In the 1980s, the Soviet Union bugged the IBM Selectric typewriters in the US Embassy in Moscow. This NSA document discusses how the US discovered the bugs and what we did about it. Codename is GUNMAN.
Is this the world's first keylogger? Maybe.
Delicious recipe of squid with cabbage, bean sprouts, and noodles.
As usual, you can also use this squid post to talk about the security stories in the news that I haven't covered.
EDITED TO ADD (10/9): Posted a day early by mistake....
The show is about security theater. I am a disembodied head on a scooter.
The scooter idea was a hack when I couldn't find the time to fly to LA for live filming. The whole thing was a lot of fun.
There's a new cryptanalysis result against the hash function SHA-1:
Abstract: We present in this article a freestart collision example for SHA-1, i.e., a collision for its internal compression function. This is the first practical break of the full SHA-1, reaching all 80 out of 80 steps, while only 10 days of computation on a 64 GPU cluster were necessary to perform the attack. This work builds on a continuous series of cryptanalytic advancements on SHA-1 since the theoretical collision attack breakthrough in 2005. In particular, we extend the recent freestart collision work on reduced-round SHA-1 from CRYPTO 2015 that leverages the computational power of graphic cards and adapt it to allow the use of boomerang speed-up techniques. We also leverage the cryptanalytic techniques by Stevens from EUROCRYPT 2013 to obtain optimal attack conditions, which required further refinements for this work. Freestart collisions, like the one presented here, do not directly imply a collision for SHA-1.
However, this work is an important milestone towards an actual SHA-1 collision and it further shows how graphics cards can be used very efficiently for these kind of attacks. Based on the state-of-the-art collision attack on SHA-1 by Stevens from EUROCRYPT 2013, we are able to present new projections on the computational/financial cost required by a SHA-1 collision computation. These projections are significantly lower than previously anticipated by the industry, due to the use of the more cost efficient graphics cards compared to regular CPUs. We therefore recommend the industry, in particular Internet browser vendors and Certification Authorities, to retract SHA-1 soon. We hope the industry has learned from the events surrounding the cryptanalytic breaks of MD5 and will retract SHA-1 before example signature forgeries appear in the near future. With our new cost projections in mind, we strongly and urgently recommend against a recent proposal to extend the issuance of SHA-1 certificates by a year in the CAB/forum (the vote closes on October 16 2015 after a discussion period ending on October 9).
Especially note this bit: "Freestart collisions, like the one presented here, do not directly imply a collision for SHA-1. However, this work is an important milestone towards an actual SHA-1 collision and it further shows how graphics cards can be used very efficiently for these kind of attacks." In other words: don't panic, but prepare for a future panic.
This is not that unexpected. We've long known that SHA-1 is broken, at least theoretically. All the major browsers are planning to stop accepting SHA-1 signatures by 2017. Microsoft is retiring it on that same schedule. What's news is that our previous estimates may be too conservative.
There's a saying inside the NSA: "Attacks always get better; they never get worse." This is obviously true, but it's worth explaining why. Attacks get better for three reasons. One, Moore's Law means that computers are always getting faster, which means that any cryptanalytic attack gets faster. Two, we're forever making tweaks in existing attacks, which make them faster. (Note above: "...due to the use of the more cost efficient graphics cards compared to regular CPUs.") And three, we regularly invent new cryptanalytic attacks. The first of those is generally predictable, the second is somewhat predictable, and the third is not at all predictable.
This new result is important right now:
Thursday's research showing SHA1 is weaker than previously thought comes as browser developers and certificate authorities are considering a proposal that would extend the permitted issuance of the SHA1-based HTTPS certificates by 12 months, that is through the end of 2016 rather than no later than January of that year. The proposal argued that some large organizations currently find it hard to move to a more secure hashing algorithm for their digital certificates and need the additional year to make the transition.
As the papers' authors note, approving this proposal is a bad idea.
More on the paper here.
The European Court of Justice ruled that sending personal data to the US violates their right to privacy:
The ruling, by the European Court of Justice, said the so-called safe harbor agreement was flawed because it allowed American government authorities to gain routine access to Europeans' online information. The court said leaks from Edward J. Snowden, the former contractor for the National Security Agency, made it clear that American intelligence agencies had almost unfettered access to the data, infringing on Europeans' rights to privacy.
This is a big deal, because it directly affects all the large American Internet companies. If this stands, expect much more pressure on the NSA to stop their indiscriminate spying on everyone.
EDITED TO ADD (10/13): Quick explanation.
ID checks were a common response to the terrorist attacks of 9/11, but they'll soon be obsolete. You won't have to show your ID, because you'll be identified automatically. A security camera will capture your face, and it'll be matched with your name and a whole lot of other information besides. Welcome to the world of automatic facial recognition. Those who have access to databases of identified photos will have the power to identify us. Yes, it'll enable some amazing personalized services; but it'll also enable whole new levels of surveillance. The underlying technologies are being developed today, and there are currently no rules limiting their use.
Walk into a store, and the salesclerks will know your name. The store's cameras and computers will have figured out your identity, and looked you up in both their store database and a commercial marketing database they've subscribed to. They'll know your name, salary, interests, what sort of sales pitches you're most vulnerable to, and how profitable a customer you are. Maybe they'll have read a profile based on your tweets and know what sort of mood you're in. Maybe they'll know your political affiliation or sexual identity, both predictable by your social media activity. And they're going to engage with you accordingly, perhaps by making sure you're well taken care of or possibly by trying to make you so uncomfortable that you'll leave.
Walk by a policeman, and she will know your name, address, criminal record, and with whom you routinely are seen. The potential for discrimination is enormous, especially in low-income communities where people are routinely harassed for things like unpaid parking tickets and other minor violations. And in a country where people are arrested for their political views, the use of this technology quickly turns into a nightmare scenario.
The critical technology here is computer face recognition. Traditionally it has been pretty poor, but it's slowly improving. A computer is now as good as a person. Already Google's algorithms can accurately match child and adult photos of the same person, and Facebook has an algorithm that works by recognizing hair style, body shape, and body language - and works even when it can't see faces. And while we humans are pretty much as good at this as we're ever going to get, computers will continue to improve. Over the next years, they'll continue to get more accurate, making better matches using even worse photos.
Matching photos with names also requires a database of identified photos, and we have plenty of those too. Driver's license databases are a gold mine: all shot face forward, in good focus and even light, with accurate identity information attached to each photo. The enormous photo collections of social media and photo archiving sites are another. They contain photos of us from all sorts of angles and in all sorts of lighting conditions, and we helpfully do the identifying step for the companies by tagging ourselves and our friends. Maybe this data will appear on handheld screens. Maybe it'll be automatically displayed on computer-enhanced glasses. Imagine salesclerks -- or politicians -- being able to scan a room and instantly see wealthy customers highlighted in green, or policemen seeing people with criminal records highlighted in red.
Science fiction writers have been exploring this future in both books and movies for decades. Ads followed people from billboard to billboard in the movie Minority Report. In John Scalzi's recent novel Lock In, characters scan each other like the salesclerks I described above.
This is no longer fiction. High-tech billboards can target ads based on the gender of who's standing in front of them. In 2011, researchers at Carnegie Mellon pointed a camera at a public area on campus and were able to match live video footage with a public database of tagged photos in real time. Already government and commercial authorities have set up facial recognition systems to identify and monitor people at sporting events, music festivals, and even churches. The Dubai police are working on integrating facial recognition into Google Glass, and more US local police forces are using the technology.
Facebook, Google, Twitter, and other companies with large databases of tagged photos know how valuable their archives are. They see all kinds of services powered by their technologies services they can sell to businesses like the stores you walk into and the governments you might interact with.
Other companies will spring up whose business models depend on capturing our images in public and selling them to whoever has use for them. If you think this is farfetched, consider a related technology that's already far down that path: license-plate capture.
Today in the US there's a massive but invisible industry that records the movements of cars around the country. Cameras mounted on cars and tow trucks capture license places along with date/time/location information, and companies use that data to find cars that are scheduled for repossession. One company, Vigilant Solutions, claims to collect 70 million scans in the US every month. The companies that engage in this business routinely share that data with the police, giving the police a steady stream of surveillance information on innocent people that they could not legally collect on their own. And the companies are already looking for other profit streams, selling that surveillance data to anyone else who thinks they have a need for it.
This could easily happen with face recognition. Finding bail jumpers could even be the initial driving force, just as finding cars to repossess was for license plate capture.
Already the FBI has a database of 52 million faces, and describes its integration of facial recognition software with that database as "fully operational." In 2014, FBI Director James Comey told Congress that the database would not include photos of ordinary citizens, although the FBI's own documents indicate otherwise. And just last month, we learned that the FBI is looking to buy a system that will collect facial images of anyone an officer stops on the street.
In 2013, Facebook had a quarter of a trillion user photos in its database. There's currently a class-action lawsuit in Illinois alleging that the company has over a billion "face templates" of people, collected without their knowledge or consent.
Last year, the US Department of Commerce tried to prevail upon industry representatives and privacy organizations to write a voluntary code of conduct for companies using facial recognition technologies. After 16 months of negotiations, all of the consumer-focused privacy organizations pulled out of the process because industry representatives were unable to agree on any limitations on something as basic as nonconsensual facial recognition.
When we talk about surveillance, we tend to concentrate on the problems of data collection: CCTV cameras, tagged photos, purchasing habits, our writings on sites like Facebook and Twitter. We think much less about data analysis. But effective and pervasive surveillance is just as much about analysis. It's sustained by a combination of cheap and ubiquitous cameras, tagged photo databases, commercial databases of our actions that reveal our habits and personalities, and -- most of all -- fast and accurate face recognition software.
Don't expect to have access to this technology for yourself anytime soon. This is not facial recognition for all. It's just for those who can either demand or pay for access to the required technologies -- most importantly, the tagged photo databases. And while we can easily imagine how this might be misused in a totalitarian country, there are dangers in free societies as well. Without meaningful regulation, we're moving into a world where governments and corporations will be able to identify people both in real time and backwards in time, remotely and in secret, without consent or recourse.
Despite protests from industry, we need to regulate this budding industry. We need limitations on how our images can be collected without our knowledge or consent, and on how they can be used. The technologies aren't going away, and we can't uninvent these capabilities. But we can ensure that they're used ethically and responsibly, and not just as a mechanism to increase police and corporate power over us.
This essay previously appeared on Forbes.com.
Photo of Bruce Schneier by Per Ervland.
Schneier on Security is a personal website. Opinions expressed are not necessarily those of Resilient Systems, Inc.