AWEB to Bridge Cybersecurity Attack Patterns and Weaknesses

Industrial Control Systems (ICS) are pivotal in critical sectors like energy, transportation, and manufacturing. However, their increasing interconnectivity and complex digital environment have amplified cyber threat risks. Ensuring cyber resilience for ICS requires not just the use of current security management tools to address existing threats, but also a forward-thinking approach to anticipating and mitigating future risks. This paper proposes a novel concept: the Attack-Weakness Embedding Bridge (AWEB), which leverages separate graph structures and textual data from MITRE ATT&CK and CWE to create a unified analytical space. AWEB has the potential to discover previously unrecognized relationships between system weaknesses and attack patterns, significantly enhancing cybersecurity defenses. The model has the flexibility of leveraging fine-tuned or pre-trained LLM embeddings to capture the nuances of the two datasets. The experimental results demonstrate that our proposed model effectively brings attack patterns and common weaknesses in a mathematical space, providing valuable insights for cybersecurity practitioners.