CRISPR/Cas-based nucleic acid detection systems have become essential tools in molecular diagnostics and biosensing. These systems utilize various CRISPR/Cas proteins (e.g., Cas9, Cas12, Cas13, Cas14, and Cas3) to detect and differentiate nucleic acids with high specificity. They are often combined with amplification techniques like PCR, LAMP, and RPA to enhance sensitivity and detection capabilities. CRISPR/Cas-based biosensors are used for detecting viral and bacterial pathogens in clinical samples, as well as in life sciences applications such as biosecurity, food safety, and environmental monitoring. These systems offer improved specificity compared to traditional molecular diagnostic methods. This review discusses various CRISPR/Cas-based nucleic acid detection methods, highlighting their development, components, and operational challenges. It also addresses the advantages and disadvantages of different systems, emphasizing the need for further improvements in CRISPR/Cas-based nucleic acid testing. CRISPR/Cas9-based methods include techniques like NASBACC, CAS-EXPAR, FELUDA, and CASLFA, which utilize CRISPR/Cas9 for nucleic acid detection with high sensitivity and specificity. dCas9-based systems, such as DNA-FISH and CRISPR-Chip, use dCas9 for detection without cleavage. Pair Cas9-based systems, like ctPCR and CARP, offer improved detection capabilities. CRISPR/Cas12-based methods, including DETECTR, OR-DETECTR, and E-CRISPR, provide high sensitivity and rapid detection. CRISPR/Cas13-based systems, such as SHERLOCK and SHERLOCKv2, are effective for RNA detection with high specificity. CRISPR/Cas3-based methods, like CONAN, are suitable for point-of-care testing. CRISPR/Cas14-based systems, such as Cas14-DETECTR, offer unique advantages in detecting nucleic acids. Despite their advantages, CRISPR/Cas-based systems face challenges such as high background noise, potential off-target detection, and reliance on fluorescence labels. These systems have the potential to address limitations of traditional molecular diagnostic techniques, offering lower cost, simpler procedures, and faster detection. However, further optimization is needed for widespread commercialization.CRISPR/Cas-based nucleic acid detection systems have become essential tools in molecular diagnostics and biosensing. These systems utilize various CRISPR/Cas proteins (e.g., Cas9, Cas12, Cas13, Cas14, and Cas3) to detect and differentiate nucleic acids with high specificity. They are often combined with amplification techniques like PCR, LAMP, and RPA to enhance sensitivity and detection capabilities. CRISPR/Cas-based biosensors are used for detecting viral and bacterial pathogens in clinical samples, as well as in life sciences applications such as biosecurity, food safety, and environmental monitoring. These systems offer improved specificity compared to traditional molecular diagnostic methods. This review discusses various CRISPR/Cas-based nucleic acid detection methods, highlighting their development, components, and operational challenges. It also addresses the advantages and disadvantages of different systems, emphasizing the need for further improvements in CRISPR/Cas-based nucleic acid testing. CRISPR/Cas9-based methods include techniques like NASBACC, CAS-EXPAR, FELUDA, and CASLFA, which utilize CRISPR/Cas9 for nucleic acid detection with high sensitivity and specificity. dCas9-based systems, such as DNA-FISH and CRISPR-Chip, use dCas9 for detection without cleavage. Pair Cas9-based systems, like ctPCR and CARP, offer improved detection capabilities. CRISPR/Cas12-based methods, including DETECTR, OR-DETECTR, and E-CRISPR, provide high sensitivity and rapid detection. CRISPR/Cas13-based systems, such as SHERLOCK and SHERLOCKv2, are effective for RNA detection with high specificity. CRISPR/Cas3-based methods, like CONAN, are suitable for point-of-care testing. CRISPR/Cas14-based systems, such as Cas14-DETECTR, offer unique advantages in detecting nucleic acids. Despite their advantages, CRISPR/Cas-based systems face challenges such as high background noise, potential off-target detection, and reliance on fluorescence labels. These systems have the potential to address limitations of traditional molecular diagnostic techniques, offering lower cost, simpler procedures, and faster detection. However, further optimization is needed for widespread commercialization.