The field of cybersecurity and reverse engineering is rapidly evolving, with a growing focus on proactive mitigation of phishing campaigns and the application of Large Language Models (LLMs) to improve software security. Recent developments have seen the introduction of adaptive multi-agent systems, such as PhishLumos, which can identify entire attack campaigns before they are confirmed by cybersecurity experts. LLMs are also being used to enhance reverse engineering tasks, including binary decompilation and vulnerability detection. Notable papers in this area include PhishLumos, which demonstrated a 100% success rate in identifying phishing campaigns, and SK2Decompile, which achieved a 21.6% average re-executability rate gain over existing baselines. Other significant contributions include the development of AGNOMIN, a novel architecture-agnostic approach for multi-label function name prediction, and CORTEX, a multi-agent LLM architecture for high-stakes alert triage. These advancements have the potential to significantly improve the security and reliability of software systems, and are expected to have a major impact on the field in the coming years. Noteworthy papers include: PhishLumos, which introduced an adaptive multi-agent system for proactive phishing campaign mitigation. SK2Decompile, which presented a novel two-phase approach to decompile from the skeleton to the skin of programs.