How to use cebollet/fine-tuned-mitre-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cebollet/fine-tuned-mitre-model") sentences = [ "sh; enable; system; shell; /bin/busybox", "Defense Evasion: The adversary is trying to avoid being detected.\n\nDefense Evasion consists of techniques that adversaries use to avoid detection throughout their compromise. Techniques used for defense evasion include uninstalling/disabling security software or obfuscating/encrypting data and scripts. Adversaries also leverage and abuse trusted processes to hide and masquerade their malware. Other tactics’ techniques are cross-listed here when those techniques include the added benefit of subverting defenses. ", "Defense Evasion: The adversary is trying to avoid being detected.\n\nDefense Evasion consists of techniques that adversaries use to avoid detection throughout their compromise. Techniques used for defense evasion include uninstalling/disabling security software or obfuscating/encrypting data and scripts. Adversaries also leverage and abuse trusted processes to hide and masquerade their malware. Other tactics’ techniques are cross-listed here when those techniques include the added benefit of subverting defenses. ", "Lateral Movement: The adversary is trying to move through your environment.\n\nLateral Movement consists of techniques that adversaries use to enter and control remote systems on a network. Following through on their primary objective often requires exploring the network to find their target and subsequently gaining access to it. Reaching their objective often involves pivoting through multiple systems and accounts to gain. Adversaries might install their own remote access tools to accomplish Lateral Movement or use legitimate credentials with native network and operating system tools, which may be stealthier. " ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
