ForenSift: Gen-AI powered integrated Digital Forensics and Incident Response platform using LangChain Framework

ForenSift brings innovation to the domain of Digital Forensics and Incident Response using Generative AI and the LangChain framework to combat the significant surge in the complexity and volume of digital evidence discovered in cybersecurity investigations. ForenSift deals with key issues in cybersecurity investigation work, specifically time constraints and the need for deep analysis of huge datasets. We have proposed an integrated solution that would automate key parts of the DFIR workflow that ranges from evidence collection, artifact management, anomaly detection, to report generation. ForenSift architecture is based on a strong, evidence-preserving workflow, integrating fully with existing forensic tools but introducing AI-driven analysis capabilities. We have focused on utilisation of Large Language Models (LLMs) together with multi-agent systems at the platform level to notably enhance efficacy and accuracy in DFIR procedures. Concluding, we elaborate on how ForenSift may revolutionize DFIR as it is scalable, combining AI-driven analysis with human expertise. They indicate future possible improvements to be applied in the hybrid system, such as adding a quantum computing machine and blockchain technology to further increase processing speed and maintain data security. This research contributes to the emerging field of AI-enabled cybersecurity by proposing a well-rounded framework that addresses the emerging needs of digital forensic investigations in an increasingly complex threat landscape.