There was a public outcry followed by ICO “making enquiries” when Troy Hunt published a post about Tesco’s plaintext password reminders exactly a month ago.
I wanted to use the reference for a text I was writing last week when someone asked me about online accounts of Companies House. At that moment I said to myself, wait a second. Companies House sends plaintext reminders as well. How strange. I sent a link to a short post to ComputerWorld. They in turn managed to get a statement from Companies House that includes:
“… although it is [Companies House] certified to the ISO 27001 standard and adheres to the government’s Security Policy Framework, it will carry out a review of its systems in order to establish whether there is a threat to companies’ confidential information.” Continue reading Plaintext Password Reminders
Alex Henney and I have decided to publish a paper on smart metering that we prepared in February for the Cabinet Office and for ministers. DECC is running a smart metering project that is supposed to save energy by replacing all Britain’s gas and electricity meters with computerised ones by 2019, and to cost only £11bn. Yet the meters will be controlled by the utilities, whose interest is to maximise sales volumes, so there is no realistic prospect that the meters will save energy. What’s more, smart metering already exhibits all the classic symptoms of a failed public-sector IT project.
The paper we release today describes how, when Ed Milliband was Secretary of State, DECC cooked the books to make the project appear economically worthwhile. It then avoided the control procedures that are mandatory for large IT procurements by pretending it was not an IT project but an engineering project. We have already written on the security economics of smart meters, their technical security, the privacy aspects and why the project is failing.
We managed to secure a Cabinet Office review of the project which came up with a red traffic light – a recommendation that the project be abandoned. However DECC dug its heels in and the project appears to be going ahead. Hey, we did our best. The failure should be evident in time for the next election; just remember, you read it here first.
November last, on the Eurostar back from Paris, something struck me as I looked at the logs of ATM withdrawals disputed by Alex Gambin, a customer of HSBC in Malta. Comparing four grainy log pages on a tiny phone screen, I had to scroll away from the transaction data to see the page numbers, so I couldn’t take in the big picture in one go. I differentiated pages instead using the EMV Unpredictable Number field – a 32 bit field that’s supposed to be unique to each transaction. I soon got muddled up… it turned out that the unpredictable numbers… well… weren’t. Each shared 17 bits in common and the remaining 15 looked at first glance like a counter. The numbers are tabulated as follows:
And with that the ball started rolling on an exciting direction of research that’s kept us busy the last nine months. You see, an EMV payment card authenticates itself with a MAC of transaction data, for which the freshly generated component is the unpredictable number (UN). If you can predict it, you can record everything you need from momentary access to a chip card to play it back and impersonate the card at a future date and location. You can as good as clone the chip. It’s called a “pre-play” attack. Just like most vulnerabilities we find these days some in industry already knew about it but covered it up; we have indications the crooks know about this too, and we believe it explains a good portion of the unsolved phantom withdrawal cases reported to us for which we had until recently no explanation.
Mike Bond, Omar Choudary, Steven J. Murdoch, Sergei Skorobogatov, and Ross Anderson wrote a paper on the research, and Steven is presenting our work as keynote speaker at Cryptographic Hardware and Embedded System (CHES) 2012, in Leuven, Belgium. We discovered that the significance of these numbers went far beyond this one case.
Continue reading Chip and Skim: cloning EMV cards with the pre-play attack
Yesterday, I took a critical look at the difficulty of interpreting progress in password cracking. Today I’ll make a broader argument that even if we had good data to evaluate cracking efficiency, recent progress isn’t a major threat the vast majority of web passwords. Efficient and powerful cracking tools are useful in some targeted attack scenarios, but just don’t change the economics of industrial-scale attacks against web accounts. The basic mechanics of web passwords mean highly-efficient cracking doesn’t offer much benefit in untargeted attacks. Continue reading Password cracking, part II: when does password cracking matter?
Password cracking has returned to the news, with a thorough Ars Technica article on the increasing potency of cracking tools and the third Crack Me If You Can contest at this year’s DEFCON. Taking a critical view, I’ll argue that it’s not clear exactly how much password cracking is improving and that the cracking community could do a much better job of measuring progress.
Password cracking can be evaluated on two nearly independent axes: power (the ability to check a large number of guesses quickly and cheaply using optimized software, GPUs, FPGAs, and so on) and efficiency (the ability to generate large lists of candidate passwords accurately ranked by real-world likelihood using sophisticated models). It’s relatively simple to measure cracking power in units of hashes evaluated per second or hashes per second per unit cost. There are details to account for, like the complexity of the hash being evaluated, but this problem is generally similar to cryptographic brute force against unknown (random) keys and power is generally increasing exponentially in tune with Moore’s law. The move to hardware-based cracking has enabled well-documented orders-of-magnitude speedups.
Cracking efficiency, by contrast, is rarely measured well. Useful data points, some of which I curated in my PhD thesis, consist of the number of guesses made against a given set of password hashes and the proportion of hashes which were cracked as a result. Ideally many such points should be reported, allowing us to plot a curve showing the marginal returns as additional guessing effort is expended. Unfortunately results are often stated in terms of the total number of hashes cracked (here are some examples). Sometimes the runtime of a cracking tool is reported, which is an improvement but conflates efficiency with power. Continue reading Password cracking, part I: how much has cracking improved?