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AI Security
Practice tests · 43 items

Software, Data & Model Supply Chain practice test

Code and model provenance, dependency analysis (SCA), secret scanning and CI/CD security. Review build authority, artifact promotion, infrastructure evidence and verified repairs across the software, data and model supply chain. The pool for this topic holds 11 easy, 20 medium and 12 hard items. Each answer comes with its reasoning and a link to the question or concept page it was drawn from.

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11 in this pool · about 7 min
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Sample items with answers

easy · sample
What does a valid signature on a software release actually prove?
The code has been reviewed and contains no malware
✓The file is unchanged since someone holding the signing key signed it
The binary was compiled from exactly the source code published in the public repository
The publisher's build servers were not compromised at the time the release was produced

A signature binds a hash of the artifact to a key. It proves integrity and origin: these exact bytes were signed by that key holder. It says nothing about whether the code is safe, how it was built, or whether the signer was compromised.

easy · sample
Why do model hubs push safetensors over pickle-based checkpoints?
✓A safetensors file holds a header and raw tensor bytes, so loading it runs no code
Safetensors files are encrypted
Safetensors compresses weights to roughly half the size of the equivalent pickle file
Safetensors embeds a signature from the hub that the loader checks before reading

Pickle is a small program the unpickler executes, and it can call arbitrary functions, so a pickle checkpoint is untrusted code. Safetensors is a JSON header plus raw buffers, parsed rather than executed. It removes code execution at load time; it does not prove where the weights came from.

After the test

Choosing from options is easier than reasoning it out in front of a panel. These pages make you reason it out: