Tag Archives: breaches

The Importance of Protecting Cybersecurity Whistleblowers

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/06/the_importance_3.html

Interesting essay arguing that we need better legislation to protect cybersecurity whistleblowers.

Congress should act to protect cybersecurity whistleblowers because information security has never been so important, or so challenging. In the wake of a barrage of shocking revelations about data breaches and companies mishandling of customer data, a bipartisan consensus has emerged in support of legislation to give consumers more control over their personal information, require companies to disclose how they collect and use consumer data, and impose penalties for data breaches and misuse of consumer data. The Federal Trade Commission (“FTC”) has been held out as the best agency to implement this new regulation. But for any such legislation to be effective, it must protect the courageous whistleblowers who risk their careers to expose data breaches and unauthorized use of consumers’ private data.

Whistleblowers strengthen regulatory regimes, and cybersecurity regulation would be no exception. Republican and Democratic leaders from the executive and legislative branches have extolled the virtues of whistleblowers. High-profile cases abound. Recently, Christopher Wylie exposed Cambridge Analytica’s misuse of Facebook user data to manipulate voters, including its apparent theft of data from 50 million Facebook users as part of a psychological profiling campaign. Though additional research is needed, the existing empirical data reinforces the consensus that whistleblowers help prevent, detect, and remedy misconduct. Therefore it is reasonable to conclude that protecting and incentivizing whistleblowers could help the government address the many complex challenges facing our nation’s information systems.

Hey Secret Service: Don’t Plug Suspect USB Sticks into Random Computers

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/04/hey_secret_serv.html

I just noticed this bit from the incredibly weird story of the Chinese woman arrested at Mar-a-Lago:

Secret Service agent Samuel Ivanovich, who interviewed Zhang on the day of her arrest, testified at the hearing. He stated that when another agent put Zhang’s thumb drive into his computer, it immediately began to install files, a “very out-of-the-ordinary” event that he had never seen happen before during this kind of analysis. The agent had to immediately stop the analysis to halt any further corruption of his computer, Ivanovich testified. The analysis is ongoing but still inconclusive, he said.

This is what passes for forensics at the Secret Service? I expect better.

EDITED TO ADD (4/9): I know this post is peripherally related to Trump. I know some readers can’t help themselves from talking about broader issues surrounding Trump, Russia, and so on. Please do not comment to those posts. I will delete them as soon as I see them.

EDITED TO ADD (4/9): Ars Technica has more detail.

Congressional Report on the 2017 Equifax Data Breach

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/12/congressional_r.html

The US House of Representatives Committee on Oversight and Government Reform has just released a comprehensive report on the 2017 Equifax hack. It’s a great piece of writing, with a detailed timeline, root cause analysis, and lessons learned. Lance Spitzner also commented on this.

Here is my testimony before before the House Subcommittee on Digital Commerce and Consumer Protection last November.

ISP Sued For Breaching User Privacy After Blocking Pirate Sites

Post Syndicated from Andy original https://torrentfreak.com/isp-sued-for-breaching-user-privacy-after-blocking-pirate-sites-180428/

After hinting at moves to curb online piracy last month, on April 13 the Japanese government announced
emergency measures to target websites hosting pirated manga, anime and other types of content.

In common with dozens of counterparts around the world, the government said it favored site-blocking as the first line of defense. However, with no specific legislation to fall back on, authorities asked local ISPs if they’d come along for the ride voluntarily. On Monday, the Nippon Telegraph and Telephone Corp. (NTT) announced that it would.

“We have taken short-term emergency measures until legal systems on site-blocking are implemented,” NTT in a statement.

NTT Communications Corp., NTT Docomo Inc. and NTT Plala Inc., said they would target three sites highlighted by the government – Mangamura, AniTube! and MioMio – which together have a huge following in Japan.

The service providers added that at least in the short-term, they would prevent access to the sites using DNS blocking and would restrict access to other sites if requested to do so by the government. But, just a few days on, NTT is already facing problems.

Lawyer Yuichi Nakazawa has now launched legal action against NTT, demanding that the corporation immediately ends its site-blocking operations.

The complaint, filed at the Tokyo District Court, notes that the lawyer uses an Internet connection provided by NTT. Crucially, it also states that in order to block access to the sites in question, NTT would need to spy on customers’ Internet connections to find out if they’re trying to access the banned sites.

The lawyer informs TorrentFreak that the ISP’s decision prompted him into action.

“NTT’s decision was made arbitrarily on the site without any legal basis. No matter how legitimate the objective of copyright infringement is, it is very dangerous,” Nakazawa explains.

“I felt that ‘freedom,’ which is an important value of the Internet, was threatened. Actually, when the interruption of communications had begun, the company thought it would be impossible to reverse the situation, so I filed a lawsuit at this stage.”

Breaches of privacy could present a significant problem under Japanese law. The Telecommunications Business Act guarantees privacy of communications and prevents censorship, as does Article 21 of the Constitution.

“The secrecy of communications being handled by a telecommunications carrier shall not be violated,” the Telecommunications Business Act states, adding that “no communications being handled by a telecommunications carrier shall be censored.”

The Constitution is also clear, stating that “no censorship shall be maintained, nor shall the secrecy of any means of communication be violated.”

For his part, lawyer Yuichi Nakazawa is also concerned that his contract with the ISP is being breached.

“There is an Internet connection agreement between me and NTT. I am a customer of NTT. There is no provision in the contract between me and NTT to allow arbitrary interruption of communications,” he explains.

Nakazawa doesn’t appear to be against site-blocking per se, he’s just concerned that relevant laws and agreements are being broken.

“It is necessary to restrict sites of pirated publications but that does not mean you can do anything,” Nakazawa said, as quoted by Mainichi. “We should have sufficient discussions for an appropriate measure, including revising the law.”

The question of whether site-blocking does indeed represent an invasion of privacy will probably come down to how the ISP implements it and how that is interpreted by the courts.

A source familiar with the situation told TF that spying on user connections is clearly a problem but the deployment of an outer network firewall rule that simply prevents traffic passing through might be viewed differently.

Such a rule would provide no secret or private information that wasn’t already available to the ISP when the customer requested a banned site through a web browser, although it still falls foul of the “no censorship” requirements of both the Constitution and Telecommunications Business Act.

NTT Communications has declined to comment on the lawsuit but says it had no plans to backtrack on plans to block the sites. Earlier this week, SoftBank Corp., another ISP considering a blockade, expressed concerns that site-blocking has the potential to infringe secrecy of communications rules.

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

Cybersecurity Insurance

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/04/cybersecurity_i_1.html

Good article about how difficult it is to insure an organization against Internet attacks, and how expensive the insurance is.

Companies like retailers, banks, and healthcare providers began seeking out cyberinsurance in the early 2000s, when states first passed data breach notification laws. But even with 20 years’ worth of experience and claims data in cyberinsurance, underwriters still struggle with how to model and quantify a unique type of risk.

“Typically in insurance we use the past as prediction for the future, and in cyber that’s very difficult to do because no two incidents are alike,” said Lori Bailey, global head of cyberrisk for the Zurich Insurance Group. Twenty years ago, policies dealt primarily with data breaches and third-party liability coverage, like the costs associated with breach class-action lawsuits or settlements. But more recent policies tend to accommodate first-party liability coverage, including costs like online extortion payments, renting temporary facilities during an attack, and lost business due to systems failures, cloud or web hosting provider outages, or even IT configuration errors.

In my new book — out in September — I write:

There are challenges to creating these new insurance products. There are two basic models for insurance. There’s the fire model, where individual houses catch on fire at a fairly steady rate, and the insurance industry can calculate premiums based on that rate. And there’s the flood model, where an infrequent large-scale event affects large numbers of people — but again at a fairly steady rate. Internet+ insurance is complicated because it follows neither of those models but instead has aspects of both: individuals are hacked at a steady (albeit increasing) rate, while class breaks and massive data breaches affect lots of people at once. Also, the constantly changing technology landscape makes it difficult to gather and analyze the historical data necessary to calculate premiums.

BoingBoing article.

Facebook and Cambridge Analytica

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/03/facebook_and_ca.html

In the wake of the Cambridge Analytica scandal, news articles and commentators have focused on what Facebook knows about us. A lot, it turns out. It collects data from our posts, our likes, our photos, things we type and delete without posting, and things we do while not on Facebook and even when we’re offline. It buys data about us from others. And it can infer even more: our sexual orientation, political beliefs, relationship status, drug use, and other personality traits — even if we didn’t take the personality test that Cambridge Analytica developed.

But for every article about Facebook’s creepy stalker behavior, thousands of other companies are breathing a collective sigh of relief that it’s Facebook and not them in the spotlight. Because while Facebook is one of the biggest players in this space, there are thousands of other companies that spy on and manipulate us for profit.

Harvard Business School professor Shoshana Zuboff calls it “surveillance capitalism.” And as creepy as Facebook is turning out to be, the entire industry is far creepier. It has existed in secret far too long, and it’s up to lawmakers to force these companies into the public spotlight, where we can all decide if this is how we want society to operate and — if not — what to do about it.

There are 2,500 to 4,000 data brokers in the United States whose business is buying and selling our personal data. Last year, Equifax was in the news when hackers stole personal information on 150 million people, including Social Security numbers, birth dates, addresses, and driver’s license numbers.

You certainly didn’t give it permission to collect any of that information. Equifax is one of those thousands of data brokers, most of them you’ve never heard of, selling your personal information without your knowledge or consent to pretty much anyone who will pay for it.

Surveillance capitalism takes this one step further. Companies like Facebook and Google offer you free services in exchange for your data. Google’s surveillance isn’t in the news, but it’s startlingly intimate. We never lie to our search engines. Our interests and curiosities, hopes and fears, desires and sexual proclivities, are all collected and saved. Add to that the websites we visit that Google tracks through its advertising network, our Gmail accounts, our movements via Google Maps, and what it can collect from our smartphones.

That phone is probably the most intimate surveillance device ever invented. It tracks our location continuously, so it knows where we live, where we work, and where we spend our time. It’s the first and last thing we check in a day, so it knows when we wake up and when we go to sleep. We all have one, so it knows who we sleep with. Uber used just some of that information to detect one-night stands; your smartphone provider and any app you allow to collect location data knows a lot more.

Surveillance capitalism drives much of the internet. It’s behind most of the “free” services, and many of the paid ones as well. Its goal is psychological manipulation, in the form of personalized advertising to persuade you to buy something or do something, like vote for a candidate. And while the individualized profile-driven manipulation exposed by Cambridge Analytica feels abhorrent, it’s really no different from what every company wants in the end. This is why all your personal information is collected, and this is why it is so valuable. Companies that can understand it can use it against you.

None of this is new. The media has been reporting on surveillance capitalism for years. In 2015, I wrote a book about it. Back in 2010, the Wall Street Journal published an award-winning two-year series about how people are tracked both online and offline, titled “What They Know.”

Surveillance capitalism is deeply embedded in our increasingly computerized society, and if the extent of it came to light there would be broad demands for limits and regulation. But because this industry can largely operate in secret, only occasionally exposed after a data breach or investigative report, we remain mostly ignorant of its reach.

This might change soon. In 2016, the European Union passed the comprehensive General Data Protection Regulation, or GDPR. The details of the law are far too complex to explain here, but some of the things it mandates are that personal data of EU citizens can only be collected and saved for “specific, explicit, and legitimate purposes,” and only with explicit consent of the user. Consent can’t be buried in the terms and conditions, nor can it be assumed unless the user opts in. This law will take effect in May, and companies worldwide are bracing for its enforcement.

Because pretty much all surveillance capitalism companies collect data on Europeans, this will expose the industry like nothing else. Here’s just one example. In preparation for this law, PayPal quietly published a list of over 600 companies it might share your personal data with. What will it be like when every company has to publish this sort of information, and explicitly explain how it’s using your personal data? We’re about to find out.

In the wake of this scandal, even Mark Zuckerberg said that his industry probably should be regulated, although he’s certainly not wishing for the sorts of comprehensive regulation the GDPR is bringing to Europe.

He’s right. Surveillance capitalism has operated without constraints for far too long. And advances in both big data analysis and artificial intelligence will make tomorrow’s applications far creepier than today’s. Regulation is the only answer.

The first step to any regulation is transparency. Who has our data? Is it accurate? What are they doing with it? Who are they selling it to? How are they securing it? Can we delete it? I don’t see any hope of Congress passing a GDPR-like data protection law anytime soon, but it’s not too far-fetched to demand laws requiring these companies to be more transparent in what they’re doing.

One of the responses to the Cambridge Analytica scandal is that people are deleting their Facebook accounts. It’s hard to do right, and doesn’t do anything about the data that Facebook collects about people who don’t use Facebook. But it’s a start. The market can put pressure on these companies to reduce their spying on us, but it can only do that if we force the industry out of its secret shadows.

This essay previously appeared on CNN.com.

EDITED TO ADD (4/2): Slashdot thread.

Zeynep Tufekci on Facebook and Cambridge Analytica

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/03/zeynep_tufekci_.html

Zeynep Tufekci is particularly cogent about Facebook and Cambridge Analytica.

Several news outlets asked me to write about this issue. I didn’t, because 1) my book manuscript is due on Monday (finally!), and 2) I knew Zeynep would say what I would say, only better.

Election Security

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/02/election_securi_2.html

I joined a letter supporting the Secure Elections Act (S. 2261):

The Secure Elections Act strikes a careful balance between state and federal action to secure American voting systems. The measure authorizes appropriation of grants to the states to take important and time-sensitive actions, including:

  • Replacing insecure paperless voting systems with new equipment that will process a paper ballot;
  • Implementing post-election audits of paper ballots or records to verify electronic tallies;

  • Conducting “cyber hygiene” scans and “risk and vulnerability” assessments and supporting state efforts to remediate identified vulnerabilities.

    The legislation would also create needed transparency and accountability in elections systems by establishing clear protocols for state and federal officials to communicate regarding security breaches and emerging threats.

Jumping Air Gaps

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/02/jumping_air_gap_2.html

Nice profile of Mordechai Guri, who researches a variety of clever ways to steal data over air-gapped computers.

Guri and his fellow Ben-Gurion researchers have shown, for instance, that it's possible to trick a fully offline computer into leaking data to another nearby device via the noise its internal fan generates, by changing air temperatures in patterns that the receiving computer can detect with thermal sensors, or even by blinking out a stream of information from a computer hard drive LED to the camera on a quadcopter drone hovering outside a nearby window. In new research published today, the Ben-Gurion team has even shown that they can pull data off a computer protected by not only an air gap, but also a Faraday cage designed to block all radio signals.

Here’s a page with all the research results.

BoingBoing post.

Security Breaches Don’t Affect Stock Price

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/01/security_breach.html

Interesting research: “Long-term market implications of data breaches, not,” by Russell Lange and Eric W. Burger.

Abstract: This report assesses the impact disclosure of data breaches has on the total returns and volatility of the affected companies’ stock, with a focus on the results relative to the performance of the firms’ peer industries, as represented through selected indices rather than the market as a whole. Financial performance is considered over a range of dates from 3 days post-breach through 6 months post-breach, in order to provide a longer-term perspective on the impact of the breach announcement.

Key findings:

  • While the difference in stock price between the sampled breached companies and their peers was negative (1.13%) in the first 3 days following announcement of a breach, by the 14th day the return difference had rebounded to + 0.05%, and on average remained positive through the period assessed.
  • For the differences in the breached companies’ betas and the beta of their peer sets, the differences in the means of 8 months pre-breach versus post-breach was not meaningful at 90, 180, and 360 day post-breach periods.

  • For the differences in the breached companies’ beta correlations against the peer indices pre- and post-breach, the difference in the means of the rolling 60 day correlation 8 months pre- breach versus post-breach was not meaningful at 90, 180, and 360 day post-breach periods.

  • In regression analysis, use of the number of accessed records, date, data sensitivity, and malicious versus accidental leak as variables failed to yield an R2 greater than 16.15% for response variables of 3, 14, 60, and 90 day return differential, excess beta differential, and rolling beta correlation differential, indicating that the financial impact on breached companies was highly idiosyncratic.

  • Based on returns, the most impacted industries at the 3 day post-breach date were U.S. Financial Services, Transportation, and Global Telecom. At the 90 day post-breach date, the three most impacted industries were U.S. Financial Services, U.S. Healthcare, and Global Telecom.

The market isn’t going to fix this. If we want better security, we need to regulate the market.

Note: The article is behind a paywall. An older version is here. A similar article is here.

Using Amazon CloudWatch and Amazon SNS to Notify when AWS X-Ray Detects Elevated Levels of Latency, Errors, and Faults in Your Application

Post Syndicated from Bharath Kumar original https://aws.amazon.com/blogs/devops/using-amazon-cloudwatch-and-amazon-sns-to-notify-when-aws-x-ray-detects-elevated-levels-of-latency-errors-and-faults-in-your-application/

AWS X-Ray helps developers analyze and debug production applications built using microservices or serverless architectures and quantify customer impact. With X-Ray, you can understand how your application and its underlying services are performing and identify and troubleshoot the root cause of performance issues and errors. You can use these insights to identify issues and opportunities for optimization.

In this blog post, I will show you how you can use Amazon CloudWatch and Amazon SNS to get notified when X-Ray detects high latency, errors, and faults in your application. Specifically, I will show you how to use this sample app to get notified through an email or SMS message when your end users observe high latencies or server-side errors when they use your application. You can customize the alarms and events by updating the sample app code.

Sample App Overview

The sample app uses the X-Ray GetServiceGraph API to get the following information:

  • Aggregated response time.
  • Requests that failed with 4xx status code (errors).
  • 429 status code (throttle).
  • 5xx status code (faults).
Sample app architecture

Overview of sample app architecture

Getting started

The sample app uses AWS CloudFormation to deploy the required resources.
To install the sample app:

  1. Run git clone to get the sample app.
  2. Update the JSON file in the Setup folder with threshold limits and notification details.
  3. Run the install.py script to install the sample app.

For more information about the installation steps, see the readme file on GitHub.

You can update the app configuration to include your phone number or email to get notified when your application in X-Ray breaches the latency, error, and fault limits you set in the configuration. If you prefer to not provide your phone number and email, then you can use the CloudWatch alarm deployed by the sample app to monitor your application in X-Ray.

The sample app deploys resources with the sample app namespace you provided during setup. This enables you to have multiple sample apps in the same region.

CloudWatch rules

The sample app uses two CloudWatch rules:

  1. SCHEDULEDLAMBDAFOR-sample_app_name to trigger at regular intervals the AWS Lambda function that queries the GetServiceGraph API.
  2. XRAYALERTSFOR-sample_app_name to look for published CloudWatch events that match the pattern defined in this rule.
CloudWatch Rules for sample app

CloudWatch rules created for the sample app

CloudWatch alarms

If you did not provide your phone number or email in the JSON file, the sample app uses a CloudWatch alarm named XRayCloudWatchAlarm-sample_app_name in combination with the CloudWatch event that you can use for monitoring.

CloudWatch Alarm for sample app

CloudWatch alarm created for the sample app

Amazon SNS messages

The sample app creates two SNS topics:

  • sample_app_name-cloudwatcheventsnstopic to send out an SMS message when the CloudWatch event matches a pattern published from the Lambda function.
  • sample_app_name-cloudwatchalarmsnstopic to send out an email message when the CloudWatch alarm goes into an ALARM state.
Amazon SNS for sample app

Amazon SNS created for the sample app

Getting notifications

The CloudWatch event looks for the following matching pattern:

{
  "detail-type": [
    "XCW Notification for Alerts"
  ],
  "source": [
    "<sample_app_name>-xcw.alerts"
  ]
}

The event then invokes an SNS topic that sends out an SMS message.

SMS in sample app

SMS that is sent when CloudWatch Event invokes Amazon SNS topic

The CloudWatch alarm looks for the TriggeredRules metric that is published whenever the CloudWatch event matches the event pattern. It goes into the ALARM state whenever TriggeredRules > 0 for the specified evaluation period and invokes an SNS topic that sends an email message.

Email sent in sample app

Email that is sent when CloudWatch Alarm goes to ALARM state

Stopping notifications

If you provided your phone number or email address, but would like to stop getting notified, change the SUBSCRIBE_TO_EMAIL_SMS environment variable in the Lambda function to No. Then, go to the Amazon SNS console and delete the subscriptions. You can still monitor your application for elevated levels of latency, errors, and faults by using the CloudWatch console.

Lambda environment variable in sample app

Change environment variable in Lambda

 

Delete subscription in SNS for sample app

Delete subscriptions to stop getting notified

Uninstalling the sample app

To uninstall the sample app, run the uninstall.py script in the Setup folder.

Extending the sample app

The sample app notifes you when when X-Ray detects high latency, errors, and faults in your application. You can extend it to provide more value for your use cases (for example, to perform an action on a resource when the state of a CloudWatch alarm changes).

To summarize, after this set up you will be able to get notified through Amazon SNS when X-Ray detects high latency, errors and faults in your application.

I hope you found this information about setting up alarms and alerts for your application in AWS X-Ray helpful. Feel free to leave questions or other feedback in the comments. Feel free to learn more about AWS X-Ray, Amazon SNS and Amazon CloudWatch

About the Author

Bharath Kumar is a Sr.Product Manager with AWS X-Ray. He has developed and launched mobile games, web applications on microservices and serverless architecture.

The deal with Bitcoin

Post Syndicated from Michal Zalewski original http://lcamtuf.blogspot.com/2017/12/the-deal-with-bitcoin.html

♪ Used to have a little now I have a lot
I’m still, I’m still Jenny from the block
          chain ♪

For all that has been written about Bitcoin and its ilk, it is curious that the focus is almost solely what the cryptocurrencies are supposed to be. Technologists wax lyrical about the potential for blockchains to change almost every aspect of our lives. Libertarians and paleoconservatives ache for the return to “sound money” that can’t be conjured up at the whim of a bureaucrat. Mainstream economists wag their fingers, proclaiming that a proper currency can’t be deflationary, that it must maintain a particular velocity, or that the government must be able to nip crises of confidence in the bud. And so on.

Much of this may be true, but the proponents of cryptocurrencies should recognize that an appeal to consequences is not a guarantee of good results. The critics, on the other hand, would be best served to remember that they are drawing far-reaching conclusions about the effects of modern monetary policies based on a very short and tumultuous period in history.

In this post, my goal is to ditch most of the dogma, talk a bit about the origins of money – and then see how “crypto” fits the bill.

1. The prehistory of currencies

The emergence of money is usually explained in a very straightforward way. You know the story: a farmer raised a pig, a cobbler made a shoe. The cobbler needed to feed his family while the farmer wanted to keep his feet warm – and so they met to exchange the goods on mutually beneficial terms. But as the tale goes, the barter system had a fatal flaw: sometimes, a farmer wanted a cooking pot, a potter wanted a knife, and a blacksmith wanted a pair of pants. To facilitate increasingly complex, multi-step exchanges without requiring dozens of people to meet face to face, we came up with an abstract way to represent value – a shiny coin guaranteed to be accepted by every tradesman.

It is a nice parable, but it probably isn’t very true. It seems far more plausible that early societies relied on the concept of debt long before the advent of currencies: an informal tally or a formal ledger would be used to keep track of who owes what to whom. The concept of debt, closely associated with one’s trustworthiness and standing in the community, would have enabled a wide range of economic activities: debts could be paid back over time, transferred, renegotiated, or forgotten – all without having to engage in spot barter or to mint a single coin. In fact, such non-monetary, trust-based, reciprocal economies are still common in closely-knit communities: among families, neighbors, coworkers, or friends.

In such a setting, primitive currencies probably emerged simply as a consequence of having a system of prices: a cow being worth a particular number of chickens, a chicken being worth a particular number of beaver pelts, and so forth. Formalizing such relationships by settling on a single, widely-known unit of account – say, one chicken – would make it more convenient to transfer, combine, or split debts; or to settle them in alternative goods.

Contrary to popular belief, for communal ledgers, the unit of account probably did not have to be particularly desirable, durable, or easy to carry; it was simply an accounting tool. And indeed, we sometimes run into fairly unusual units of account even in modern times: for example, cigarettes can be the basis of a bustling prison economy even when most inmates don’t smoke and there are not that many packs to go around.

2. The age of commodity money

In the end, the development of coinage might have had relatively little to do with communal trade – and far more with the desire to exchange goods with strangers. When dealing with a unfamiliar or hostile tribe, the concept of a chicken-denominated ledger does not hold up: the other side might be disinclined to honor its obligations – and get away with it, too. To settle such problematic trades, we needed a “spot” medium of exchange that would be easy to carry and authenticate, had a well-defined value, and a near-universal appeal. Throughout much of the recorded history, precious metals – predominantly gold and silver – proved to fit the bill.

In the most basic sense, such commodities could be seen as a tool to reconcile debts across societal boundaries, without necessarily replacing any local units of account. An obligation, denominated in some local currency, would be created on buyer’s side in order to procure the metal for the trade. The proceeds of the completed transaction would in turn allow the seller to settle their own local obligations that arose from having to source the traded goods. In other words, our wondrous chicken-denominated ledgers could coexist peacefully with gold – and when commodity coinage finally took hold, it’s likely that in everyday trade, precious metals served more as a useful abstraction than a precise store of value. A “silver chicken” of sorts.

Still, the emergence of commodity money had one interesting side effect: it decoupled the unit of debt – a “claim on the society”, in a sense – from any moral judgment about its origin. A piece of silver would buy the same amount of food, whether earned through hard labor or won in a drunken bet. This disconnect remains a central theme in many of the debates about social justice and unfairly earned wealth.

3. The State enters the game

If there is one advantage of chicken ledgers over precious metals, it’s that all chickens look and cluck roughly the same – something that can’t be said of every nugget of silver or gold. To cope with this problem, we needed to shape raw commodities into pieces of a more predictable shape and weight; a trusted party could then stamp them with a mark to indicate the value and the quality of the coin.

At first, the task of standardizing coinage rested with private parties – but the responsibility was soon assumed by the State. The advantages of this transition seemed clear: a single, widely-accepted and easily-recognizable currency could be now used to settle virtually all private and official debts.

Alas, in what deserves the dubious distinction of being one of the earliest examples of monetary tomfoolery, some States succumbed to the temptation of fiddling with the coinage to accomplish anything from feeding the poor to waging wars. In particular, it would be common to stamp coins with the same face value but a progressively lower content of silver and gold. Perhaps surprisingly, the strategy worked remarkably well; at least in the times of peace, most people cared about the value stamped on the coin, not its precise composition or weight.

And so, over time, representative money was born: sooner or later, most States opted to mint coins from nearly-worthless metals, or print banknotes on paper and cloth. This radically new currency was accompanied with a simple pledge: the State offered to redeem it at any time for its nominal value in gold.

Of course, the promise was largely illusory: the State did not have enough gold to honor all the promises it had made. Still, as long as people had faith in their rulers and the redemption requests stayed low, the fundamental mechanics of this new representative currency remained roughly the same as before – and in some ways, were an improvement in that they lessened the insatiable demand for a rare commodity. Just as importantly, the new money still enabled international trade – using the underlying gold exchange rate as a reference point.

4. Fractional reserve banking and fiat money

For much of the recorded history, banking was an exceptionally dull affair, not much different from running a communal chicken
ledger of the old. But then, something truly marvelous happened in the 17th century: around that time, many European countries have witnessed
the emergence of fractional-reserve banks.

These private ventures operated according to a simple scheme: they accepted people’s coin
for safekeeping, promising to pay a premium on every deposit made. To meet these obligations and to make a profit, the banks then
used the pooled deposits to make high-interest loans to other folks. The financiers figured out that under normal circumstances
and when operating at a sufficient scale, they needed only a very modest reserve – well under 10% of all deposited money – to be
able to service the usual volume and size of withdrawals requested by their customers. The rest could be loaned out.

The very curious consequence of fractional-reserve banking was that it pulled new money out of thin air.
The funds were simultaneously accounted for in the statements shown to the depositor, evidently available for withdrawal or
transfer at any time; and given to third-party borrowers, who could spend them on just about anything. Heck, the borrowers could
deposit the proceeds in another bank, creating even more money along the way! Whatever they did, the sum of all funds in the monetary
system now appeared much higher than the value of all coins and banknotes issued by the government – let alone the amount of gold
sitting in any vault.

Of course, no new money was being created in any physical sense: all that banks were doing was engaging in a bit of creative accounting – the sort of which would probably land you in jail if you attempted it today in any other comparably vital field of enterprise. If too many depositors were to ask for their money back, or if too many loans were to go bad, the banking system would fold. Fortunes would evaporate in a puff of accounting smoke, and with the disappearance of vast quantities of quasi-fictitious (“broad”) money, the wealth of the entire nation would shrink.

In the early 20th century, the world kept witnessing just that; a series of bank runs and economic contractions forced the governments around the globe to act. At that stage, outlawing fractional-reserve banking was no longer politically or economically tenable; a simpler alternative was to let go of gold and move to fiat money – a currency implemented as an abstract social construct, with no predefined connection to the physical realm. A new breed of economists saw the role of the government not in trying to peg the value of money to an inflexible commodity, but in manipulating its supply to smooth out economic hiccups or to stimulate growth.

(Contrary to popular beliefs, such manipulation is usually not done by printing new banknotes; more sophisticated methods, such as lowering reserve requirements for bank deposits or enticing banks to invest its deposits into government-issued securities, are the preferred route.)

The obvious peril of fiat money is that in the long haul, its value is determined strictly by people’s willingness to accept a piece of paper in exchange for their trouble; that willingness, in turn, is conditioned solely on their belief that the same piece of paper would buy them something nice a week, a month, or a year from now. It follows that a simple crisis of confidence could make a currency nearly worthless overnight. A prolonged period of hyperinflation and subsequent austerity in Germany and Austria was one of the precipitating factors that led to World War II. In more recent times, dramatic episodes of hyperinflation plagued the fiat currencies of Israel (1984), Mexico (1988), Poland (1990), Yugoslavia (1994), Bulgaria (1996), Turkey (2002), Zimbabwe (2009), Venezuela (2016), and several other nations around the globe.

For the United States, the switch to fiat money came relatively late, in 1971. To stop the dollar from plunging like a rock, the Nixon administration employed a clever trick: they ordered the freeze of wages and prices for the 90 days that immediately followed the move. People went on about their lives and paid the usual for eggs or milk – and by the time the freeze ended, they were accustomed to the idea that the “new”, free-floating dollar is worth about the same as the old, gold-backed one. A robust economy and favorable geopolitics did the rest, and so far, the American adventure with fiat currency has been rather uneventful – perhaps except for the fact that the price of gold itself skyrocketed from $35 per troy ounce in 1971 to $850 in 1980 (or, from $210 to $2,500 in today’s dollars).

Well, one thing did change: now better positioned to freely tamper with the supply of money, the regulators in accord with the bankers adopted a policy of creating it at a rate that slightly outstripped the organic growth in economic activity. They did this to induce a small, steady degree of inflation, believing that doing so would discourage people from hoarding cash and force them to reinvest it for the betterment of the society. Some critics like to point out that such a policy functions as a “backdoor” tax on savings that happens to align with the regulators’ less noble interests; still, either way: in the US and most other developed nations, the purchasing power of any money kept under a mattress will drop at a rate of somewhere between 2 to 10% a year.

5. So what’s up with Bitcoin?

Well… countless tomes have been written about the nature and the optimal characteristics of government-issued fiat currencies. Some heterodox economists, notably including Murray Rothbard, have also explored the topic of privately-issued, decentralized, commodity-backed currencies. But Bitcoin is a wholly different animal.

In essence, BTC is a global, decentralized fiat currency: it has no (recoverable) intrinsic value, no central authority to issue it or define its exchange rate, and it has no anchoring to any historical reference point – a combination that until recently seemed nonsensical and escaped any serious scrutiny. It does the unthinkable by employing three clever tricks:

  1. It allows anyone to create new coins, but only by solving brute-force computational challenges that get more difficult as the time goes by,

  2. It prevents unauthorized transfer of coins by employing public key cryptography to sign off transactions, with only the authorized holder of a coin knowing the correct key,

  3. It prevents double-spending by using a distributed public ledger (“blockchain”), recording the chain of custody for coins in a tamper-proof way.

The blockchain is often described as the most important feature of Bitcoin, but in some ways, its importance is overstated. The idea of a currency that does not rely on a centralized transaction clearinghouse is what helped propel the platform into the limelight – mostly because of its novelty and the perception that it is less vulnerable to government meddling (although the government is still free to track down, tax, fine, or arrest any participants). On the flip side, the everyday mechanics of BTC would not be fundamentally different if all the transactions had to go through Bitcoin Bank, LLC.

A more striking feature of the new currency is the incentive structure surrounding the creation of new coins. The underlying design democratized the creation of new coins early on: all you had to do is leave your computer running for a while to acquire a number of tokens. The tokens had no practical value, but obtaining them involved no substantial expense or risk. Just as importantly, because the difficulty of the puzzles would only increase over time, the hope was that if Bitcoin caught on, latecomers would find it easier to purchase BTC on a secondary market than mine their own – paying with a more established currency at a mutually beneficial exchange rate.

The persistent publicity surrounding Bitcoin and other cryptocurrencies did the rest – and today, with the growing scarcity of coins and the rapidly increasing demand, the price of a single token hovers somewhere south of $15,000.

6. So… is it bad money?

Predicting is hard – especially the future. In some sense, a coin that represents a cryptographic proof of wasted CPU cycles is no better or worse than a currency that relies on cotton decorated with pictures of dead presidents. It is true that Bitcoin suffers from many implementation problems – long transaction processing times, high fees, frequent security breaches of major exchanges – but in principle, such problems can be overcome.

That said, currencies live and die by the lasting willingness of others to accept them in exchange for services or goods – and in that sense, the jury is still out. The use of Bitcoin to settle bona fide purchases is negligible, both in absolute terms and in function of the overall volume of transactions. In fact, because of the technical challenges and limited practical utility, some companies that embraced the currency early on are now backing out.

When the value of an asset is derived almost entirely from its appeal as an ever-appreciating investment vehicle, the situation has all the telltale signs of a speculative bubble. But that does not prove that the asset is destined to collapse, or that a collapse would be its end. Still, the built-in deflationary mechanism of Bitcoin – the increasing difficulty of producing new coins – is probably both a blessing and a curse.

It’s going to go one way or the other; and when it’s all said and done, we’re going to celebrate the people who made the right guess. Because future is actually pretty darn easy to predict — in retrospect.

Serverless Automated Cost Controls, Part1

Post Syndicated from Shankar Ramachandran original https://aws.amazon.com/blogs/compute/serverless-automated-cost-controls-part1/

This post courtesy of Shankar Ramachandran, Pubali Sen, and George Mao

In line with AWS’s continual efforts to reduce costs for customers, this series focuses on how customers can build serverless automated cost controls. This post provides an architecture blueprint and a sample implementation to prevent budget overruns.

This solution uses the following AWS products:

  • AWS Budgets – An AWS Cost Management tool that helps customers define and track budgets for AWS costs, and forecast for up to three months.
  • Amazon SNS – An AWS service that makes it easy to set up, operate, and send notifications from the cloud.
  • AWS Lambda – An AWS service that lets you run code without provisioning or managing servers.

You can fine-tune a budget for various parameters, for example filtering by service or tag. The Budgets tool lets you post notifications on an SNS topic. A Lambda function that subscribes to the SNS topic can act on the notification. Any programmatically implementable action can be taken.

The diagram below describes the architecture blueprint.

In this post, we describe how to use this blueprint with AWS Step Functions and IAM to effectively revoke the ability of a user to start new Amazon EC2 instances, after a budget amount is exceeded.

Freedom with guardrails

AWS lets you quickly spin up resources as you need them, deploying hundreds or even thousands of servers in minutes. This means you can quickly develop and roll out new applications. Teams can experiment and innovate more quickly and frequently. If an experiment fails, you can always de-provision those servers without risk.

This improved agility also brings in the need for effective cost controls. Your Finance and Accounting department must budget, monitor, and control the AWS spend. For example, this could be a budget per project. Further, Finance and Accounting must take appropriate actions if the budget for the project has been exceeded, for example. Call it “freedom with guardrails” – where Finance wants to give developers freedom, but with financial constraints.

Architecture

This section describes how to use the blueprint introduced earlier to implement a “freedom with guardrails” solution.

  1. The budget for “Project Beta” is set up in Budgets. In this example, we focus on EC2 usage and identify the instances that belong to this project by filtering on the tag Project with the value Beta. For more information, see Creating a Budget.
  2. The budget configuration also includes settings to send a notification on an SNS topic when the usage exceeds 100% of the budgeted amount. For more information, see Creating an Amazon SNS Topic for Budget Notifications.
  3. The master Lambda function receives the SNS notification.
  4. It triggers execution of a Step Functions state machine with the parameters for completing the configured action.
  5. The action Lambda function is triggered as a task in the state machine. The function interacts with IAM to effectively remove the user’s permissions to create an EC2 instance.

This decoupled modular design allows for extensibility.  New actions (serially or in parallel) can be added by simply adding new steps.

Implementing the solution

All the instructions and code needed to implement the architecture have been posted on the Serverless Automated Cost Controls GitHub repo. We recommend that you try this first in a Dev/Test environment.

This implementation description can be broken down into two parts:

  1. Create a solution stack for serverless automated cost controls.
  2. Verify the solution by testing the EC2 fleet.

To tie this back to the “freedom with guardrails” scenario, the Finance department performs a one-time implementation of the solution stack. To simulate resources for Project Beta, the developers spin up the test EC2 fleet.

Prerequisites

There are two prerequisites:

  • Make sure that you have the necessary IAM permissions. For more information, see the section titled “Required IAM permissions” in the README.
  • Define and activate a cost allocation tag with the key Project. For more information, see Using Cost Allocation Tags. It can take up to 12 hours for the tags to propagate to Budgets.

Create resources

The solution stack includes creating the following resources:

  • Three Lambda functions
  • One Step Functions state machine
  • One SNS topic
  • One IAM group
  • One IAM user
  • IAM policies as needed
  • One budget

Two of the Lambda functions were described in the previous section, to a) receive the SNS notification and b) trigger the Step Functions state machine. Another Lambda function is used to create the budget, as a custom AWS CloudFormation resource. The SNS topic connects Budgets with Lambda function A. Lambda function B is configured as a task in Step Functions. A budget for $2 is created which is filtered by Service: EC2 and Tag: Project, Beta. A test IAM group and user is created to enable you to validate this Cost Control Solution.

To create the serverless automated cost control solution stack, choose the button below. It takes few minutes to spin up the stack. You can monitor the progress in the CloudFormation console.

When you see the CREATE_COMPLETE status for the stack you had created, choose Outputs. Copy the following four values that you need later:

  • TemplateURL
  • UserName
  • SignInURL
  • Password

Verify the stack

The next step is to verify the serverless automated cost controls solution stack that you just created. To do this, spin up an EC2 fleet of t2.micro instances, representative of the resources needed for Project Beta, and tag them with Project, Beta.

  1. Browse to the SignInURL, and log in using the UserName and Password values copied on from the stack output.
  2. In the CloudFormation console, choose Create Stack.
  3. For Choose a template, select Choose an Amazon S3 template URL and paste the TemplateURL value from the preceding section. Choose Next.
  4. Give this stack a name, such as “testEc2FleetForProjectBeta”. Choose Next.
  5. On the Specify Details page, enter parameters such as the UserName and Password copied in the previous section. Choose Next.
  6. Ignore any errors related to listing IAM roles. The test user has a minimal set of permissions that is just sufficient to spin up this test stack (in line with security best practices).
  7. On the Options page, choose Next.
  8. On the Review page, choose Create. It takes a few minutes to spin up the stack, and you can monitor the progress in the CloudFormation console. 
  9. When you see the status “CREATE_COMPLETE”, open the EC2 console to verify that four t2.micro instances have been spun up, with the tag of Project, Beta.

The hourly cost for these instances depends on the region in which they are running. On the average (irrespective of the region), you can expect the aggregate cost for this EC2 fleet to exceed the set $2 budget in 48 hours.

Verify the solution

The first step is to identify the test IAM group that was created in the previous section. The group should have “projectBeta” in the name, prepended with the CloudFormation stack name and appended with an alphanumeric string. Verify that the managed policy associated is: “EC2FullAccess”, which indicates that the users in this group have unrestricted access to EC2.

There are two stages of verification for this serverless automated cost controls solution: simulating a notification and waiting for a breach.

Simulated notification

Because it takes at least a few hours for the aggregate cost of the EC2 fleet to breach the set budget, you can verify the solution by simulating the notification from Budgets.

  1. Log in to the SNS console (using your regular AWS credentials).
  2. Publish a message on the SNS topic that has “budgetNotificationTopic” in the name. The complete name is appended by the CloudFormation stack identifier.  
  3. Copy the following text as the body of the notification: “This is a mock notification”.
  4. Choose Publish.
  5. Open the IAM console to verify that the policy for the test group has been switched to “EC2ReadOnly”. This prevents users in this group from creating new instances.
  6. Verify that the test user created in the previous section cannot spin up new EC2 instances.  You can log in as the test user and try creating a new EC2 instance (via the same CloudFormation stack or the EC2 console). You should get an error message indicating that you do not have the necessary permissions.
  7. If you are proceeding to stage 2 of the verification, then you must switch the permissions back to “EC2FullAccess” for the test group, which can be done in the IAM console.

Automatic notification

Within 48 hours, the aggregate cost of the EC2 fleet spun up in the earlier section breaches the budget rule and triggers an automatic notification. This results in the permissions getting switched out, just as in the simulated notification.

Clean up

Use the following steps to delete your resources and stop incurring costs.

  1. Open the CloudFormation console.
  2. Delete the EC2 fleet by deleting the appropriate stack (for example, delete the stack named “testEc2FleetForProjectBeta”).                                               
  3. Next, delete the “costControlStack” stack.                                                                                                                                                    

Conclusion

Using Lambda in tandem with Budgets, you can build Serverless automated cost controls on AWS. Find all the resources (instructions, code) for implementing the solution discussed in this post on the Serverless Automated Cost Controls GitHub repo.

Stay tuned to this series for more tips about building serverless automated cost controls. In the next post, we discuss using smart lighting to influence developer behavior and describe a solution to encourage cost-aware development practices.

If you have questions or suggestions, please comment below.

 

Event-Driven Computing with Amazon SNS and AWS Compute, Storage, Database, and Networking Services

Post Syndicated from Christie Gifrin original https://aws.amazon.com/blogs/compute/event-driven-computing-with-amazon-sns-compute-storage-database-and-networking-services/

Contributed by Otavio Ferreira, Manager, Software Development, AWS Messaging

Like other developers around the world, you may be tackling increasingly complex business problems. A key success factor, in that case, is the ability to break down a large project scope into smaller, more manageable components. A service-oriented architecture guides you toward designing systems as a collection of loosely coupled, independently scaled, and highly reusable services. Microservices take this even further. To improve performance and scalability, they promote fine-grained interfaces and lightweight protocols.

However, the communication among isolated microservices can be challenging. Services are often deployed onto independent servers and don’t share any compute or storage resources. Also, you should avoid hard dependencies among microservices, to preserve maintainability and reusability.

If you apply the pub/sub design pattern, you can effortlessly decouple and independently scale out your microservices and serverless architectures. A pub/sub messaging service, such as Amazon SNS, promotes event-driven computing that statically decouples event publishers from subscribers, while dynamically allowing for the exchange of messages between them. An event-driven architecture also introduces the responsiveness needed to deal with complex problems, which are often unpredictable and asynchronous.

What is event-driven computing?

Given the context of microservices, event-driven computing is a model in which subscriber services automatically perform work in response to events triggered by publisher services. This paradigm can be applied to automate workflows while decoupling the services that collectively and independently work to fulfil these workflows. Amazon SNS is an event-driven computing hub, in the AWS Cloud, that has native integration with several AWS publisher and subscriber services.

Which AWS services publish events to SNS natively?

Several AWS services have been integrated as SNS publishers and, therefore, can natively trigger event-driven computing for a variety of use cases. In this post, I specifically cover AWS compute, storage, database, and networking services, as depicted below.

Compute services

  • Auto Scaling: Helps you ensure that you have the correct number of Amazon EC2 instances available to handle the load for your application. You can configure Auto Scaling lifecycle hooks to trigger events, as Auto Scaling resizes your EC2 cluster.As an example, you may want to warm up the local cache store on newly launched EC2 instances, and also download log files from other EC2 instances that are about to be terminated. To make this happen, set an SNS topic as your Auto Scaling group’s notification target, then subscribe two Lambda functions to this SNS topic. The first function is responsible for handling scale-out events (to warm up cache upon provisioning), whereas the second is in charge of handling scale-in events (to download logs upon termination).

  • AWS Elastic Beanstalk: An easy-to-use service for deploying and scaling web applications and web services developed in a number of programming languages. You can configure event notifications for your Elastic Beanstalk environment so that notable events can be automatically published to an SNS topic, then pushed to topic subscribers.As an example, you may use this event-driven architecture to coordinate your continuous integration pipeline (such as Jenkins CI). That way, whenever an environment is created, Elastic Beanstalk publishes this event to an SNS topic, which triggers a subscribing Lambda function, which then kicks off a CI job against your newly created Elastic Beanstalk environment.

  • Elastic Load Balancing: Automatically distributes incoming application traffic across Amazon EC2 instances, containers, or other resources identified by IP addresses.You can configure CloudWatch alarms on Elastic Load Balancing metrics, to automate the handling of events derived from Classic Load Balancers. As an example, you may leverage this event-driven design to automate latency profiling in an Amazon ECS cluster behind a Classic Load Balancer. In this example, whenever your ECS cluster breaches your load balancer latency threshold, an event is posted by CloudWatch to an SNS topic, which then triggers a subscribing Lambda function. This function runs a task on your ECS cluster to trigger a latency profiling tool, hosted on the cluster itself. This can enhance your latency troubleshooting exercise by making it timely.

Storage services

  • Amazon S3: Object storage built to store and retrieve any amount of data.You can enable S3 event notifications, and automatically get them posted to SNS topics, to automate a variety of workflows. For instance, imagine that you have an S3 bucket to store incoming resumes from candidates, and a fleet of EC2 instances to encode these resumes from their original format (such as Word or text) into a portable format (such as PDF).In this example, whenever new files are uploaded to your input bucket, S3 publishes these events to an SNS topic, which in turn pushes these messages into subscribing SQS queues. Then, encoding workers running on EC2 instances poll these messages from the SQS queues; retrieve the original files from the input S3 bucket; encode them into PDF; and finally store them in an output S3 bucket.

  • Amazon EFS: Provides simple and scalable file storage, for use with Amazon EC2 instances, in the AWS Cloud.You can configure CloudWatch alarms on EFS metrics, to automate the management of your EFS systems. For example, consider a highly parallelized genomics analysis application that runs against an EFS system. By default, this file system is instantiated on the “General Purpose” performance mode. Although this performance mode allows for lower latency, it might eventually impose a scaling bottleneck. Therefore, you may leverage an event-driven design to handle it automatically.Basically, as soon as the EFS metric “Percent I/O Limit” breaches 95%, CloudWatch could post this event to an SNS topic, which in turn would push this message into a subscribing Lambda function. This function automatically creates a new file system, this time on the “Max I/O” performance mode, then switches the genomics analysis application to this new file system. As a result, your application starts experiencing higher I/O throughput rates.

  • Amazon Glacier: A secure, durable, and low-cost cloud storage service for data archiving and long-term backup.You can set a notification configuration on an Amazon Glacier vault so that when a job completes, a message is published to an SNS topic. Retrieving an archive from Amazon Glacier is a two-step asynchronous operation, in which you first initiate a job, and then download the output after the job completes. Therefore, SNS helps you eliminate polling your Amazon Glacier vault to check whether your job has been completed, or not. As usual, you may subscribe SQS queues, Lambda functions, and HTTP endpoints to your SNS topic, to be notified when your Amazon Glacier job is done.

  • AWS Snowball: A petabyte-scale data transport solution that uses secure appliances to transfer large amounts of data.You can leverage Snowball notifications to automate workflows related to importing data into and exporting data from AWS. More specifically, whenever your Snowball job status changes, Snowball can publish this event to an SNS topic, which in turn can broadcast the event to all its subscribers.As an example, imagine a Geographic Information System (GIS) that distributes high-resolution satellite images to users via Web browser. In this example, the GIS vendor could capture up to 80 TB of satellite images; create a Snowball job to import these files from an on-premises system to an S3 bucket; and provide an SNS topic ARN to be notified upon job status changes in Snowball. After Snowball changes the job status from “Importing” to “Completed”, Snowball publishes this event to the specified SNS topic, which delivers this message to a subscribing Lambda function, which finally creates a CloudFront web distribution for the target S3 bucket, to serve the images to end users.

Database services

  • Amazon RDS: Makes it easy to set up, operate, and scale a relational database in the cloud.RDS leverages SNS to broadcast notifications when RDS events occur. As usual, these notifications can be delivered via any protocol supported by SNS, including SQS queues, Lambda functions, and HTTP endpoints.As an example, imagine that you own a social network website that has experienced organic growth, and needs to scale its compute and database resources on demand. In this case, you could provide an SNS topic to listen to RDS DB instance events. When the “Low Storage” event is published to the topic, SNS pushes this event to a subscribing Lambda function, which in turn leverages the RDS API to increase the storage capacity allocated to your DB instance. The provisioning itself takes place within the specified DB maintenance window.

  • Amazon ElastiCache: A web service that makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud.ElastiCache can publish messages using Amazon SNS when significant events happen on your cache cluster. This feature can be used to refresh the list of servers on client machines connected to individual cache node endpoints of a cache cluster. For instance, an ecommerce website fetches product details from a cache cluster, with the goal of offloading a relational database and speeding up page load times. Ideally, you want to make sure that each web server always has an updated list of cache servers to which to connect.To automate this node discovery process, you can get your ElastiCache cluster to publish events to an SNS topic. Thus, when ElastiCache event “AddCacheNodeComplete” is published, your topic then pushes this event to all subscribing HTTP endpoints that serve your ecommerce website, so that these HTTP servers can update their list of cache nodes.

  • Amazon Redshift: A fully managed data warehouse that makes it simple to analyze data using standard SQL and BI (Business Intelligence) tools.Amazon Redshift uses SNS to broadcast relevant events so that data warehouse workflows can be automated. As an example, imagine a news website that sends clickstream data to a Kinesis Firehose stream, which then loads the data into Amazon Redshift, so that popular news and reading preferences might be surfaced on a BI tool. At some point though, this Amazon Redshift cluster might need to be resized, and the cluster enters a ready-only mode. Hence, this Amazon Redshift event is published to an SNS topic, which delivers this event to a subscribing Lambda function, which finally deletes the corresponding Kinesis Firehose delivery stream, so that clickstream data uploads can be put on hold.At a later point, after Amazon Redshift publishes the event that the maintenance window has been closed, SNS notifies a subscribing Lambda function accordingly, so that this function can re-create the Kinesis Firehose delivery stream, and resume clickstream data uploads to Amazon Redshift.

  • AWS DMS: Helps you migrate databases to AWS quickly and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database.DMS also uses SNS to provide notifications when DMS events occur, which can automate database migration workflows. As an example, you might create data replication tasks to migrate an on-premises MS SQL database, composed of multiple tables, to MySQL. Thus, if replication tasks fail due to incompatible data encoding in the source tables, these events can be published to an SNS topic, which can push these messages into a subscribing SQS queue. Then, encoders running on EC2 can poll these messages from the SQS queue, encode the source tables into a compatible character set, and restart the corresponding replication tasks in DMS. This is an event-driven approach to a self-healing database migration process.

Networking services

  • Amazon Route 53: A highly available and scalable cloud-based DNS (Domain Name System). Route 53 health checks monitor the health and performance of your web applications, web servers, and other resources.You can set CloudWatch alarms and get automated Amazon SNS notifications when the status of your Route 53 health check changes. As an example, imagine an online payment gateway that reports the health of its platform to merchants worldwide, via a status page. This page is hosted on EC2 and fetches platform health data from DynamoDB. In this case, you could configure a CloudWatch alarm for your Route 53 health check, so that when the alarm threshold is breached, and the payment gateway is no longer considered healthy, then CloudWatch publishes this event to an SNS topic, which pushes this message to a subscribing Lambda function, which finally updates the DynamoDB table that populates the status page. This event-driven approach avoids any kind of manual update to the status page visited by merchants.

  • AWS Direct Connect (AWS DX): Makes it easy to establish a dedicated network connection from your premises to AWS, which can reduce your network costs, increase bandwidth throughput, and provide a more consistent network experience than Internet-based connections.You can monitor physical DX connections using CloudWatch alarms, and send SNS messages when alarms change their status. As an example, when a DX connection state shifts to 0 (zero), indicating that the connection is down, this event can be published to an SNS topic, which can fan out this message to impacted servers through HTTP endpoints, so that they might reroute their traffic through a different connection instead. This is an event-driven approach to connectivity resilience.

More event-driven computing on AWS

In addition to SNS, event-driven computing is also addressed by Amazon CloudWatch Events, which delivers a near real-time stream of system events that describe changes in AWS resources. With CloudWatch Events, you can route each event type to one or more targets, including:

Many AWS services publish events to CloudWatch. As an example, you can get CloudWatch Events to capture events on your ETL (Extract, Transform, Load) jobs running on AWS Glue and push failed ones to an SQS queue, so that you can retry them later.

Conclusion

Amazon SNS is a pub/sub messaging service that can be used as an event-driven computing hub to AWS customers worldwide. By capturing events natively triggered by AWS services, such as EC2, S3 and RDS, you can automate and optimize all kinds of workflows, namely scaling, testing, encoding, profiling, broadcasting, discovery, failover, and much more. Business use cases presented in this post ranged from recruiting websites, to scientific research, geographic systems, social networks, retail websites, and news portals.

Start now by visiting Amazon SNS in the AWS Management Console, or by trying the AWS 10-Minute Tutorial, Send Fan-out Event Notifications with Amazon SNS and Amazon SQS.

 

Long Article on NSA and the Shadow Brokers

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/11/long_article_on_1.html

The New York Times just published a long article on the Shadow Brokers and their effects on NSA operations. Summary: it’s been an operational disaster, the NSA still doesn’t know who did it or how, and NSA morale has suffered considerably.

This is me on the Shadow Brokers from last May.

Google’s Data on Login Thefts

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/11/googles_data_on.html

This is interesting research and data:

With Google accounts as a case-study, we teamed up with the University of California, Berkeley to better understand how hijackers attempt to take over accounts in the wild. From March 2016 to March 2017, we analyzed several black markets to see how hijackers steal passwords and other sensitive data.

[…]

Our research tracked several black markets that traded third-party password breaches, as well as 25,000 blackhat tools used for phishing and keylogging. In total, these sources helped us identify 788,000 credentials stolen via keyloggers, 12 million credentials stolen via phishing, and 3.3 billion credentials exposed by third-party breaches.

The report.

Me on the Equifax Breach

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/11/me_on_the_equif.html

Testimony and Statement for the Record of Bruce Schneier
Fellow and Lecturer, Belfer Center for Science and International Affairs, Harvard Kennedy School
Fellow, Berkman Center for Internet and Society at Harvard Law School

Hearing on “Securing Consumers’ Credit Data in the Age of Digital Commerce”

Before the

Subcommittee on Digital Commerce and Consumer Protection
Committee on Energy and Commerce
United States House of Representatives

1 November 2017
2125 Rayburn House Office Building
Washington, DC 20515

Mister Chairman and Members of the Committee, thank you for the opportunity to testify today concerning the security of credit data. My name is Bruce Schneier, and I am a security technologist. For over 30 years I have studied the technologies of security and privacy. I have authored 13 books on these subjects, including Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World (Norton, 2015). My popular newsletter CryptoGram and my blog Schneier on Security are read by over 250,000 people.

Additionally, I am a Fellow and Lecturer at the Harvard Kennedy School of Government –where I teach Internet security policy — and a Fellow at the Berkman-Klein Center for Internet and Society at Harvard Law School. I am a board member of the Electronic Frontier Foundation, AccessNow, and the Tor Project; and an advisory board member of Electronic Privacy Information Center and VerifiedVoting.org. I am also a special advisor to IBM Security and the Chief Technology Officer of IBM Resilient.

I am here representing none of those organizations, and speak only for myself based on my own expertise and experience.

I have eleven main points:

1. The Equifax breach was a serious security breach that puts millions of Americans at risk.

Equifax reported that 145.5 million US customers, about 44% of the population, were impacted by the breach. (That’s the original 143 million plus the additional 2.5 million disclosed a month later.) The attackers got access to full names, Social Security numbers, birth dates, addresses, and driver’s license numbers.

This is exactly the sort of information criminals can use to impersonate victims to banks, credit card companies, insurance companies, cell phone companies and other businesses vulnerable to fraud. As a result, all 143 million US victims are at greater risk of identity theft, and will remain at risk for years to come. And those who suffer identify theft will have problems for months, if not years, as they work to clean up their name and credit rating.

2. Equifax was solely at fault.

This was not a sophisticated attack. The security breach was a result of a vulnerability in the software for their websites: a program called Apache Struts. The particular vulnerability was fixed by Apache in a security patch that was made available on March 6, 2017. This was not a minor vulnerability; the computer press at the time called it “critical.” Within days, it was being used by attackers to break into web servers. Equifax was notified by Apache, US CERT, and the Department of Homeland Security about the vulnerability, and was provided instructions to make the fix.

Two months later, Equifax had still failed to patch its systems. It eventually got around to it on July 29. The attackers used the vulnerability to access the company’s databases and steal consumer information on May 13, over two months after Equifax should have patched the vulnerability.

The company’s incident response after the breach was similarly damaging. It waited nearly six weeks before informing victims that their personal information had been stolen and they were at increased risk of identity theft. Equifax opened a website to help aid customers, but the poor security around that — the site was at a domain separate from the Equifax domain — invited fraudulent imitators and even more damage to victims. At one point, the official Equifax communications even directed people to that fraudulent site.

This is not the first time Equifax failed to take computer security seriously. It confessed to another data leak in January 2017. In May 2016, one of its websites was hacked, resulting in 430,000 people having their personal information stolen. Also in 2016, a security researcher found and reported a basic security vulnerability in its main website. And in 2014, the company reported yet another security breach of consumer information. There are more.

3. There are thousands of data brokers with similarly intimate information, similarly at risk.

Equifax is more than a credit reporting agency. It’s a data broker. It collects information about all of us, analyzes it all, and then sells those insights. It might be one of the biggest, but there are 2,500 to 4,000 other data brokers that are collecting, storing, and selling information about us — almost all of them companies you’ve never heard of and have no business relationship with.

The breadth and depth of information that data brokers have is astonishing. Data brokers collect and store billions of data elements covering nearly every US consumer. Just one of the data brokers studied holds information on more than 1.4 billion consumer transactions and 700 billion data elements, and another adds more than 3 billion new data points to its database each month.

These brokers collect demographic information: names, addresses, telephone numbers, e-mail addresses, gender, age, marital status, presence and ages of children in household, education level, profession, income level, political affiliation, cars driven, and information about homes and other property. They collect lists of things we’ve purchased, when we’ve purchased them, and how we paid for them. They keep track of deaths, divorces, and diseases in our families. They collect everything about what we do on the Internet.

4. These data brokers deliberately hide their actions, and make it difficult for consumers to learn about or control their data.

If there were a dozen people who stood behind us and took notes of everything we purchased, read, searched for, or said, we would be alarmed at the privacy invasion. But because these companies operate in secret, inside our browsers and financial transactions, we don’t see them and we don’t know they’re there.

Regarding Equifax, few consumers have any idea what the company knows about them, who they sell personal data to or why. If anyone knows about them at all, it’s about their business as a credit bureau, not their business as a data broker. Their website lists 57 different offerings for business: products for industries like automotive, education, health care, insurance, and restaurants.

In general, options to “opt-out” don’t work with data brokers. It’s a confusing process, and doesn’t result in your data being deleted. Data brokers will still collect data about consumers who opt out. It will still be in those companies’ databases, and will still be vulnerable. It just don’t be included individually when they sell data to their customers.

5. The existing regulatory structure is inadequate.

Right now, there is no way for consumers to protect themselves. Their data has been harvested and analyzed by these companies without their knowledge or consent. They cannot improve the security of their personal data, and have no control over how vulnerable it is. They only learn about data breaches when the companies announce them — which can be months after the breaches occur — and at that point the onus is on them to obtain credit monitoring services or credit freezes. And even those only protect consumers from some of the harms, and only those suffered after Equifax admitted to the breach.

Right now, the press is reporting “dozens” of lawsuits against Equifax from shareholders, consumers, and banks. Massachusetts has sued Equifax for violating state consumer protection and privacy laws. Other states may follow suit.

If any of these plaintiffs win in the court, it will be a rare victory for victims of privacy breaches against the companies that have our personal information. Current law is too narrowly focused on people who have suffered financial losses directly traceable to a specific breach. Proving this is difficult. If you are the victim of identity theft in the next month, is it because of Equifax or does the blame belong to another of the thousands of companies who have your personal data? As long as one can’t prove it one way or the other, data brokers remain blameless and liability free.

Additionally, much of this market in our personal data falls outside the protections of the Fair Credit Reporting Act. And in order for the Federal Trade Commission to levy a fine against Equifax, it needs to have a consent order and then a subsequent violation. Any fines will be limited to credit information, which is a small portion of the enormous amount of information these companies know about us. In reality, this is not an effective enforcement regime.

Although the FTC is investigating Equifax, it is unclear if it has a viable case.

6. The market cannot fix this because we are not the customers of data brokers.

The customers of these companies are people and organizations who want to buy information: banks looking to lend you money, landlords deciding whether to rent you an apartment, employers deciding whether to hire you, companies trying to figure out whether you’d be a profitable customer — everyone who wants to sell you something, even governments.

Markets work because buyers choose from a choice of sellers, and sellers compete for buyers. None of us are Equifax’s customers. None of us are the customers of any of these data brokers. We can’t refuse to do business with the companies. We can’t remove our data from their databases. With few limited exceptions, we can’t even see what data these companies have about us or correct any mistakes.

We are the product that these companies sell to their customers: those who want to use our personal information to understand us, categorize us, make decisions about us, and persuade us.

Worse, the financial markets reward bad security. Given the choice between increasing their cybersecurity budget by 5%, or saving that money and taking the chance, a rational CEO chooses to save the money. Wall Street rewards those whose balance sheets look good, not those who are secure. And if senior management gets unlucky and the a public breach happens, they end up okay. Equifax’s CEO didn’t get his $5.2 million severance pay, but he did keep his $18.4 million pension. Any company that spends more on security than absolutely necessary is immediately penalized by shareholders when its profits decrease.

Even the negative PR that Equifax is currently suffering will fade. Unless we expect data brokers to put public interest ahead of profits, the security of this industry will never improve without government regulation.

7. We need effective regulation of data brokers.

In 2014, the Federal Trade Commission recommended that Congress require data brokers be more transparent and give consumers more control over their personal information. That report contains good suggestions on how to regulate this industry.

First, Congress should help plaintiffs in data breach cases by authorizing and funding empirical research on the harm individuals receive from these breaches.

Specifically, Congress should move forward legislative proposals that establish a nationwide “credit freeze” — which is better described as changing the default for disclosure from opt-out to opt-in — and free lifetime credit monitoring services. By this I do not mean giving customers free credit-freeze options, a proposal by Senators Warren and Schatz, but that the default should be a credit freeze.

The credit card industry routinely notifies consumers when there are suspicious charges. It is obvious that credit reporting agencies should have a similar obligation to notify consumers when there is suspicious activity concerning their credit report.

On the technology side, more could be done to limit the amount of personal data companies are allowed to collect. Increasingly, privacy safeguards impose “data minimization” requirements to ensure that only the data that is actually needed is collected. On the other hand, Congress should not create a new national identifier to replace the Social Security Numbers. That would make the system of identification even more brittle. Better is to reduce dependence on systems of identification and to create contextual identification where necessary.

Finally, Congress needs to give the Federal Trade Commission the authority to set minimum security standards for data brokers and to give consumers more control over their personal information. This is essential as long as consumers are these companies’ products and not their customers.

8. Resist complaints from the industry that this is “too hard.”

The credit bureaus and data brokers, and their lobbyists and trade-association representatives, will claim that many of these measures are too hard. They’re not telling you the truth.

Take one example: credit freezes. This is an effective security measure that protects consumers, but the process of getting one and of temporarily unfreezing credit is made deliberately onerous by the credit bureaus. Why isn’t there a smartphone app that alerts me when someone wants to access my credit rating, and lets me freeze and unfreeze my credit at the touch of the screen? Too hard? Today, you can have an app on your phone that does something similar if you try to log into a computer network, or if someone tries to use your credit card at a physical location different from where you are.

Moreover, any credit bureau or data broker operating in Europe is already obligated to follow the more rigorous EU privacy laws. The EU General Data Protection Regulation will come into force, requiring even more security and privacy controls for companies collecting storing the personal data of EU citizens. Those companies have already demonstrated that they can comply with those more stringent regulations.

Credit bureaus, and data brokers in general, are deliberately not implementing these 21st-century security solutions, because they want their services to be as easy and useful as possible for their actual customers: those who are buying your information. Similarly, companies that use this personal information to open accounts are not implementing more stringent security because they want their services to be as easy-to-use and convenient as possible.

9. This has foreign trade implications.

The Canadian Broadcast Corporation reported that 100,000 Canadians had their data stolen in the Equifax breach. The British Broadcasting Corporation originally reported that 400,000 UK consumers were affected; Equifax has since revised that to 15.2 million.

Many American Internet companies have significant numbers of European users and customers, and rely on negotiated safe harbor agreements to legally collect and store personal data of EU citizens.

The European Union is in the middle of a massive regulatory shift in its privacy laws, and those agreements are coming under renewed scrutiny. Breaches such as Equifax give these European regulators a powerful argument that US privacy regulations are inadequate to protect their citizens’ data, and that they should require that data to remain in Europe. This could significantly harm American Internet companies.

10. This has national security implications.

Although it is still unknown who compromised the Equifax database, it could easily have been a foreign adversary that routinely attacks the servers of US companies and US federal agencies with the goal of exploiting security vulnerabilities and obtaining personal data.

When the Fair Credit Reporting Act was passed in 1970, the concern was that the credit bureaus might misuse our data. That is still a concern, but the world has changed since then. Credit bureaus and data brokers have far more intimate data about all of us. And it is valuable not only to companies wanting to advertise to us, but foreign governments as well. In 2015, the Chinese breached the database of the Office of Personal Management and stole the detailed security clearance information of 21 million Americans. North Korea routinely engages in cybercrime as way to fund its other activities. In a world where foreign governments use cyber capabilities to attack US assets, requiring data brokers to limit collection of personal data, securely store the data they collect, and delete data about consumers when it is no longer needed is a matter of national security.

11. We need to do something about it.

Yes, this breach is a huge black eye and a temporary stock dip for Equifax — this month. Soon, another company will have suffered a massive data breach and few will remember Equifax’s problem. Does anyone remember last year when Yahoo admitted that it exposed personal information of a billion users in 2013 and another half billion in 2014?

Unless Congress acts to protect consumer information in the digital age, these breaches will continue.

Thank you for the opportunity to testify today. I will be pleased to answer your questions.