Friday Squid Blogging: Japanese Squid Recipe

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.

Posted on October 8, 2015 at 4:26 PM9 Comments

I'm a Guest on "Adam Ruins Everything"

The show is about security theater. I am a disembodied head on a scooter.

Here's a teaser. Here's the full episode (for pay, but cheap).

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.

Posted on October 8, 2015 at 2:11 PM4 Comments

SHA-1 Freestart Collision

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.

Way back in 2004, I wrote: "It's time for us all to migrate away from SHA-1." Since then, we have developed an excellent replacement: SHA-3 has been agreed on since 2012, and just became a standard.

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.

Posted on October 8, 2015 at 11:44 AM3 Comments

European Court of Justice Rules Against Safe Harbor

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.

The judgment. The court's press release. A good summary of the decision and the issues involved. Intercept article.

EFF blog post. Commentary by Henry Farrell.

Commentary by Max Schrems, who started this proceeding. More commentary by someone involved with the proceedings.

Even more commentary.

Posted on October 7, 2015 at 7:27 AM69 Comments

Automatic Face Recognition and Surveillance

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

EDITED TO ADD: Two articles that say much the same thing.

Posted on October 5, 2015 at 6:11 AM94 Comments

Friday Squid Blogging: Bobtail Squid Keeps Bacteria to Protect Its Eggs

The Hawaiian Bobtail Squid deposits bacteria on its eggs to keep them safe.

As usual, you can also use this squid post to talk about the security stories in the news that I haven't covered.

Posted on October 2, 2015 at 4:11 PM165 Comments

Resilient Systems News

Former Raytheon CEO Bill Swanson has joined our board of directors.

For those who don't know, Resilient Systems is my company. I'm the CTO, and we sell an incident-response management platform that...well...helps IR teams to manage incidents. It's a single hub that allows a team to collect data about an incident, assign and manage tasks, automate actions, integrate intelligence information, and so on. It's designed to be powerful, flexible, and intuitive -- if your HR or legal person needs to get involved, she has to be able to use it without any training. I'm really impressed with how well it works. Incident response is all about people, and the platform makes teams more effective. This is probably the best description of what we do.

We have lots of large- and medium-sized companies as customers. They're all happy, and we continue to sell this thing at an impressive rate. Our Q3 numbers were fantastic. It's kind of scary, really.

Posted on October 2, 2015 at 2:06 PM19 Comments

Stealing Fingerprints

The news from the Office of Personnel Management hack keeps getting worse. In addition to the personal records of over 20 million US government employees, we've now learned that the hackers stole fingerprint files for 5.6 million of them.

This is fundamentally different from the data thefts we regularly read about in the news, and should give us pause before we entrust our biometric data to large networked databases.

There are three basic kinds of data that can be stolen. The first, and most common, is authentication credentials. These are passwords and other information that allows someone else access into our accounts and -- usually -- our money. An example would be the 56 million credit card numbers hackers stole from Home Depot in 2014, or the 21.5 million Social Security numbers hackers stole in the OPM breach. The motivation is typically financial. The hackers want to steal money from our bank accounts, process fraudulent credit card charges in our name, or open new lines of credit or apply for tax refunds.

It's a huge illegal business, but we know how to deal with it when it happens. We detect these hacks as quickly as possible, and update our account credentials as soon as we detect an attack. (We also need to stop treating Social Security numbers as if they were secret.)

The second kind of data stolen is personal information. Examples would be the medical data stolen and exposed when Sony was hacked in 2014, or the very personal data from the infidelity website Ashley Madison stolen and published this year. In these instances, there is no real way to recover after a breach. Once the data is public, or in the hands of an adversary, it's impossible to make it private again.

This is the main consequence of the OPM data breach. Whoever stole the data -- we suspect it was the Chinese -- got copies the security-clearance paperwork of all those government employees. This documentation includes the answers to some very personal and embarrassing questions, and now opens these employees up to blackmail and other types of coercion.

Fingerprints are another type of data entirely. They're used to identify people at crime scenes, but increasingly they're used as an authentication credential. If you have an iPhone, for example, you probably use your fingerprint to unlock your phone. This type of authentication is increasingly common, replacing a password -- something you know -- with a biometric: something you are. The problem with biometrics is that they can't be replaced. So while it's easy to update your password or get a new credit card number, you can't get a new finger.

And now, for the rest of their lives, 5.6 million US government employees need to remember that someone, somewhere, has their fingerprints. And we really don't know the future value of this data. If, in twenty years, we routinely use our fingerprints at ATM machines, that fingerprint database will become very profitable to criminals. If fingerprints start being used on our computers to authorize our access to files and data, that database will become very profitable to spies.

Of course, it's not that simple. Fingerprint readers employ various technologies to prevent being fooled by fake fingers: detecting temperature, pores, a heartbeat, and so on. But this is an arms race between attackers and defenders, and there are many ways to fool fingerprint readers. When Apple introduced its iPhone fingerprint reader, hackers figured out how to fool it within days, and have continued to fool each new generation of phone readers equally quickly.

Not every use of biometrics requires the biometric data to be stored in a central server somewhere. Apple's system, for example, only stores the data locally: on your phone. That way there's no central repository to be hacked. And many systems don't store the biometric data at all, only a mathematical function of the data that can be used for authentication but can't be used to reconstruct the actual biometric. Unfortunately, OPM stored copies of actual fingerprints.

Ashley Madison has taught us all the dangers of entrusting our intimate secrets to a company's computers and networks, because once that data is out there's no getting it back. All biometric data, whether it be fingerprints, retinal scans, voiceprints, or something else, has that same property. We should be skeptical of any attempts to store this data en masse, whether by governments or by corporations. We need our biometrics for authentication, and we can't afford to lose them to hackers.

This essay previously appeared on Motherboard.

Posted on October 2, 2015 at 6:35 AM64 Comments

Photo of Bruce Schneier by Per Ervland.

Schneier on Security is a personal website. Opinions expressed are not necessarily those of Resilient Systems, Inc.