Run an Adversarial-Robustness Audit on a Face-Liveness Model for a Fintech
Overview
What this challenge is about.
Audit a face-liveness model with digital and physical attacks, then propose mitigations and earn your verifiable certificate.
The scenario
The neobank (around 1,200 staff, 2.5 million customers across Germany and Austria) is preparing for a quarterly risk-committee review and wants the audit before any media coverage forces it.
The Brief
What you'll do, and what you'll demonstrate.
Run a structured adversarial-robustness audit of the face-liveness model and propose ranked mitigations for the risk committee.
Earning criteria — what you'll demonstrate
- Implement standard adversarial attacks against vision models
- Design controlled audits that produce comparable results across attacks
- Reason about the gap between digital and physical adversarial attacks
- Communicate model risk to a risk-committee audience
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Adversarial Robustness
Apply adversarial robustness to solve real industry problems and demonstrate production-level capability.
- Face Liveness
Apply face liveness to solve real industry problems and demonstrate production-level capability.
- Pytorch
Apply pytorch to solve real industry problems and demonstrate production-level capability.
- Attack Implementation
Apply attack implementation to solve real industry problems and demonstrate production-level capability.
- Risk Reporting
Apply risk reporting to solve real industry problems and demonstrate production-level capability.
- Mitigation Design
Apply mitigation design to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
AI Safety Researcher
Structured adversarial-robustness audits with risk-committee output are the canonical AI safety researcher deliverable in fintech and identity-product companies.
This challenge sharpens
- adversarial-robustness
- risk-reporting
- mitigation-design
Computer Vision Engineer
Understanding adversarial threat models is increasingly required for CV engineers shipping face or biometric models.
This challenge sharpens
- adversarial-robustness
- face-liveness
- pytorch
Research Scientist
Producing reproducible attack implementations and budget-controlled curves is the kind of research-rigor expected of a junior research scientist.
This challenge sharpens
- adversarial-robustness
- attack-implementation
- pytorch