Datasets:
Sampath1987
/
RE_data_train

Dataset card Data Studio Files
xet
Community
2
text
stringlengths
597
1.55k
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('attackers', 'skills in English and in impersonation'), entity_labels:('THREAT_ACTOR', 'ATTACK_RESOURCE_LEVEL'), possible_labels:hasresource [/INST] hasresource </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Sandworm', 'victim ’s substation environment'), entity_labels:('THREAT_ACTOR', 'INFRASTRUCTURE'), possible_labels:target,uses,compromise,controls [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('the backdoor', 'Duuzer'), entity_labels:('ATTACK_TOOL', 'MALWARE'), possible_labels:No [/INST] variant </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('identify similar patterns and techniques used by different threat actors , providing defenders with a way to proactively detect and block the new variants at the initial stage of an attack', 'Conti'), entity_labels:('IMPACT', 'MALWARE'), possible_labels:caused [/INST] caused </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('scammers', 'Facebook users are clicking on posts that lead to external websites'), entity_labels:('THREAT_ACTOR', 'OBSERVED_DATA'), possible_labels:uses,controls [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('SysUpdate backdoor SysUpdate DLL inicore_v2.3.30.dll', 'SysUpdate'), entity_labels:('MALWARE', 'MALWARE'), possible_labels:uses,variant,m_controls [/INST] variant </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Iran', 'Iranian cyber operations'), entity_labels:('THREAT_ACTOR', 'INTRUSION_SET'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Tortoiseshell', 'targets outside of the Middle East'), entity_labels:('THREAT_ACTOR', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('TIEDYE', 'proxy_socks4'), entity_labels:('MALWARE', 'INFRASTRUCTURE'), possible_labels:target,uses,exfiltrates,communicate [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Facilitation extrinsic Cyber attackers', 'organizations'), entity_labels:('INTRUSION_SET', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:("analyze the source code and understand the attacker 's tactics , techniques and procedures ( TTPs )", 'BlackCat'), entity_labels:('COURSE_OF_ACTION', 'MALWARE'), possible_labels:No [/INST] counters </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Within 24 hours of gaining initial access to systems in the victim environment , the threat actor deployed additional backdoors and established persistence via plists', 'malicious code'), entity_labels:('ATTACK_PATTERN', 'MALWARE'), possible_labels:uses,delivers [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('malware', 'external command and control server'), entity_labels:('MALWARE', 'INFRASTRUCTURE'), possible_labels:target,uses,exfiltrates,communicate [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('APT group', 'multinational electronics manufacturer'), entity_labels:('THREAT_ACTOR', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Tunisia', 'diplomatic organizations'), entity_labels:('LOCATION', 'VICTIM_IDENTITY'), possible_labels:No [/INST] located </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('can confuse or mislead investigators', 'misattribute the activity to the wrong actor'), entity_labels:('IMPACT', 'VULNERABILITY'), possible_labels:caused [/INST] caused </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('LockBit', 'GoAnywhere MFT'), entity_labels:('THREAT_ACTOR', 'GENERAL_TOOL'), possible_labels:uses,controls [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('began approximately 1 hour before Russia launched its major invasion of Ukraine', 'the Ukrainian military'), entity_labels:('ATTACK_PATTERN', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('phishing', 'Rhysida'), entity_labels:('ATTACK_PATTERN', 'MALWARE'), possible_labels:uses,delivers [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('attackers', 'attempting to connect in realtime with victims over phones and video conferences for conversations rather than just engaging over email'), entity_labels:('THREAT_ACTOR', 'ATTACK_PATTERN'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('having a PTR record to the domain previously identified .', 'C2 domain prontoposer[.]com'), entity_labels:('ATTACK_PATTERN', 'INFRASTRUCTURE'), possible_labels:target,uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('cyber criminals', 'putting companies and customers in an unimaginable bind'), entity_labels:('CAMPAIGN', 'IMPACT'), possible_labels:No [/INST] caused </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Winnti group', 'self - developed technically - proficient tools'), entity_labels:('THREAT_ACTOR', 'ATTACK_SOPHISTICATION_LEVEL'), possible_labels:sophistication [/INST] sophistication </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('or other non - native files', 'leaving behind traces of malicious activities'), entity_labels:('ATTACK_PATTERN', 'IMPACT'), possible_labels:No [/INST] caused </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Properly configure firewalls and proxies to limit outgoing traffic to only necessary ports for that particular network segment', 'APT32 backdoor'), entity_labels:('COURSE_OF_ACTION', 'MALWARE'), possible_labels:No [/INST] counters </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Properly configure firewalls and proxies to limit outgoing traffic to only necessary ports for that particular network segment', 'njRAT'), entity_labels:('COURSE_OF_ACTION', 'MALWARE'), possible_labels:No [/INST] counters </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('threat actors', 'more technologically sophisticated'), entity_labels:('THREAT_ACTOR', 'ATTACK_SOPHISTICATION_LEVEL'), possible_labels:sophistication [/INST] sophistication </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('threats Russia', 'Viasat'), entity_labels:('INTRUSION_SET', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Lazarus', 'activity is ongoing'), entity_labels:('THREAT_ACTOR', 'ATTACK_SOPHISTICATION_LEVEL'), possible_labels:sophistication [/INST] sophistication </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('the group', 'IT and communication companies'), entity_labels:('THREAT_ACTOR', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('understanding the TTPs of the leaked source codes , defenders will gain invaluable insights that are helpful in identifying and mitigating any existing security weakness in their environment and improving their security defense against these attack vectors', 'BlackCat'), entity_labels:('IMPACT', 'MALWARE'), possible_labels:caused [/INST] caused </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Universal Dark Service', 'the Russian government'), entity_labels:('CAMPAIGN', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('threat actors', 'loss of regulated personal data'), entity_labels:('THREAT_ACTOR', 'IMPACT'), possible_labels:No [/INST] caused </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Budworm', 'DLL sideloading using an application it has used for this purpose before'), entity_labels:('THREAT_ACTOR', 'ATTACK_PATTERN'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('NetSupport RAT', 'files are hosted on the same compromised WordPress site used earlier to download the Internet shortcut'), entity_labels:('MALWARE', 'OBSERVED_DATA'), possible_labels:uses,communicate [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:("geopolitical related research . Kaspersky 's Global Research and", ','), entity_labels:('VICTIM_IDENTITY', 'LOCATION'), possible_labels:located [/INST] located </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('OilRig', 'Shark backdoor'), entity_labels:('INTRUSION_SET', 'MALWARE'), possible_labels:uses,controls [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Iranian wiper attacks', 'Middle Eastern targets'), entity_labels:('CAMPAIGN', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Duqu', 'CVE-2013 - 0640'), entity_labels:('MALWARE', 'VULNERABILITY'), possible_labels:target,exploits [/INST] exploits </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('online video game companies', 'South East Asia'), entity_labels:('VICTIM_IDENTITY', 'LOCATION'), possible_labels:located [/INST] located </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('investigated using Endpoint Detection and Response EDR solutions', 'These requests are aimed at spreading the attack laterally within the network'), entity_labels:('COURSE_OF_ACTION', 'ATTACK_PATTERN'), possible_labels:No [/INST] counters </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('tens of thousands of terminals have been damaged', 'subsequent cyber - attack'), entity_labels:('IMPACT', 'INTRUSION_SET'), possible_labels:caused [/INST] caused </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('cause electric power disruption by interacting with IEC 60870 - 5 - 104 ( IEC-104 ) devices , such as remote terminal units ( RTUs ) , that are commonly leveraged in electric transmission and distribution operations', 'novel operational technology ( OT ) / industrial control system ( ICS)-oriented malware'), entity_labels:('IMPACT', 'MALWARE'), possible_labels:caused [/INST] caused </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Bundlore', 'make unique file and directory names for payloads , such as TMP_DIR=`mktemp -d -t x.[5'), entity_labels:('MALWARE', 'OBSERVED_DATA'), possible_labels:uses,communicate [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Winnti group', 'previously unreported malware samples'), entity_labels:('THREAT_ACTOR', 'MALWARE'), possible_labels:uses,controls [/INST] controls </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Foudre', 'novel documents containing macros that extract the embedded package once opened and execute it once the document closes instead of having the victim click on a video link as before'), entity_labels:('MALWARE', 'ATTACK_PATTERN'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Tarrask', 'create " hidden " scheduled tasks by deleting the Security Descriptor ( SD ) registry value.[9'), entity_labels:('ATTACK_TOOL', 'ATTACK_PATTERN'), possible_labels:No [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('RA Group', 'South Korea'), entity_labels:('THREAT_ACTOR', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('An internal data defense strategy requires prevention , detection and response capabilities', 'ransomware attacks'), entity_labels:('COURSE_OF_ACTION', 'ATTACK_PATTERN'), possible_labels:No [/INST] counters </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('identify similar patterns and techniques used by different threat actors , providing defenders with a way to proactively detect and block the new variants at the initial stage of an attack', 'Yanluowang'), entity_labels:('IMPACT', 'MALWARE'), possible_labels:caused [/INST] caused </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('on affected', 'as well'), entity_labels:('THREAT_ACTOR', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('legal and professional services , technology , and government organizations', 'Americas'), entity_labels:('VICTIM_IDENTITY', 'LOCATION'), possible_labels:located [/INST] located </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Babuk', 'aka Boriselcin'), entity_labels:('MALWARE', 'THREAT_ACTOR'), possible_labels:tech_attributed [/INST] attributed </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('malicious links', 'Google Cloud Run'), entity_labels:('INTRUSION_SET', 'INFRASTRUCTURE'), possible_labels:target,uses,compromise,controls [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('and exfiltrates data to a C2 server . CozyDuke', 'spyware components'), entity_labels:('ATTACK_PATTERN', 'INFRASTRUCTURE'), possible_labels:target,uses [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('ransomware attacks', 'attacks themselves are not growing in sophistication'), entity_labels:('ATTACK_PATTERN', 'ATTACK_SOPHISTICATION_LEVEL'), possible_labels:sophistication [/INST] sophistication </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('had spillover impacts into other European countries', 'cyber attacks'), entity_labels:('IMPACT', 'INTRUSION_SET'), possible_labels:caused [/INST] caused </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('FakeSG', 'WordPress'), entity_labels:('MALWARE', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('longrunning Iranian attack campaign', 'Americans'), entity_labels:('CAMPAIGN', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Aclip backdoor', 'send system data , files , and screenshots to the C2 while receiving PowerShell commands at the same time'), entity_labels:('MALWARE', 'ATTACK_PATTERN'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('secondary payloads', 'Rhysida'), entity_labels:('ATTACK_PATTERN', 'MALWARE'), possible_labels:uses,delivers [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('removed fewer than 200 fake profiles from its platforms as a result of the investigation', 'longrunning Iranian attack campaign'), entity_labels:('COURSE_OF_ACTION', 'CAMPAIGN'), possible_labels:No [/INST] counters </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('It decodes the binary and writes it to a Java temporary directory with name “ ntuser.bin ”', 'ntuser.bin'), entity_labels:('ATTACK_PATTERN', 'OBSERVED_DATA'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('scammers', 'several Facebook accounts that were posting a number of stories , ranging from clickbait articles to newsworthy content'), entity_labels:('THREAT_ACTOR', 'OBSERVED_DATA'), possible_labels:uses,controls [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('APT', 'Detbosit'), entity_labels:('THREAT_ACTOR', 'MALWARE'), possible_labels:uses,controls [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Network intrusion detection and prevention systems that use network signatures to identify traffic for specific adversary malware can be used to mitigate activity at the network level', 'FIN7'), entity_labels:('COURSE_OF_ACTION', 'THREAT_ACTOR'), possible_labels:No [/INST] counters </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('cyber attacks', 'disrupt Ukrainian command and control during the invasion'), entity_labels:('INTRUSION_SET', 'ATTACK_MOTIVATION'), possible_labels:motive [/INST] motive </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Monitor network data flows for unexpected patterns and metadata that may be indicative of a mismatch between protocol and utilized port', 'Silence'), entity_labels:('COURSE_OF_ACTION', 'THREAT_ACTOR'), possible_labels:No [/INST] counters </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('includes personal details skimmed from social media or other publicly available information', 'victims who may be busy , distracted or caught in an especially wellcrafted attack'), entity_labels:('ATTACK_PATTERN', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Marlin', 'OilRig'), entity_labels:('MALWARE', 'INTRUSION_SET'), possible_labels:uses,tech_attributed [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Babuk', 'healthcare'), entity_labels:('ATTACK_PATTERN', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('on affected', '('), entity_labels:('THREAT_ACTOR', 'MALWARE'), possible_labels:uses,controls [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Winnti malware', 'The cryptographic certificates'), entity_labels:('MALWARE', 'INFRASTRUCTURE'), possible_labels:target,uses,exfiltrates,communicate [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Network intrusion detection and prevention systems that use network signatures to identify traffic for specific adversary malware can be used to mitigate activity at the network level', 'BendyBear'), entity_labels:('COURSE_OF_ACTION', 'MALWARE'), possible_labels:No [/INST] counters </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('APT group', 'multinational electronics manufacturer'), entity_labels:('THREAT_ACTOR', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Attackers', "to prevent the malware they 're spreading from being detected"), entity_labels:('THREAT_ACTOR', 'ATTACK_MOTIVATION'), possible_labels:motive [/INST] motive </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Winnti malware', 'Digital certificates'), entity_labels:('MALWARE', 'INFRASTRUCTURE'), possible_labels:target,uses,exfiltrates,communicate [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('The initial payloads and second stage backdoors were removed from the system .', 'malicious code'), entity_labels:('ATTACK_PATTERN', 'MALWARE'), possible_labels:uses,delivers [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('spearphishing', 'ITbrain'), entity_labels:('ATTACK_PATTERN', 'ATTACK_TOOL'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('HAFNIUM', 'engineering firm'), entity_labels:('THREAT_ACTOR', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('a cloud', 'store and download malware onto infected systems using a multi - dropper scheme . To get in , the attacker used spear phishing emails with a self - extracting archive attachment pretending to be a voicemail . When the victim opened an'), entity_labels:('THREAT_ACTOR', 'ATTACK_PATTERN'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Metamorfo', 'communicated with hosts over raw TCP on port 9999.[24'), entity_labels:('MALWARE', 'OBSERVED_DATA'), possible_labels:uses,communicate [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Implement rigorous configuration management programs', 'Russian malicious cyber activity'), entity_labels:('COURSE_OF_ACTION', 'CAMPAIGN'), possible_labels:No [/INST] counters </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:("North Korea 's Lazarus", 'web shell ( Notice.php )'), entity_labels:('THREAT_ACTOR', 'GENERAL_TOOL'), possible_labels:uses,controls [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('The PDF usually named “ CriticalBreachDetected.pdf ” is generated using content embedded in the ransomware binary , including the skeleton PDF and the ransom note . The ransom note is also used to generate a message in the form of the background wallpaper typically located at “ C:/Users / Public / bg.jpg ” .', 'Rhysida'), entity_labels:('MALWARE_ANALYSIS', 'MALWARE'), possible_labels:m_analysis,characterizes [/INST] m_analysis </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('they all include its core capabilities', 'Rising Sun'), entity_labels:('ATTACK_PATTERN', 'ATTACK_TOOL'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Lazarus', 'relied on similar versions of Rising Sun in activity tracked in 2017'), entity_labels:('THREAT_ACTOR', 'ATTACK_PATTERN'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('used it to exfiltrate the user name and password data encoded', 'CSP rule system'), entity_labels:('ATTACK_PATTERN', 'INFRASTRUCTURE'), possible_labels:target,uses [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('employ similar methods found in traditional online threats', 'exploits'), entity_labels:('ATTACK_PATTERN', 'INTRUSION_SET'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('campaign', 'government'), entity_labels:('CAMPAIGN', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('KillNet', 'Ukraine'), entity_labels:('CAMPAIGN', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Russia - affiliated domains', 'high - profile Russian individuals opposed to the war .'), entity_labels:('INTRUSION_SET', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('or other non - native files', 'non - native files and other data may be removed over the course of an intrusion'), entity_labels:('ATTACK_PATTERN', 'OBSERVED_DATA'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('to obtain environment information , such as MSSQL server IP addresses , MSSQL credentials , and target IEC-104 device IP addresses . The sample of', 'object addresses ( IOA ) , which typically correlate with input or output data elements on a device and may correspond to power line switches or circuit breakers in an RTU or relay configuration . However , IOA'), entity_labels:('ATTACK_PATTERN', 'OBSERVED_DATA'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Sandworm', "GRU 's disruptive playbook"), entity_labels:('THREAT_ACTOR', 'CAMPAIGN'), possible_labels:No [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Winnti malware', 'Tibetan'), entity_labels:('MALWARE', 'VICTIM_IDENTITY'), possible_labels:target [/INST] target </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('Targeted attacks', 'transfer this to a location that the attackers control'), entity_labels:('INTRUSION_SET', 'ATTACK_MOTIVATION'), possible_labels:motive [/INST] motive </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('the Russian playbook', 'distributed denial - of - service ( DDoS ) attacks'), entity_labels:('CAMPAIGN', 'ATTACK_PATTERN'), possible_labels:uses [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('attackers', 'malware campaigns'), entity_labels:('THREAT_ACTOR', 'CAMPAIGN'), possible_labels:No [/INST] uses </s>
<s>[INST] You are an expert in cybersecurity and natural language processing, tasked with extracting named entity relationships. Your goal is to determine the relationship label between two provided entities using their entity labels and set of possible labels. The predicted label must be one of the possible labels provided. Only provide the predicted label and do not give any explanations. Your task is critical, as incorrect predictions will result in penalties. Here are the inputs: entity:('send data to be collected in his own account instance', 'this creates an open window to exfiltrate data'), entity_labels:('ATTACK_PATTERN', 'IMPACT'), possible_labels:No [/INST] caused </s>