Comments (5)
Hi! This is indeed an expected behavior for types that implement the Copy
trait, for which dropping the value won't zeroize
the original memory.
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So, clearing the original memory doesn't matter because STARKs don't have a trapdoor?
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I am not sure to understand your sentence.
This library is intended to provide a mid-level API of elliptic curve operations over a specific curve. If you intend to use it (which I don't recommend by the way as it is unmaintained, unless it is for academic/educative purposes), in a context where Scalar
values have to remain secret, you can use a wrapper that doesn't implement Copy
, and will properly wipe-out memory on drop
.
from cheetah.
I am not sure to understand your sentence.
This library is intended to provide a mid-level API of elliptic curve operations over a specific curve. If you intend to use it (which I don't recommend by the way as it is unmaintained, unless it is for academic/educative purposes), in a context whereScalar
values have to remain secret, you can use a wrapper that doesn't implementCopy
, and will properly wipe-out memory ondrop
.
As the description says that Cheetah is STARK friendly, I am just saying STARK has no trapdoor unlike traditional Cryptography which has a trapdoor in keys, signatures, etc. So, Scalar implements the Copy trait.
Yeah, if someone prefers to use Scalar as a secret, they can wrap the limb array with Box. But, this must be mentioned somewhere.
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The zeroize
crate is already fairly well documented on what guarantees it provides and which situations that may leave unwanted copies of your data in memory. If you want to use a higher-level abstraction, you can use the secrecy
crate. Again, while you mention STARKs, this library is solely intended to provide on its own support for elliptic curve operations over the so-called Cheetah
curve. It is not the purpose of this library, or any library for what it's worth, to describe the behavior of all its internal dependencies.
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Related Issues (17)
- Speed-up scalar multiplication in the group HOT 2
- Investigate inline assembly
- Add w-NAF scalar multiplication
- Lookup tables with AffinePoint for Projective scalar multiplication
- Use towered extension internally HOT 2
- Bring back Montgomery form?
- Add custom implementation of double() and square() HOT 1
- Generalization of Shamir's trick for N points HOT 1
- Faster Fp^6 square root HOT 1
- Custom squaring in Fp HOT 1
- Custom implementation of group operations
- Faster squaring in Fp HOT 1
- Pacify clippy HOT 1
- Integrate conditional winterfell-related feature? HOT 1
- Add hashing to curve
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