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TPM-Fail Attacks Against Cryptographic Coprocessors

Really interesting research: TPM-FAIL: TPM meets Timing and Lattice Attacks, by Daniel Moghimi, Berk Sunar, Thomas Eisenbarth, and Nadia Heninger.

Abstract: Trusted Platform Module (TPM) serves as a hardware-based root of trust that protects cryptographic keys from privileged system and physical adversaries. In this work, we per-form a black-box timing analysis of TPM 2.0 devices deployed on commodity computers. Our analysis reveals that some of these devices feature secret-dependent execution times during signature generation based on elliptic curves. In particular, we discovered timing leakage on an Intel firmware-based TPM as well as a hardware TPM. We show how this information allows an attacker to apply lattice techniques to recover 256-bit private keys for ECDSA and ECSchnorr signatures. On Intel fTPM, our key recovery succeeds after about1,300 observations and in less than two minutes. Similarly, we extract the private ECDSA key from a hardware TPM manufactured by STMicroelectronics, which is certified at CommonCriteria (CC) EAL 4+, after fewer than 40,000 observations. We further highlight the impact of these vulnerabilities by demonstrating a remote attack against a StrongSwan IPsecVPN that uses a TPM to generate the digital signatures for authentication. In this attack, the remote client recovers the server’s private authentication key by timing only 45,000 authentication handshakes via a network connection.

The vulnerabilities we have uncovered emphasize the difficulty of correctly implementing known constant-time techniques, and show the importance of evolutionary testing and transparent evaluation of cryptographic implementations.Even certified devices that claim resistance against attacks require additional scrutiny by the community and industry, as we learn more about these attacks.

These are real attacks, and take between 4-20 minutes to extract the key. Intel has a firmware update.

Attack website. News articles. Boing Boing post. Slashdot thread.

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Friday Squid Blogging: Triassic Kraken

Research paper: “Triassic Kraken: The Berlin Ichthyosaur Death Assemblage Interpreted as a Giant Cephalopod Midden“:

Abstract: The Luning Formation at Berlin Ichthyosaur State Park, Nevada, hosts a puzzling assemblage of at least 9 huge (≤14 m) juxtaposed ichthyosaurs (Shonisaurus popularis). Shonisaurs were cephalopod eating predators comparable to sperm whales (Physeter). Hypotheses presented to explain the apparent mass mortality at the site have included: tidal flat stranding, sudden burial by slope failure, and phytotoxin poisoning. Citing the wackestone matrix, J. A. Holger argued convincingly for a deeper water setting, but her phytotoxicity hypothesis cannot explain how so many came to rest at virtually the same spot. Skeletal articulation indicates that animals were deposited on the sea floor shortly after death. Currents or other factors placed them in a north south orientation. Adjacent skeletons display different taphonomic histories and degrees of disarticulation, ruling out catastrophic mass death, but allowing a scenario in which dead ichthyosaurs were sequentially transported to a sea floor midden. We hypothesize that the shonisaurs were killed and carried to the site by an enormous Triassic cephalopod, a “kraken,” with estimated length of approximately 30 m, twice that of the modern Colossal Squid Mesonychoteuthis. In this scenario, shonisaurs were ambushed by a Triassic kraken, drowned, and dumped on a midden like that of a modern octopus. Where vertebrae in the assemblage are disarticulated, disks are arranged in curious linear patterns with almost geometric regularity. Close fitting due to spinal ligament contraction is disproved by the juxtaposition of different-sized vertebrae from different parts of the vertebral column. The proposed Triassic kraken, which could have been the most intelligent invertebrate ever, arranged the vertebral discs in biserial patterns, with individual pieces nesting in a fitted fashion as if they were part of a puzzle. The arranged vertebrae resemble the pattern of sucker discs on a cephalopod tentacle, with each amphicoelous vertebra strongly resembling a coleoid sucker. Thus the tessellated vertebral disc pavement may represent the earliest known self portrait. The submarine contest between cephalopods and seagoing tetrapods has a long history. A Triassic kraken would have posed a deadly risk for shonisaurs as they dove in pursuit of their smaller cephalopod prey.

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.

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Mapping Security and Privacy Research across the Decades

This is really interesting: “A Data-Driven Reflection on 36 Years of Security and Privacy Research,” by Aniqua Baset and Tamara Denning:

Abstract: Meta-research—research about research—allows us, as a community, to examine trends in our research and make informed decisions regarding the course of our future research activities. Additionally, overviews of past research are particularly useful for researchers or conferences new to the field. In this work we use topic modeling to identify topics within the field of security and privacy research using the publications of the IEEE Symposium on Security & Privacy (1980-2015), the ACM Conference on Computer and Communications Security (1993-2015), the USENIX Security Symposium (1993-2015), and the Network and Distributed System Security Symposium (1997-2015). We analyze and present data via the perspective of topics trends and authorship. We believe our work serves to contextualize the academic field of computer security and privacy research via one of the first data-driven analyses. An interactive visualization of the topics and corresponding publications is available at https://secprivmeta.net.

I like seeing how our field has morphed over the years.

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Using Machine Learning to Detect IP Hijacking

This is interesting research:

In a BGP hijack, a malicious actor convinces nearby networks that the best path to reach a specific IP address is through their network. That’s unfortunately not very hard to do, since BGP itself doesn’t have any security procedures for validating that a message is actually coming from the place it says it’s coming from.

[…]

To better pinpoint serial attacks, the group first pulled data from several years’ worth of network operator mailing lists, as well as historical BGP data taken every five minutes from the global routing table. From that, they observed particular qualities of malicious actors and then trained a machine-learning model to automatically identify such behaviors.

The system flagged networks that had several key characteristics, particularly with respect to the nature of the specific blocks of IP addresses they use:

  • Volatile changes in activity: Hijackers’ address blocks seem to disappear much faster than those of legitimate networks. The average duration of a flagged network’s prefix was under 50 days, compared to almost two years for legitimate networks.

  • Multiple address blocks: Serial hijackers tend to advertise many more blocks of IP addresses, also known as “network prefixes.”

  • IP addresses in multiple countries: Most networks don’t have foreign IP addresses. In contrast, for the networks that serial hijackers advertised that they had, they were much more likely to be registered in different countries and continents.

Note that this is much more likely to detect criminal attacks than nation-state activities. But it’s still good work.

Academic paper.

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Factoring 2048-bit Numbers Using 20 Million Qubits

This theoretical paper shows how to factor 2048-bit RSA moduli with a 20-million qubit quantum computer in eight hours. It’s interesting work, but I don’t want overstate the risk.

We know from Shor’s Algorithm that both factoring and discrete logs are easy to solve on a large, working quantum computer. Both of those are currently beyond our technological abilities. We barely have quantum computers with 50 to 100 qubits. Extending this requires advances not only in the number of qubits we can work with, but in making the system stable enough to read any answers. You’ll hear this called “error rate” or “coherence” — this paper talks about “noise.”

Advances are hard. At this point, we don’t know if they’re “send a man to the moon” hard or “faster-than-light travel” hard. If I were guessing, I would say they’re the former, but still harder than we can accomplish with our current understanding of physics and technology.

I write about all this generally, and in detail, here. (Short summary: Our work on quantum-resistant algorithms is outpacing our work on quantum computers, so we’ll be fine in the short run. But future theoretical work on quantum computing could easily change what “quantum resistant” means, so it’s possible that public-key cryptography will simply not be possible in the long run. That’s not terrible, though; we have a lot of good scalable secret-key systems that do much the same things.)

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More Cryptanalysis of Solitaire

In 1999, I invented the Solitaire encryption algorithm, designed to manually encrypt data using a deck of cards. It was written into the plot of Neal Stephenson’s novel Cryptonomicon, and I even wrote an afterward to the book describing the cipher.

I don’t talk about it much, mostly because I made a dumb mistake that resulted in the algorithm not being reversible. Still, for the short message lengths you’re likely to use a manual cipher for, it’s still secure and will likely remain secure.

Here’s some new cryptanalysis:

Abstract: The Solitaire cipher was designed by Bruce Schneier as a plot point in the novel Cryptonomicon by Neal Stephenson. The cipher is intended to fit the archetype of a modern stream cipher whilst being implementable by hand using a standard deck of cards with two jokers. We find a model for repetitions in the keystream in the stream cipher Solitaire that accounts for the large majority of the repetition bias. Other phenomena merit further investigation. We have proposed modifications to the cipher that would reduce the repetition bias, but at the cost of increasing the complexity of the cipher (probably beyond the goal of allowing manual implementation). We have argued that the state update function is unlikely to lead to cycles significantly shorter than those of a random bijection.

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On Cybersecurity Insurance

Good paper on cybersecurity insurance: both the history and the promise for the future. From the conclusion:

Policy makers have long held high hopes for cyber insurance as a tool for improving security. Unfortunately, the available evidence so far should give policymakers pause. Cyber insurance appears to be a weak form of governance at present. Insurers writing cyber insurance focus more on organisational procedures than technical controls, rarely include basic security procedures in contracts, and offer discounts that only offer a marginal incentive to invest in security. However, the cost of external response services is covered, which suggests insurers believe ex-post responses to be more effective than ex-ante mitigation. (Alternatively, they can more easily translate the costs associated with ex-post responses into manageable claims.)

The private governance role of cyber insurance is limited by market dynamics. Competitive pressures drive a race-to-the-bottom in risk assessment standards and prevent insurers including security procedures in contracts. Policy interventions, such as minimum risk assessment standards, could solve this collective action problem. Policy-holders and brokers could also drive this change by looking to insurers who conduct rigorous assessments. Doing otherwise ensures adverse selection and moral hazard will increase costs for firms with responsible security postures. Moving toward standardised risk assessment via proposal forms or external scans supports the actuarial base in the long-term. But there is a danger policyholders will succumb to Goodhart’s law by internalising these metrics and optimising the metric rather than minimising risk. This is particularly likely given these assessments are constructed by private actors with their own incentives. Search-light effects may drive the scores towards being based on what can be measured, not what is important.

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Attacking the Intel Secure Enclave

Interesting paper by Michael Schwarz, Samuel Weiser, Daniel Gruss. The upshot is that both Intel and AMD have assumed that trusted enclaves will run only trustworthy code. Of course, that’s not true. And there are no security mechanisms that can deal with malicious enclaves, because the designers couldn’t imagine that they would be necessary. The results are predictable.

The paper: “Practical Enclave Malware with Intel SGX.”

Abstract: Modern CPU architectures offer strong isolation guarantees towards user applications in the form of enclaves. For instance, Intel’s threat model for SGX assumes fully trusted enclaves, yet there is an ongoing debate on whether this threat model is realistic. In particular, it is unclear to what extent enclave malware could harm a system. In this work, we practically demonstrate the first enclave malware which fully and stealthily impersonates its host application. Together with poorly-deployed application isolation on personal computers, such malware can not only steal or encrypt documents for extortion, but also act on the user’s behalf, e.g., sending phishing emails or mounting denial-of-service attacks. Our SGX-ROP attack uses new TSX-based memory-disclosure primitive and a write-anything-anywhere primitive to construct a code-reuse attack from within an enclave which is then inadvertently executed by the host application. With SGX-ROP, we bypass ASLR, stack canaries, and address sanitizer. We demonstrate that instead of protecting users from harm, SGX currently poses a security threat, facilitating so-called super-malware with ready-to-hit exploits. With our results, we seek to demystify the enclave malware threat and lay solid ground for future research on and defense against enclave malware.

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