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Google: Software is never going to be able to fix Spectre-type bugs

Google: Software is never going to be able to fix Spectre-type bugs

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Researchers from Google investigating the scope and impact of the Spectre attack have published a paper asserting that Spectre-like vulnerabilities are likely to be a continued feature of processors and, further, that software-based techniques for protecting against them will both impose a high performance cost. In any case, the researchers continue, the software will be inadequate—some Spectre flaws don't appear to have any effective software-based defense. As such, Spectre is going to be a continued feature of the computing landscape, with no straightforward resolution.

The discovery and development of the Meltdown and Spectre attacks was undoubtedly the big security story of 2018. First revealed last January, new variants and related discoveries were made throughout the rest of the year. Both attacks rely on discrepancies between the theoretical architectural behavior of a processor—the documented behavior that programmers depend on and write their programs against—and the real behavior of implementations.

Specifically, modern processors all perform speculative execution; they make assumptions about, for example, a value being read from memory or whether an if condition is true or false, and they allow their execution to run ahead based on these assumptions. If the assumptions are correct, the speculated results are kept; if it isn't, the speculated results are discarded and the processor redoes the calculation. Speculative execution is not an architectural feature of the processor; it's a feature of implementations, and so it's supposed to be entirely invisible to running programs. When the processor discards the bad speculation, it should be as if the speculation never even happened.

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New Spectre attack enables secrets to be leaked over a network

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When the Spectre and Meltdown attacks were disclosed earlier this year, the initial exploits required an attacker to be able to run code of their choosing on a victim system. This made browsers vulnerable, as suitably crafted JavaScript could be used to perform Spectre attacks. Cloud hosts were susceptible, too. But outside these situations, the impact seemed relatively limited.

That impact is now a little larger. Researchers from Graz University of Technology, including one of the original Meltdown discoverers, Daniel Gruss, have described NetSpectre: a fully remote attack based on Spectre. With NetSpectre, an attacker can remotely read the memory of a victim system without running any code on that system.

All the variants of the Spectre attacks follow a common set of principles. Each processor has an architectural behavior (the documented behavior that describes how the instructions work and that programmers depend on to write their programs) and a microarchitectural behavior (the way an actual implementation of the architecture behaves). These can diverge in subtle ways. For example, architecturally, a program that loads a value from a particular address in memory will wait until the address is known before trying to perform the load. Microarchitecturally, however, the processor might try to speculatively guess at the address so that it can start loading the value from memory (which is slow) even before it's absolutely certain of which address it should use.

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New Spectre-like attack uses speculative execution to overflow buffers

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When the Spectre and Meltdown attacks were disclosed earlier this year, the expectation was that these attacks would be the first of many, as researchers took a closer look at the way that the speculative execution in modern processors could be used to leak sensitive information and undermine the security of software running on those processors. In May, we saw the speculative store bypass, and today we have a new variant on this theme: speculative buffer overflows, discovered by Vladimir Kiriansky at MIT and independent researcher Carl Waldspurger.

All the attacks follow a common set of principles. Each processor has an architectural behavior (the documented behavior that describes how the instructions work and that programmers depend on to write their programs) and a microarchitectural behavior (the way an actual implementation of the architecture behaves). These can diverge in subtle ways. For example, architecturally, a program that loads a value from a particular address in memory will wait until the address is known before trying to perform the load. Microarchitecturally, however, the processor might try to speculatively guess at the address so that it can start loading the value from memory (which is slow) even before it's absolutely certain of which address it should use.

If the processor guesses wrong, it will ignore the guessed-at value and perform the load again, this time with the correct address. The architecturally defined behavior is thus preserved. But that faulty guess will disturb other parts of the processor—in particular the contents of the cache. These microarchitectural disturbances can be detected and measured, allowing a malicious program to make inferences about the values stored in memory.

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Hyperthreading under scrutiny with new TLBleed crypto key leak

Enlarge / A shiny wafer full of Kaby Lake refresh parts. (credit: Intel)

Last week, developers on OpenBSD—the open-source operating system that prioritizes security—disabled hyperthreading on Intel processors. Project leader Theo de Raadt said that a research paper due to be presented at Black Hat in August prompted the change, but he would not elaborate further.

The situation has since become a little clearer. The Register reported on Friday that researchers at Vrije Universiteit Amsterdam in the Netherlands have found a new side-channel vulnerability on hyperthreaded processors that's been dubbed TLBleed. The vulnerability means that processes that share a physical core—but which are using different logical cores—can inadvertently leak information to each other.

In a proof of concept, researchers ran a program calculating cryptographic signatures using the Curve 25519 EdDSA algorithm implemented in libgcrypt on one logical core and their attack program on the other logical core. The attack program could determine the 256-bit encryption key used to calculate the signature with a combination of two milliseconds of observation, followed by 17 seconds of machine-learning-driven guessing and a final fraction of a second of brute-force guessing.

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