text
stringlengths 306
1.51k
|
|---|
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'REDBALDKNIGHT , also known as BRONZE BUTLER and Tick , is a cyberespionage group known to target Japan such as government agencies as well as those in biotechnology , electronics manufacturing , and industrial chemistry .' [/INST] [REDBALDKNIGHT:B-HackOrg, ,:O, also:O, known:O, as:O, BRONZE:B-HackOrg, BUTLER:I-HackOrg, and:O, Tick:B-HackOrg, ,:O, is:O, a:O, cyberespionage:B-HackOrg, group:I-HackOrg, known:O, to:O, target:O, Japan:B-Area, such:O, as:O, government:B-Org, agencies:I-Org, as:O, well:O, as:O, those:O, in:O, biotechnology:B-Idus, ,:O, electronics:B-Idus, manufacturing:I-Idus, ,:O, and:O, industrial:B-Idus, chemistry:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We believe that the Carbanak campaign is a clear indicator of a new era in cybercrime in which criminals use APT techniques directly against the financial industry instead of through its customers .' [/INST] [We:O, believe:O, that:O, the:O, Carbanak:B-Exp, campaign:B-OffAct, is:O, a:O, clear:O, indicator:O, of:O, a:O, new:O, era:O, in:O, cybercrime:O, in:O, which:O, criminals:B-HackOrg, use:O, APT:B-Way, techniques:I-Way, directly:O, against:O, the:O, financial:B-Idus, industry:I-Idus, instead:O, of:O, through:O, its:O, customers:B-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This report describes the details and type of operations carried out by Carbanak that focuses on financial industry , such as payment providers , retail industry and PR companies .' [/INST] [This:O, report:O, describes:O, the:O, details:O, and:O, type:O, of:O, operations:O, carried:O, out:O, by:O, Carbanak:B-Exp, that:O, focuses:O, on:O, financial:B-Idus, industry:I-Idus, ,:O, such:O, as:O, payment:B-Org, providers:I-Org, ,:O, retail:B-Idus, industry:I-Idus, and:O, PR:B-Org, companies:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'From 2013 Carbanak intensified its activity focused on banks and electronic payment systems in Russia and in the post-Soviet space .' [/INST] [From:O, 2013:B-Time, Carbanak:B-Exp, intensified:O, its:O, activity:B-OffAct, focused:O, on:O, banks:B-Idus, and:O, electronic:B-Idus, payment:I-Idus, systems:O, in:O, Russia:B-Area, and:O, in:O, the:O, post-Soviet:B-Area, space:B-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Since 2013 Carbanak has successfully gained access to networks of more than 50 banks and 5 payment systems .' [/INST] [Since:O, 2013:B-Time, Carbanak:B-Exp, has:O, successfully:O, gained:O, access:O, to:O, networks:O, of:O, more:O, than:O, 50:O, banks:B-Idus, and:O, 5:O, payment:B-Idus, systems:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Charming Kitten' focus appears to be individuals of interest to Iran in the fields of academic research .' [/INST] [The:O, Charming:B-HackOrg, Kitten':I-HackOrg, focus:O, appears:O, to:O, be:O, individuals:O, of:O, interest:O, to:O, Iran:B-Area, in:O, the:O, fields:O, of:O, academic:B-Idus, research:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , even though the TTPs of the Cleaver team have some overlap to techniques used by Iranian Cyber Army ( botnets ) , Ashiyane ( SQL injection ) and Syrian Electronic Army ( phishing ) , we believe this is largely the work of a new team .' [/INST] [However:O, ,:O, even:O, though:O, the:O, TTPs:O, of:O, the:O, Cleaver:B-HackOrg, team:O, have:O, some:O, overlap:O, to:O, techniques:O, used:O, by:O, Iranian:B-Area, Cyber:B-HackOrg, Army:I-HackOrg, (:O, botnets:O, ):O, ,:O, Ashiyane:B-HackOrg, (:O, SQL:B-Way, injection:I-Way, ):O, and:O, Syrian:B-Idus, Electronic:I-Idus, Army:I-Idus, (:O, phishing:B-Way, ):O, ,:O, we:O, believe:O, this:O, is:O, largely:O, the:O, work:O, of:O, a:O, new:O, team:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Since 2013 , the Cobalt have attempted to attack banks and financial institutions using pieces of malware they designed .' [/INST] [Since:O, 2013:B-Time, ,:O, the:O, Cobalt:B-HackOrg, have:O, attempted:O, to:O, attack:O, banks:B-Idus, and:O, financial:B-Org, institutions:I-Org, using:O, pieces:O, of:O, malware:O, they:O, designed:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Since 2013 , the cybercrime gang have attempted to attack banks , e-payment systems and financial institutions using pieces of malware they designed , known as Carbanak and Cobalt .' [/INST] [Since:O, 2013:B-Time, ,:O, the:O, cybercrime:B-HackOrg, gang:I-HackOrg, have:O, attempted:O, to:O, attack:O, banks:B-Idus, ,:O, e-payment:B-Idus, systems:O, and:O, financial:B-Org, institutions:I-Org, using:O, pieces:O, of:O, malware:O, they:O, designed:O, ,:O, known:O, as:O, Carbanak:B-Exp, and:O, Cobalt:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Gallmaker 's activity appears to be highly targeted , with its victims all related to government , military , or defense sectors .' [/INST] [Gallmaker:B-HackOrg, 's:O, activity:B-OffAct, appears:O, to:O, be:O, highly:O, targeted:O, ,:O, with:O, its:O, victims:O, all:O, related:O, to:O, government:B-Idus, ,:O, military:B-Idus, ,:O, or:O, defense:B-Org, sectors:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'There are no obvious links between the Eastern European and Middle Eastern targets , but it is clear that Gallmaker is specifically targeting the defense , military , and government sectors .' [/INST] [There:O, are:O, no:O, obvious:O, links:O, between:O, the:O, Eastern:B-Area, European:I-Area, and:O, Middle:B-Area, Eastern:I-Area, targets:O, ,:O, but:O, it:O, is:O, clear:O, that:O, Gallmaker:B-HackOrg, is:O, specifically:O, targeting:O, the:O, defense:B-Idus, ,:O, military:B-Idus, ,:O, and:O, government:B-Org, sectors:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'traditionally targeted the aerospace , energy , government , high-tech , consulting services , and chemicals / manufacturing / mining sectors .' [/INST] [traditionally:O, targeted:O, the:O, aerospace:B-Idus, ,:O, energy:B-Idus, ,:O, government:B-Idus, ,:O, high-tech:B-Idus, ,:O, consulting:B-Idus, services:I-Idus, ,:O, and:O, chemicals:B-Idus, /:O, manufacturing:B-Idus, /:O, mining:B-Org, sectors:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Ke3chang have used three types of malware over the years and have traditionally targeted the aerospace , energy , government , high-tech , consulting services , chemicals , manufacturing , mining sectors .' [/INST] [The:O, Ke3chang:B-HackOrg, have:O, used:O, three:O, types:O, of:O, malware:O, over:O, the:O, years:O, and:O, have:O, traditionally:O, targeted:O, the:O, aerospace:B-Idus, ,:O, energy:B-Idus, ,:O, government:B-Idus, ,:O, high-tech:B-Idus, ,:O, consulting:B-Idus, services:I-Idus, ,:O, chemicals:B-Idus, ,:O, manufacturing:B-Idus, ,:O, mining:B-Org, sectors:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The attackers have used three types of malware over the years and have traditionally targeted the aerospace , energy , government , high-tech , consulting services , and chemicals / manufacturing / mining sectors .' [/INST] [The:O, attackers:B-HackOrg, have:O, used:O, three:O, types:O, of:O, malware:O, over:O, the:O, years:O, and:O, have:O, traditionally:O, targeted:O, the:O, aerospace:B-Idus, ,:O, energy:B-Idus, ,:O, government:B-Idus, ,:O, high-tech:B-Idus, ,:O, consulting:B-Idus, services:I-Idus, ,:O, and:O, chemicals:B-Idus, /:O, manufacturing:B-Idus, /:O, mining:B-Org, sectors:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT15 was targeting information related to UK government departments and military technology .' [/INST] [APT15:B-HackOrg, was:O, targeting:O, information:O, related:O, to:O, UK:B-Area, government:B-Idus, departments:O, and:O, military:B-Idus, technology:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT15 is known for committing cyberespionage against companies and organizations located in many different countries , targeting different sectors such as the oil industry , government contractors , military , and more .' [/INST] [APT15:B-HackOrg, is:O, known:O, for:O, committing:O, cyberespionage:B-HackOrg, against:O, companies:O, and:O, organizations:O, located:O, in:O, many:O, different:O, countries:O, ,:O, targeting:O, different:O, sectors:O, such:O, as:O, the:O, oil:B-Idus, industry:I-Idus, ,:O, government:B-Org, contractors:I-Org, ,:O, military:B-Idus, ,:O, and:O, more:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'cyber actors of the North Korean to target the media , aerospace , financial , and critical infrastructure sectors in the United States and globally .' [/INST] [cyber:B-HackOrg, actors:I-HackOrg, of:O, the:O, North:B-Area, Korean:I-Area, to:O, target:O, the:O, media:B-Idus, ,:O, aerospace:B-Idus, ,:O, financial:B-Idus, ,:O, and:O, critical:B-Org, infrastructure:I-Org, sectors:I-Org, in:O, the:O, United:B-Area, States:I-Area, and:O, globally:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'According to trusted third-party reporting , HIDDEN COBRA actors have likely been using FALLCHILL malware since 2016 to target the aerospace , telecommunications , and finance industries .' [/INST] [According:O, to:O, trusted:O, third-party:O, reporting:O, ,:O, HIDDEN:B-HackOrg, COBRA:I-HackOrg, actors:I-HackOrg, have:O, likely:O, been:O, using:O, FALLCHILL:B-Tool, malware:I-Tool, since:O, 2016:B-Time, to:O, target:O, the:O, aerospace:B-Idus, ,:O, telecommunications:B-Idus, ,:O, and:O, finance:B-Idus, industries:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'McAfee Advanced Threat Research analysts have uncovered a global data reconnaissance campaign assaulting a wide number of industries including critical infrastructure , entertainment , finance , health care , and telecommunications .' [/INST] [McAfee:B-SecTeam, Advanced:I-SecTeam, Threat:I-SecTeam, Research:I-SecTeam, analysts:O, have:O, uncovered:O, a:O, global:O, data:O, reconnaissance:O, campaign:B-OffAct, assaulting:O, a:O, wide:O, number:O, of:O, industries:O, including:O, critical:B-Idus, infrastructure:I-Idus, ,:O, entertainment:B-Idus, ,:O, finance:B-Idus, ,:O, health:B-Idus, care:I-Idus, ,:O, and:O, telecommunications:B-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Since at least 2013 , HIDDEN COBRA actors have been observed using Volgmer malware in the wild to target the government , financial , automotive , and media industries .' [/INST] [Since:O, at:O, least:O, 2013:B-Time, ,:O, HIDDEN:B-HackOrg, COBRA:I-HackOrg, actors:I-HackOrg, have:O, been:O, observed:O, using:O, Volgmer:B-Tool, malware:I-Tool, in:O, the:O, wild:O, to:O, target:O, the:O, government:B-Idus, ,:O, financial:B-Idus, ,:O, automotive:B-Idus, ,:O, and:O, media:B-Idus, industries:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Ransomware that has been publicly named , WannaCry , , , WCry , or , WanaCrypt0r , ( based on strings in the binary and encrypted files ) has spread to at least 74 countries as of Friday 12 May 2017 , reportedly targeting Russia initially , and spreading to telecommunications , shipping , car manufacturers , universities and health care industries , among others .' [/INST] [Ransomware:O, that:O, has:O, been:O, publicly:O, named:O, ,:O, WannaCry:B-Tool, ,:O, ,:O, ,:O, WCry:B-Tool, ,:O, or:O, ,:O, WanaCrypt0r:B-Tool, ,:O, (:O, based:O, on:O, strings:O, in:O, the:O, binary:O, and:O, encrypted:O, files:O, ):O, has:O, spread:O, to:O, at:O, least:O, 74:O, countries:O, as:O, of:O, Friday:B-Time, 12:I-Time, May:I-Time, 2017:I-Time, ,:O, reportedly:O, targeting:O, Russia:B-Area, initially:O, ,:O, and:O, spreading:O, to:O, telecommunications:B-Idus, ,:O, shipping:B-Idus, ,:O, car:B-Idus, manufacturers:I-Idus, ,:O, universities:B-Idus, and:O, health:B-Idus, care:I-Idus, industries:I-Idus, ,:O, among:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Ransomware that has been publicly named , WannaCry , , , WCry , or , WanaCrypt0r , ( based on strings in the binary and encrypted files ) has spread to at least 74 countries as of Friday 12 May 2017 , reportedly targeting Russia initially , and spreading to telecommunications , shipping , car manufacturers , universities and health care industries , among others .' [/INST] [Ransomware:O, that:O, has:O, been:O, publicly:O, named:O, ,:O, WannaCry:B-Tool, ,:O, ,:O, ,:O, WCry:B-Tool, ,:O, or:O, ,:O, WanaCrypt0r:B-Tool, ,:O, (:O, based:O, on:O, strings:O, in:O, the:O, binary:O, and:O, encrypted:O, files:O, ):O, has:O, spread:O, to:O, at:O, least:O, 74:O, countries:O, as:O, of:O, Friday:B-Time, 12:I-Time, May:I-Time, 2017:I-Time, ,:O, reportedly:O, targeting:O, Russia:B-Area, initially:O, ,:O, and:O, spreading:O, to:O, telecommunications:B-Idus, ,:O, shipping:B-Idus, ,:O, car:B-Idus, manufacturers:I-Idus, ,:O, universities:B-Idus, and:O, health:B-Idus, care:I-Idus, industries:I-Idus, ,:O, among:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Known targets of the Leviathan have been involved in the maritime industry , and research institutes , academic organizations , and private firms in the United States .' [/INST] [Known:O, targets:O, of:O, the:O, Leviathan:B-HackOrg, have:O, been:O, involved:O, in:O, the:O, maritime:B-Idus, industry:I-Idus, ,:O, and:O, research:B-Org, institutes:I-Org, ,:O, academic:B-Org, organizations:I-Org, ,:O, and:O, private:B-Org, firms:I-Org, in:O, the:O, United:B-Area, States:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Active since at least 2013 , TEMP.Periscope has primarily focused on maritime-related targets across multiple verticals , including engineering firms , shipping and transportation , manufacturing , defense , government offices , and research universities .' [/INST] [Active:O, since:O, at:O, least:O, 2013:B-Time, ,:O, TEMP.Periscope:B-HackOrg, has:O, primarily:O, focused:O, on:O, maritime-related:O, targets:O, across:O, multiple:O, verticals:O, ,:O, including:O, engineering:B-Org, firms:I-Org, ,:O, shipping:B-Idus, and:O, transportation:B-Idus, ,:O, manufacturing:B-Idus, ,:O, defense:B-Idus, ,:O, government:B-Org, offices:I-Org, ,:O, and:O, research:B-Idus, universities:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Within a year APT40 was observed masquerading as a UUV manufacturer , and targeting universities engaged in naval research .' [/INST] [Within:O, a:O, year:O, APT40:B-HackOrg, was:O, observed:O, masquerading:O, as:O, a:O, UUV:O, manufacturer:O, ,:O, and:O, targeting:O, universities:B-Idus, engaged:O, in:O, naval:O, research:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT40 engages in broader regional targeting against traditional intelligence targets , especially organizations with operations in Southeast Asia .' [/INST] [APT40:B-HackOrg, engages:O, in:O, broader:O, regional:O, targeting:O, against:O, traditional:B-Purp, intelligence:I-Purp, targets:I-Purp, ,:O, especially:O, organizations:O, with:O, operations:O, in:O, Southeast:B-Area, Asia:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Lotus Blossom targeted the government , higher education , and high tech companies .' [/INST] [Lotus:B-HackOrg, Blossom:I-HackOrg, targeted:O, the:O, government:B-Idus, ,:O, higher:B-Idus, education:I-Idus, ,:O, and:O, high:B-Org, tech:I-Org, companies:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Lotus Blossom largely targets military or government , with some cases of higher education and high tech companies .' [/INST] [The:O, Lotus:B-HackOrg, Blossom:I-HackOrg, largely:O, targets:O, military:B-Idus, or:O, government:B-Idus, ,:O, with:O, some:O, cases:O, of:O, higher:B-Idus, education:I-Idus, and:O, high:B-Org, tech:I-Org, companies:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Organizations in the government , energy , and technology sectors have been targeted by Magic Hound , specifically organizations based in or doing business in Saudi Arabia .' [/INST] [Organizations:O, in:O, the:O, government:B-Idus, ,:O, energy:B-Idus, ,:O, and:O, technology:B-Org, sectors:I-Org, have:O, been:O, targeted:O, by:O, Magic:O, Hound:O, ,:O, specifically:O, organizations:O, based:O, in:O, or:O, doing:O, business:O, in:O, Saudi:B-Area, Arabia:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Since at least 2014 , APT32 , also known as the OceanLotus Group , has targeted foreign corporations with investments in Vietnam , foreign governments , journalists , and Vietnamese dissidents .' [/INST] [Since:O, at:O, least:O, 2014:B-Time, ,:O, APT32:B-HackOrg, ,:O, also:O, known:O, as:O, the:O, OceanLotus:B-HackOrg, Group:I-HackOrg, ,:O, has:O, targeted:O, foreign:B-Idus, corporations:I-Idus, with:O, investments:O, in:O, Vietnam:B-Area, ,:O, foreign:B-Org, governments:I-Org, ,:O, journalists:B-Org, ,:O, and:O, Vietnamese:B-Area, dissidents:B-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Evidence also suggests that APT32 has targeted network security and technology infrastructure corporations with connections to foreign investors .' [/INST] [Evidence:O, also:O, suggests:O, that:O, APT32:B-HackOrg, has:O, targeted:O, network:B-Idus, security:I-Idus, and:O, technology:B-Org, infrastructure:I-Org, corporations:I-Org, with:O, connections:O, to:O, foreign:O, investors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Since at least 2014 , APT32 , also known as the OceanLotus Group , has targeted foreign corporations foreign governments .' [/INST] [Since:O, at:O, least:O, 2014:B-Time, ,:O, APT32:B-HackOrg, ,:O, also:O, known:O, as:O, the:O, OceanLotus:B-HackOrg, Group:I-HackOrg, ,:O, has:O, targeted:O, foreign:B-Idus, corporations:I-Idus, foreign:O, governments:B-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Additionally , there is evidence to suggest APT33 targeted Saudi Arabian and Western organizations that provide training , maintenance and support for Saudi Arabia 's military and commercial fleets .' [/INST] [Additionally:O, ,:O, there:O, is:O, evidence:O, to:O, suggest:O, APT33:B-HackOrg, targeted:O, Saudi:B-Area, Arabian:I-Area, and:O, Western:B-Area, organizations:O, that:O, provide:O, training:O, ,:O, maintenance:O, and:O, support:O, for:O, Saudi:B-Area, Arabia:I-Area, 's:O, military:B-Idus, and:O, commercial:B-Idus, fleets:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The OilRig group conducts operations primarily in the Middle East , targeting financial , government , energy , chemical , telecommunications and other industries .' [/INST] [The:O, OilRig:B-HackOrg, group:I-HackOrg, conducts:O, operations:O, primarily:O, in:O, the:O, Middle:B-Area, East:I-Area, ,:O, targeting:O, financial:B-Idus, ,:O, government:B-Idus, ,:O, energy:B-Idus, ,:O, chemical:B-Idus, ,:O, telecommunications:B-Idus, and:O, other:O, industries:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT35 typically targets military , diplomatic and government , media , energy , engineering , business services and telecommunications sectors in U.S. and the Middle East .' [/INST] [APT35:B-HackOrg, typically:O, targets:O, military:B-Idus, ,:O, diplomatic:B-Idus, and:O, government:B-Idus, ,:O, media:B-Idus, ,:O, energy:B-Idus, ,:O, engineering:B-Idus, ,:O, business:B-Idus, services:I-Idus, and:O, telecommunications:B-Org, sectors:I-Org, in:O, U.S.:B-Area, and:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT35 typically targets U.S. and the Middle Eastern military , diplomatic and government personnel , organizations in the media , energy and defense industrial base ( DIB ) , and engineering , business services and telecommunications sectors .' [/INST] [APT35:B-HackOrg, typically:O, targets:O, U.S.:B-Area, and:O, the:O, Middle:B-Area, Eastern:I-Area, military:B-Org, ,:O, diplomatic:B-Org, and:O, government:B-Org, personnel:I-Org, ,:O, organizations:B-Idus, in:O, the:O, media:B-Idus, ,:O, energy:B-Idus, and:O, defense:B-Org, industrial:I-Org, base:I-Org, (:O, DIB:B-Org, ):O, ,:O, and:O, engineering:B-Idus, ,:O, business:B-Idus, services:I-Idus, and:O, telecommunications:B-Org, sectors:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Since at least 2013 , the Iranian threat group that FireEye tracks as APT33 has carried out a cyber espionage operation to collect information from defense , aerospace and petrochemical organizations .' [/INST] [Since:O, at:O, least:O, 2013:B-Time, ,:O, the:O, Iranian:B-Area, threat:B-HackOrg, group:I-HackOrg, that:O, FireEye:B-SecTeam, tracks:O, as:O, APT33:B-HackOrg, has:O, carried:O, out:O, a:O, cyber:O, espionage:O, operation:O, to:O, collect:O, information:O, from:O, defense:B-Idus, ,:O, aerospace:B-Idus, and:O, petrochemical:B-Org, organizations:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Since at least 2013 , the Iranian threat group FireEye tracks as APT33 has carried out a cyber espionage operation to collect information from defense , aerospace and petrochemical organizations .' [/INST] [Since:O, at:O, least:O, 2013:B-Time, ,:O, the:O, Iranian:B-Area, threat:B-HackOrg, group:I-HackOrg, FireEye:B-SecTeam, tracks:O, as:O, APT33:B-HackOrg, has:O, carried:O, out:O, a:O, cyber:O, espionage:O, operation:O, to:O, collect:O, information:O, from:O, defense:B-Idus, ,:O, aerospace:B-Idus, and:O, petrochemical:B-Org, organizations:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Ultimately , APT35 had used access to hundreds of mailboxes to read email communications and steal data related to Middle East organizations , which later became victims of destructive attacks .' [/INST] [Ultimately:O, ,:O, APT35:B-HackOrg, had:O, used:O, access:O, to:O, hundreds:O, of:O, mailboxes:O, to:O, read:O, email:B-Idus, communications:I-Idus, and:O, steal:B-Purp, data:I-Purp, related:O, to:O, Middle:B-Area, East:I-Area, organizations:O, ,:O, which:O, later:O, became:O, victims:O, of:O, destructive:B-OffAct, attacks:I-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Further analysis revealed a well-established collection of fake social media profiles that appear intended to build trust and rapport with potential victims .' [/INST] [Further:O, analysis:O, revealed:O, a:O, well-established:O, collection:O, of:O, fake:O, social:B-Idus, media:I-Idus, profiles:O, that:O, appear:O, intended:O, to:O, build:B-Features, trust:I-Features, and:O, rapport:B-Features, with:I-Features, potential:I-Features, victims:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'COBALT GYPSY has used spearphishing to target telecommunications , government , defense , oil , and financial services organizations based in or affiliated with the MENA region , identifying individual victims through social media sites .' [/INST] [COBALT:B-HackOrg, GYPSY:I-HackOrg, has:O, used:O, spearphishing:B-Way, to:O, target:O, telecommunications:B-Idus, ,:O, government:B-Idus, ,:O, defense:B-Idus, ,:O, oil:B-Idus, ,:O, and:O, financial:B-Org, services:I-Org, organizations:I-Org, based:O, in:O, or:O, affiliated:O, with:O, the:O, MENA:B-Area, region:O, ,:O, identifying:O, individual:B-Org, victims:I-Org, through:O, social:B-Idus, media:I-Idus, sites:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Magic Hound has repeatedly used social media to identify and interact with employees at targeted organizations and then used weaponized Excel documents .' [/INST] [The:O, Magic:O, Hound:O, has:O, repeatedly:O, used:O, social:B-Idus, media:I-Idus, to:O, identify:O, and:O, interact:O, with:O, employees:B-Org, at:O, targeted:O, organizations:O, and:O, then:O, used:O, weaponized:O, Excel:B-Way, documents:I-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We identified decoy files which indicate these attacks began with spear phishing messages but have not observed the actual messages .' [/INST] [We:O, identified:O, decoy:B-SamFile, files:I-SamFile, which:O, indicate:O, these:O, attacks:B-OffAct, began:O, with:O, spear:B-Way, phishing:I-Way, messages:I-Way, but:O, have:O, not:O, observed:O, the:O, actual:O, messages:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This group has used a large array of infection vectors , mostly revolving around drive-by downloads and spam .' [/INST] [This:O, group:B-HackOrg, has:O, used:O, a:O, large:O, array:O, of:O, infection:O, vectors:O, ,:O, mostly:O, revolving:O, around:O, drive-by:B-Way, downloads:I-Way, and:O, spam:B-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To infect individuals with access to the data the actors desire , Scarlet Mimic deploys both spear-phishing and watering hole ( strategic web compromise ) attacks .' [/INST] [To:O, infect:O, individuals:O, with:O, access:O, to:O, the:O, data:O, the:O, actors:B-HackOrg, desire:O, ,:O, Scarlet:B-HackOrg, Mimic:I-HackOrg, deploys:O, both:O, spear-phishing:B-Way, and:O, watering:B-OffAct, hole:I-OffAct, (:O, strategic:O, web:O, compromise:O, ):O, attacks:B-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'As with many other attackers who use spear-phishing to infect victims , Scarlet Mimic makes heavy use of , decoy , files .' [/INST] [As:O, with:O, many:O, other:O, attackers:B-HackOrg, who:O, use:O, spear-phishing:B-Way, to:O, infect:O, victims:O, ,:O, Scarlet:B-HackOrg, Mimic:I-HackOrg, makes:O, heavy:O, use:O, of:O, ,:O, decoy:O, ,:O, files:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The most recent Scarlet Mimic attacks we have identified were conducted in 2015 and suggest the group has a significant interest in both Muslim activists and those interested in critiques of the Russian government and Russian President Vladimir Putin .' [/INST] [The:O, most:O, recent:O, Scarlet:B-OffAct, Mimic:I-OffAct, attacks:I-OffAct, we:O, have:O, identified:O, were:O, conducted:O, in:O, 2015:B-Time, and:O, suggest:O, the:O, group:B-HackOrg, has:O, a:O, significant:O, interest:O, in:O, both:O, Muslim:B-Org, activists:I-Org, and:O, those:O, interested:O, in:O, critiques:O, of:O, the:O, Russian:B-Area, government:O, and:O, Russian:B-Area, President:O, Vladimir:O, Putin:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Using these tactics Scarlet Mimic can directly target previously identified individuals ( spear phishing ) as well as unidentified individuals who are interested in a specific subject ( watering hole ) .' [/INST] [Using:O, these:O, tactics:O, Scarlet:B-HackOrg, Mimic:I-HackOrg, can:O, directly:O, target:O, previously:O, identified:O, individuals:O, (:O, spear:B-Way, phishing:I-Way, ):O, as:O, well:O, as:O, unidentified:O, individuals:O, who:O, are:O, interested:O, in:O, a:O, specific:O, subject:O, (:O, watering:B-OffAct, hole:I-OffAct, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Scarlet Mimic primarily deploys spear-phishing e-mails to infect its targets , but was also responsible for a watering hole attack in 2013 .' [/INST] [Scarlet:B-HackOrg, Mimic:I-HackOrg, primarily:O, deploys:O, spear-phishing:B-Way, e-mails:I-Way, to:O, infect:O, its:O, targets:O, ,:O, but:O, was:O, also:O, responsible:O, for:O, a:O, watering:B-OffAct, hole:I-OffAct, attack:I-OffAct, in:O, 2013:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Scarlet Mimic has carried out attacks using both spear-phishing and watering holes since at least 2009 with increasingly advanced malware , and has deployed malware to attack multiple operating systems and platforms .' [/INST] [Scarlet:B-HackOrg, Mimic:I-HackOrg, has:O, carried:O, out:O, attacks:B-OffAct, using:O, both:O, spear-phishing:B-Way, and:O, watering:B-Way, holes:I-Way, since:O, at:O, least:O, 2009:B-Time, with:O, increasingly:O, advanced:O, malware:O, ,:O, and:O, has:O, deployed:O, malware:O, to:O, attack:O, multiple:O, operating:O, systems:O, and:O, platforms:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The group primarily deploys spear-phishing e-mails to infect its targets , but was also responsible for a watering hole attack in 2013 .' [/INST] [The:O, group:B-HackOrg, primarily:O, deploys:O, spear-phishing:B-Way, e-mails:I-Way, to:O, infect:O, its:O, targets:O, ,:O, but:O, was:O, also:O, responsible:O, for:O, a:O, watering:B-OffAct, hole:I-OffAct, attack:I-OffAct, in:O, 2013:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'When using email scams , SilverTerrier actors preferred to use large target audiences , which maximized the likelihood of success with very little risk .' [/INST] [When:O, using:O, email:B-Way, scams:I-Way, ,:O, SilverTerrier:B-HackOrg, actors:I-HackOrg, preferred:O, to:O, use:O, large:O, target:O, audiences:O, ,:O, which:O, maximized:O, the:O, likelihood:O, of:O, success:O, with:O, very:O, little:O, risk:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The malware may inject itself into browser processes and explorer.exe .' [/INST] [The:O, malware:B-Tool, may:O, inject:B-Way, itself:I-Way, into:O, browser:O, processes:O, and:O, explorer.exe:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In early May , the phishing lures leveraged RTF attachments that exploited the Microsoft Windows vulnerability described in CVE-2017-0199 .' [/INST] [In:O, early:O, May:B-Time, ,:O, the:O, phishing:B-Way, lures:I-Way, leveraged:O, RTF:B-SamFile, attachments:I-SamFile, that:O, exploited:O, the:O, Microsoft:O, Windows:O, vulnerability:O, described:O, in:O, CVE-2017-0199:B-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In their current campaign , APT32 has leveraged ActiveMime files that employ social engineering methods to entice the victim into enabling macros .' [/INST] [In:O, their:O, current:O, campaign:B-OffAct, ,:O, APT32:B-HackOrg, has:O, leveraged:O, ActiveMime:B-SamFile, files:I-SamFile, that:O, employ:O, social:B-Way, engineering:I-Way, methods:O, to:O, entice:O, the:O, victim:O, into:O, enabling:O, macros:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT32 actors continue to deliver the malicious attachments via spear-phishing emails .' [/INST] [APT32:B-HackOrg, actors:O, continue:O, to:O, deliver:O, the:O, malicious:B-SamFile, attachments:I-SamFile, via:O, spear-phishing:B-Way, emails:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In the following weeks , FireEye released threat intelligence products and updated malware profiles to customers while developing new detection techniques for APT32’s tools and phishing lures .' [/INST] [In:O, the:O, following:O, weeks:O, ,:O, FireEye:B-SecTeam, released:O, threat:O, intelligence:O, products:O, and:O, updated:O, malware:O, profiles:O, to:O, customers:O, while:O, developing:O, new:O, detection:O, techniques:O, for:O, APT32’s:B-HackOrg, tools:O, and:O, phishing:B-Way, lures:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FIN7 is a financially motivated intrusion set that selectively targets victims and uses spear phishing to distribute its malware .' [/INST] [FIN7:B-HackOrg, is:O, a:O, financially:B-Idus, motivated:O, intrusion:O, set:O, that:O, selectively:O, targets:O, victims:O, and:O, uses:O, spear:B-Way, phishing:I-Way, to:O, distribute:O, its:O, malware:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The malware was initially distributed through a compromised software update system and then self-propagated through stolen credentials and SMB exploits , including the EternalBlue exploit used in the WannaCry attack from May 2017 .' [/INST] [The:O, malware:B-SamFile, was:O, initially:O, distributed:O, through:O, a:O, compromised:O, software:O, update:O, system:O, and:O, then:O, self-propagated:O, through:O, stolen:B-Way, credentials:I-Way, and:O, SMB:B-Way, exploits:I-Way, ,:O, including:O, the:O, EternalBlue:B-Tool, exploit:I-Tool, used:O, in:O, the:O, WannaCry:B-HackOrg, attack:O, from:O, May:B-Time, 2017:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The threat actors , observed by FireEye Labs , use a variety of different methods to either compromise or acquire already compromised payment card credentials , including sharing or purchasing dumps online , hacking vulnerable merchant websites and compromising payment card processing devices .' [/INST] [The:O, threat:O, actors:B-HackOrg, ,:O, observed:O, by:O, FireEye:B-SecTeam, Labs:I-SecTeam, ,:O, use:O, a:O, variety:O, of:O, different:O, methods:O, to:O, either:O, compromise:O, or:O, acquire:O, already:O, compromised:O, payment:B-Purp, card:I-Purp, credentials:I-Purp, ,:O, including:O, sharing:O, or:O, purchasing:O, dumps:O, online:O, ,:O, hacking:O, vulnerable:O, merchant:O, websites:O, and:O, compromising:B-Way, payment:I-Way, card:I-Way, processing:O, devices:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Another common step taken by threat actors is changing their system's MAC Address to avoid being uniquely identified .' [/INST] [Another:O, common:O, step:O, taken:O, by:O, threat:O, actors:B-HackOrg, is:O, changing:B-Way, their:I-Way, system's:I-Way, MAC:O, Address:O, to:O, avoid:O, being:O, uniquely:O, identified:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The attachment in these emails is a weaponized Microsoft Office document containing a malicious macro that – when enabled – leads to the download of Hancitor .' [/INST] [The:O, attachment:O, in:O, these:O, emails:O, is:O, a:O, weaponized:O, Microsoft:B-Way, Office:I-Way, document:I-Way, containing:O, a:O, malicious:O, macro:O, that:O, –:O, when:O, enabled:O, –:O, leads:O, to:O, the:O, download:O, of:O, Hancitor:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye Labs detects this phishing attack and customers will be protected against the usage of these sites in possible future campaigns .' [/INST] [FireEye:B-SecTeam, Labs:O, detects:O, this:O, phishing:B-Way, attack:O, and:O, customers:O, will:O, be:O, protected:O, against:O, the:O, usage:O, of:O, these:O, sites:O, in:O, possible:O, future:O, campaigns:B-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The threat actors used two publicly available techniques , an AppLocker whitelisting bypass and a script to inject shellcode into the userinit.exe process .' [/INST] [The:O, threat:O, actors:B-HackOrg, used:O, two:O, publicly:O, available:O, techniques:O, ,:O, an:O, AppLocker:O, whitelisting:O, bypass:O, and:O, a:O, script:O, to:O, inject:B-Way, shellcode:I-Way, into:O, the:O, userinit.exe:B-SamFile, process:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To run its code in kernel mode in the most recent versions of operating systems , that have Driver Signature Enforcement , Slingshot loads signed vulnerable drivers and runs its own code through their vulnerabilities .' [/INST] [To:O, run:O, its:O, code:O, in:O, kernel:O, mode:O, in:O, the:O, most:O, recent:O, versions:O, of:O, operating:O, systems:O, ,:O, that:O, have:O, Driver:O, Signature:O, Enforcement:O, ,:O, Slingshot:B-Tool, loads:O, signed:O, vulnerable:B-Way, drivers:I-Way, and:O, runs:O, its:O, own:O, code:O, through:O, their:O, vulnerabilities:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To date , all observed Snake Wine 's attacks were the result of spear phishing attempts against the victim organizations .' [/INST] [To:O, date:O, ,:O, all:O, observed:O, Snake:B-HackOrg, Wine:I-HackOrg, 's:O, attacks:B-OffAct, were:O, the:O, result:O, of:O, spear:B-Way, phishing:I-Way, attempts:O, against:O, the:O, victim:O, organizations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Beginning in mid-January 2019 , TA542 distributed millions of Emotet-laden emails in both English and German .' [/INST] [Beginning:O, in:O, mid-January:B-Time, 2019:I-Time, ,:O, TA542:O, distributed:O, millions:O, of:O, Emotet-laden:B-Way, emails:I-Way, in:O, both:O, English:O, and:O, German:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Proofpoint researchers observed one DanaBot affiliate ( Affid 11 ) specifically targeting Canada with , Canada Post , themed lures between January 1 and May 1 , 2019 .' [/INST] [Proofpoint:B-SecTeam, researchers:O, observed:O, one:O, DanaBot:B-Tool, affiliate:O, (:O, Affid:O, 11:O, ):O, specifically:O, targeting:O, Canada:B-Area, with:O, ,:O, Canada:B-Org, Post:I-Org, ,:O, themed:B-Way, lures:I-Way, between:O, January:O, 1:O, and:O, May:B-Time, 1:I-Time, ,:O, 2019:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In all emails sent to these government officials , the actor used the same attachment : a malicious Microsoft Word document that exploited the CVE-2012-0158 vulnerability to drop a malicious payload .' [/INST] [In:O, all:O, emails:B-Way, sent:O, to:O, these:O, government:B-Org, officials:I-Org, ,:O, the:O, actor:O, used:O, the:O, same:O, attachment:O, ::O, a:O, malicious:B-SamFile, Microsoft:I-SamFile, Word:I-SamFile, document:I-SamFile, that:O, exploited:O, the:O, CVE-2012-0158:B-Exp, vulnerability:O, to:O, drop:O, a:O, malicious:O, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this latest incident , the group registered a fake news domain , timesofindiaa.in , on May 18 , 2016 , and then used it to send spear phishing emails to Indian government officials on the same day .' [/INST] [In:O, this:O, latest:O, incident:O, ,:O, the:O, group:O, registered:O, a:O, fake:O, news:O, domain:O, ,:O, timesofindiaa.in:O, ,:O, on:O, May:B-Time, 18:I-Time, ,:O, 2016:B-Time, ,:O, and:O, then:O, used:O, it:O, to:O, send:O, spear:B-Way, phishing:I-Way, emails:I-Way, to:O, Indian:B-Area, government:B-Org, officials:I-Org, on:O, the:O, same:O, day:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In previous incidents involving this threat actor , we observed them using malicious documents hosted on websites about the Indian Army , instead of sending these documents directly as an email attachment .' [/INST] [In:O, previous:O, incidents:O, involving:O, this:O, threat:O, actor:O, ,:O, we:O, observed:O, them:O, using:O, malicious:O, documents:O, hosted:O, on:O, websites:O, about:O, the:O, Indian:B-Idus, Army:I-Idus, ,:O, instead:O, of:O, sending:O, these:O, documents:O, directly:O, as:O, an:O, email:B-Way, attachment:I-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this latest incident , Transparent Tribe registered a fake news domain , timesofindiaa.in , on May 18 , 2016 , and then used it to send spear phishing emails to Indian government officials on the same day .' [/INST] [In:O, this:O, latest:O, incident:O, ,:O, Transparent:O, Tribe:O, registered:O, a:O, fake:O, news:O, domain:O, ,:O, timesofindiaa.in:O, ,:O, on:O, May:B-Time, 18:I-Time, ,:O, 2016:B-Time, ,:O, and:O, then:O, used:O, it:O, to:O, send:O, spear:B-Way, phishing:I-Way, emails:I-Way, to:O, Indian:O, government:B-Org, officials:I-Org, on:O, the:O, same:O, day:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This exploit file made use of the same shellcode that we have observed Transparent Tribe use across a number of spear phishing incidents .' [/INST] [This:O, exploit:O, file:O, made:O, use:O, of:O, the:O, same:O, shellcode:O, that:O, we:O, have:O, observed:O, Transparent:O, Tribe:O, use:O, across:O, a:O, number:O, of:O, spear:B-Way, phishing:I-Way, incidents:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'According to the security firm , this campaign targeted Indian military officials via spear-phishing emails , distributing spyware to its victims via an Adobe Reader vulnerability .' [/INST] [According:O, to:O, the:O, security:B-Org, firm:I-Org, ,:O, this:O, campaign:B-OffAct, targeted:O, Indian:O, military:B-Org, officials:I-Org, via:O, spear-phishing:B-Way, emails:I-Way, ,:O, distributing:O, spyware:O, to:O, its:O, victims:O, via:O, an:O, Adobe:B-Exp, Reader:I-Exp, vulnerability:I-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Whitefly compromises its victims using custom malware alongside open-source hacking tools and living off the land tactics , such as malicious PowerShell scripts .' [/INST] [Whitefly:B-HackOrg, compromises:O, its:O, victims:O, using:O, custom:O, malware:O, alongside:O, open-source:O, hacking:O, tools:O, and:O, living:O, off:O, the:O, land:B-Way, tactics:I-Way, ,:O, such:O, as:O, malicious:O, PowerShell:B-Tool, scripts:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'After the demise of Storm , it was replaced by another new botnet known as Waledac that also leveraged peer-to-peer communications .' [/INST] [After:O, the:O, demise:O, of:O, Storm:O, ,:O, it:O, was:O, replaced:O, by:O, another:O, new:O, botnet:O, known:O, as:O, Waledac:B-Tool, that:O, also:O, leveraged:O, peer-to-peer:B-Way, communications:I-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'ESET recently analyzed a new Mac OS sample from the OceanLotus group that had been uploaded to VirusTotal .' [/INST] [ESET:B-SecTeam, recently:O, analyzed:O, a:O, new:O, Mac:O, OS:O, sample:B-SamFile, from:O, the:O, OceanLotus:B-HackOrg, group:O, that:O, had:O, been:O, uploaded:B-Way, to:I-Way, VirusTotal:I-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'At this point , the attackers know the user has opened the document and send another spear-phishing email , this time containing an MS Word document with an embedded executable .' [/INST] [At:O, this:O, point:O, ,:O, the:O, attackers:B-HackOrg, know:O, the:O, user:O, has:O, opened:O, the:O, document:O, and:O, send:O, another:O, spear-phishing:B-Way, email:I-Way, ,:O, this:O, time:O, containing:O, an:O, MS:B-SamFile, Word:I-SamFile, document:I-SamFile, with:O, an:O, embedded:O, executable:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In one case from 2013 , the target was sent a malicious document through a spear phishing email message .' [/INST] [In:O, one:O, case:O, from:O, 2013:B-Time, ,:O, the:O, target:O, was:O, sent:O, a:O, malicious:B-SamFile, document:I-SamFile, through:O, a:O, spear:B-Way, phishing:I-Way, email:I-Way, message:I-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The malware may communicate with its command and control (C2) server over The Onion Router (Tor) network if configured to do so .' [/INST] [The:O, malware:B-SamFile, may:O, communicate:O, with:O, its:O, command:O, and:O, control:O, (C2):O, server:O, over:O, The:B-Way, Onion:I-Way, Router:I-Way, (Tor):O, network:O, if:O, configured:O, to:O, do:O, so:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Harvested credentials provided by an embedded Mimikatz executable facilitate the infection of other systems on the network .' [/INST] [Harvested:B-Way, credentials:I-Way, provided:O, by:O, an:O, embedded:O, Mimikatz:B-SamFile, executable:O, facilitate:O, the:O, infection:O, of:O, other:O, systems:O, on:O, the:O, network:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This time , however , TA459 opportunistically used spear-phishing emails with a Microsoft Word attachment exploiting the recently patched CVE-2017-0199 to deploy the ZeroT Trojan , which in turn downloaded the PlugX Remote Access Trojan ( RAT ) .' [/INST] [This:O, time:O, ,:O, however:O, ,:O, TA459:O, opportunistically:O, used:O, spear-phishing:B-Way, emails:I-Way, with:O, a:O, Microsoft:B-SamFile, Word:I-SamFile, attachment:I-SamFile, exploiting:O, the:O, recently:O, patched:O, CVE-2017-0199:B-Exp, to:O, deploy:O, the:O, ZeroT:B-Tool, Trojan:I-Tool, ,:O, which:O, in:O, turn:O, downloaded:O, the:O, PlugX:B-Tool, Remote:I-Tool, Access:I-Tool, Trojan:I-Tool, (:O, RAT:B-Tool, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This time , however , attackers opportunistically used spear-phishing emails with a Microsoft Word attachment exploiting the recently patched CVE-2017-0199 to deploy the ZeroT Trojan , which in turn downloaded the PlugX Remote Access Trojan ( RAT ) .' [/INST] [This:O, time:O, ,:O, however:O, ,:O, attackers:O, opportunistically:O, used:O, spear-phishing:B-Way, emails:I-Way, with:O, a:O, Microsoft:B-SamFile, Word:I-SamFile, attachment:I-SamFile, exploiting:O, the:O, recently:O, patched:O, CVE-2017-0199:B-Exp, to:O, deploy:O, the:O, ZeroT:B-Tool, Trojan:I-Tool, ,:O, which:O, in:O, turn:O, downloaded:O, the:O, PlugX:B-Tool, Remote:I-Tool, Access:I-Tool, Trojan:I-Tool, (:O, RAT:B-Tool, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The documents attached to spear-phishing e-mails used in both attacks contain code that exploits CVE-2012-0158 , which despite its age remains one of the most common Microsoft Word vulnerabilities being exploited by multiple threat actors .' [/INST] [The:O, documents:B-SamFile, attached:O, to:O, spear-phishing:B-Way, e-mails:I-Way, used:O, in:O, both:O, attacks:B-OffAct, contain:O, code:O, that:O, exploits:O, CVE-2012-0158:B-Exp, ,:O, which:O, despite:O, its:O, age:O, remains:O, one:O, of:O, the:O, most:O, common:O, Microsoft:B-Exp, Word:I-Exp, vulnerabilities:I-Exp, being:O, exploited:O, by:O, multiple:O, threat:O, actors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In all emails sent to these government officials , the actor used the same attachment : a malicious Microsoft Word document that exploited the CVE-2012-0158 vulnerability to drop a malicious payload .' [/INST] [In:O, all:O, emails:B-Way, sent:O, to:O, these:O, government:B-Org, officials:I-Org, ,:O, the:O, actor:O, used:O, the:O, same:O, attachment:O, ::O, a:O, malicious:B-SamFile, Microsoft:I-SamFile, Word:I-SamFile, document:I-SamFile, that:O, exploited:O, the:O, CVE-2012-0158:B-Exp, vulnerability:O, to:O, drop:O, a:O, malicious:O, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'According to the security firm , this campaign targeted Indian military officials via spear-phishing emails , distributing spyware to its victims via an Adobe Reader vulnerability .' [/INST] [According:O, to:O, the:O, security:B-Org, firm:I-Org, ,:O, this:O, campaign:B-OffAct, targeted:O, Indian:O, military:B-Org, officials:I-Org, via:O, spear-phishing:B-Way, emails:I-Way, ,:O, distributing:O, spyware:O, to:O, its:O, victims:O, via:O, an:O, Adobe:B-Exp, Reader:I-Exp, vulnerability:I-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'PLATINUM 's persistent use of spear phishing tactics ( phishing attempts aimed at specific individuals ) and access to previously undiscovered zero-day exploits have made it a highly resilient threat .' [/INST] [PLATINUM:B-HackOrg, 's:O, persistent:O, use:O, of:O, spear:B-Way, phishing:I-Way, tactics:I-Way, (:O, phishing:B-Way, attempts:O, aimed:O, at:O, specific:B-Org, individuals:I-Org, ):O, and:O, access:O, to:O, previously:O, undiscovered:O, zero-day:B-Exp, exploits:I-Exp, have:O, made:O, it:O, a:O, highly:O, resilient:O, threat:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The group 's persistent use of spear phishing tactics ( phishing attempts aimed at specific individuals ) and access to previously undiscovered zero-day exploits have made it a highly resilient threat .' [/INST] [The:O, group:B-HackOrg, 's:O, persistent:O, use:O, of:O, spear:B-Way, phishing:I-Way, tactics:I-Way, (:O, phishing:B-Way, attempts:O, aimed:O, at:O, specific:B-Org, individuals:I-Org, ):O, and:O, access:O, to:O, previously:O, undiscovered:O, zero-day:B-Exp, exploits:I-Exp, have:O, made:O, it:O, a:O, highly:O, resilient:O, threat:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We believe that the Carbanak campaign is a clear indicator of a new era in cybercrime in which criminals use APT techniques directly against the financial industry instead of through its customers .' [/INST] [We:O, believe:O, that:O, the:O, Carbanak:B-Exp, campaign:B-OffAct, is:O, a:O, clear:O, indicator:O, of:O, a:O, new:O, era:O, in:O, cybercrime:O, in:O, which:O, criminals:B-HackOrg, use:O, APT:B-Way, techniques:I-Way, directly:O, against:O, the:O, financial:B-Idus, industry:I-Idus, instead:O, of:O, through:O, its:O, customers:B-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We believe that the Carbanak campaign is a clear indicator of a new era in cybercrime in which criminals use APT techniques directly against the financial industry instead of through its customers .' [/INST] [We:O, believe:O, that:O, the:O, Carbanak:B-Exp, campaign:B-OffAct, is:O, a:O, clear:O, indicator:O, of:O, a:O, new:O, era:O, in:O, cybercrime:O, in:O, which:O, criminals:B-HackOrg, use:O, APT:B-Way, techniques:I-Way, directly:O, against:O, the:O, financial:B-Idus, industry:I-Idus, instead:O, of:O, through:O, its:O, customers:B-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Alternatively , it is also possible that APT41 injected malicious code into the package prior to compilation , circumventing the need to steal the code-signing certificate and compile it on their own .' [/INST] [Alternatively:O, ,:O, it:O, is:O, also:O, possible:O, that:O, APT41:B-HackOrg, injected:B-Way, malicious:I-Way, code:I-Way, into:O, the:O, package:O, prior:O, to:O, compilation:O, ,:O, circumventing:B-Purp, the:O, need:O, to:O, steal:O, the:O, code-signing:O, certificate:O, and:O, compile:O, it:O, on:O, their:O, own:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'SectorJ04 used the spear phishing email to spread malicious Excel or malicious Word files , and downloaded the MSI files from the attacker’s server when the malicious documents were run .' [/INST] [SectorJ04:B-HackOrg, used:O, the:O, spear:B-Way, phishing:I-Way, email:O, to:O, spread:B-Purp, malicious:I-Purp, Excel:O, or:O, malicious:O, Word:O, files:O, ,:O, and:O, downloaded:B-Purp, the:O, MSI:O, files:O, from:O, the:O, attacker’s:B-HackOrg, server:O, when:O, the:O, malicious:O, documents:O, were:O, run:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Spam emails targeting email accounts used in the integrated mail service of public officials were also found in the hacking activity .' [/INST] [Spam:B-Way, emails:I-Way, targeting:O, email:O, accounts:O, used:O, in:O, the:O, integrated:O, mail:O, service:O, of:O, public:O, officials:O, were:O, also:O, found:O, in:O, the:O, hacking:B-OffAct, activity:I-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Instead of using fake Google Docs phishing pages to collect personal email login credentials , Scattered Canary began using phishing pages of commonly used business applications to compromise enterprise credentials .' [/INST] [Instead:O, of:O, using:O, fake:O, Google:O, Docs:O, phishing:B-Way, pages:O, to:O, collect:B-Purp, personal:O, email:O, login:O, credentials:O, ,:O, Scattered:B-HackOrg, Canary:I-HackOrg, began:O, using:O, phishing:B-Way, pages:O, of:O, commonly:O, used:O, business:O, applications:O, to:O, compromise:B-Purp, enterprise:I-Purp, credentials:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'During a recent campaign , APT32 leveraged social engineering emails with Microsoft ActiveMime file attachments to deliver malicious macros .' [/INST] [During:O, a:O, recent:O, campaign:B-OffAct, ,:O, APT32:B-HackOrg, leveraged:O, social:B-Way, engineering:I-Way, emails:I-Way, with:O, Microsoft:B-SamFile, ActiveMime:I-SamFile, file:I-SamFile, attachments:O, to:O, deliver:B-Purp, malicious:I-Purp, macros:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Tactic #1: Delivering the miner directly to a vulnerable serverSome tactics we've observed involve exploiting CVE-2017-10271 , leveraging PowerShell to download the miner directly onto the victim’s system (Figure 1) , and executing it using ShellExecute() .' [/INST] [Tactic:O, #1::O, Delivering:O, the:O, miner:O, directly:O, to:O, a:O, vulnerable:O, serverSome:O, tactics:O, we've:O, observed:O, involve:O, exploiting:O, CVE-2017-10271:B-Exp, ,:O, leveraging:O, PowerShell:B-Tool, to:O, download:B-Purp, the:O, miner:O, directly:O, onto:O, the:O, victim’s:O, system:O, (Figure:O, 1):O, ,:O, and:O, executing:B-Way, it:O, using:B-Way, ShellExecute():I-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This time , however , TA459 opportunistically used spear-phishing emails with a Microsoft Word attachment exploiting the recently patched CVE-2017-0199 to deploy the ZeroT Trojan , which in turn downloaded the PlugX Remote Access Trojan ( RAT ) .' [/INST] [This:O, time:O, ,:O, however:O, ,:O, TA459:O, opportunistically:O, used:O, spear-phishing:B-Way, emails:I-Way, with:O, a:O, Microsoft:B-SamFile, Word:I-SamFile, attachment:I-SamFile, exploiting:O, the:O, recently:O, patched:O, CVE-2017-0199:B-Exp, to:O, deploy:O, the:O, ZeroT:B-Tool, Trojan:I-Tool, ,:O, which:O, in:O, turn:O, downloaded:O, the:O, PlugX:B-Tool, Remote:I-Tool, Access:I-Tool, Trojan:I-Tool, (:O, RAT:B-Tool, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This time , however , attackers opportunistically used spear-phishing emails with a Microsoft Word attachment exploiting the recently patched CVE-2017-0199 to deploy the ZeroT Trojan , which in turn downloaded the PlugX Remote Access Trojan ( RAT ) .' [/INST] [This:O, time:O, ,:O, however:O, ,:O, attackers:O, opportunistically:O, used:O, spear-phishing:B-Way, emails:I-Way, with:O, a:O, Microsoft:B-SamFile, Word:I-SamFile, attachment:I-SamFile, exploiting:O, the:O, recently:O, patched:O, CVE-2017-0199:B-Exp, to:O, deploy:O, the:O, ZeroT:B-Tool, Trojan:I-Tool, ,:O, which:O, in:O, turn:O, downloaded:O, the:O, PlugX:B-Tool, Remote:I-Tool, Access:I-Tool, Trojan:I-Tool, (:O, RAT:B-Tool, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The documents attached to spear-phishing e-mails used in both attacks contain code that exploits CVE-2012-0158 , which despite its age remains one of the most common Microsoft Word vulnerabilities being exploited by multiple threat actors .' [/INST] [The:O, documents:B-SamFile, attached:O, to:O, spear-phishing:B-Way, e-mails:I-Way, used:O, in:O, both:O, attacks:B-OffAct, contain:O, code:O, that:O, exploits:O, CVE-2012-0158:B-Exp, ,:O, which:O, despite:O, its:O, age:O, remains:O, one:O, of:O, the:O, most:O, common:O, Microsoft:B-Exp, Word:I-Exp, vulnerabilities:I-Exp, being:O, exploited:O, by:O, multiple:O, threat:O, actors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'According to the security firm , this campaign targeted Indian military officials via spear-phishing emails , distributing spyware to its victims via an Adobe Reader vulnerability .' [/INST] [According:O, to:O, the:O, security:B-Org, firm:I-Org, ,:O, this:O, campaign:B-OffAct, targeted:O, Indian:O, military:O, officials:O, via:O, spear-phishing:B-Way, emails:I-Way, ,:O, distributing:O, spyware:O, to:O, its:O, victims:O, via:O, an:O, Adobe:B-Exp, Reader:I-Exp, vulnerability:I-Exp, .:O] </s> |