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Research shows that what a food is called affects how we think about it.
Research paper.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Read my blog posting guidelines here.
Stuxnet famously used legitimate digital certificates to sign its malware. A research paper from last year found that the practice is much more common than previously thought.
Now, researchers have presented proof that digitally signed malware is much more common than previously believed. What’s more, it predated Stuxnet, with the first known instance occurring in 2003. The researchers said they found 189 malware samples bearing valid digital signatures that were created using compromised certificates issued by recognized certificate authorities and used to sign legitimate software. In total, 109 of those abused certificates remain valid. The researchers, who presented their findings Wednesday at the ACM Conference on Computer and Communications Security, found another 136 malware samples signed by legitimate CA-issued certificates, although the signatures were malformed.
The results are significant because digitally signed software is often able to bypass User Account Control and other Windows measures designed to prevent malicious code from being installed. Forged signatures also represent a significant breach of trust because certificates provide what’s supposed to be an unassailable assurance to end users that the software was developed by the company named in the certificate and hasn’t been modified by anyone else. The forgeries also allow malware to evade antivirus protections. Surprisingly, weaknesses in the majority of available AV programs prevented them from detecting known malware that was digitally signed even though the signatures weren’t valid.
It’s really hard to estimate the cost of an insecure Internet. Studies are all over the map. A methodical study by RAND is the best work I’ve seen at trying to put a number on this. The results are, well, all over the map:
“Estimating the Global Cost of Cyber Risk: Methodology and Examples“:
Abstract: There is marked variability from study to study in the estimated direct and systemic costs of cyber incidents, which is further complicated by the considerable variation in cyber risk in different countries and industry sectors. This report shares a transparent and adaptable methodology for estimating present and future global costs of cyber risk that acknowledges the considerable uncertainty in the frequencies and costs of cyber incidents. Specifically, this methodology (1) identifies the value at risk by country and industry sector; (2) computes direct costs by considering multiple financial exposures for each industry sector and the fraction of each exposure that is potentially at risk to cyber incidents; and (3) computes the systemic costs of cyber risk between industry sectors using Organisation for Economic Co-operation and Development input, output, and value-added data across sectors in more than 60 countries. The report has a companion Excel-based modeling and simulation platform that allows users to alter assumptions and investigate a wide variety of research questions. The authors used a literature review and data to create multiple sample sets of parameters. They then ran a set of case studies to show the model’s functionality and to compare the results against those in the existing literature. The resulting values are highly sensitive to input parameters; for instance, the global cost of cyber crime has direct gross domestic product (GDP) costs of $275 billion to $6.6 trillion and total GDP costs (direct plus systemic) of $799 billion to $22.5 trillion (1.1 to 32.4 percent of GDP).
Here’s Rand’s risk calculator, if you want to play with the parameters yourself.
Note: I was an advisor to the project.
Separately, Symantec has published a new cybercrime report with their own statistics.
The mating and death characteristics of some squid are fascinating.
Research paper.
EDITED TO ADD (2/5): Additional info and photos.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Read my blog posting guidelines here.
A new vulnerability in WhatsApp has been discovered:
…the researchers unearthed far more significant gaps in WhatsApp’s security: They say that anyone who controls WhatsApp’s servers could effortlessly insert new people into an otherwise private group, even without the permission of the administrator who ostensibly controls access to that conversation.
Matthew Green has a good description:
If all you want is the TL;DR, here’s the headline finding: due to flaws in both Signal and WhatsApp (which I single out because I use them), it’s theoretically possible for strangers to add themselves to an encrypted group chat. However, the caveat is that these attacks are extremely difficult to pull off in practice, so nobody needs to panic. But both issues are very avoidable, and tend to undermine the logic of having an end-to-end encryption protocol in the first place.
Here’s the research paper.
EDITED TO ADD (2/12): Commentary from Moxie Marlinspike, the developer of the protocol.
This is clever:
Researchers at Ben Gurion University in Beer Sheva, Israel have built a proof-of-concept system for counter-surveillance against spy drones that demonstrates a clever, if not exactly simple, way to determine whether a certain person or object is under aerial surveillance. They first generate a recognizable pattern on whatever subject—a window, say—someone might want to guard from potential surveillance. Then they remotely intercept a drone’s radio signals to look for that pattern in the streaming video the drone sends back to its operator. If they spot it, they can determine that the drone is looking at their subject.
In other words, they can see what the drone sees, pulling out their recognizable pattern from the radio signal, even without breaking the drone’s encrypted video.
The details have to do with the way drone video is compressed:
The researchers’ technique takes advantage of an efficiency feature streaming video has used for years, known as “delta frames.” Instead of encoding video as a series of raw images, it’s compressed into a series of changes from the previous image in the video. That means when a streaming video shows a still object, it transmits fewer bytes of data than when it shows one that moves or changes color.
That compression feature can reveal key information about the content of the video to someone who’s intercepting the streaming data, security researchers have shown in recent research, even when the data is encrypted.
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.
Experiments on the oval squid.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Read my blog posting guidelines here.
The security of pretty much every computer on the planet has just gotten a lot worse, and the only real solution—which of course is not a solution—is to throw them all away and buy new ones.
On Wednesday, researchers just announced a series of major security vulnerabilities in the microprocessors at the heart of the world’s computers for the past 15-20 years. They’ve been named Spectre and Meltdown, and they have to do with manipulating different ways processors optimize performance by rearranging the order of instructions or performing different instructions in parallel. An attacker who controls one process on a system can use the vulnerabilities to steal secrets elsewhere on the computer. (The research papers are here and here.)
This means that a malicious app on your phone could steal data from your other apps. Or a malicious program on your computer—maybe one running in a browser window from that sketchy site you’re visiting, or as a result of a phishing attack—can steal data elsewhere on your machine. Cloud services, which often share machines amongst several customers, are especially vulnerable. This affects corporate applications running on cloud infrastructure, and end-user cloud applications like Google Drive. Someone can run a process in the cloud and steal data from every other user on the same hardware.
Information about these flaws has been secretly circulating amongst the major IT companies for months as they researched the ramifications and coordinated updates. The details were supposed to be released next week, but the story broke early and everyone is scrambling. By now all the major cloud vendors have patched their systems against the vulnerabilities that can be patched against.
“Throw it away and buy a new one” is ridiculous security advice, but it’s what US-CERT recommends. It is also unworkable. The problem is that there isn’t anything to buy that isn’t vulnerable. Pretty much every major processor made in the past 20 years is vulnerable to some flavor of these vulnerabilities. Patching against Meltdown can degrade performance by almost a third. And there’s no patch for Spectre; the microprocessors have to be redesigned to prevent the attack, and that will take years. (Here’s a running list of who’s patched what.)
This is bad, but expect it more and more. Several trends are converging in a way that makes our current system of patching security vulnerabilities harder to implement.
The first is that these vulnerabilities affect embedded computers in consumer devices. Unlike our computers and phones, these systems are designed and produced at a lower profit margin with less engineering expertise. There aren’t security teams on call to write patches, and there often aren’t mechanisms to push patches onto the devices. We’re already seeing this with home routers, digital video recorders, and webcams. The vulnerability that allowed them to be taken over by the Mirai botnet last August simply can’t be fixed.
The second is that some of the patches require updating the computer’s firmware. This is much harder to walk consumers through, and is more likely to permanently brick the device if something goes wrong. It also requires more coordination. In November, Intel released a firmware update to fix a vulnerability in its Management Engine (ME): another flaw in its microprocessors. But it couldn’t get that update directly to users; it had to work with the individual hardware companies, and some of them just weren’t capable of getting the update to their customers.
We’re already seeing this. Some patches require users to disable the computer’s password, which means organizations can’t automate the patch. Some antivirus software blocks the patch, or—worse—crashes the computer. This results in a three-step process: patch your antivirus software, patch your operating system, and then patch the computer’s firmware.
The final reason is the nature of these vulnerabilities themselves. These aren’t normal software vulnerabilities, where a patch fixes the problem and everyone can move on. These vulnerabilities are in the fundamentals of how the microprocessor operates.
It shouldn’t be surprising that microprocessor designers have been building insecure hardware for 20 years. What’s surprising is that it took 20 years to discover it. In their rush to make computers faster, they weren’t thinking about security. They didn’t have the expertise to find these vulnerabilities. And those who did were too busy finding normal software vulnerabilities to examine microprocessors. Security researchers are starting to look more closely at these systems, so expect to hear about more vulnerabilities along these lines.
Spectre and Meltdown are pretty catastrophic vulnerabilities, but they only affect the confidentiality of data. Now that they—and the research into the Intel ME vulnerability—have shown researchers where to look, more is coming—and what they’ll find will be worse than either Spectre or Meltdown. There will be vulnerabilities that will allow attackers to manipulate or delete data across processes, potentially fatal in the computers controlling our cars or implanted medical devices. These will be similarly impossible to fix, and the only strategy will be to throw our devices away and buy new ones.
This isn’t to say you should immediately turn your computers and phones off and not use them for a few years. For the average user, this is just another attack method amongst many. All the major vendors are working on patches and workarounds for the attacks they can mitigate. All the normal security advice still applies: watch for phishing attacks, don’t click on strange e-mail attachments, don’t visit sketchy websites that might run malware on your browser, patch your systems regularly, and generally be careful on the Internet.
You probably won’t notice that performance hit once Meltdown is patched, except maybe in backup programs and networking applications. Embedded systems that do only one task, like your programmable thermostat or the computer in your refrigerator, are unaffected. Small microprocessors that don’t do all of the vulnerable fancy performance tricks are unaffected. Browsers will figure out how to mitigate this in software. Overall, the security of the average Internet-of-Things device is so bad that this attack is in the noise compared to the previously known risks.
It’s a much bigger problem for cloud vendors; the performance hit will be expensive, but I expect that they’ll figure out some clever way of detecting and blocking the attacks. All in all, as bad as Spectre and Meltdown are, I think we got lucky.
But more are coming, and they’ll be worse. 2018 will be the year of microprocessor vulnerabilities, and it’s going to be a wild ride.
Note: A shorter version of this essay previously appeared on CNN.com. My previous blog post on this topic contains additional links.
Sidebar photo of Bruce Schneier by Joe MacInnis.