Tag Archives: defcon

Securing Elections

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/04/securing_electi_1.html

Elections serve two purposes. The first, and obvious, purpose is to accurately choose the winner. But the second is equally important: to convince the loser. To the extent that an election system is not transparently and auditably accurate, it fails in that second purpose. Our election systems are failing, and we need to fix them.

Today, we conduct our elections on computers. Our registration lists are in computer databases. We vote on computerized voting machines. And our tabulation and reporting is done on computers. We do this for a lot of good reasons, but a side effect is that elections now have all the insecurities inherent in computers. The only way to reliably protect elections from both malice and accident is to use something that is not hackable or unreliable at scale; the best way to do that is to back up as much of the system as possible with paper.

Recently, there have been two graphic demonstrations of how bad our computerized voting system is. In 2007, the states of California and Ohio conducted audits of their electronic voting machines. Expert review teams found exploitable vulnerabilities in almost every component they examined. The researchers were able to undetectably alter vote tallies, erase audit logs, and load malware on to the systems. Some of their attacks could be implemented by a single individual with no greater access than a normal poll worker; others could be done remotely.

Last year, the Defcon hackers’ conference sponsored a Voting Village. Organizers collected 25 pieces of voting equipment, including voting machines and electronic poll books. By the end of the weekend, conference attendees had found ways to compromise every piece of test equipment: to load malicious software, compromise vote tallies and audit logs, or cause equipment to fail.

It’s important to understand that these were not well-funded nation-state attackers. These were not even academics who had been studying the problem for weeks. These were bored hackers, with no experience with voting machines, playing around between parties one weekend.

It shouldn’t be any surprise that voting equipment, including voting machines, voter registration databases, and vote tabulation systems, are that hackable. They’re computers — often ancient computers running operating systems no longer supported by the manufacturers — and they don’t have any magical security technology that the rest of the industry isn’t privy to. If anything, they’re less secure than the computers we generally use, because their manufacturers hide any flaws behind the proprietary nature of their equipment.

We’re not just worried about altering the vote. Sometimes causing widespread failures, or even just sowing mistrust in the system, is enough. And an election whose results are not trusted or believed is a failed election.

Voting systems have another requirement that makes security even harder to achieve: the requirement for a secret ballot. Because we have to securely separate the election-roll system that determines who can vote from the system that collects and tabulates the votes, we can’t use the security systems available to banking and other high-value applications.

We can securely bank online, but can’t securely vote online. If we could do away with anonymity — if everyone could check that their vote was counted correctly — then it would be easy to secure the vote. But that would lead to other problems. Before the US had the secret ballot, voter coercion and vote-buying were widespread.

We can’t, so we need to accept that our voting systems are insecure. We need an election system that is resilient to the threats. And for many parts of the system, that means paper.

Let’s start with the voter rolls. We know they’ve already been targeted. In 2016, someone changed the party affiliation of hundreds of voters before the Republican primary. That’s just one possibility. A well-executed attack that deletes, for example, one in five voters at random — or changes their addresses — would cause chaos on election day.

Yes, we need to shore up the security of these systems. We need better computer, network, and database security for the various state voter organizations. We also need to better secure the voter registration websites, with better design and better internet security. We need better security for the companies that build and sell all this equipment.

Multiple, unchangeable backups are essential. A record of every addition, deletion, and change needs to be stored on a separate system, on write-only media like a DVD. Copies of that DVD, or — even better — a paper printout of the voter rolls, should be available at every polling place on election day. We need to be ready for anything.

Next, the voting machines themselves. Security researchers agree that the gold standard is a voter-verified paper ballot. The easiest (and cheapest) way to achieve this is through optical-scan voting. Voters mark paper ballots by hand; they are fed into a machine and counted automatically. That paper ballot is saved, and serves as a final true record in a recount in case of problems. Touch-screen machines that print a paper ballot to drop in a ballot box can also work for voters with disabilities, as long as the ballot can be easily read and verified by the voter.

Finally, the tabulation and reporting systems. Here again we need more security in the process, but we must always use those paper ballots as checks on the computers. A manual, post-election, risk-limiting audit varies the number of ballots examined according to the margin of victory. Conducting this audit after every election, before the results are certified, gives us confidence that the election outcome is correct, even if the voting machines and tabulation computers have been tampered with. Additionally, we need better coordination and communications when incidents occur.

It’s vital to agree on these procedures and policies before an election. Before the fact, when anyone can win and no one knows whose votes might be changed, it’s easy to agree on strong security. But after the vote, someone is the presumptive winner — and then everything changes. Half of the country wants the result to stand, and half wants it reversed. At that point, it’s too late to agree on anything.

The politicians running in the election shouldn’t have to argue their challenges in court. Getting elections right is in the interest of all citizens. Many countries have independent election commissions that are charged with conducting elections and ensuring their security. We don’t do that in the US.

Instead, we have representatives from each of our two parties in the room, keeping an eye on each other. That provided acceptable security against 20th-century threats, but is totally inadequate to secure our elections in the 21st century. And the belief that the diversity of voting systems in the US provides a measure of security is a dangerous myth, because few districts can be decisive and there are so few voting-machine vendors.

We can do better. In 2017, the Department of Homeland Security declared elections to be critical infrastructure, allowing the department to focus on securing them. On 23 March, Congress allocated $380m to states to upgrade election security.

These are good starts, but don’t go nearly far enough. The constitution delegates elections to the states but allows Congress to “make or alter such Regulations”. In 1845, Congress set a nationwide election day. Today, we need it to set uniform and strict election standards.

This essay originally appeared in the Guardian.

Improve the Operational Efficiency of Amazon Elasticsearch Service Domains with Automated Alarms Using Amazon CloudWatch

Post Syndicated from Veronika Megler original https://aws.amazon.com/blogs/big-data/improve-the-operational-efficiency-of-amazon-elasticsearch-service-domains-with-automated-alarms-using-amazon-cloudwatch/

A customer has been successfully creating and running multiple Amazon Elasticsearch Service (Amazon ES) domains to support their business users’ search needs across products, orders, support documentation, and a growing suite of similar needs. The service has become heavily used across the organization.  This led to some domains running at 100% capacity during peak times, while others began to run low on storage space. Because of this increased usage, the technical teams were in danger of missing their service level agreements.  They contacted me for help.

This post shows how you can set up automated alarms to warn when domains need attention.

Solution overview

Amazon ES is a fully managed service that delivers Elasticsearch’s easy-to-use APIs and real-time analytics capabilities along with the availability, scalability, and security that production workloads require.  The service offers built-in integrations with a number of other components and AWS services, enabling customers to go from raw data to actionable insights quickly and securely.

One of these other integrated services is Amazon CloudWatch. CloudWatch is a monitoring service for AWS Cloud resources and the applications that you run on AWS. You can use CloudWatch to collect and track metrics, collect and monitor log files, set alarms, and automatically react to changes in your AWS resources.

CloudWatch collects metrics for Amazon ES. You can use these metrics to monitor the state of your Amazon ES domains, and set alarms to notify you about high utilization of system resources.  For more information, see Amazon Elasticsearch Service Metrics and Dimensions.

While the metrics are automatically collected, the missing piece is how to set alarms on these metrics at appropriate levels for each of your domains. This post includes sample Python code to evaluate the current state of your Amazon ES environment, and to set up alarms according to AWS recommendations and best practices.

There are two components to the sample solution:

  • es-check-cwalarms.py: This Python script checks the CloudWatch alarms that have been set, for all Amazon ES domains in a given account and region.
  • es-create-cwalarms.py: This Python script sets up a set of CloudWatch alarms for a single given domain.

The sample code can also be found in the amazon-es-check-cw-alarms GitHub repo. The scripts are easy to extend or combine, as described in the section “Extensions and Adaptations”.

Assessing the current state

The first script, es-check-cwalarms.py, is used to give an overview of the configurations and alarm settings for all the Amazon ES domains in the given region. The script takes the following parameters:

python es-checkcwalarms.py -h
usage: es-checkcwalarms.py [-h] [-e ESPREFIX] [-n NOTIFY] [-f FREE][-p PROFILE] [-r REGION]
Checks a set of recommended CloudWatch alarms for Amazon Elasticsearch Service domains (optionally, those beginning with a given prefix).
optional arguments:
  -h, --help   		show this help message and exit
  -e ESPREFIX, --esprefix ESPREFIX	Only check Amazon Elasticsearch Service domains that begin with this prefix.
  -n NOTIFY, --notify NOTIFY    List of CloudWatch alarm actions; e.g. ['arn:aws:sns:xxxx']
  -f FREE, --free FREE  Minimum free storage (MB) on which to alarm
  -p PROFILE, --profile PROFILE     IAM profile name to use
  -r REGION, --region REGION       AWS region for the domain. Default: us-east-1

The script first identifies all the domains in the given region (or, optionally, limits them to the subset that begins with a given prefix). It then starts running a set of checks against each one.

The script can be run from the command line or set up as a scheduled Lambda function. For example, for one customer, it was deemed appropriate to regularly run the script to check that alarms were correctly set for all domains. In addition, because configuration changes—cluster size increases to accommodate larger workloads being a common change—might require updates to alarms, this approach allowed the automatic identification of alarms no longer appropriately set as the domain configurations changed.

The output shown below is the output for one domain in my account.

Starting checks for Elasticsearch domain iotfleet , version is 53
Iotfleet Automated snapshot hour (UTC): 0
Iotfleet Instance configuration: 1 instances; type:m3.medium.elasticsearch
Iotfleet Instance storage definition is: 4 GB; free storage calced to: 819.2 MB
iotfleet Desired free storage set to (in MB): 819.2
iotfleet WARNING: Not using VPC Endpoint
iotfleet WARNING: Does not have Zone Awareness enabled
iotfleet WARNING: Instance count is ODD. Best practice is for an even number of data nodes and zone awareness.
iotfleet WARNING: Does not have Dedicated Masters.
iotfleet WARNING: Neither index nor search slow logs are enabled.
iotfleet WARNING: EBS not in use. Using instance storage only.
iotfleet Alarm ok; definition matches. Test-Elasticsearch-iotfleet-ClusterStatus.yellow-Alarm ClusterStatus.yellow
iotfleet Alarm ok; definition matches. Test-Elasticsearch-iotfleet-ClusterStatus.red-Alarm ClusterStatus.red
iotfleet Alarm ok; definition matches. Test-Elasticsearch-iotfleet-CPUUtilization-Alarm CPUUtilization
iotfleet Alarm ok; definition matches. Test-Elasticsearch-iotfleet-JVMMemoryPressure-Alarm JVMMemoryPressure
iotfleet WARNING: Missing alarm!! ('ClusterIndexWritesBlocked', 'Maximum', 60, 5, 'GreaterThanOrEqualToThreshold', 1.0)
iotfleet Alarm ok; definition matches. Test-Elasticsearch-iotfleet-AutomatedSnapshotFailure-Alarm AutomatedSnapshotFailure
iotfleet Alarm: Threshold does not match: Test-Elasticsearch-iotfleet-FreeStorageSpace-Alarm Should be:  819.2 ; is 3000.0

The output messages fall into the following categories:

  • System overview, Informational: The Amazon ES version and configuration, including instance type and number, storage, automated snapshot hour, etc.
  • Free storage: A calculation for the appropriate amount of free storage, based on the recommended 20% of total storage.
  • Warnings: best practices that are not being followed for this domain. (For more about this, read on.)
  • Alarms: An assessment of the CloudWatch alarms currently set for this domain, against a recommended set.

The script contains an array of recommended CloudWatch alarms, based on best practices for these metrics and statistics. Using the array allows alarm parameters (such as free space) to be updated within the code based on current domain statistics and configurations.

For a given domain, the script checks if each alarm has been set. If the alarm is set, it checks whether the values match those in the array esAlarms. In the output above, you can see three different situations being reported:

  • Alarm ok; definition matches. The alarm set for the domain matches the settings in the array.
  • Alarm: Threshold does not match. An alarm exists, but the threshold value at which the alarm is triggered does not match.
  • WARNING: Missing alarm!! The recommended alarm is missing.

All in all, the list above shows that this domain does not have a configuration that adheres to best practices, nor does it have all the recommended alarms.

Setting up alarms

Now that you know that the domains in their current state are missing critical alarms, you can correct the situation.

To demonstrate the script, set up a new domain named “ver”, in us-west-2. Specify 1 node, and a 10-GB EBS disk. Also, create an SNS topic in us-west-2 with a name of “sendnotification”, which sends you an email.

Run the second script, es-create-cwalarms.py, from the command line. This script creates (or updates) the desired CloudWatch alarms for the specified Amazon ES domain, “ver”.

python es-create-cwalarms.py -r us-west-2 -e test -c ver -n "['arn:aws:sns:us-west-2:xxxxxxxxxx:sendnotification']"
EBS enabled: True type: gp2 size (GB): 10 No Iops 10240  total storage (MB)
Desired free storage set to (in MB): 2048.0
Creating  Test-Elasticsearch-ver-ClusterStatus.yellow-Alarm
Creating  Test-Elasticsearch-ver-ClusterStatus.red-Alarm
Creating  Test-Elasticsearch-ver-CPUUtilization-Alarm
Creating  Test-Elasticsearch-ver-JVMMemoryPressure-Alarm
Creating  Test-Elasticsearch-ver-FreeStorageSpace-Alarm
Creating  Test-Elasticsearch-ver-ClusterIndexWritesBlocked-Alarm
Creating  Test-Elasticsearch-ver-AutomatedSnapshotFailure-Alarm
Successfully finished creating alarms!

As with the first script, this script contains an array of recommended CloudWatch alarms, based on best practices for these metrics and statistics. This approach allows you to add or modify alarms based on your use case (more on that below).

After running the script, navigate to Alarms on the CloudWatch console. You can see the set of alarms set up on your domain.

Because the “ver” domain has only a single node, cluster status is yellow, and that alarm is in an “ALARM” state. It’s already sent a notification that the alarm has been triggered.

What to do when an alarm triggers

After alarms are set up, you need to identify the correct action to take for each alarm, which depends on the alarm triggered. For ideas, guidance, and additional pointers to supporting documentation, see Get Started with Amazon Elasticsearch Service: Set CloudWatch Alarms on Key Metrics. For information about common errors and recovery actions to take, see Handling AWS Service Errors.

In most cases, the alarm triggers due to an increased workload. The likely action is to reconfigure the system to handle the increased workload, rather than reducing the incoming workload. Reconfiguring any backend store—a category of systems that includes Elasticsearch—is best performed when the system is quiescent or lightly loaded. Reconfigurations such as setting zone awareness or modifying the disk type cause Amazon ES to enter a “processing” state, potentially disrupting client access.

Other changes, such as increasing the number of data nodes, may cause Elasticsearch to begin moving shards, potentially impacting search performance on these shards while this is happening. These actions should be considered in the context of your production usage. For the same reason I also do not recommend running a script that resets all domains to match best practices.

Avoid the need to reconfigure during heavy workload by setting alarms at a level that allows a considered approach to making the needed changes. For example, if you identify that each weekly peak is increasing, you can reconfigure during a weekly quiet period.

While Elasticsearch can be reconfigured without being quiesced, it is not a best practice to automatically scale it up and down based on usage patterns. Unlike some other AWS services, I recommend against setting a CloudWatch action that automatically reconfigures the system when alarms are triggered.

There are other situations where the planned reconfiguration approach may not work, such as low or zero free disk space causing the domain to reject writes. If the business is dependent on the domain continuing to accept incoming writes and deleting data is not an option, the team may choose to reconfigure immediately.

Extensions and adaptations

You may wish to modify the best practices encoded in the scripts for your own environment or workloads. It’s always better to avoid situations where alerts are generated but routinely ignored. All alerts should trigger a review and one or more actions, either immediately or at a planned date. The following is a list of common situations where you may wish to set different alarms for different domains:

  • Dev/test vs. production
    You may have a different set of configuration rules and alarms for your dev environment configurations than for test. For example, you may require zone awareness and dedicated masters for your production environment, but not for your development domains. Or, you may not have any alarms set in dev. For test environments that mirror your potential peak load, test to ensure that the alarms are appropriately triggered.
  • Differing workloads or SLAs for different domains
    You may have one domain with a requirement for superfast search performance, and another domain with a heavy ingest load that tolerates slower search response. Your reaction to slow response for these two workloads is likely to be different, so perhaps the thresholds for these two domains should be set at a different level. In this case, you might add a “max CPU utilization” alarm at 100% for 1 minute for the fast search domain, while the other domain only triggers an alarm when the average has been higher than 60% for 5 minutes. You might also add a “free space” rule with a higher threshold to reflect the need for more space for the heavy ingest load if there is danger that it could fill the available disk quickly.
  • “Normal” alarms versus “emergency” alarms
    If, for example, free disk space drops to 25% of total capacity, an alarm is triggered that indicates action should be taken as soon as possible, such as cleaning up old indexes or reconfiguring at the next quiet period for this domain. However, if free space drops below a critical level (20% free space), action must be taken immediately in order to prevent Amazon ES from setting the domain to read-only. Similarly, if the “ClusterIndexWritesBlocked” alarm triggers, the domain has already stopped accepting writes, so immediate action is needed. In this case, you may wish to set “laddered” alarms, where one threshold causes an alarm to be triggered to review the current workload for a planned reconfiguration, but a different threshold raises a “DefCon 3” alarm that immediate action is required.

The sample scripts provided here are a starting point, intended for you to adapt to your own environment and needs.

Running the scripts one time can identify how far your current state is from your desired state, and create an initial set of alarms. Regularly re-running these scripts can capture changes in your environment over time and adjusting your alarms for changes in your environment and configurations. One customer has set them up to run nightly, and to automatically create and update alarms to match their preferred settings.

Removing unwanted alarms

Each CloudWatch alarm costs approximately $0.10 per month. You can remove unwanted alarms in the CloudWatch console, under Alarms. If you set up a “ver” domain above, remember to remove it to avoid continuing charges.

Conclusion

Setting CloudWatch alarms appropriately for your Amazon ES domains can help you avoid suboptimal performance and allow you to respond to workload growth or configuration issues well before they become urgent. This post gives you a starting point for doing so. The additional sleep you’ll get knowing you don’t need to be concerned about Elasticsearch domain performance will allow you to focus on building creative solutions for your business and solving problems for your customers.

Enjoy!


Additional Reading

If you found this post useful, be sure to check out Analyzing Amazon Elasticsearch Service Slow Logs Using Amazon CloudWatch Logs Streaming and Kibana and Get Started with Amazon Elasticsearch Service: How Many Shards Do I Need?

 


About the Author

Dr. Veronika Megler is a senior consultant at Amazon Web Services. She works with our customers to implement innovative big data, AI and ML projects, helping them accelerate their time-to-value when using AWS.

 

 

 

Накратко за киберсигурността

Post Syndicated from Bozho original https://blog.bozho.net/blog/3063

През уикенда се проведе събитие в рамките на „Български манифест за Европа“ на тема „Европейски съюз за отбрана и сигурност и неговите черноморски измерения“

Тъй като не успях да присъствам, записах кратко видео, с което да обясня какво е и какво не е киберсигурност. Разбира се, 5-минутно видео няма как да обхване сложната тема, но все пак целта беше да дам базова представа.

Основната ми теза е, че киберсигурността не е просто активна отбранителна дейност – тя е набор от много мерки, които в голямата си част са пасивни – добри практики, политики за сигурност, квалифициран персонал и то както в публичния, така и в частния сектор.

Защото кибератаките не са само атаки по държавните системи (напр. изборни системи, публични регистри, уебсайтове на институции и др.) а и атаки по ключови частни компании – банки, мобилни оператори. Например преди няколко години БОРИКА имаше технически проблем, който доведе до пълно спиране на работа на банкомати и ПОС-терминали в цялата страна. И докато банкоматите не са чак толкова критична инфраструктура, то например електропреносната мрежа е. В случай, че нейни части, управлявани от софтуер, биват „ударени“, това може да значи спиране на електричеството (както предупреждава, например, Washington Post). Да не говорим за оборудване, използване в ядрената енергетика, което може да бъде увредено от вирус (като известният вирус Stuxnet, забавил значително иранската ядрена програма).

Но дори да няма реални щети, атаките могат да имат сериозен имиджов ефект. Например при атаките срещу уебсайтове на институции (вкл. ЦИК) преди няколко години реално нямаше нанесени щети – просто сайтовете не бяха достъпни. Но самият факт, че институции бяха атакувани в деня на референдума за електронно гласуване пося (или поля) семето на несигурността от технологиите в изборния процес.

И защитата от всички тези атаки изобщо не е тривиална. „Дупки“ в сигурността на най-различни системи се появяват постоянно (а понякога разбираме, че ги има чак когато някой ги използва, т.нар. 0-day exploits). Ако човек гледа няколко лекции на DefCon или CCC (хакерски конференции) му идва да изхвърли цялата си техника, да отиде в планината, да си изкопае дупка и да живее спокойно там, далеч от всички „пробити“ технологии на света. Нещата не са чак толкова страшни (най-вече защото няма практическа полза от злоупотребата с немалко от техническите уязвимости), но все пак киберзащитата е набор от много, много мерки – технологични, организационни, правни.

Но ако всичко това трябва да се обобщи – трябва да инвестираме доста повече – и като държава, и като бизнес – в информационна сигурност. И лесно и бързо решение за киберсигурността няма.

Надявам се видеото да е интересно (спецификата на осветлението ме прави да изглеждам като „хакер в мазе“, което не е търсен ефект)

Self-Driving Cars Should Be Open Source

Post Syndicated from Bozho original https://techblog.bozho.net/self-driving-cars-open-source/

Self-driving cars are (will be) the pinnacle of consumer products automation – robot vacuum cleaners, smart fridges and TVs are just toys compared to self-driving cars. Both in terms of technology and in terms of impact. We aren’t yet on level 5 self driving cars , but they are behind the corner.

But as software engineers we know how fragile software is. And self-driving cars are basically software, so we can see all the risks involved with putting our lives in the hands anonymous (from our point of view) developers and unknown (to us) processes and quality standards. One may argue that this has been the case for every consumer product ever, but with software is different – software is way more complex than anything else.

So I have an outrageous proposal – self-driving cars should be open source. We have to be able to verify and trust the code that’s navigating our helpless bodies around the highways. Not only that, but we have to be able to verify if it is indeed that code that is currently running in our car, and not something else.

In fact, let me extend that – all cars should be open source. Before you say “but that will ruin the competitive advantage of manufacturers and will be deadly for business”, I don’t actually care how they trained their neural networks, or what their datasets are. That’s actually the secret sauce of the self-driving car and in my view it can remain proprietary and closed. What I’d like to see open-sourced is everything else. (Under what license – I’d be fine to even have it copyrighted and so not “real” open source, but that’s a separate discussion).

Why? This story about remote carjacking using the entertainment system of a Jeep is a scary example. Attackers that reverse engineer the car software can remotely control everything in the car. Why did that happen? Well, I guess it’s complicated and we have to watch the DEFCON talk.

And also read the paper, but a paragraph in wikipedia about the CAN bus used in most cars gives us a hint:

CAN is a low-level protocol and does not support any security features intrinsically. There is also no encryption in standard CAN implementations, which leaves these networks open to man-in-the-middle packet interception. In most implementations, applications are expected to deploy their own security mechanisms; e.g., to authenticate incoming commands or the presence of certain devices on the network. Failure to implement adequate security measures may result in various sorts of attacks if the opponent manages to insert messages on the bus. While passwords exist for some safety-critical functions, such as modifying firmware, programming keys, or controlling antilock brake actuators, these systems are not implemented universally and have a limited number of seed/key pair

I don’t know in what world it makes sense to even have a link between the entertainment system and the low-level network that operates the physical controls. As apparent from the talk, the two systems are supposed to be air-gapped, but in reality they aren’t.

Rookie mistakes were abound – unauthenticated “execute” method, running as root, firmware is not signed, hard-coded passwords, etc. How do we know that there aren’t tons of those in all cars out there right now, and in the self-driving cars of the future (which will likely use the same legacy technologies of the current cars)? Recently I heard a negative comment about the source code of one of the self-driving cars “players”, and I’m pretty sure there are many of those rookie mistakes.

Why this is this even more risky for self-driving cars? I’m not an expert in car programming, but it seems like the attack surface is bigger. I might be completely off target here, but on a typical car you’d have to “just” properly isolate the CAN bus. With self-driving cars the autonomous system that watches the surrounding and makes decisions on what to do next has to be connected to the CAN bus. With Tesla being able to send updates over the wire, the attack surface is even bigger (although that’s actually a good feature – to be able to patch all cars immediately once a vulnerability is discovered).

Of course, one approach would be to introduce legislation that regulates car software. It might work, but it would rely on governments to to proper testing, which won’t always be the case.

The alternative is to open-source it and let all the white-hats find your issues, so that you can close them before the car hits the road. Not only that, but consumers like me will feel safer, and geeks would be able to verify whether the car is really running the software it claims to run by verifying the fingerprints.

Richard Stallman might be seen as a fanatic when he advocates against closed source software, but in cases like … cars, his concerns seem less extreme.

“But the Jeep vulnerability was fixed”, you may say. And that might be seen as being the way things are – vulnerabilities appear, they get fixed, life goes on. No person was injured because of the bug, right? Well, not yet. And “gaining control” is the extreme scenario – there are still pretty bad scenarios, like being able to track a car through its GPS, or cause panic by controlling the entertainment system. It might be over wifi, or over GPRS, or even by physically messing with the car by inserting a flash drive. Is open source immune to those issues? No, but it has proven to be more resilient.

One industry where the problem of proprietary software on a product that the customer bought is … tractors. It turns out farmers are hacking their tractors, because of multiple issues and the inability of the vendor to resolve them in a timely manner. This is likely to happen to cars soon, when only authorized repair shops are allowed to touch anything on the car. And with unauthorized repair shops the attack surface becomes even bigger.

In fact, I’d prefer open source not just for cars, but for all consumer products. The source code of a smart fridge or a security camera is trivial, it would rarely mean sacrificing competitive advantage. But refrigerators get hacked, security cameras are active part of botnets, the “internet of shit” is getting ubiquitous. A huge amount of these issues are dumb, beginner mistakes. We have the right to know what shit we are running – in our frdges, DVRs and ultimatey – cars.

Your fridge may soon by spying on you, your vacuum cleaner may threaten your pet in demand of “ransom”. The terrorists of the future may crash planes without being armed, can crash vans into crowds without being in the van, and can “explode” home equipment without being in the particular home. And that’s not just a hypothetical.

Will open source magically solve the issue? No. But it will definitely make things better and safer, as it has done with operating systems and web servers.

The post Self-Driving Cars Should Be Open Source appeared first on Bozho's tech blog.

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.

Is DefCon Wifi safe?

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/07/is-defcon-wifi-safe.html

DEF CON is the largest U.S. hacker conference that takes place every summer in Las Vegas. It offers WiFi service. Is it safe?

Probably.

The trick is that you need to download the certificate from https://wifireg.defcon.org and import it into your computer. They have instructions for all your various operating systems. For macOS, it was as simple as downloading “dc25.mobileconfig” and importing it.

I haven’t validated the DefCon team did the right thing for all platforms, but I know that safety is possible. If a hacker could easily hack into arbitrary WiFi, then equipment vendors would fix it. Corporations widely use WiFi — they couldn’t do this if it weren’t safe.

The first step in safety is encryption, obviously. WPA does encryption well, you you are good there.

The second step is authentication — proving that the access-point is who it says it is. Otherwise, somebody could setup their own access-point claiming to be “DefCon”, and you’d happily connect to it. Encrypted connect to the evil access-point doesn’t help you. This is what the certificate you download does — you import it into your system, so that you’ll trust only the “DefCon” access-point that has the private key.

That’s not to say you are completely safe. There’s a known vulnerability for the Broadcom WiFi chip imbedded in many devices, including iPhone and Android phones. If you have one of these devices, you should either upgrade your software with a fix or disable WiFi.

There may also be unknown vulnerabilities in WiFi stacks. the Broadcom bug shows that after a couple decades, we still haven’t solved the problem of simple buffer overflows in WiFi stacks/drivers. Thus, some hacker may have an unknown 0day vulnerability they are using to hack you.

Of course, this can apply to any WiFi usage anywhere. Frankly, if I had such an 0day, I wouldn’t use it at DefCon. Along with black-hat hackers DefCon is full of white-hat researchers monitoring the WiFi — looking for hackers using exploits. They are likely to discover the 0day and report it. Thus, I’d rather use such 0-days in international airpots, catching business types, getting into their company secrets. Or, targeting government types.

So it’s impossible to guarantee any security. But what the DefCon network team bas done looks right, the same sort of thing corporations do to secure themselves, so you are probably secure.

On the other hand, don’t use “DefCon-Open” — not only is it insecure, there are explicitly a ton of hackers spying on it at the “Wall of Sheep” to point out the “sheep” who don’t secure their passwords.

Slowloris all the things

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/07/slowloris-all-things.html

At DEFCON, some researchers are going to announce a Slowloris-type exploit for SMB — SMBloris. I thought I’d write up some comments.

The original Slowloris from several years creates a ton of connections to a web server, but only sends partial headers. The server allocates a large amount of memory to handle the requests, expecting to free that memory soon when the requests are completed. But the requests are never completed, so the memory remains tied up indefinitely. Moreover, this also consumes a lot of CPU resources — every time Slowloris dribbles a few more bytes on the TCP connection is forces the CPU to walk through a lot of data structures to handle those bytes.

The thing about Slowloris is that it’s not specific to HTTP. It’s a principle that affects pretty much every service that listens on the Internet. For example, on Linux servers running NFS, you can exploit the RPC fragmentation feature in order to force the server to allocate all the memory in a box waiting for fragments that never arrive.

SMBloris does the same thing for SMB. It’s an easy attack to carry out in general, the only question is how much resources are required on the attacker’s side. That’s probably what this talk is about, causing the maximum consequences on the server with minimal resources on the attacker’s machine, thus allowing a Raspberry Pi to tie up all the resources on even the largest enterprise server.

According to the ThreatPost article, the attack was created looking at the NSA ETERNALBLUE exploit. That exploit works by causing the server to allocate memory chunks from fragmented requests. How to build a Slowloris exploit from this is then straightforward — just continue executing the first part of the ETERNALBLUE exploit, with larger chunks. I say “straightforward”, but of course, the researchers have probably discovered some additional clever tricks.

Samba, the SMB rewrite for non-Windows systems, probably falls victim to related problems. Maybe not this particular attack that affects Windows, but almost certainly something else. If not SMB, then the DCE-RPC service on top of it.

Microsoft has said they aren’t going to fix the SMBloris bug, and for good reason: it might be unfixable. Sure, there’s probably some kludge that fixes this specific script, but would still leave the system vulnerable to slight variations. The same reasoning applies to other services — Slowloris is an inherent problem in all Internet services and is not something easily addressed without re-writing the service from the ground up to specifically deal with the problem.

The best answer to Slowloris is the “langsec” discipline, which counsels us to separate “parsing” input from “processing” it. Most services combine the two, partially processing partial input. This should be changed to fully validate input consuming the least resources possible, before processing it. In other words, services should have a light-weight front-end that consumes the least resources possible, waiting for the request to complete, before it then forwards the request to the rest of the system.

Burner laptops for DEF CON

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/07/burner-laptops-for-def-con.html

Hacker summer camp (Defcon, Blackhat, BSidesLV) is upon us, so I thought I’d write up some quick notes about bringing a “burner” laptop. Chrome is your best choice in terms of security, but I need Windows/Linux tools, so I got a Windows laptop.

I chose the Asus e200ha for $199 from Amazon with free (and fast) shipping. There are similar notebooks with roughly the same hardware and price from other manufacturers (HP, Dell, etc.), so I’m not sure how this compares against those other ones. However, it fits my needs as a “burner” laptop, namely:

  • cheap
  • lasts 10 hours easily on battery
  • weighs 2.2 pounds (1 kilogram)
  • 11.6 inch and thin

Some other specs are:

  • 4 gigs of RAM
  • 32 gigs of eMMC flash memory
  • quad core 1.44 GHz Intel Atom CPU
  • Windows 10
  • free Microsoft Office 365 for one year
  • good, large keyboard
  • good, large touchpad
  • USB 3.0
  • microSD
  • WiFi ac
  • no fans, completely silent

There are compromises, of course.

  • The Atom CPU is slow, thought it’s only noticeable when churning through heavy webpages. Adblocking addons or Brave are a necessity. Most things are usably fast, such as using Microsoft Word.
  • Crappy sound and video, though VLC does a fine job playing movies with headphones on the airplane. Using in bright sunlight will be difficult.
  • micro-HDMI, keep in mind if intending to do presos from it, you’ll need an HDMI adapter
  • It has limited storage, 32gigs in theory, about half that usable.
  • Does special Windows 10 compressed install that you can’t actually upgrade without a completely new install. It doesn’t have the latest Windows 10 Creators update. I lost a gig thinking I could compress system files.

Copying files across the 802.11ac WiFi to the disk was quite fast, several hundred megabits-per-second. The eMMC isn’t as fast as an SSD, but its a lot faster than typical SD card speeds.

The first thing I did once I got the notebook was to install the free VeraCrypt full disk encryption. The CPU has AES acceleration, so it’s fast. There is a problem with the keyboard driver during boot that makes it really hard to enter long passwords — you have to carefully type one key at a time to prevent extra keystrokes from being entered.

You can’t really install Linux on this computer, but you can use virtual machines. I installed VirtualBox and downloaded the Kali VM. I had some problems attaching USB devices to the VM. First of all, VirtualBox requires a separate downloaded extension to get USB working. Second, it conflicts with USBpcap that I installed for Wireshark.

It comes with one year of free Office 365. Obviously, Microsoft is hoping to hook the user into a longer term commitment, but in practice next year at this time I’d get another burner $200 laptop rather than spend $99 on extending the Office 365 license.

Let’s talk about the CPU. It’s Intel’s “Atom” processor, not their mainstream (Core i3 etc.) processor. Even though it has roughly the same GHz as the processor in a 11inch MacBook Air and twice the cores, it’s noticeably and painfully slower. This is especially noticeable on ad-heavy web pages, while other things seem to work just fine. It has hardware acceleration for most video formats, though I had trouble getting Netflix to work.

The tradeoff for a slow CPU is phenomenal battery life. It seems to last forever on battery. It’s really pretty cool.

Conclusion

A Chromebook is likely more secure, but for my needs, this $200 is perfect.

EQGRP tools are post-exploitation

Post Syndicated from Robert Graham original http://blog.erratasec.com/2016/08/eqgrp-tools-are-post-exploitation.html

A recent leak exposed hackings tools from the “Equation Group”, a group likely related to the NSA TAO (the NSA/DoD hacking group). I thought I’d write up some comments.

Despite the existence of 0days, these tools seem to be overwhelmingly post-exploitation. They aren’t the sorts of tools you use to break into a network — but the sorts of tools you use afterwards.

The focus of the tools appear to be about hacking into network equipment, installing implants, achievement permanence, and using the equipment to sniff network traffic.

Different pentesters have different ways of doing things once they’ve gotten inside a network, and this is reflected in their toolkits. Some focus on Windows and getting domain admin control, and have tools like mimikatz. Other’s focus on webapps, and how to install hostile PHP scripts. In this case, these tools reflect a methodology that goes after network equipment.

It’s a good strategy. Finding equipment is easy, and undetectable, just do a traceroute. As long as network equipment isn’t causing problems, sysadmins ignore it, so your implants are unlikely to be detected. Internal network equipment is rarely patched, so old exploits are still likely to work. Some tools appear to target bugs in equipment that are likely older than Equation Group itself.

In particular, because network equipment is at the network center instead of the edges, you can reach out and sniff packets through the equipment. Half the time it’s a feature of the network equipment, so no special implant is needed. Conversely, when on the edge of the network, switches often prevent you from sniffing packets, and even if you exploit the switch (e.g. ARP flood), all you get are nearby machines. Getting critical machines from across the network requires remotely hacking network devices.

So you see a group of pentest-type people (TAO hackers) with a consistent methodology, and toolmakers who develop and refine tools for them. Tool development is a rare thing amount pentesters — they use tools, they don’t develop them. Having programmers on staff dramatically changes the nature of pentesting.

Consider the program xml2pcap. I don’t know what it does, but it looks like similar tools I’ve written in my own pentests. Various network devices will allow you to sniff packets, but produce output in custom formats. Therefore, you need to write a quick-and-dirty tool that converts from that weird format back into the standard pcap format for use with tools like Wireshark. More than once I’ve had to convert HTML/XML output to pcap. Setting port filters for 21 (FTP) and Telnet (23) produces low-bandwidth traffic with high return (admin passwords) within networks — all you need is a script that can convert the packets into standard format to exploit this.

Also consider the tftpd tool in the dump. Many network devices support that protocol for updating firmware and configuration. That’s pretty much all it’s used for. This points to a defensive security strategy for your organization: log all TFTP traffic.

Same applies to SNMP. By the way, SNMP vulnerabilities in network equipment is still low hanging fruit. SNMP stores thousands of configuration parameters and statistics in a big tree, meaning that it has an enormous attack surface. Anything value that’s a settable, variable-length value (OCTECT STRING, OBJECT IDENTIFIER) is something you can play with for buffer-overflows and format string bugs. The Cisco 0day in the toolkit was one example.

Some have pointed out that the code in the tools is crappy, and they make obvious crypto errors (such as using the same initialization vectors). This is nonsense. It’s largely pentesters, not software developers, creating these tools. And they have limited threat models — encryption is to avoid easy detection that they are exfiltrating data, not to prevent somebody from looking at the data.

From that perspective, then, this is fine code, with some effort spent at quality for tools that don’t particularly need it. I’m a professional coder, and my little scripts often suck worse than the code I see here.

Lastly, I don’t think it’s a hack of the NSA themselves. Those people are over-the-top paranoid about opsec. But 95% of the US cyber-industrial-complex is made of up companies, who are much more lax about security than the NSA itself. It’s probably one of those companies that got popped — such as an employee who went to DEFCON and accidentally left his notebook computer open on the hotel WiFi.

Conclusion

Despite the 0days, these appear to be post-exploitation tools. They look like the sort of tools pentesters might develop over years, where each time they pop a target, they do a little development based on the devices they find inside that new network in order to compromise more machines/data.

Defcon 24: Blinded By The Light

Post Syndicated from Craig original http://www.devttys0.com/2016/08/defcon-24-blinded-by-the-light/

I won’t be at Defcon this year in body, but I’ll be there in spirit! I got to design the hardware used in @tb69rr’s and @bjt2n3904‘s Defcon talk, Blinded By The Light.

A walk through of the hardware design is given in the video below; if you’re interested in how the collected infrared data can be used to identify and track your phone, be sure to check out their talk at the wireless village!

Security Vulnerabilities in Wireless Keyboards

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/08/security_vulner_7.html

Most of them are unencrypted, which makes them vulnerable to all sorts of attacks:

On Tuesday Bastille’s research team revealed a new set of wireless keyboard attacks they’re calling Keysniffer. The technique, which they’re planning to detail at the Defcon hacker conference in two weeks, allows any hacker with a $12 radio device to intercept the connection between any of eight wireless keyboards and a computer from 250 feet away. What’s more, it gives the hacker the ability to both type keystrokes on the victim machine and silently record the target’s typing.

This is a continuation of their previous work

More news articles. Here are lists of affected devices.

Researchers Discover Tor Nodes Designed to Spy on Hidden Services

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/07/researchers_dis.html

Two researchers have discovered over 100 Tor nodes that are spying on hidden services. Cory Doctorow explains:

These nodes — ordinary nodes, not exit nodes — sorted through all the traffic that passed through them, looking for anything bound for a hidden service, which allowed them to discover hidden services that had not been advertised. These nodes then attacked the hidden services by making connections to them and trying common exploits against the server-software running on them, seeking to compromise and take them over.

The researchers used “honeypot” .onion servers to find the spying computers: these honeypots were .onion sites that the researchers set up in their own lab and then connected to repeatedly over the Tor network, thus seeding many Tor nodes with the information of the honions’ existence. They didn’t advertise the honions’ existence in any other way and there was nothing of interest at these sites, and so when the sites logged new connections, the researchers could infer that they were being contacted by a system that had spied on one of their Tor network circuits.

This attack was already understood as a theoretical problem for the Tor project, which had recently undertaken a rearchitecting of the hidden service system that would prevent it from taking place.

No one knows who is running the spying nodes: they could be run by criminals, governments, private suppliers of “infowar” weapons to governments, independent researchers, or other scholars (though scholarly research would not normally include attempts to hack the servers once they were discovered).

The Tor project is working on redesigning its system to block this attack.

Vice Motherboard article. Defcon talk announcement.

Unicorn – PowerShell Downgrade Attack

Post Syndicated from Darknet original http://feedproxy.google.com/~r/darknethackers/~3/ZyaTsabV8ew/

Magic Unicorn is a simple tool for using a PowerShell downgrade attack to inject shellcode straight into memory. Based on Matthew Graeber’s PowerShell attacks and the PowerShell bypass technique presented by David Kennedy (TrustedSec) and Josh Kelly at Defcon 18. Usage is simple, just run Magic Unicorn (ensure Metasploit is installed and in the…

Read the full post at darknet.org.uk