Anthropic Cloud, Container & AI Infrastructure Security interview questions

The question is really 'what does hostile code have to break to reach the host?' Answer that for each option and the choice follows.

Every layer parses something an attacker wrote, every request costs real money, and tenants share hardware. Walk the path and price each risk.

Assume the code is hostile and design until that stops mattering. Then the interviewer adds a GPU and the internet, and you design again.

One copy is a total loss. The design is about how few places weights exist, how few people can touch them, and whether a bulk copy can leave unnoticed.

Training clusters hold the data and the weights, and run code from hundreds of dependencies. Default-deny egress is the control that holds when everything else is fooled.

An AI request can cost a thousand times more than a web request, so volumetric thinking alone fails. The scored answer layers network, request and cost controls, and protects the GPU tier from ever seeing junk.

The people who build frontier models need access to them, which is exactly the risk. The scored answer reduces who can touch weights directly, makes exfiltration hard and visible, and does it without poisoning research culture.

A framework that ties security investment to attacker capability. The scored answer explains the five levels, why the top ones are qualitatively different, and how labs use the idea.

Weights pass through more systems than most teams draw. The scored answer maps every hop, asks what an attacker could steal or swap at each, and puts integrity checks where they cannot be skipped.

One link-local address hands out the machine's credentials to anything that can make a request from it. That includes a fooled agent with a fetch tool.

The provider secures the model service. Everything you put into it, connect to it and build on top of it is still yours.

Many ML tools assume they run on a trusted network and offer 'run this code' as a feature. Put them on the internet and that feature is remote code execution.

Training jobs need privileged-looking things: device access, big volumes, fast networking. Hardening is about granting exactly those and nothing else.

GPUs were built for throughput, not mutual distrust. Each sharing mode makes a different promise about memory, and some make none.

Containers are a bundle of kernel features, each limiting a different thing. The scored answer explains what each restricts, what it does not, and how to combine them for an untrusted workload.

Managed AI services remove servers, not responsibility. The scored answer covers identity, network, data, model, logging and governance controls that remain the customer's.

A customer model is customer code: loading it can execute anything, and serving it shares expensive hardware. The scored answer isolates execution, scans and constrains artefacts, and keeps tenants apart on GPUs and networks.

An AI system's behaviour lives in more places than its code. The scored answer versions every one of them together, so you can return to a known-good state in minutes after a bad change or a poisoning.

Most cloud breaches start with a setting, not an exploit. The scored answer moves those settings into reviewed code, checks them before deployment, and catches the drift that happens anyway.

Cloud attackers mostly use the same APIs your engineers do. The scored answer collects the right logs, writes detections for attacker behaviour, and keeps the logs out of the attacker's reach.

GPU nodes carry layers most patch programmes forget: drivers, firmware, CUDA libraries and container toolkits. The scored answer inventories them, prioritises by exposure, and patches without breaking month-long training runs.

Serving images bundle a model runtime, GPU libraries and dozens of Python packages. The scored answer controls what goes in, proves where it came from, and admits only verified images to production.

Sending prompts to a provider is a data flow like any other. The scored answer keeps it on private paths where possible, forces all model traffic through one controlled exit, and blocks everything else.

GPU hosts attract cryptominers and hold valuable weights and data. The scored answer contains without destroying evidence, scopes across the fleet, and rebuilds rather than cleans.