Slope failures have been traditionally detected by field inspection and aerial-photo interpretation. These approaches are generally insufficient to identify subtle landforms, especially those generated during the early stages of failures, and particularly where the site is located in forested and remote terrains. We present the identification and characterization of several large and medium size slope failures previously undetected within the Orri massif, Central Pyrenees. Around 130 scarps were interpreted as being part of Rock Slope Failures (RSFs), while other smaller and more superficial failures were interpreted as complex movements combining colluvium slow flow/slope creep and RSFs. Except for one of them, these slope failures had not been previously detected, albeit they extend across a 15% of the studied region. The failures were identified through the analysis of a high-resolution (1m) LIDAR-derived bare earth Digital Elevation Model (DEM). Most of the scarps are undetectable either by fieldwork, photo interpretation or 5m resolution topography analysis owing to their small heights (0.5 to 2m) and their location within forest areas. In many cases, these landforms are not evident in the field due to the presence of other minor irregularities in the slope and the lack of open views due to the forest. 2D and 3D visualization of hillshade maps with different sun azimuths provided an overall picture of the scarp assemblage and permitted a more complete analysis of the geometry of the scarps with respect to the slope and the structural fabric. The sharpness of some of the landforms suggests ongoing activity, which should be explored in future detailed studies in order to assess potential hazards affecting the Portainé ski resort. Our results reveal that close analysis of the 1m LIDAR-derived DEM can significantly help to detect early-stage slope deformations in high mountain regions, and that expert judgment of the DEM is essential when dealing with subtle landforms. The incorporation of this approach in regional mapping represents a great advance in completing the catalogue of slope failures and will eventually contribute to a better understanding of the spatial factors controlling them.