GenSAM is a method for camouflage object detection (COD) that utilizes Cross-modal Chains of Thought Prompting (CCTP) technology to understand visual prompts and leverages general text prompts to obtain reliable visual prompts. The method achieves efficient and accurate camouflage object segmentation through progressive masking generation (PMG) during testing, automatically generating and optimizing visual prompts without additional training.