Parameters:
  stackPrefix:
    Type: String
    Description: The prefix to use when naming resources in this stack. Normally we would use the stack name, but since this template can be us\
ed as a resource in other stacks we want to keep the naming consistent. No symbols allowed.
    ConstraintDescription: Alphanumeric characters only, maximum 10 characters
    AllowedPattern: ^[a-zA-z0-9]+$
    MaxLength: 10
    Default: generic
  stackScope:
    Type: String
    Description: You can deploy this stack at a regional level, for regional WAF targets like Application Load Balancers, or for global targets\
, such as Amazon CloudFront distributions.
    AllowedValues:
      - Global
      - Regional
    Default: Regional
...

Attend our Webinar
If you would like to learn more about the topics discussed in this new white paper, please plan to attend our upcoming webinar, Secure Your Applications with AWS Web Application Firewall (WAF) and AWS Shield. On July 12, 2017, my colleagues Jeffrey Lyon and Sundar Jayashekar will show you how to secure your web applications and how to defend against the most common Layer 7 attacks.

Jeff;

 

 

 

New Security Whitepaper Now Available: Use AWS WAF to Mitigate OWASP’s Top 10 Web Application Vulnerabilities

Post Syndicated from Vlad Vlasceanu original https://aws.amazon.com/blogs/security/new-security-whitepaper-now-available-use-aws-waf-to-mitigate-owasps-top-10-web-application-vulnerabilities/

Whitepaper image

Today, we released a new security whitepaper: Use AWS WAF to Mitigate OWASP’s Top 10 Web Application Vulnerabilities. This whitepaper describes how you can use AWS WAF, a web application firewall, to address the top application security flaws as named by the Open Web Application Security Project (OWASP). Using AWS WAF, you can write rules to match patterns of exploitation attempts in HTTP requests and block requests from reaching your web servers. This whitepaper discusses manifestations of these security vulnerabilities, AWS WAF–based mitigation strategies, and other AWS services or solutions that can help address these threats.

– Vlad

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Jeff;

Torrents Help Researchers Worldwide to Study Babies’ Brains

Post Syndicated from Ernesto original https://torrentfreak.com/torrents-help-researchers-worldwide-to-study-babies-brains-170603/

One of the core pillars of academic research is sharing.

By letting other researchers know what you do, ideas are criticized, improved upon and extended. In today’s digital age, sharing is easier than ever before, especially with help from torrents.

One of the leading scientific projects that has adopted BitTorrent is the developing Human Connectome Project, or dHCP for short. The goal of the project is to map the brain wiring of developing babies in the wombs of their mothers.

To do so, a consortium of researchers with expertise ranging from computer science, to MRI physics and clinical medicine, has teamed up across three British institutions: Imperial College London, King’s College London and the University of Oxford.

The collected data is extremely valuable for the neuroscience community and the project has received mainstream press coverage and financial backing from the European Union Research Council. Not only to build the dataset, but also to share it with researchers around the globe. This is where BitTorrent comes in.

Sharing more than 150 GB of data with researchers all over the world can be quite a challenge. Regular HTTP downloads are not really up to the task, and many other transfer options have a high failure rate.

Baby brain scan (Credit: Developing Human Connectome Project)

This is why Jonathan Passerat-Palmbach, Research Associate Department of Computing Imperial College London, came up with the idea to embrace BitTorrent instead.

“For me, it was a no-brainer from day one that we couldn’t rely on plain old HTTP to make this dataset available. Our first pilot release is 150GB, and I expect the next ones to reach a couple of TB. Torrents seemed like the de facto solution to share this data with the world’s scientific community.” Passerat-Palmbach says.

The researchers opted to go for the Academic Torrents tracker, which specializes in sharing research data. A torrent with the first batch of images was made available there a few weeks ago.

“This initial release contains 3,629 files accounting for 167.20GB of data. While this figure might not appear extremely large at the moment, it will significantly grow as the project aims to make the data of 1,000 subjects available by the time it has completed.”

Torrent of the first dataset

The download numbers are nowhere in the region of an average Hollywood blockbuster, of course. Thus far the tracker has registered just 28 downloads. That said, as a superior and open file-transfer protocol, BitTorrent does aid in critical research that helps researchers to discover more about the development of conditions such as ADHD and autism.

Interestingly, the biggest challenges of implementing the torrent solution were not of a technical nature. Most time and effort went into assuring other team members that this was the right solution.

“I had to push for more than a year for the adoption of torrents within the consortium. While my colleagues could understand the potential of the approach and its technical inputs, they remained skeptical as to the feasibility to implement such a solution within an academic context and its reception by the world community.

“However, when the first dataset was put together, amounting to 150GB, it became obvious all the HTTP and FTP fallback plans would not fit our needs,” Passerat-Palmbach adds.

Baby brain scans (Credit: Developing Human Connectome Project)

When the consortium finally agreed that BitTorrent was an acceptable way to share the data, local IT staff at the university had to give their seal of approval. Imperial College London doesn’t allow torrent traffic to flow freely across the network, so an exception had to be made.

“Torrents are blocked across the wireless and VPN networks at Imperial. Getting an explicit firewall exception created for our seeding machine was not a walk in the park. It was the first time they were faced with such a situation and we were clearly told that it was not to become the rule.”

Then, finally, the data could be shared around the world.

While BitTorrent is probably the most efficient way to share large files, there were other proprietary solutions that could do the same. However, Passerat-Palmbach preferred not to force other researchers to install “proprietary black boxes” on their machines.

Torrents are free and open, which is more in line with the Open Access approach more academics take today.

Looking back, it certainly wasn’t a walk in the park to share the data via BitTorrent. Passerat-Palmbach was frequently confronted with the piracy stigma torrents have amoung many of his peers, even among younger generations.

“Considering how hard it was to convince my colleagues within the project to actually share this dataset using torrents (‘isn’t it illegal?’ and other kinds of misconceptions…), I think there’s still a lot of work to do to demystify the use of torrents with the public.

“I was even surprised to see that these misconceptions spread out not only to more senior scientists but also to junior researchers who I was expecting to be more tech-aware,” Passerat-Palmbach adds.

That said, the hard work is done now and in the months and years ahead the neuroscience community will have access to Petabytes of important data, with help from BitTorrent. That is definitely worth the effort.

Finally, we thought it was fitting to end with Passerat-Palmbach’s “pledge to seed,” which he shared with his peers. Keep on sharing!


On the importance of seeding

Dear fellow scientist,

Thank for you very much for the interest you are showing in the dHCP dataset!

Once you start downloading the dataset, you’ll notice that your torrent client mentions a sharing / seeding ratio. It means that as soon as you start downloading the dataset, you become part of our community of sharers and contribute to making the dataset available to other researchers all around the world!

There’s no reason to be scared! It’s perfectly legal as long as you’re allowed to have a copy of the dataset (that’s the bit you need to forward to your lab’s IT staff if they’re blocking your ports).

You’re actually providing a tremendous contribution to dHCP by spreading the data, so thank you again for that!

With your help, we can make sure this data remains available and can be downloaded relatively fast in the future. Over time, the dataset will grow and your contribution will be more and more important so that each and everyone of you can still obtain the data in the smoothest possible way.

We cannot do it without you. By seeding, you’re actually saying “cheers!” to your peers whom you downloaded your data from. So leave your client open and stay tuned!

All this is made possible thanks to the amazing folks at academictorrents and their infrastructure, so kudos academictorrents!

You can learn more about their project here and get some help to get started with torrent downloading here.

Jonathan Passerat-Palmbach

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

Some notes on Trump’s cybersecurity Executive Order

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/05/some-notes-on-trumps-cybersecurity.html

President Trump has finally signed an executive order on “cybersecurity”. The first draft during his first weeks in power were hilariously ignorant. The current draft, though, is pretty reasonable as such things go. I’m just reading the plain language of the draft as a cybersecurity expert, picking out the bits that interest me. In reality, there’s probably all sorts of politics in the background that I’m missing, so I may be wildly off-base.

Holding managers accountable

This is a great idea in theory. But government heads are rarely accountable for anything, so it’s hard to see if they’ll have the nerve to implement this in practice. When the next breech happens, we’ll see if anybody gets fired.
“antiquated and difficult to defend Information Technology”

The government uses laughably old computers sometimes. Forces in government wants to upgrade them. This won’t work. Instead of replacing old computers, the budget will simply be used to add new computers. The old computers will still stick around.
“Legacy” is a problem that money can’t solve. Programmers know how to build small things, but not big things. Everything starts out small, then becomes big gradually over time through constant small additions. What you have now is big legacy systems. Attempts to replace a big system with a built-from-scratch big system will fail, because engineers don’t know how to build big systems. This will suck down any amount of budget you have with failed multi-million dollar projects.
It’s not the antiquated systems that are usually the problem, but more modern systems. Antiquated systems can usually be protected by simply sticking a firewall or proxy in front of them.

“address immediate unmet budgetary needs necessary to manage risk”

Nobody cares about cybersecurity. Instead, it’s a thing people exploit in order to increase their budget. Instead of doing the best security with the budget they have, they insist they can’t secure the network without more money.

An alternate way to address gaps in cybersecurity is instead to do less. Reduce exposure to the web, provide fewer services, reduce functionality of desktop computers, and so on. Insisting that more money is the only way to address unmet needs is the strategy of the incompetent.

Use the NIST framework
Probably the biggest thing in the EO is that it forces everyone to use the NIST cybersecurity framework.
The NIST Framework simply documents all the things that organizations commonly do to secure themselves, such run intrusion-detection systems or impose rules for good passwords.
There are two problems with the NIST Framework. The first is that no organization does all the things listed. The second is that many organizations don’t do the things well.
Password rules are a good example. Organizations typically had bad rules, such as frequent changes and complexity standards. So the NIST Framework documented them. But cybersecurity experts have long opposed those complex rules, so have been fighting NIST on them.

Another good example is intrusion-detection. These days, I scan the entire Internet, setting off everyone’s intrusion-detection systems. I can see first hand that they are doing intrusion-detection wrong. But the NIST Framework recommends they do it, because many organizations do it, but the NIST Framework doesn’t demand they do it well.
When this EO forces everyone to follow the NIST Framework, then, it’s likely just going to increase the amount of money spent on cybersecurity without increasing effectiveness. That’s not necessarily a bad thing: while probably ineffective or counterproductive in the short run, there might be long-term benefit aligning everyone to thinking about the problem the same way.
Note that “following” the NIST Framework doesn’t mean “doing” everything. Instead, it means documented how you do everything, a reason why you aren’t doing anything, or (most often) your plan to eventually do the thing.
preference for shared IT services for email, cloud, and cybersecurity
Different departments are hostile toward each other, with each doing things their own way. Obviously, the thinking goes, that if more departments shared resources, they could cut costs with economies of scale. Also obviously, it’ll stop the many home-grown wrong solutions that individual departments come up with.
In other words, there should be a single government GMail-type service that does e-mail both securely and reliably.
But it won’t turn out this way. Government does not have “economies of scale” but “incompetence at scale”. It means a single GMail-like service that is expensive, unreliable, and in the end, probably insecure. It means we can look forward to government breaches that instead of affecting one department affecting all departments.

Yes, you can point to individual organizations that do things poorly, but what you are ignoring is the organizations that do it well. When you make them all share a solution, it’s going to be the average of all these things — meaning those who do something well are going to move to a worse solution.

I suppose this was inserted in there so that big government cybersecurity companies can now walk into agencies, point to where they are deficient on the NIST Framework, and say “sign here to do this with our shared cybersecurity service”.
“identify authorities and capabilities that agencies could employ to support the cybersecurity efforts of critical infrastructure entities”
What this means is “how can we help secure the power grid?”.
What it means in practice is that fiasco in the Vermont power grid. The DHS produced a report containing IoCs (“indicators of compromise”) of Russian hackers in the DNC hack. Among the things it identified was that the hackers used Yahoo! email. They pushed these IoCs out as signatures in their “Einstein” intrusion-detection system located at many power grid locations. The next person that logged into their Yahoo! email was then flagged as a Russian hacker, causing all sorts of hilarity to ensue, such as still uncorrected stories by the Washington Post how the Russians hacked our power-grid.
The upshot is that federal government help is also going to include much government hindrance. They really are this stupid sometimes and there is no way to fix this stupid. (Seriously, the DHS still insists it did the right thing pushing out the Yahoo IoCs).
Resilience Against Botnets and Other Automated, Distributed Threats

The government wants to address botnets because it’s just the sort of problem they love, mass outages across the entire Internet caused by a million machines.

But frankly, botnets don’t even make the top 10 list of problems they should be addressing. Number #1 is clearly “phishing” — you know, the attack that’s been getting into the DNC and Podesta e-mails, influencing the election. You know, the attack that Gizmodo recently showed the Trump administration is partially vulnerable to. You know, the attack that most people blame as what probably led to that huge OPM hack. Replace the entire Executive Order with “stop phishing”, and you’d go further fixing federal government security.

But solving phishing is tough. To begin with, it requires a rethink how the government does email, and how how desktop systems should be managed. So the government avoids complex problems it can’t understand to focus on the simple things it can — botnets.

Dealing with “prolonged power outage associated with a significant cyber incident”

The government has had the hots for this since 2001, even though there’s really been no attack on the American grid. After the Russian attacks against the Ukraine power grid, the issue is heating up.

Nation-wide attacks aren’t really a threat, yet, in America. We have 10,000 different companies involved with different systems throughout the country. Trying to hack them all at once is unlikely. What’s funny is that it’s the government’s attempts to standardize everything that’s likely to be our downfall, such as sticking Einstein sensors everywhere.

What they should be doing is instead of trying to make the grid unhackable, they should be trying to lessen the reliance upon the grid. They should be encouraging things like Tesla PowerWalls, solar panels on roofs, backup generators, and so on. Indeed, rather than industrial system blackout, industry backup power generation should be considered as a source of grid backup. Factories and even ships were used to supplant the electric power grid in Japan after the 2011 tsunami, for example. The less we rely on the grid, the less a blackout will hurt us.

“cybersecurity risks facing the defense industrial base, including its supply chain”

So “supply chain” cybersecurity is increasingly becoming a thing. Almost anything electronic comes with millions of lines of code, silicon chips, and other things that affect the security of the system. In this context, they may be worried about intentional subversion of systems, such as that recent article worried about Kaspersky anti-virus in government systems. However, the bigger concern is the zillions of accidental vulnerabilities waiting to be discovered. It’s impractical for a vendor to secure a product, because it’s built from so many components the vendor doesn’t understand.

“strategic options for deterring adversaries and better protecting the American people from cyber threats”

Deterrence is a funny word.

Rumor has it that we forced China to backoff on hacking by impressing them with our own hacking ability, such as reaching into China and blowing stuff up. This works because the Chinese governments remains in power because things are going well in China. If there’s a hiccup in economic growth, there will be mass actions against the government.

But for our other cyber adversaries (Russian, Iran, North Korea), things already suck in their countries. It’s hard to see how we can make things worse by hacking them. They also have a strangle hold on the media, so hacking in and publicizing their leader’s weird sex fetishes and offshore accounts isn’t going to work either.

Also, deterrence relies upon “attribution”, which is hard. While news stories claim last year’s expulsion of Russian diplomats was due to election hacking, that wasn’t the stated reason. Instead, the claimed reason was Russia’s interference with diplomats in Europe, such as breaking into diplomat’s homes and pooping on their dining room table. We know it’s them when they are brazen (as was the case with Chinese hacking), but other hacks are harder to attribute.

Deterrence of nation states ignores the reality that much of the hacking against our government comes from non-state actors. It’s not clear how much of all this Russian hacking is actually directed by the government. Deterrence polices may be better directed at individuals, such as the recent arrest of a Russian hacker while they were traveling in Spain. We can’t get Russian or Chinese hackers in their own countries, so we have to wait until they leave.

Anyway, “deterrence” is one of those real-world concepts that hard to shoe-horn into a cyber (“cyber-deterrence”) equivalent. It encourages lots of bad thinking, such as export controls on “cyber-weapons” to deter foreign countries from using them.

“educate and train the American cybersecurity workforce of the future”

The problem isn’t that we lack CISSPs. Such blanket certifications devalue the technical expertise of the real experts. The solution is to empower the technical experts we already have.

In other words, mandate that whoever is the “cyberczar” is a technical expert, like how the Surgeon General must be a medical expert, or how an economic adviser must be an economic expert. For over 15 years, we’ve had a parade of non-technical people named “cyberczar” who haven’t been experts.

Once you tell people technical expertise is valued, then by nature more students will become technical experts.

BTW, the best technical experts are software engineers and sysadmins. The best cybersecurity for Windows is already built into Windows, whose sysadmins need to be empowered to use those solutions. Instead, they are often overridden by a clueless cybersecurity consultant who insists on making the organization buy a third-party product instead that does a poorer job. We need more technical expertise in our organizations, sure, but not necessarily more cybersecurity professionals.

Conclusion

This is really a government document, and government people will be able to explain it better than I. These are just how I see it as a technical-expert who is a government-outsider.

My guess is the most lasting consequential thing will be making everyone following the NIST Framework, and the rest will just be a lot of aspirational stuff that’ll be ignored.

Intel AMT on wireless networks

Post Syndicated from Matthew Garrett original http://mjg59.dreamwidth.org/48837.html

More details about Intel’s AMT vulnerablity have been released – it’s about the worst case scenario, in that it’s a total authentication bypass that appears to exist independent of whether the AMT is being used in Small Business or Enterprise modes (more background in my previous post here). One thing I claimed was that even though this was pretty bad it probably wasn’t super bad, since Shodan indicated that there were only a small number of thousand machines on the public internet and accessible via AMT. Most deployments were probably behind corporate firewalls, which meant that it was plausibly a vector for spreading within a company but probably wasn’t a likely initial vector.

I’ve since done some more playing and come to the conclusion that it’s rather worse than that. AMT actually supports being accessed over wireless networks. Enabling this is a separate option – if you simply provision AMT it won’t be accessible over wireless by default, you need to perform additional configuration (although this is as simple as logging into the web UI and turning on the option). Once enabled, there are two cases:

  1. The system is not running an operating system, or the operating system has not taken control of the wireless hardware. In this case AMT will attempt to join any network that it’s been explicitly told about. Note that in default configuration, joining a wireless network from the OS is not sufficient for AMT to know about it – there needs to be explicit synchronisation of the network credentials to AMT. Intel provide a wireless manager that does this, but the stock behaviour in Windows (even after you’ve installed the AMT support drivers) is not to do this.
  2. The system is running an operating system that has taken control of the wireless hardware. In this state, AMT is no longer able to drive the wireless hardware directly and counts on OS support to pass packets on. Under Linux, Intel’s wireless drivers do not appear to implement this feature. Under Windows, they do. This does not require any application level support, and uninstalling LMS will not disable this functionality. This also appears to happen at the driver level, which means it bypasses the Windows firewall.

Case 2 is the scary one. If you have a laptop that supports AMT, and if AMT has been provisioned, and if AMT has had wireless support turned on, and if you’re running Windows, then connecting your laptop to a public wireless network means that AMT is accessible to anyone else on that network[1]. If it hasn’t received a firmware update, they’ll be able to do so without needing any valid credentials.

If you’re a corporate IT department, and if you have AMT enabled over wifi, turn it off. Now.

[1] Assuming that the network doesn’t block client to client traffic, of course

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Looking at the Netgear Arlo home IP camera

Post Syndicated from Matthew Garrett original http://mjg59.dreamwidth.org/48215.html

Another in the series of looking at the security of IoT type objects. This time I’ve gone for the Arlo network connected cameras produced by Netgear, specifically the stock Arlo base system with a single camera. The base station is based on a Broadcom 5358 SoC with an 802.11n radio, along with a single Broadcom gigabit ethernet interface. Other than it only having a single ethernet port, this looks pretty much like a standard Netgear router. There’s a convenient unpopulated header on the board that turns out to be a serial console, so getting a shell is only a few minutes work.

Normal setup is straight forward. You plug the base station into a router, wait for all the lights to come on and then you visit arlo.netgear.com and follow the setup instructions – by this point the base station has connected to Netgear’s cloud service and you’re just associating it to your account. Security here is straightforward: you need to be coming from the same IP address as the Arlo. For most home users with NAT this works fine. I sat frustrated as it repeatedly failed to find any devices, before finally moving everything behind a backup router (my main network isn’t NATted) for initial setup. Once you and the Arlo are on the same IP address, the site shows you the base station’s serial number for confirmation and then you attach it to your account. Next step is adding cameras. Each base station is broadcasting an 802.11 network on the 2.4GHz spectrum. You connect a camera by pressing the sync button on the base station and then the sync button on the camera. The camera associates with the base station via WDS and now you’re up and running.

This is the point where I get bored and stop following instructions, but if you’re using a desktop browser (rather than using the mobile app) you appear to need Flash in order to actually see any of the camera footage. Bleah.

But back to the device itself. The first thing I traced was the initial device association. What I found was that once the device is associated with an account, it can’t be attached to another account. This is good – I can’t simply request that devices be rebound to my account from someone else’s. Further, while the serial number is displayed to the user to disambiguate between devices, it doesn’t seem to be what’s used internally. Tracing the logon traffic from the base station shows it sending a long random device ID along with an authentication token. If you perform a factory reset, these values are regenerated. The device to account mapping seems to be based on this random device ID, which means that once the device is reset and bound to another account there’s no way for the initial account owner to regain access (other than resetting it again and binding it back to their account). This is far better than many devices I’ve looked at.

Performing a factory reset also changes the WPA PSK for the camera network. Newsky Security discovered that doing so originally reset it to 12345678, which is, uh, suboptimal? That’s been fixed in newer firmware, along with their discovery that the original random password choice was not terribly random.

All communication from the base station to the cloud seems to be over SSL, and everything validates certificates properly. This also seems to be true for client communication with the cloud service – camera footage is streamed back over port 443 as well.

Most of the functionality of the base station is provided by two daemons, xagent and vzdaemon. xagent appears to be responsible for registering the device with the cloud service, while vzdaemon handles the camera side of things (including motion detection). All of this is running as root, so in the event of any kind of vulnerability the entire platform is owned. For such a single purpose device this isn’t really a big deal (the only sensitive data it has is the camera feed – if someone has access to that then root doesn’t really buy them anything else). They’re statically linked and stripped so I couldn’t be bothered spending any significant amount of time digging into them. In any case, they don’t expose any remotely accessible ports and only connect to services with verified SSL certificates. They’re probably not a big risk.

Other than the dependence on Flash, there’s nothing immediately concerning here. What is a little worrying is a family of daemons running on the device and listening to various high numbered UDP ports. These appear to be provided by Broadcom and a standard part of all their router platforms – they’re intended for handling various bits of wireless authentication. It’s not clear why they’re listening on 0.0.0.0 rather than 127.0.0.1, and it’s not obvious whether they’re vulnerable (they mostly appear to receive packets from the driver itself, process them and then stick packets back into the kernel so who knows what’s actually going on), but since you can’t set one of these devices up in the first place without it being behind a NAT gateway it’s unlikely to be of real concern to most users. On the other hand, the same daemons seem to be present on several Broadcom-based router platforms where they may end up being visible to the outside world. That’s probably investigation for another day, though.

Overall: pretty solid, frustrating to set up if your network doesn’t match their expectations, wouldn’t have grave concerns over having it on an appropriately firewalled network.

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"Fast and Furious 8: Fate of the Furious"

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/04/fast-and-furious-8-fate-of-furious.html

So “Fast and Furious 8” opened this weekend to world-wide box office totals of $500,000,000. I thought I’d write up some notes on the “hacking” in it. The tl;dr version is this: yes, while the hacking is a bit far fetched, it’s actually more realistic than the car chase scenes, such as winning a race with the engine on fire while in reverse.

[SPOILERS]


Car hacking


The most innovative cyber-thing in the movie is the car hacking. In one scene, the hacker takes control of the cars in a parking structure, and makes them rain on to the street. In another scene, the hacker takes control away from drivers, with some jumping out of their moving cars in fear.

How real is this?

Well, today, few cars have a mechanical link between the computer and the steering wheel. No amount of hacking will fix the fact that this component is missing.

With that said, most new cars have features that make hacking possible. I’m not sure, but I’d guess more than half of new cars have internet connections (via the mobile phone network), cameras (for backing up, but also looking forward for lane departure warnings), braking (for emergencies), and acceleration.

In other words, we are getting really close.

As this Wikipedia article describes, there are levels for autonomous cars. At level 2 or 3, cars get automated steering, either for parking or for staying in the lane. Level 3 autonomy is especially useful, as it means you can sit back and relax while your car is sitting in a traffic jam. Higher levels of autonomy are still decades away, but most new cars, even the cheapest low end cars, will be level 3 within 5 years. That they make traffic jams bearable makes this an incredibly attractive feature.

Thus, while this scene is laughable today, it’ll be taken seriously in 10 years. People will look back on how smart this movie was at predicting the future.

Car hacking, part 2

Quite apart from the abilities of cars, let’s talk about the abilities of hackers.

The recent ShadowBrokers dump of NSA hacking tools show that hackers simply don’t have a lot of range. Hacking one car is easy — hacking all different models, makes, and years of cars is far beyond the ability of any hacking group, even the NSA.

I mean, a single hack may span more than one car model, and even across more than one manufacturer, because they buy such components from third-party manufacturers. Most cars that have cameras buy them from MobileEye, which was recently acquired by Intel.  As I blogged before, both my Parrot drone and Tesla car have the same WiFi stack, and both could be potential hacked with the same vulnerability. So hacking many cars at once isn’t totally out of the question.

It’s just that hacking all the different cars in a garage is completely implausible.

God’s Eye

The plot of the last two movies as been about the “God’s Eye”, a device that hacks into every camera and satellite to view everything going on in the world.

First of all, all hacking is software. The idea of stealing a hardware device in order enable hacking is therefore (almost) always fiction. There’s one corner case where a quantum chip factoring RSA would enable some previously impossible hacking, but it still can’t reach out and hack a camera behind a firewall.

Hacking security cameras around the world is indeed possible, though. The Mirai botnet of last year demonstrated this. It wormed its way form camera to camera, hacking hundreds of thousands of cameras that weren’t protected by firewalls. It used these devices as simply computers, to flood major websites, taking them offline. But it could’ve also used the camera features, to upload pictures and video’s to the hacker controlling these cameras.

However, most security cameras are behind firewalls, and can’t be reached. Building a “Gody’s Eye” view of the world, to catch a target every time they passed in front of a camera, would therefore be unrealistic.

Moreover, they don’t have either the processing power nor the bandwidth to work like that. It takes heavy number crunching in order to detect faces, or even simple things like license plates, within videos. The cameras don’t have that. Instead, cameras could upload the videos/pictures to supercomputers controlled by the hypothetical hacker, but the bandwidth doesn’t exist. The Internet is being rapidly upgraded, but still, Internet links are built for low-bandwidth webpages, not high-bandwidth streaming from millions of sources.

This rapidly changing. Cameras are rapidly being upgraded with “neural network” chips that will have some rudimentary capabilities to recognize things like license plates, or the outline of a face that could then be uploaded for more powerful number crunching elsewhere. Your car’s cameras already have this, for backup warnings and lane departure warnings, soon all security cameras will have something like this. Likewise, the Internet is steadily being upgraded to replace TV broadcast, where everyone can stream from Netflix all the time, so high-bandwidth streams from cameras will become more of the norm.

Even getting behind a firewall to the camera will change in the future, as owners will simply store surveillance video in the cloud instead of locally. Thus, the hypothetical hacker would only need to hack a small number of surveillance camera companies instead of a billion security cameras.

Evil villain lair: ghost airplane

The evil villain in the movie (named “Cipher”, or course) has her secret headquarters on an airplane that flies along satellite “blind spots” so that it can’t be tracked.

This is nonsense. Low resolution satellites, like NOAA satellites tracking the weather, cover the entire planet (well, as far as such airplanes are concerned, unless you are landing in Antartica). While such satellites might not see the plane, they can track the contrail (I mean, chemtrail). Conversely high resolution satellites miss most of the planet. If they haven’t been tasked to aim at something, they won’t see it. And they can’t be aimed at you unless they already know where you are. Sure, there are moving blind spots where even tasked satellites can’t find you, but it’s unlikely they’d be tracking you anyway.

Since the supervillain was a hacker, the airplane was full of computers. This is nonsense. Any compute power I need as a hacker is better left on the Earth’s surface, either by hacking cloud providers (like Amazon AWS, Microsoft Azure, or Rackspace), or by hiding data centers in Siberia and Tibet. All I need is satellite communication to the Internet from my laptop to be a supervillain. Indeed, I’m unlikely to get the bandwidth I need to process things on the plane. Instead, I’ll need to process everything on the Earth anyway, and send the low-bandwidth results to the plane.

In any case, if I were writing fiction, I’d have nuclear-powered airplanes that stayed aloft for months, operating out of remote bases in the Himalayas or Antartica.

EMP pulses

Small EMP pulse weapons exist, that’s not wholly fictional.

However, an EMP with the features, power, and effects in the movie is, of course, fictional. EMPs, even non-nuclear ones, are abused in films/TV so much that the Wikipedia pages on them spend a lot of time debunking them.

It would be cool if, one day, they used EMP realistically. In this movie, real missile-tipped with non-nuclear explosively-pumped flux compression generators could’ve been used for the same effect. Of course, simple explosives that blow up electronics also work.

Since hacking is the goto deus ex machina these days, they could’ve just had the hackers disable the power instead of using the EMP to do it.

Conclusion

In the movie, the hero uses his extraordinary driving skills to blow up a submarine. Given this level of willing disbelief, the exaggerated hacking is actually the least implausible bits of the movie. Indeed, as technology changes, making some of this more possible, the movie might be seen as predicting the future.

Steampunk laptop powered by Pi: OMG so fancy!

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/steampunk-laptop/

In this digital age, where backup computers and multiple internet-connected devices are a must, maker phrazelle built this beautiful Raspberry Pi-powered steampunk laptop for his girlfriend.

And now we all want one. I mean, just look at it!

Raspberry Pi Steampunk laptop

There’s no denying that, had Liz seen this before me, she’d have copied the link into an email and titled it INSTABLOG before sending it to my inbox.

This build is gorgeous. And as a fan of quirky-looking tech builds and of making things out of wood, it caught my eye in a heartbeat, causing me to exclaim “Why, I – ugh! – I want a Steampunk laptop?!” Shortly afterwards, there followed the realisation that there is an Instructables page for the project, leading me to rejoice that I could make my own. “You’ll never finish it,” chides the incomplete Magic Mirror beneath my desk. I shush it with a kick.

Winging it

“I didn’t really spec this out when I started building. I knew I wanted a box, but didn’t know how I was going to approach it,” explains phrazelle, a maker after my own “meh, I’ll wing it” heart. He continues, “I started with a mechanical keyboard with some typewriter-esque keys and built out a board for it. This went in a few directions, and I wound up with a Frankenstein keyboard tray.”

Originally wanting a hole for each key, phrazelle used a paint relief method to mark the place of each one. However, this didn’t work out too well, so he decided to jigsaw out a general space for the keys in a group. After a few attempts and an application of Gorilla Glue, it was looking good.

Building a Steampunk laptop

With his father’s help, phrazelle’s next step was to build the box for the body of the laptop. Again, it was something of an unplanned mashup, resulting in a box that was built around the keyboard tray. Via a series of mitred joints, routing, and some last minute trim, he was able to fit an LCD screen from a cannibalised laptop into the lid, complete with an LCD driver acquired from eBay.

All of the Steampunk trimmings

“As I was going in the Steampunk direction, gears and gauges seemed to make sense,” says phrazelle. “I found a lot of cool stuff on Etsy and Amazon. The front battery gauge, back switch plate, and LED indicator housings came off Etsy.” He also discovered that actual watch gears, which he had purchased in bulk, were too flimsy for use as decoration, so he replaced them with some brass replicas from Amazon instead. Hand-blown marbles worked as LED defusers and the case was complete.

Inside the belly of the (beautiful) beast

Within the laptop body, phrazelle (do let us know your actual name, by the way) included a Talentcell battery pack which he modified to cut the output lines, something that was causing grief when trying to charge the battery. He utilised a plugable USB 2.4 four-port powered hub to power the Raspberry Pi and optional USB devices. He also added a bushel of various other modifications, all of which he explains on his Instructables page.

I ran with the Pixel distro for this build. Then I went through and did some basic security housekeeping like changing the default password, closing every unnecessary port on the firewall, and disabling the Bluetooth. I even put the Bro IDS platform on it to keep an eye out for shifty hackers… *shakes fist*

This thing runs like a champ! For its intended functionality, it does everything it needs to. You can get on the internet, write papers, check email… If you want to get nerdy, you can even brush up on your coding skillz.

Instructables and you

As I said, we love this build. Not only is it a great example of creating an all-in-one Raspberry Pi laptop, but it’s also gorgeous! Make sure to check out phrazelle’s other builds on Instructables, including his Zelda-themed bartop arcade and his ornate magic mirror.

While you’re there, check out the other Raspberry Pi-themed builds on Instructables. There are LOADS of them. And they’re great. And if you wrote any of them – ahem! – like I did, you should be proud of yourself – ahem! – like I am. *clears throat even more pointedly*

Have you built your own Pi laptop? Tell us about it in the comments below. We can’t wait to see it!

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