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How Watermarks Fail

February 24, 2006 by

I wrote Wednesday about Randy Picker’s suggestion of using digital watermarks to embed users’ personal financial information into media files, to discourage users from sharing the files. Today, I want to talk more generally about watermarks and how they tend to fail.

First, some background. Watermarks are subtle signals embedded in the background of media files. They are supposed to be unobtrusive but easy to detect if you know where to look. Different media have different kinds of watermarks. In a photo, the watermark might be hidden in subtle patterns of shading. In music, it might be in a very soft background buzz, or a barely audible echo.

In many applications, a watermark must resist attempts by an adversary to remove it. For example, in Randy’s scheme, a user might want to remove the identifying watermark from a media file because he wants to share the file illegally, or because he doesn’t want his personal information exposed to cyber-intruders. It is often important to know how resistant a particular watermark is to removal. There has been plenty of research on this topic, from which we can draw lessons about how watermark removal tends to work.

One theme is the power of Rosetta Stone attacks. The original Rosetta Stone was a stone tablet with the same text written in three ancient languages. This gave scholars who understood one of the languages a big boost in deciphering another one that they didn’t understand. Similarly, watermarks tend to be defeated if an adversary can get his hands on a watermarked file, and the same file without the watermark. By comparing the two, the adversary can determine where the watermark lives, which is usually sufficient to remove the watermark from other files. Alex used this method in deciphering the MediaMax watermark (as described in our Sony CD DRM paper), and my colleagues and I used it also in analyzing the SDMI watermarks back in 2000.

Almost as powerful as a Rosetta Stone attack is a comparison attack, where the adversary does not have an unwatermarked file, but does have the same file with several different watermarks in it. Any place where two of the files differ is a place where watermark information lives. Given several marked files, an attacker can locate all or most of the places the watermark is hidden, which is again the first step in removing the watermark.

(In theory it might be possible to stop an adversary with access to a limited number of individually watermarked files from completely removing the watermark, if the watermark has lots of places to hide and is constructed cleverly. There is an interesting body of theory about how to do this and when it works. But in practice the assumptions underlying that theory rarely hold.)

Even if the adversary cannot get access to multiple versions of a file (so that Roseta Stone or comparison attacks are not possible), he can usually still defeat a watermark if he has access to a device that can detect watermarks. By reverse engineering the device, he can figure out where it is looking for the watermark, which again puts him in a position to remove it. (Even if he can’t dissect the device, he can use it as an oracle that tells him whether a particular file has a detectable watermark. Oracles are very helpful in attacking watermarks – Alex used one in his MediaMax watermark analysis, and my colleagues and I used one in our SDMI analysis.)

All of this helps us to understand where watermarks are likely to be effective and where they’re not. The best case for watermarking is where each file is published in a single version, with a watermark in a location that is not disclosed to the public and is not implemented in a device available to the public. This would hold true, for example, in a system that put a distinctive mark into all released versions of a file, and then looked for such watermarks in content broadcast on the radio or TV or downloaded from the net.

Not nearly as strong is a system where there is a single watermark per file, and consumer devices check for the mark – it is subject to reverse engineering and oracle attacks.

Weaker yet is a system where files are watermarked individually for each consumer – it is subject to comparison attacks.

Weakest of all is a system where files are watermarked individually for each consumer and everyone is told how to read the watermarks. Here the adversary can use comparison attacks, and reverse engineering is not even necessary because the inner working of the watermark detector are well known.

Alert readers will have noticed that all of the uses of watermarks for DRM (copy protection) seem to fall into the weak categories. That is because DRM applications require either that all devices check for the watermark – opening up reverse engineering and oracle attacks – or alternatively that a file be given separate watermarks for separate consumers – opening up comparison attacks. Watermarking has its uses, but it doesn’t seem well suited for DRM.

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Mistrust-Based DRM

February 22, 2006 by

Randy Picker has an interesting post on the Chicago Law Faculty blog, describing what he calls “mistrust-based DRM”. The idea is that when an online music store gives you a song, it embeds into the song a watermark that contains your credit card number, or some other information that would let a (dishonest) person spend your money. This gives you an incentive not to distribute the song.

This is an instructive idea, but not a practical one.

In analyzing this idea, it’s helpful to divide it into two pieces: (1) embed a watermark that identifies the user, and (2) make that watermark a secret of the user and readable by the anyone who gets the file. Piece (1), taken alone, is a widely discussed DRM strategy which has not been used much in practice, for reasons I plan to discuss tomorrow. Today, I want to focus on the second piece.

Specifically, I want to compare two systems. In the more traditional system, the watermark is secret – it can be read only by the copyright owner or its agents – and users fear being sued for infringement if their files end up on P2P. In Randy’s system, the watermark is public – anybody can read it – and users fear being victimized by fraud if their files end up on P2P. I’ll call these two alternatives “secret-watermark” and “public-watermark”.

How do they compare? For starters, a secret watermark is much harder for an adversary to find and remove. If a watermark is public, everybody knows exactly where in the music it is stored. Common sense, and experience too, says that if you know where in a file information is stored, you can modify that part of the file and obliterate the information. But if the watermark is secret, then an adversary isn’t told where to look for it or how to change the file to remove it. Robustness of the watermark is an important issue that has been the downfall of past watermark systems.

A bigger problem with the public-watermark design, I think, are the forces unleashed when your design principle is to enable fraud. For example, the system will lose its force if unrelated anti-fraud measures become more effective, or if the financial system acts to protect users from fraud. Today, a consumer’s liability for fraudulent credit card transactions is capped at $50, and credit card companies often forgive even that $50. (You could use some other account information instead of the credit card number, but similar issues would still apply.) Copyright owners would be the only online merchants who wanted a higher level of fraud on the Net.

Worse yet, even law-abiding consumers would face a higher risk of fraud, because any loss or theft of their music or movie files would expose their financial information. Spyware programs could collect this information from users’ computers – and studies show that at least half of end-user PCs are infected with spyware. Law-abiding users would have a strong incentive to scrub the information out of their files, even if they had no intention of infringing. Alert anti-virus or anti-spyware vendors would be eager to provide this service.

Given the disadvantages of a public-watermark scheme, what are the arguments for it? Randy Picker argues that it gives end users an incentive to distrust fly-by-night purveyors of ripping software, worrying that they might steal the user’s information from the files and commit fraud. This isn’t entirely convincing: some such tools already contain heinous spyware that could cause users lots of harm, and reputable security suppliers are likely to provide watermark-scrubbing tools anyway. I think the threat of secret watermarks hidden in files, which fly-by-night vendors have no incentive to remove, would probably scare users enough.

On the whole, then, I think a secret-watermark scheme is better than a public-watermark one. But it should be noted that secret-watermark schemes themselves aren’t looking too good. They have mostly failed in the market, for reasons I’ll start digging into tomorrow.

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Software Security: Creativity in a New Discipline

February 21, 2006 by

This is the last excerpt from my new book, Software Security: Building Security In. This might be a good time to buy the book.

Creativity in a New Discipline

We are experiencing a time of great creativity in computer security and must seize the opportunity presented by our current situation while we can. The diversity of backgrounds represented by today’s security practitioners may be a high-water mark. Consider that today’s security thought leaders were trained in fields as diverse as biostatistics, divinity, economics, and cognitive science, and thus bring with them interesting new perspectives on the security challenge. This leads to creative interplay in the field and has resulted in interesting progress, including the emergence of economic theories of security, an embrace of risk management, an emphasis on process-driven approaches (versus product sets), a shift toward software security, the rise of security engineering, and so on. As the worldwide security paradigm shift from guns, dogs, and concrete to networks, information systems, and computers continues unabated, we must leverage this time of creative diversity for all it’s worth.

A number of young researchers joined the computer security field in the mid-1990s, changing the focus of security research from spookware and national defense (think crypto, multilevel security, communications monitoring, and the like) to commercial systems and commerce. This movement away from military-oriented research was driven in part by the widespread public adoption of the Internet and the growing trend of e-commerce. With money at stake, security quickly became as relevant to business as it was to national defense. This influx of “new blood” shook up the scientific security research community and continues to have far-reaching effects that are only now affecting commercial security—the commercialization of firewalls, the rise of antivirus technology, and the adoption of modern security platforms, such as Java and .NET, were all predicted and spearheaded by new thinkers in the security research community.

Where Today’s Security People Come From

Only a handful of people working in computer security today started their careers in the field. In fact, academic programs expressly designed to train security practitioners are a recent phenomenon and remain rare.

Interestingly, it may be in this dearth of “qualified” people trained in security that a critical opportunity can be found. Though few practitioners have academic security training, they most assuredly do have academic training in some field of study. That means that as a collective, the computer security field is filled with diverse and interesting points of view. This is exactly the sort of Petri dish of ideas that led to the Renaissance at the end of the Dark Ages.

Diversity of ideas is healthy, and it lends a creativity and drive to the security field that we must take advantage of. A great example of this can be found in the new subfield of software security. Only five years ago the notion that bad software might be a major root cause of security issues was not common. Today, software security is the subject of keynote talks at the RSA security conference, and
we all seem to agree that we have a software problem to solve. This change was partially due to the involvement of programming languages people (once found only at obscure academic conferences like OOPSLA) in the security field. Such involvement resulted in the creation of modern languages like Java and .NET that include security models in their very design. When languages are declared “secure,” things get interesting! The evolutionary arms race between attackers and defenders jumps a level, new avenues for security design emerge, and dusty but thorny problems (think “buffer overflow”) become less relevant to the next generation of systems.

Where Tomorrow’s Security People Will Come From

These days, academic and professional training programs are being put in place to train the next generation of security professionals. Soon, standard curricula will be developed, and students will be required to understand the same core set of concepts. This will certainly help to solidify the field of computer security, but at the same time, there is a danger that generalization may lead to a homogenization of security. Instead of the creative soup afforded by a multiplicity of points of view spanning many fields, security runs the risk of becoming staid and static. If we are careful to avoid complete homogenization of the field, we can retain the benefits of diversity while building a solid academic discipline. One way to do this might be to encourage those students seeking computer security degrees to study widely in other supposedly unrelated disciplines as well. Another is to ensure that outside perspectives remain welcome in the field and are not dismissed out of hand. Computer security must remain an inclusive discipline in order to retain its creativity.

In any case, we must take advantage of the situation we find ourselves in now. Computer security is, in fact, experiencing an important rebirth, and now is the time to make great progress. We must pay close attention to different ideas, embrace change, and help security continue to evolve even as it begins to crystallize.

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Software Security: A Case Study

February 17, 2006 by

Here is another excerpt from my new book, Software Security: Building Security In..

An Example: Java Card Security Testing

Doing effective security testing requires experience and knowledge. Examples and case studies like the one I present here are thus useful tools for understanding the approach.

In an effort to enhance payment cards with new functionality—such as the ability to provide secure cardholder identification or remember personal references—many credit-card companies are turning to multi-application smart cards. These cards use resident software applications to process and store thousands of times more information than traditional magnetic-stripe cards.

Security and fraud issues are critical concerns for the financial institutions and merchants spearheading smart-card adoption. By developing and deploying smart-card technology, credit-card companies provide important new tools in the effort to lower fraud and abuse. For instance, smart cards typically use a sophisticated crypto system to authenticate transactions and verify the identities of the cardholder and issuing bank. However, protecting against fraud and maintaining security and privacy are both very complex problems because of the rapidly evolving nature of smart-card technology.

The security community has been involved in security risk analysis and mitigation for Open Platform (now known as Global Platform, or GP) and Java Card since early 1997. Because product security is an essential aspect of credit-card companies’ brand protection regimen, companies like Visa and MasterCard spend plenty of time and effort on security testing and risk analysis. One central finding emphasizes the importance of testing particular vendor implementations according to our two testing categories: adherence to functional security design and proper behavior under particular attacks motivated by security risks.

The latter category, adversarial security testing (linked directly to risk analysis findings), ensures that cards can perform securely in the field even when under attack. Risk analysis results can be used to guide manual security testing. As an example, consider the risk that, as designed, the object-sharing mechanism in Java Card is complex and thus is likely to suffer from security-critical implementation errors on any given manufacturer’s card. Testing for this sort of risk involves creating and manipulating stored objects where sharing is involved. Given a technical description of this risk, building specific probing tests is possible.

Automating Security Testing

Over the years, Cigital has been involved in several projects that have identified architectural risks in the GP/Java Card platform, suggested several design improvements, and designed and built automated security tests for final products (each of which has multiple vendors).

Several years ago, we began developing an automated security test framework for GP cards built on Java Card 2.1.1 and based on extensive risk analysis results. The end result is a sophisticated test framework that runs with minimal human intervention and results in a qualitative security testing analysis of a sample smart card. This automated framework is now in use at MasterCard and the U.S. National Security Agency.

The first test set, the functional security test suite, directly probes low-level card security functionality. It includes automated testing of class codes, available commands, and crypto functionality. This test suite also actively probes for inappropriate card behavior of the sort that can lead to security compromise.

The second test set, the hostile applet test suite, is a sophisticated set of intentionally hostile Java Card applets designed to probe high-risk aspects of the GP on a Java Card implementation.

Results: Nonfunctional Security Testing Is Essential

Most cards tested with the automated test framework (but not all) pass all functional security tests, which we expect because smart-card vendors are diligent with functional testing (including security functionality). Because smart cards are complex embedded devices, vendors realize that exactly meeting functional requirements is an absolute necessity for customers to accept the cards. After all, they must perform properly worldwide.

However, every card submitted to the risk-based testing paradigm exhibited some manner of failure when tested with the hostile applet suite. Some failures pointed directly to critical security vulnerabilities on the card; others were less specific and required further exploration to determine the card’s true security posture.

As an example, consider that risk analysis of Java Card’s design documents indicates that proper implementation of atomic transaction processing is critical for maintaining a secure card. Java Card has the capability of defining transaction boundaries to ensure that if a transaction fails, data roll back to a pre-transaction state. In the event that transaction processing fails, transactions can go into any number of possible states, depending on what the applet was attempting. In the case of a stored-value card, bad transaction processing could allow an attacker to “print money” by forcing the card to roll back value counters while actually purchasing goods or services. This is called a “torn transaction” attack in credit-card risk lingo.

When creating risk-based tests to probe transaction processing, we directly exercised transaction-processing error handling by simulating an attacker attempting to violate a transaction—specifically, transactions were aborted or never committed, transaction buffers were completely filled, and transactions were nested (a no-no according to the Java Card specification). These tests were not based strictly on the card’s functionality—instead, security test engineers intentionally created them, thinking like an attacker given the results of a risk analysis.

Several real-world cards failed subsets of the transaction tests. The vulnerabilities discovered as a result of these tests would allow an attacker to terminate a transaction in a potentially advantageous manner—a critical test failure that wouldn’t have been uncovered under normal functional security testing. Fielding cards with these vulnerabilities would allow an attacker to execute successful attacks on live cards issued to the public. Because of proper risk-based security testing, the vendors were notified of the problems and corrected the code responsible before release.

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Software Security: The Badness-ometer

February 16, 2006 by

Here is another excerpt from my new book, Software Security: Building Security In.

Application Security Tools: Good or Bad?

Application security testing products are being sold as a solution to the problem of insecure software. Unfortunately, these first-generation solutions are not all they are cracked up to be. They may help us diagnose, describe, and demonstrate the problem, but they do little to help us fix it.

Today’s application security products treat software applications as “black boxes” that are prone to misbehave and must be probed and prodded to prevent security disaster. Unfortunately, this approach is too simple.

Software testing requires planning and should be based on software requirements and the architecture of the code under test. You can’t “test quality in” by painstakingly finding and removing bugs once the code is done. The same goes for security; running a handful of canned tests that “simulate malicious hackers” by sending malformed input streams to a program will not work. Real attackers don’t simply “fuzz” a program with input to find problems. Attackers take software apart, determine how it works, and make it misbehave by doing what users are not supposed to do. The essence of the disconnect is that black box testing approaches, including application security testing tools, only scratch the surface of software in an outside→in fashion instead of digging into the guts of software and securing things from the inside.

Badness-ometers

That said, application security testing tools can tell you something about security—namely, that you’re in very deep trouble. That is, if your software fails any of the canned tests, you have some serious security work to do. The tools can help uncover known issues. But if you pass all the tests with flying colors, you know nothing more than that you passed a handful of tests with flying colors.

Put in more basic terms, application security testing tools are “badness-ometers,” as shown in the figure above. They provide a reading in a range from “deep trouble” to “who knows,” but they do not provide a reading into the “security” range at all. Most vulnerabilities that exist in the architecture and the code are beyond the reach of simple canned tests, so passing all the tests is not that reassuring. (Of course, knowing you’re in deep trouble can be helpful!)

The other major weakness with application security testing tools is that they focus only on input to an application provided over port 80. Understanding and testing a complex program by relying only on the protocol it uses to communicate provides a shallow analysis. Though many attacks do arrive via HTTP, this is only one category of security problem. First of all, input arrives to modern applications in many forms other than HTTP: consider SSL, environment variables, outside libraries, distributed components that communicate using other protocols, and so on. Beyond program input, software security must consider architectural soundness, data security, access control, software environment, and any number of other aspects, all of which are dependent on the application itself. There is no set of prefab tests that will probe every possible application in a meaningful way.

The only good use for application security tools is testing commercial off-the-shelf software. Simple dynamic checks set a reasonably low bar to hold vendors to. If software that is delivered to you fails to pass simple tests, you can either reject it out of hand or take steps to monitor its behavior.

In the final analysis, application security testing tools do provide a modicum of value. Organizations that are just beginning to think through software security issues can use them as badness-ometers to help determine how much trouble they are in. Results can alert all the interested parties to the presence of the problem and motivate some mitigation activity. However, you won’t get anything more than a rudimentary analysis with these tools. Fixing the problems they expose requires building better software to begin with—whether you created the software or not.

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