Malware’s unrelenting boom and developing complexity offer critical boundaries to IT systems’ safety. Effective intrusion detection and prevention systems are vital to countering this hazard. In order to beautify contemporary systems, this research article gives a modern malware detection programme that integrates present day technologies along with device getting to know, behavioural evaluation, and signature-based detection. In navigating the cutting-edge terrain of malware assaults, the thing highlights the significance of proactive defence tactics. The layout and implementation of the proposed utility are defined extensive, after which its effectiveness is classed the usage of tremendous overall performance metrics and real-world checking out scenarios. Keywords: cybersecurity, machine learning, behavioural analysis, signature-based totally detection, intrusion detection, prevention, and malware detection. The consequences spotlight how essential a malware detection programme is to strengthening IT security. The document analyses the existing state of malware threats and intrusion detection and prevention structures through a thorough exam of the literature. The software’s design and execution are covered by way of the look at technique, which sheds mild on its beneficial functions. The efficacy of the programme is evaluated using performance signs together with fake positives, response time, and detection fee. Real-world trying out is used to in addition validate the utility’s abilties. This take a look at adds to the continuing conversation about cybersecurity by offering a thorough technique of malware detection that is in step with the ever-converting nature of cutting-edge threats. Keywords: cybersecurity, gadget studying, behavioural evaluation, signature-based detection, intrusion detection, prevention, and malware detection.