  Safety filters ensure that only safe control actions are executed. We propose
a simple and stealthy false-data injection attack for deactivating such safety
filters; in particular, we focus on deactivating safety filters that are based
on control-barrier functions. The attack injects false sensor measurements to
bias state estimates to the interior of a safety region, which makes the safety
filter accept unsafe control actions. To detect such attacks, we also propose a
detector that detects biases manufactured by the proposed attack policy, which
complements conventional detectors when safety filters are used. The proposed
attack policy and detector are illustrated on a double integrator example.
