Nano-seismic Monitoring (NM) techniques can be used to detect extremely low signals (ML >-4.0) generated by active subsurface instabilities around shallow cavities. The data is acquired by portable sparse seismic arrays, which are deployed as close as possible to a presumed zone of instability. Events detection is carried out by semi-automated pattern recognition-supported schemes that scan for broad-band energy spikes within continuous data records sampled at 200 to 500 Hz. The authenticity of source signals is verified by true-scale simulation in the field. Comprehensive waveform characterization process includes full-spectral analysis, 3-D source location, waveform cross correlation and source magnitude evaluation. In this paper, we present the application of NM techniques to the detection of incipient instabilities around shallow caverns excavated in soft and homogenous chalk. We present laboratory results, field calibration and field monitoring data of both active and inactive failure processes.