Impact

Due to a non-constant-time implementation, information about the private key is leaked through timing information which is observable over the network. An attacker may be able to use that information to recover the key.

Patches

No patch is yet available, however work is underway to migrate to a fully constant-time implementation.

Workarounds

The only currently available workaround is to avoid using the rsa crate in settings where attackers are able to observe timing information, e.g. local use on a non-compromised computer is fine.

References

This vulnerability was discovered as part of the "Marvin Attack", which revealed several implementations of RSA including OpenSSL had not properly mitigated timing sidechannel attacks.

Timing variability of any kind is problematic when working with potentially secret values such as elliptic curve scalars, and such issues can potentially leak private keys and other secrets. Such a problem was recently discovered in curve25519-dalek.

The Scalar29::sub (32-bit) and Scalar52::sub (64-bit) functions contained usage of a mask value inside a loop where LLVM saw an opportunity to insert a branch instruction (jns on x86) to conditionally bypass this code section when the mask value is set to zero as can be seen in godbolt:

• 32-bit (see L106): https://godbolt.org/z/zvaWxzvqv
• 64-bit (see L48): https://godbolt.org/z/PczYj7Pda

A similar problem was recently discovered in the Kyber reference implementation:

https://groups.google.com/a/list.nist.gov/g/pqc-forum/c/hqbtIGFKIpU/m/cnE3pbueBgAJ

As discussed on that thread, one portable solution, which is also used in this PR, is to introduce a volatile read as an optimization barrier, which prevents the compiler from optimizing it away.

The fix can be validated in godbolt here:

• 32-bit: https://godbolt.org/z/jc9j7eb8E
• 64-bit: https://godbolt.org/z/x8d46Yfah

The problem was discovered and the solution independently verified by Alexander Wagner [email protected] and Lea Themint [email protected] using their DATA tool:

https://github.com/Fraunhofer-AISEC/DATA