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0 pointsbiosboiii1y ago0 comments

But then you could compromise the GPU, probably :)

Look at the bootloader, can you open a console?

If not, can you desolder the flash and read the key?

If not, can you access the bootloader when the flash is not detected anymore?

...

Can you solder off the capacitors and glitch the power line, to do a [Voltage Fault Injection](https://www.synacktiv.com/en/publications/how-to-voltage-fau...)?

Can you solder a shunt resistor to the power line, observe the fluctuations and do [Power analysis](https://en.wikipedia.org/wiki/Power_analysis)?

There are a lot of doors and every time someone closes them a window remains tilted.

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bangaladore1y ago

Any company serious about building silicon that has keys, wouldn't just be storing them in flash.

Try getting a private key off a TPM. There have been novel attacks, but they are few and far between.

Try getting a key from Apple's trusted enclave (or whatever buzz-word they call it).

biosboiiiOP1y ago

You're right about the TPM, I won't get the key out of it. It's a special ASIC which doesn't even have the silicon gates to give me the key.

But is the TPM doing matrix-mulitiplication at 1.3 Petaflops?

Or are you just sending the encrypted file to the TPM, getting the unencrypted file back from it, which I can intercept, be it on SPI or by gaining higher privileges on the core itself? Just like with this app but down lower?

Whatever core executes the multiplications will be vulnerable by some way or the other, for an motivated attacker which has the proper resources. This is true for every hardware device, but the attack vector of someone jailbreaking a Nintendo Switch by using a electron microscope and a ion-beam miller is neglectable.

If you are that paranoid about AI models being stolen, they are worth it, so some attacker will have enough motivation to power through.

Stealing the private key out of a GPU which allows you steal a lot of valuable AI models is break-once-break-everywhere.

Apple trusted enclave is also just a TPM with other branding, or maybe a HSM dunno.

bangaladore1y ago

I'll concede you are correct that whether the key is extractable or not doesn't really matter if the GPU eventually will eventually need to store the decrypted model in memory.

However, if NVidia or similar was serious about securing these models, I'd be pretty sure they could integrate the crypto in hardware multipliers / etc such that the model doesn't need to be decrypted anywhere in memory.

But at this point there isn't much value in deploying models to the edge. Particularly the type of models they would really want to protect as they are too large.

The types of models deployed to edge devices (like the Apple ones) are generally quite small and frankly not too difficult (computationally) to reimplement.

j / k navigate · click thread line to collapse

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bangaladore1y ago

Any company serious about building silicon that has keys, wouldn't just be storing them in flash.

Try getting a private key off a TPM. There have been novel attacks, but they are few and far between.

Try getting a key from Apple's trusted enclave (or whatever buzz-word they call it).

biosboiiiOP1y ago

You're right about the TPM, I won't get the key out of it. It's a special ASIC which doesn't even have the silicon gates to give me the key.

But is the TPM doing matrix-mulitiplication at 1.3 Petaflops?

If you are that paranoid about AI models being stolen, they are worth it, so some attacker will have enough motivation to power through.

Stealing the private key out of a GPU which allows you steal a lot of valuable AI models is break-once-break-everywhere.

Apple trusted enclave is also just a TPM with other branding, or maybe a HSM dunno.

bangaladore1y ago

I'll concede you are correct that whether the key is extractable or not doesn't really matter if the GPU eventually will eventually need to store the decrypted model in memory.

But at this point there isn't much value in deploying models to the edge. Particularly the type of models they would really want to protect as they are too large.

The types of models deployed to edge devices (like the Apple ones) are generally quite small and frankly not too difficult (computationally) to reimplement.

j / k navigate · click thread line to collapse