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<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 expect APT33 activity will continue to cover a broad scope of targeted entities , and may spread into other regions and sectors as Iranian interests dictate .' [/INST] [We:O, expect:O, APT33:B-OffAct, activity:I-OffAct, will:O, continue:O, to:O, cover:O, a:O, broad:O, scope:O, of:O, targeted:O, entities:O, ,:O, and:O, may:O, spread:O, into:O, other:O, regions:O, and:O, sectors:O, as:O, Iranian:B-Area, interests:O, dictate: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 Elfin espionage group ( aka APT33 ) has remained highly active over the past three years , attacking at least 50 organizations in Saudi Arabia , the United States , and a range of other countries .' [/INST] [The:O, Elfin:B-HackOrg, espionage:B-HackOrg, group:I-HackOrg, (:O, aka:O, APT33:B-HackOrg, ):O, has:O, remained:O, highly:O, active:O, over:O, the:O, past:O, three:O, years:O, ,:O, attacking:O, at:O, least:O, 50:O, organizations:O, in:O, Saudi:B-Area, Arabia:I-Area, ,:O, the:O, United:B-Area, States:I-Area, ,:O, and:O, a:O, range:O, of:O, other:O, countries: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: 'On May 16 , 2019 FireEye 's Advanced Practices team attributed the remaining , suspected APT33 activity , ( referred to as GroupB in this blog post ) to APT33 , operating at the behest of the Iranian government .' [/INST] [On:O, May:B-Time, 16:I-Time, ,:I-Time, 2019:I-Time, FireEye:B-SecTeam, 's:I-SecTeam, Advanced:I-SecTeam, Practices:I-SecTeam, team:O, attributed:O, the:O, remaining:O, ,:O, suspected:O, APT33:B-OffAct, activity:I-OffAct, ,:O, (:O, referred:O, to:O, as:O, GroupB:O, in:O, this:O, blog:O, post:O, ):O, to:O, APT33:B-HackOrg, ,:O, operating:O, at:O, the:O, behest:O, of:O, the:O, Iranian:B-Area, government: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 Elfin group ( aka APT33 ) has remained highly active over the past three years , attacking at least 50 organizations in Saudi Arabia , the United States , and a range of other countries .' [/INST] [The:O, Elfin:B-HackOrg, group:I-HackOrg, (:O, aka:O, APT33:B-HackOrg, ):O, has:O, remained:O, highly:O, active:O, over:O, the:O, past:O, three:O, years:O, ,:O, attacking:O, at:O, least:O, 50:O, organizations:O, in:O, Saudi:B-Area, Arabia:I-Area, ,:O, the:O, United:B-Area, States:I-Area, ,:O, and:O, a:O, range:O, of:O, other:O, countries: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: 'On May 16 , 2019 FireEye 's Advanced Practices team attributed the remaining , suspected APT33 activity , to APT33 , operating at the behest of the Iranian government .' [/INST] [On:O, May:B-Time, 16:I-Time, ,:I-Time, 2019:I-Time, FireEye:B-SecTeam, 's:I-SecTeam, Advanced:I-SecTeam, Practices:I-SecTeam, team:O, attributed:O, the:O, remaining:O, ,:O, suspected:O, APT33:B-OffAct, activity:I-OffAct, ,:O, to:O, APT33:B-HackOrg, ,:O, operating:O, at:O, the:O, behest:O, of:O, the:O, Iranian:B-Area, government: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: 'APT37 has likely been active since at least 2012 and focuses on targeting the public and private sectors primarily in South Korea .' [/INST] [APT37:B-HackOrg, has:O, likely:O, been:O, active:O, since:O, at:O, least:O, 2012:B-Time, and:O, focuses:O, on:O, targeting:O, the:O, public:O, and:O, private:O, sectors:O, primarily:O, in:O, South:B-Area, Korea: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: 'In 2017 , APT37 expanded its targeting beyond the Korean peninsula to include Japan , Vietnam and the Middle East , and to a wider range of industry verticals , including chemicals , electronics , manufacturing , aerospace , automotive and healthcare entities .' [/INST] [In:O, 2017:B-Time, ,:O, APT37:B-HackOrg, expanded:O, its:O, targeting:O, beyond:O, the:O, Korean:B-Area, peninsula:I-Area, to:O, include:O, Japan:B-Area, ,:O, Vietnam:B-Area, and:O, the:O, Middle:B-Area, East:I-Area, ,:O, and:O, to:O, a:O, wider:O, range:O, of:O, industry:O, verticals:O, ,:O, including:O, chemicals:B-Idus, ,:O, electronics:B-Idus, ,:O, manufacturing:B-Idus, ,:O, aerospace:B-Idus, ,:O, automotive:B-Idus, and:O, healthcare:B-Org, entities: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: 'In 2017 , APT37 targeted a company in Middle East that entered into a joint venture with the North Korean government to provide telecommunications service to the country .' [/INST] [In:O, 2017:B-Time, ,:O, APT37:B-HackOrg, targeted:O, a:O, company:O, in:O, Middle:B-Area, East:I-Area, that:O, entered:O, into:O, a:O, joint:O, venture:O, with:O, the:O, North:B-Area, Korean:I-Area, government:O, to:O, provide:O, telecommunications:B-Idus, service:I-Idus, to:O, the:O, country: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: 'While not conclusive by itself , the use of publicly available Iranian hacking tools and popular Iranian hosting companies may be a result of APT33 's familiarity with them and lends support to the assessment that APT33 may be based in Iran .' [/INST] [While:O, not:O, conclusive:O, by:O, itself:O, ,:O, the:O, use:O, of:O, publicly:O, available:O, Iranian:B-Area, hacking:O, tools:O, and:O, popular:O, Iranian:B-Area, hosting:B-Org, companies:I-Org, may:O, be:O, a:O, result:O, of:O, APT33:B-HackOrg, 's:O, familiarity:O, with:O, them:O, and:O, lends:O, support:O, to:O, the:O, assessment:O, that:O, APT33:B-HackOrg, may:O, be:O, based:O, in:O, Iran:B-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: 'North Korean defector and human rights-related targeting provides further evidence that APT37 conducts operations aligned with the interests of North Korea .' [/INST] [North:B-Area, Korean:I-Area, defector:O, and:O, human:O, rights-related:O, targeting:O, provides:O, further:O, evidence:O, that:O, APT37:B-HackOrg, conducts:O, operations:O, aligned:O, with:O, the:O, interests:O, of:O, North:B-Area, Korea: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: 'In 2017 , APT37 targeted a Middle Eastern company that entered into a joint venture with the North Korean government to provide telecommunications service to the country ( read on for a case study ) .' [/INST] [In:O, 2017:B-Time, ,:O, APT37:B-HackOrg, targeted:O, a:O, Middle:B-Area, Eastern:I-Area, company:B-Org, that:O, entered:O, into:O, a:O, joint:O, venture:O, with:O, the:O, North:B-Area, Korean:I-Area, government:O, to:O, provide:O, telecommunications:B-Idus, service:I-Idus, to:O, the:O, country:O, (:O, read:O, on:O, for:O, a:O, case:O, study:O, ):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: 'APT37 targeted a research fellow , advisory member , and journalist associated with different North Korean human rights issues and strategic organizations .' [/INST] [APT37:B-HackOrg, targeted:O, a:O, research:B-Org, fellow:I-Org, ,:O, advisory:B-Org, member:I-Org, ,:O, and:O, journalist:B-Org, associated:O, with:O, different:O, North:B-Area, Korean:I-Area, human:O, rights:O, issues:O, and:O, strategic: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: 'APT37 distributed SLOWDRIFT malware using a lure referencing the Korea Global Forum against academic and strategic institutions located in South Korea .' [/INST] [APT37:B-HackOrg, distributed:O, SLOWDRIFT:B-Tool, malware:I-Tool, using:O, a:O, lure:O, referencing:O, the:O, Korea:O, Global:O, Forum:O, against:O, academic:B-Org, and:O, strategic:B-Org, institutions:I-Org, located:O, in:O, South:B-Area, Korea: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: 'We believe a organization located in Middle East was targeted by APT37 because it had been involved with a North Korean company and a business deal went bad .' [/INST] [We:O, believe:O, a:O, organization:O, located:O, in:O, Middle:B-Area, East:I-Area, was:O, targeted:O, by:O, APT37:B-HackOrg, because:O, it:O, had:O, been:O, involved:O, with:O, a:O, North:B-Area, Korean:I-Area, company:B-Org, and:O, a:O, business:O, deal:O, went:O, bad: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 instance , APT37 weaponized a video downloader application with KARAE malware that was indiscriminately distributed to South Korean victims through torrent websites .' [/INST] [In:O, one:O, instance:O, ,:O, APT37:B-HackOrg, weaponized:O, a:O, video:O, downloader:O, application:O, with:O, KARAE:B-Tool, malware:I-Tool, that:O, was:O, indiscriminately:O, distributed:O, to:O, South:B-Area, Korean:I-Area, victims:O, through:O, torrent:O, websites: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: 'FireEye confirmed that since at least November 2017 , APT37 exploited a zero-day Adobe Flash vulnerability , CVE-2018-4878 , to distribute DOGCALL malware to South Korean victims .' [/INST] [FireEye:B-SecTeam, confirmed:O, that:O, since:O, at:O, least:O, November:B-Time, 2017:I-Time, ,:O, APT37:B-HackOrg, exploited:O, a:O, zero-day:B-Exp, Adobe:I-Exp, Flash:I-Exp, vulnerability:I-Exp, ,:O, CVE-2018-4878:B-Exp, ,:O, to:O, distribute:O, DOGCALL:B-Tool, malware:I-Tool, to:O, South:B-Area, Korean:I-Area, victims: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: 'FireEye iSIGHT Intelligence confirmed that since at least November 2017 , APT37 exploited a zero-day Adobe Flash vulnerability , CVE-2018-4878 , to distribute DOGCALL malware to South Korean victims .' [/INST] [FireEye:B-SecTeam, iSIGHT:I-SecTeam, Intelligence:I-SecTeam, confirmed:O, that:O, since:O, at:O, least:O, November:B-Time, 2017:I-Time, ,:O, APT37:B-HackOrg, exploited:O, a:O, zero-day:B-Exp, Adobe:I-Exp, Flash:I-Exp, vulnerability:I-Exp, ,:O, CVE-2018-4878:B-Exp, ,:O, to:O, distribute:O, DOGCALL:B-Tool, malware:I-Tool, to:O, South:B-Area, Korean:I-Area, victims: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 April 2017 , APT37 targeted South Korean military and government organizations with the DOGCALL backdoor and RUHAPPY wiper malware .' [/INST] [In:O, April:B-Time, 2017:I-Time, ,:O, APT37:B-HackOrg, targeted:O, South:B-Area, Korean:I-Area, military:B-Org, and:O, government:B-Org, organizations:I-Org, with:O, the:O, DOGCALL:B-Tool, backdoor:I-Tool, and:O, RUHAPPY:B-Tool, wiper:I-Tool, malware: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: 'It is possible that APT37 's distribution of KARAE malware via torrent websites could assist in creating and maintaining botnets for future distributed denial-of-service ( DDoS ) attacks , or for other activity such as financially motivated campaigns or disruptive operations .' [/INST] [It:O, is:O, possible:O, that:O, APT37:B-HackOrg, 's:O, distribution:O, of:O, KARAE:B-Tool, malware:I-Tool, via:O, torrent:O, websites:O, could:O, assist:O, in:O, creating:O, and:O, maintaining:O, botnets:O, for:O, future:O, distributed:B-Way, denial-of-service:I-Way, (:O, DDoS:B-Way, ):O, attacks:B-OffAct, ,:O, or:O, for:O, other:O, activity:B-OffAct, such:O, as:O, financially:B-Purp, motivated:O, campaigns:B-OffAct, or:O, disruptive:O, operations: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 assess with high confidence that APT37 acts in support of the North Korean government and is primarily based in North Korea .' [/INST] [We:O, assess:O, with:O, high:O, confidence:O, that:O, APT37:B-HackOrg, acts:O, in:O, support:O, of:O, the:O, North:B-Area, Korean:I-Area, government:O, and:O, is:O, primarily:O, based:O, in:O, North:B-Area, Korea: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: 'The compilation times of APT37 malware is consistent with a developer operating in the North Korea time zone ( UTC +8:30 ) and follows what is believed to be a typical North Korean workday .' [/INST] [The:O, compilation:O, times:O, of:O, APT37:B-Tool, malware:I-Tool, is:O, consistent:O, with:O, a:O, developer:O, operating:O, in:O, the:O, North:B-Area, Korea:I-Area, time:O, zone:O, (:O, UTC:O, +8:30:O, ):O, and:O, follows:O, what:O, is:O, believed:O, to:O, be:O, a:O, typical:O, North:B-Area, Korean:I-Area, workday: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 majority of APT37 activity continues to target South Korea , North Korean defectors , and organizations and individuals involved in Korean Peninsula reunification efforts .' [/INST] [The:O, majority:O, of:O, APT37:B-OffAct, activity:I-OffAct, continues:O, to:O, target:O, South:B-Area, Korea:I-Area, ,:O, North:B-Area, Korean:I-Area, defectors:B-Org, ,:O, and:O, organizations:O, and:O, individuals:O, involved:O, in:O, Korean:B-Area, Peninsula:I-Area, reunification:O, efforts: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: 'Similarly , APT37 targeting of a company located in Middle East in 2017 is also consistent with North Korean objectives given the entity 's extensive relationships inside North Korea .' [/INST] [Similarly:O, ,:O, APT37:B-HackOrg, targeting:O, of:O, a:O, company:O, located:O, in:O, Middle:B-Area, East:I-Area, in:O, 2017:B-Time, is:O, also:O, consistent:O, with:O, North:B-Area, Korean:I-Area, objectives:O, given:O, the:O, entity:O, 's:O, extensive:O, relationships:O, inside:O, North:B-Area, Korea: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: 'Similarly , APT37 targeting of a Middle Eastern company in 2017 is also consistent with North Korean objectives given the entity 's extensive relationships inside North Korea .' [/INST] [Similarly:O, ,:O, APT37:B-HackOrg, targeting:O, of:O, a:O, Middle:B-Area, Eastern:I-Area, company:B-Org, in:O, 2017:B-Time, is:O, also:O, consistent:O, with:O, North:B-Area, Korean:I-Area, objectives:O, given:O, the:O, entity:O, 's:O, extensive:O, relationships:O, inside:O, North:B-Area, Korea: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: 'In May 2017 , APT37 used a bank liquidation letter as a spear phishing lure against a board member of a Middle Eastern financial company .' [/INST] [In:O, May:B-Time, 2017:I-Time, ,:O, APT37:B-HackOrg, used:O, a:O, bank:O, liquidation:O, letter:O, as:O, a:O, spear:B-Way, phishing:I-Way, lure:I-Way, against:O, a:O, board:B-Org, member:I-Org, of:O, a:O, Middle:B-Area, Eastern:I-Area, financial:B-Org, company: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: 'Though they have primarily tapped other tracked suspected North Korean teams to carry out the most aggressive actions , APT37 is an additional tool available to the regime , perhaps even desirable for its relative obscurity .' [/INST] [Though:O, they:O, have:O, primarily:O, tapped:O, other:O, tracked:O, suspected:O, North:B-Area, Korean:I-Area, teams:O, to:O, carry:O, out:O, the:O, most:O, aggressive:O, actions:O, ,:O, APT37:B-HackOrg, is:O, an:O, additional:O, tool:O, available:O, to:O, the:O, regime:O, ,:O, perhaps:O, even:O, desirable:O, for:O, its:O, relative:O, obscurity: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: 'ScarCruft is a relatively new APT group , victims have been observed in Russia , Nepal , South Korea , China , India , Kuwait and Romania .' [/INST] [ScarCruft:B-HackOrg, is:O, a:O, relatively:O, new:O, APT:B-HackOrg, group:I-HackOrg, ,:O, victims:O, have:O, been:O, observed:O, in:O, Russia:B-Area, ,:O, Nepal:B-Area, ,:O, South:B-Area, Korea:I-Area, ,:O, China:B-Area, ,:O, India:B-Area, ,:O, Kuwait:B-Area, and:O, Romania:B-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: 'Certain details , such as using the same infrastructure and targeting , make us believe that Operation Daybreak is being done by the ScarCruft APT group .' [/INST] [Certain:O, details:O, ,:O, such:O, as:O, using:O, the:O, same:O, infrastructure:O, and:O, targeting:O, ,:O, make:O, us:O, believe:O, that:O, Operation:B-OffAct, Daybreak:I-OffAct, is:O, being:O, done:O, by:O, the:O, ScarCruft:B-HackOrg, APT:B-HackOrg, group:I-HackOrg, .: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: 'Prior to the discovery of Operation Daybreak , we observed the ScarCruft APT launching a series of attacks in Operation Erebus .' [/INST] [Prior:O, to:O, the:O, discovery:O, of:O, Operation:B-OffAct, Daybreak:I-OffAct, ,:O, we:O, observed:O, the:O, ScarCruft:B-HackOrg, APT:I-HackOrg, launching:O, a:O, series:O, of:O, attacks:B-OffAct, in:O, Operation:B-OffAct, Erebus: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: 'Operation Daybreak appears to have been launched by unknown attackers to infect high profile targets through spear-phishing e-mails .' [/INST] [Operation:B-OffAct, Daybreak:I-OffAct, appears:O, to:O, have:O, been:O, launched:O, by:O, unknown:O, attackers:B-HackOrg, to:O, infect:B-Purp, high:I-Purp, profile:I-Purp, targets:I-Purp, through:O, spear-phishing:B-Way, e-mails: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: 'Operation Daybreak appears to have been launched by APT37 to infect high profile targets through spear-phishing e-mails .' [/INST] [Operation:B-OffAct, Daybreak:I-OffAct, appears:O, to:O, have:O, been:O, launched:O, by:O, APT37:B-HackOrg, to:O, infect:B-Purp, high:I-Purp, profile:I-Purp, targets:I-Purp, through:O, spear-phishing:B-Way, e-mails: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: 'On occasion the APT37 directly included the ROKRAT payload in the malicious document and during other campaigns the attackers leveraged multi-stage infection processes .' [/INST] [On:O, occasion:O, the:O, APT37:B-HackOrg, directly:O, included:O, the:O, ROKRAT:B-Tool, payload:O, in:O, the:O, malicious:O, document:O, and:O, during:O, other:O, campaigns:B-OffAct, the:O, attackers:B-HackOrg, leveraged:O, multi-stage:O, infection:O, processes: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 early part of 2017 , Group123 started the , Evil New Year , campaign .' [/INST] [In:O, the:O, early:B-Time, part:I-Time, of:I-Time, 2017:I-Time, ,:O, Group123:B-HackOrg, started:O, the:O, ,:O, Evil:B-OffAct, New:I-OffAct, Year:I-OffAct, ,:O, campaign: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: 'In November 2017 , Talos observed the latest Group123 campaign of the year , which included a new version of ROKRAT being used in the latest wave of attacks .' [/INST] [In:O, November:B-Time, 2017:I-Time, ,:O, Talos:B-SecTeam, observed:O, the:O, latest:O, Group123:B-OffAct, campaign:I-OffAct, of:O, the:O, year:O, ,:O, which:O, included:O, a:O, new:O, version:O, of:O, ROKRAT:B-Tool, being:O, used:O, in:O, the:O, latest:O, wave:O, of: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: 'Group123 is constantly evolving as the new fileless capability that was added to ROKRAT demonstrates .' [/INST] [Group123:B-HackOrg, is:O, constantly:O, evolving:O, as:O, the:O, new:O, fileless:O, capability:O, that:O, was:O, added:O, to:O, ROKRAT:B-Tool, demonstrates: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 campaign , the Group123 used a classical HWP document in order to download and execute a previously unknown malware : NavRAT .' [/INST] [In:O, this:O, campaign:B-OffAct, ,:O, the:O, Group123:B-HackOrg, used:O, a:O, classical:O, HWP:B-Tool, document:I-Tool, in:O, order:O, to:O, download:O, and:O, execute:O, a:O, previously:O, unknown:O, malware:O, ::O, NavRAT: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: 'However , we asses with medium confidence that NavRAT is linked to Group123 .' [/INST] [However:O, ,:O, we:O, asses:O, with:O, medium:O, confidence:O, that:O, NavRAT:B-Tool, is:O, linked:O, to:O, Group123:B-HackOrg, .: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: 'APT38 is a financially motivated North Korean regime-backed group responsible for conducting destructive attacks against financial institutions , as well as some of the world 's largest cyber heists .' [/INST] [APT38:B-HackOrg, is:O, a:O, financially:B-Purp, motivated:I-Purp, North:B-Area, Korean:I-Area, regime-backed:B-HackOrg, group:I-HackOrg, responsible:O, for:O, conducting:O, destructive:B-OffAct, attacks:I-OffAct, against:O, financial:B-Org, institutions:I-Org, ,:O, as:O, well:O, as:O, some:O, of:O, the:O, world:O, 's:O, largest:O, cyber:B-HackOrg, heists:I-HackOrg, .: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: 'APT38 is a financially motivated North Korean regime-backed group responsible for conducting destructive attacks against financial institutions , as well as some of the world .' [/INST] [APT38:B-HackOrg, is:O, a:O, financially:B-Purp, motivated:I-Purp, North:B-Area, Korean:I-Area, regime-backed:B-HackOrg, group:I-HackOrg, responsible:O, for:O, conducting:O, destructive:B-OffAct, attacks:I-OffAct, against:O, financial:B-Org, institutions:I-Org, ,:O, as:O, well:O, as:O, some:O, of:O, the:O, world: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: 'APT38 is believed to operate more similarly to an espionage operation , carefully conducting reconnaissance within compromised financial institutions and balancing financially motivated objectives with learning about internal systems .' [/INST] [APT38:B-HackOrg, is:O, believed:O, to:O, operate:O, more:O, similarly:O, to:O, an:O, espionage:O, operation:O, ,:O, carefully:O, conducting:O, reconnaissance:O, within:O, compromised:O, financial:B-Org, institutions:I-Org, and:O, balancing:B-Purp, financially:I-Purp, motivated:I-Purp, objectives:I-Purp, with:O, learning:O, about:O, internal:O, systems: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 has compromised more than 16 organizations in at least 13 different countries , sometimes simultaneously , since at least 2014 .' [/INST] [The:O, group:B-HackOrg, has:O, compromised:O, more:O, than:O, 16:O, organizations:O, in:O, at:O, least:O, 13:O, different:O, countries:O, ,:O, sometimes:O, simultaneously:O, ,:O, since:O, at:O, least:O, 2014: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: 'APT38 shares malware code and other development resources with TEMP.Hermit North Korean cyber espionage activity , although we consider APT38 .' [/INST] [APT38:B-HackOrg, shares:O, malware:O, code:O, and:O, other:O, development:O, resources:O, with:O, TEMP.Hermit:B-HackOrg, North:B-Area, Korean:I-Area, cyber:B-OffAct, espionage:I-OffAct, activity:I-OffAct, ,:O, although:O, we:O, consider:O, APT38:B-HackOrg, .: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 consider APT38 's operations more global and highly specialized for targeting the financial sector .' [/INST] [We:O, consider:O, APT38:B-HackOrg, 's:O, operations:O, more:O, global:O, and:O, highly:O, specialized:O, for:O, targeting:O, the:O, financial:B-Org, sector: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: 'APT38 is a financially motivated group linked to North Korean cyber espionage operators , renown for attempting to steal hundreds of millions of dollars from financial institutions and their brazen use of destructive malware .' [/INST] [APT38:B-HackOrg, is:O, a:O, financially:B-Purp, motivated:I-Purp, group:B-HackOrg, linked:O, to:O, North:B-Area, Korean:I-Area, cyber:B-HackOrg, espionage:I-HackOrg, operators:I-HackOrg, ,:O, renown:O, for:O, attempting:O, to:O, steal:B-Purp, hundreds:I-Purp, of:I-Purp, millions:I-Purp, of:I-Purp, dollars:I-Purp, from:O, financial:B-Org, institutions:I-Org, and:O, their:O, brazen:O, use:O, of:O, destructive: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: 'Because APT38 is backed by ( and acts on behalf of ) the North Korean regime , we opted to categorize the group as an , APT , instead of a , FIN , .' [/INST] [Because:O, APT38:B-HackOrg, is:O, backed:O, by:O, (:O, and:O, acts:O, on:O, behalf:O, of:O, ):O, the:O, North:B-Area, Korean:I-Area, regime:O, ,:O, we:O, opted:O, to:O, categorize:O, the:O, group:B-HackOrg, as:O, an:O, ,:O, APT:B-HackOrg, ,:O, instead:O, of:O, a:O, ,:O, FIN:O, ,: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: 'Over time these malware similarities diverged , as did targeting , intended outcomes , and TTPs , almost certainly indicating that TEMP.Hermit activity is made up of multiple operational groups primarily linked together with shared malware development resources and North Korean state sponsorship .' [/INST] [Over:O, time:O, these:O, malware:O, similarities:O, diverged:O, ,:O, as:O, did:O, targeting:O, ,:O, intended:O, outcomes:O, ,:O, and:O, TTPs:O, ,:O, almost:O, certainly:O, indicating:O, that:O, TEMP.Hermit:B-OffAct, activity:I-OffAct, is:O, made:O, up:O, of:O, multiple:O, operational:B-HackOrg, groups:I-HackOrg, primarily:O, linked:O, together:O, with:O, shared:O, malware:O, development:O, resources:O, and:O, North:B-Area, Korean:I-Area, state:O, sponsorship: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: 'Based on observed activity , we judge that APT38 's primary mission is targeting financial institutions and manipulating inter-bank financial systems to raise large sums of money for the North Korean regime .' [/INST] [Based:O, on:O, observed:O, activity:B-OffAct, ,:O, we:O, judge:O, that:O, APT38:B-HackOrg, 's:O, primary:O, mission:O, is:O, targeting:O, financial:B-Org, institutions:I-Org, and:O, manipulating:O, inter-bank:O, financial:O, systems:O, to:O, raise:B-Purp, large:I-Purp, sums:I-Purp, of:I-Purp, money:I-Purp, for:O, the:O, North:B-Area, Korean:I-Area, regime: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 2015 , APT38 has attempted to steal hundreds of millions of dollars from financial institutions .' [/INST] [Since:O, 2015:B-Time, ,:O, APT38:B-HackOrg, has:O, attempted:O, to:O, steal:B-Purp, hundreds:I-Purp, of:I-Purp, millions:I-Purp, of:I-Purp, dollars:I-Purp, from:O, financial:B-Org, institutions: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: 'APT38 has pursued their main objective of targeting banks and financial entities since at least 2014 .' [/INST] [APT38:B-HackOrg, has:O, pursued:O, their:O, main:O, objective:O, of:O, targeting:O, banks:B-Idus, and:O, financial:B-Org, entities:I-Org, since:O, at:O, least:O, 2014: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: 'We surmise that the targeting of banks , media , and government agencies is conducted in support of APT38 's primary mission .' [/INST] [We:O, surmise:O, that:O, the:O, targeting:O, of:O, banks:B-Idus, ,:O, media:B-Idus, ,:O, and:O, government:B-Org, agencies:I-Org, is:O, conducted:O, in:O, support:O, of:O, APT38:B-HackOrg, 's:O, primary:O, mission: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 APT38 targeted news outlets known for their business and financial sector reporting , probably in support of efforts to identify and compromise additional financial institutions .' [/INST] [The:O, APT38:B-HackOrg, targeted:O, news:B-Idus, outlets:I-Idus, known:O, for:O, their:O, business:O, and:O, financial:B-Org, sector:I-Org, reporting:O, ,:O, probably:O, in:O, support:O, of:O, efforts:O, to:O, identify:O, and:O, compromise:O, additional:O, financial:B-Org, institutions: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: 'APT38 also targeted financial transaction exchange companies likely because of their proximity to banks .' [/INST] [APT38:B-HackOrg, also:O, targeted:O, financial:B-Org, transaction:I-Org, exchange:I-Org, companies:I-Org, likely:O, because:O, of:O, their:O, proximity:O, to:O, banks: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: 'Given the lapse in time between the spear-phishing and the heist activity in the above example , we suggest two separate but related groups under the North Korean regime were responsible for carrying out missions ; one associated with reconnaissance ( TEMP.Hermit or a related group ) and another for the heists ( APT38 ) .' [/INST] [Given:O, the:O, lapse:O, in:O, time:O, between:O, the:O, spear-phishing:B-Way, and:O, the:O, heist:B-OffAct, activity:I-OffAct, in:O, the:O, above:O, example:O, ,:O, we:O, suggest:O, two:O, separate:O, but:O, related:O, groups:B-HackOrg, under:O, the:O, North:B-Area, Korean:I-Area, regime:O, were:O, responsible:O, for:O, carrying:O, out:O, missions:O, ;:O, one:O, associated:O, with:O, reconnaissance:O, (:O, TEMP.Hermit:B-HackOrg, or:O, a:O, related:O, group:B-HackOrg, ):O, and:O, another:O, for:O, the:O, heists:O, (:O, APT38:B-HackOrg, ):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: 'APT38 , in particular , is strongly distinguishable because of its specific focus on financial institutions and operations that attempt to use SWIFT fraud to steal millions of dollars at a time .' [/INST] [APT38:B-HackOrg, ,:O, in:O, particular:O, ,:O, is:O, strongly:O, distinguishable:O, because:O, of:O, its:O, specific:O, focus:O, on:O, financial:B-Org, institutions:I-Org, and:O, operations:O, that:O, attempt:O, to:O, use:O, SWIFT:B-Tool, fraud:O, to:O, steal:B-Purp, millions:I-Purp, of:I-Purp, dollars:I-Purp, at:O, a:O, time: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 can confirm that the APT38 operator activity is linked to the North Korean regime , but maintains a set of common characteristics , including motivation , malware , targeting , and TTPs that set it apart from other statesponsored operations .' [/INST] [We:O, can:O, confirm:O, that:O, the:O, APT38:B-OffAct, operator:I-OffAct, activity:I-OffAct, is:O, linked:O, to:O, the:O, North:B-Area, Korean:I-Area, regime:O, ,:O, but:O, maintains:O, a:O, set:O, of:O, common:O, characteristics:O, ,:O, including:O, motivation:O, ,:O, malware:O, ,:O, targeting:O, ,:O, and:O, TTPs:O, that:O, set:O, it:O, apart:O, from:O, other:O, statesponsored:O, operations: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: 'As previously mentioned , we assess with high confidence that APT38 's mission is focused on targeting financial institutions to raise money for the North Korean regime .' [/INST] [As:O, previously:O, mentioned:O, ,:O, we:O, assess:O, with:O, high:O, confidence:O, that:O, APT38:B-HackOrg, 's:O, mission:O, is:O, focused:O, on:O, targeting:O, financial:B-Org, institutions:I-Org, to:O, raise:B-Purp, money:I-Purp, for:O, the:O, North:B-Area, Korean:I-Area, regime: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: 'As previously mentioned , we assess with high confidence that APT38 's mission is focused on targeting financial institutions and financial systems to raise money for the North Korean regime .' [/INST] [As:O, previously:O, mentioned:O, ,:O, we:O, assess:O, with:O, high:O, confidence:O, that:O, APT38:B-HackOrg, 's:O, mission:O, is:O, focused:O, on:O, targeting:O, financial:B-Org, institutions:I-Org, and:O, financial:O, systems:O, to:O, raise:B-Purp, money:I-Purp, for:O, the:O, North:B-Area, Korean:I-Area, regime: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: 'Although the APT38 's primary targets appear to be Financial Exchange banks and other financial organizations , they have also Financial Exchange targeted countries ' media organizations with a focus on the financial sector .' [/INST] [Although:O, the:O, APT38:B-HackOrg, 's:O, primary:O, targets:O, appear:O, to:O, be:O, Financial:B-Org, Exchange:I-Org, banks:I-Org, and:O, other:O, financial:B-Org, organizations:I-Org, ,:O, they:O, have:O, also:O, Financial:O, Exchange:O, targeted:O, countries:O, ':O, media:B-Org, organizations:I-Org, with:O, a:O, focus:O, on:O, the:O, financial:B-Org, sector: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 the beginning of 2014 , APT38 operations have focused almost exclusively on developing and conducting financially motivated campaigns targeting international entities , whereas TEMP.Hermit is generally linked to operations focused on South Korea and the United States .' [/INST] [Since:O, at:O, least:O, the:O, beginning:B-Time, of:I-Time, 2014:I-Time, ,:O, APT38:B-HackOrg, operations:O, have:O, focused:O, almost:O, exclusively:O, on:O, developing:O, and:O, conducting:O, financially:B-Purp, motivated:O, campaigns:B-OffAct, targeting:O, international:B-Org, entities:I-Org, ,:O, whereas:O, TEMP.Hermit:B-HackOrg, is:O, generally:O, linked:O, to:O, operations:O, focused:O, on:O, South:B-Area, Korea:I-Area, and: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: 'TEMP.Hermit is generally linked to operations focused on South Korea and the United States .' [/INST] [TEMP.Hermit:B-HackOrg, is:O, generally:O, linked:O, to:O, operations:O, focused:O, on:O, South:B-Area, Korea:I-Area, and: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: 'While North Korean cyber operations against specific countries may have been driven by diplomatic factors and perceived insults against Pyongyang , the application of increasingly restrictive and numerous financial sanctions against North Korea probably contributed to the formation of APT38 .' [/INST] [While:O, North:B-Area, Korean:I-Area, cyber:O, operations:O, against:O, specific:O, countries:O, may:O, have:O, been:O, driven:O, by:O, diplomatic:O, factors:O, and:O, perceived:O, insults:O, against:O, Pyongyang:O, ,:O, the:O, application:O, of:O, increasingly:O, restrictive:O, and:O, numerous:O, financial:B-Idus, sanctions:O, against:O, North:B-Area, Korea:I-Area, probably:O, contributed:O, to:O, the:O, formation:O, of:O, APT38:B-HackOrg, .: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: 'APT38 's operations began in February 2014 and were likely influenced by financial sanctions enacted in March 2013 that blocked bulk cash transfers and restricted North Korea 's access to international banking systems .' [/INST] [APT38:B-HackOrg, 's:O, operations:O, began:O, in:O, February:B-Time, 2014:I-Time, and:O, were:O, likely:O, influenced:O, by:O, financial:O, sanctions:O, enacted:O, in:O, March:B-Time, 2013:I-Time, that:O, blocked:O, bulk:O, cash:O, transfers:O, and:O, restricted:O, North:B-Area, Korea:I-Area, 's:O, access:O, to:O, international:O, banking:O, systems: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: 'APT37 ( Reaper ) , another North Korean state-sponsored group , targeted a Middle Eastern financial company , but there was no evidence of financial fraud .' [/INST] [APT37:B-HackOrg, (:O, Reaper:B-HackOrg, ):O, ,:O, another:O, North:B-Area, Korean:I-Area, state-sponsored:B-HackOrg, group:I-HackOrg, ,:O, targeted:O, a:O, Middle:B-Area, Eastern:I-Area, financial:B-Org, company:I-Org, ,:O, but:O, there:O, was:O, no:O, evidence:O, of:O, financial:O, fraud: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: 'APT37 , another North Korean state-sponsored group , targeted a Middle Eastern financial company , but there was no evidence of financial fraud .' [/INST] [APT37:B-HackOrg, ,:O, another:O, North:B-Area, Korean:I-Area, state-sponsored:B-HackOrg, group:I-HackOrg, ,:O, targeted:O, a:O, Middle:B-Area, Eastern:I-Area, financial:B-Org, company:I-Org, ,:O, but:O, there:O, was:O, no:O, evidence:O, of:O, financial:O, fraud: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: 'Early APT38 operations suggest that the group began targeting financial institutions with an intent to manipulate financial transaction systems at least as early as February 2014 , although we did not observe fraudulent transactions until 2015 .' [/INST] [Early:O, APT38:B-HackOrg, operations:O, suggest:O, that:O, the:O, group:B-HackOrg, began:O, targeting:O, financial:B-Org, institutions:I-Org, with:O, an:O, intent:O, to:O, manipulate:O, financial:O, transaction:O, systems:O, at:O, least:O, as:O, early:O, as:O, February:B-Time, 2014:I-Time, ,:O, although:O, we:O, did:O, not:O, observe:O, fraudulent:O, transactions:O, until:O, 2015: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: 'We do not have evidence that the earliest targeted financial institutions were victimized by fraudulent transactions before APT38 left the compromised environments , possibly indicating that APT38 was conducting reconnaissance-only activity at that time .' [/INST] [We:O, do:O, not:O, have:O, evidence:O, that:O, the:O, earliest:O, targeted:O, financial:B-Org, institutions:I-Org, were:O, victimized:O, by:O, fraudulent:O, transactions:O, before:O, APT38:B-HackOrg, left:O, the:O, compromised:O, environments:O, ,:O, possibly:O, indicating:O, that:O, APT38:B-HackOrg, was:O, conducting:O, reconnaissance-only:B-OffAct, activity:I-OffAct, at:O, that:O, time: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 early 2014 , the APT38 deployed NESTEGG ( a backdoor ) and KEYLIME ( a keylogger ) malware designed to impact financial institution-specific systems at a Southeast Asian bank .' [/INST] [In:O, early:B-Time, 2014:I-Time, ,:O, the:O, APT38:B-HackOrg, deployed:O, NESTEGG:B-Tool, (:O, a:O, backdoor:O, ):O, and:O, KEYLIME:B-Tool, (:O, a:O, keylogger:B-Tool, ):O, malware:O, designed:O, to:O, impact:O, financial:O, institution-specific:O, systems:O, at:O, a:O, Southeast:B-Area, Asian:I-Area, bank: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: 'In early 2014 , the APT38 deployed NESTEGG ( a backdoor ) and KEYLIME ( a keylogger ) malware designed to impact financial institution-specific systems at a Southeast Asian bank .' [/INST] [In:O, early:B-Time, 2014:I-Time, ,:O, the:O, APT38:B-HackOrg, deployed:O, NESTEGG:B-Tool, (:O, a:O, backdoor:O, ):O, and:O, KEYLIME:B-Tool, (:O, a:O, keylogger:B-Tool, ):O, malware:O, designed:O, to:O, impact:O, financial:O, institution-specific:O, systems:O, at:O, a:O, Southeast:B-Area, Asian:I-Area, bank: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: 'From November 2015 through the end of 2016 , APT38 was involved in at least nine separate compromises against banks .' [/INST] [From:O, November:B-Time, 2015:I-Time, through:O, the:O, end:B-Time, of:I-Time, 2016:I-Time, ,:O, APT38:B-HackOrg, was:O, involved:O, in:O, at:O, least:O, nine:O, separate:O, compromises:O, against:O, banks: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: 'Per the complaint , the email account watsonhenny@gmail.com was used to send LinkedIn invitations to employees of a bank later targeted by APT38 .' [/INST] [Per:O, the:O, complaint:O, ,:O, the:O, email:B-Way, account:O, watsonhenny@gmail.com:O, was:O, used:O, to:O, send:O, LinkedIn:O, invitations:O, to:O, employees:B-Org, of:O, a:O, bank:O, later:O, targeted:O, by:O, APT38:B-HackOrg, .: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 , the recent DOJ complaint provides insight into initial compromise techniques conducted by North Korean operators against APT38 targets , which may have been leveraged as part of the initial compromise into the targeted organizations .' [/INST] [Further:O, ,:O, the:O, recent:O, DOJ:O, complaint:O, provides:O, insight:O, into:O, initial:O, compromise:O, techniques:O, conducted:O, by:O, North:B-Area, Korean:I-Area, operators:B-HackOrg, against:O, APT38:B-HackOrg, targets:O, ,:O, which:O, may:O, have:O, been:O, leveraged:O, as:O, part:O, of:O, the:O, initial:O, compromise:O, into:O, the:O, targeted: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: 'This is corroborated by our identification of TEMP.Hermit 's use of MACKTRUCK at a bank , preceding the APT38 operation targeting the bank 's SWIFT systems in late 2015 .' [/INST] [This:O, is:O, corroborated:O, by:O, our:O, identification:O, of:O, TEMP.Hermit:B-HackOrg, 's:O, use:O, of:O, MACKTRUCK:B-Tool, at:O, a:O, bank:O, ,:O, preceding:O, the:O, APT38:B-HackOrg, operation:O, targeting:O, the:O, bank:B-Idus, 's:O, SWIFT:O, systems:O, in:O, late:B-Time, 2015: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: 'APT38 relies on DYEPACK , a SWIFT transaction-hijacking framework , to initiate transactions , steal money , and hide any evidence of the fraudulent transactions from the victimized bank .' [/INST] [APT38:B-HackOrg, relies:O, on:O, DYEPACK:B-Tool, ,:O, a:O, SWIFT:O, transaction-hijacking:O, framework:O, ,:O, to:O, initiate:O, transactions:O, ,:O, steal:B-Purp, money:I-Purp, ,:O, and:O, hide:O, any:O, evidence:O, of:O, the:O, fraudulent:O, transactions:O, from:O, the:O, victimized:O, bank: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: 'The APT38 uses DYEPACK to manipulate the SWIFT transaction records and hide evidence of the malicious transactions , so bank personnel are none the wiser when they review recent transactions .' [/INST] [The:O, APT38:B-HackOrg, uses:O, DYEPACK:B-Tool, to:O, manipulate:O, the:O, SWIFT:O, transaction:O, records:O, and:O, hide:O, evidence:O, of:O, the:O, malicious:O, transactions:O, ,:O, so:O, bank:B-Org, personnel:I-Org, are:O, none:O, the:O, wiser:O, when:O, they:O, review:O, recent:O, transactions: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: 'During this heist , APT38 waited for a holiday weekend in the respective countries to increase the likelihood of hiding the transactions from banking authorities .' [/INST] [During:O, this:O, heist:O, ,:O, APT38:B-HackOrg, waited:O, for:O, a:O, holiday:O, weekend:O, in:O, the:O, respective:O, countries:O, to:O, increase:B-Purp, the:I-Purp, likelihood:I-Purp, of:O, hiding:O, the:O, transactions:O, from:O, banking:B-Idus, authorities: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: 'During one reported incident , APT38 caused an outage in the bank 's essential services .' [/INST] [During:O, one:O, reported:O, incident:O, ,:O, APT38:B-HackOrg, caused:O, an:O, outage:O, in:O, the:O, bank:B-Idus, 's:O, essential:O, services: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 attribute APT38 to North Korean state-sponsored operators based on a combination of technical indicators linking the activity to Pyongyang and details released by DOJ implicating North Korean national Park Jin Hyok in a criminal conspiracy .' [/INST] [We:O, attribute:O, APT38:B-HackOrg, to:O, North:B-Area, Korean:I-Area, state-sponsored:O, operators:B-HackOrg, based:O, on:O, a:O, combination:O, of:O, technical:O, indicators:O, linking:O, the:O, activity:B-OffAct, to:O, Pyongyang:O, and:O, details:O, released:O, by:O, DOJ:O, implicating:O, North:B-Area, Korean:I-Area, national:O, Park:O, Jin:O, Hyok:O, in:O, a:O, criminal:O, conspiracy: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: 'As detailed in the DOJ complaint , a sample of WHITEOUT malware we attribute to APT38 was used between 2015 and 2016 against a Southeast Asian bank .' [/INST] [As:O, detailed:O, in:O, the:O, DOJ:O, complaint:O, ,:O, a:O, sample:O, of:O, WHITEOUT:B-Tool, malware:I-Tool, we:O, attribute:O, to:O, APT38:B-HackOrg, was:O, used:O, between:O, 2015:B-Time, and:O, 2016:B-Time, against:O, a:O, Southeast:B-Area, Asian:I-Area, bank: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: 'APT38 's increasingly aggressive targeting against banks and other financial institutions has paralleled North Korea 's worsening financial condition .' [/INST] [APT38:B-HackOrg, 's:O, increasingly:O, aggressive:O, targeting:O, against:O, banks:B-Idus, and:O, other:O, financial:B-Org, institutions:I-Org, has:O, paralleled:O, North:B-Area, Korea:I-Area, 's:O, worsening:O, financial:O, condition: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: 'APT38 's increasingly aggressive targeting against banks and other financial institutions has paralleled North Korea 's worsening financial condition .' [/INST] [APT38:B-HackOrg, 's:O, increasingly:O, aggressive:O, targeting:O, against:O, banks:B-Idus, and:O, other:O, financial:B-Org, institutions:I-Org, has:O, paralleled:O, North:B-Area, Korea:I-Area, 's:O, worsening:O, financial:O, condition: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: 'APT38 's increasingly aggressive targeting against banks and other financial institutions has paralleled North Korea 's worsening financial condition .' [/INST] [APT38:B-HackOrg, 's:O, increasingly:O, aggressive:O, targeting:O, against:O, banks:B-Idus, and:O, other:O, financial:B-Org, institutions:I-Org, has:O, paralleled:O, North:B-Area, Korea:I-Area, 's:O, worsening:O, financial:O, condition: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: 'Malware overlaps between APT38 and TEMP.Hermit highlight the shared development resources accessible by multiple operational groups linked to North Korean state-sponsored activity .' [/INST] [Malware:O, overlaps:O, between:O, APT38:B-HackOrg, and:O, TEMP.Hermit:B-HackOrg, highlight:O, the:O, shared:O, development:O, resources:O, accessible:O, by:O, multiple:O, operational:B-HackOrg, groups:I-HackOrg, linked:O, to:O, North:B-Area, Korean:I-Area, state-sponsored:O, activity: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: 'APT39 has prioritized the telecommunications sector , with additional targeting of the travel industry and IT firms that support it and the high-tech industry .' [/INST] [APT39:B-HackOrg, has:O, prioritized:O, the:O, telecommunications:B-Org, sector:I-Org, ,:O, with:O, additional:O, targeting:O, of:O, the:O, travel:B-Idus, industry:I-Idus, and:O, IT:B-Org, firms:I-Org, that:O, support:O, it:O, and:O, the:O, high-tech:B-Idus, industry: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: 'This is evidence of shared motivation and intent to target the SWIFT system by the North Korean operators performing the reconnaissance and APT38 which later targeted that organization .' [/INST] [This:O, is:O, evidence:O, of:O, shared:O, motivation:O, and:O, intent:O, to:O, target:O, the:O, SWIFT:O, system:O, by:O, the:O, North:B-Area, Korean:I-Area, operators:B-HackOrg, performing:O, the:O, reconnaissance:O, and:O, APT38:B-HackOrg, which:O, later:O, targeted:O, that:O, organization: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: 'Although APT38 is distinct from other TEMP.Hermit activity , both groups operate consistently within the interests of the North Korean state .' [/INST] [Although:O, APT38:B-HackOrg, is:O, distinct:O, from:O, other:O, TEMP.Hermit:B-OffAct, activity:I-OffAct, ,:O, both:O, groups:B-HackOrg, operate:O, consistently:O, within:O, the:O, interests:O, of:O, the:O, North:B-Area, Korean:I-Area, state: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: 'Based on details published in the DOJ complaint against North Korean programmer Park Jin Hyok , we know that APT38 and other cyber operators linked to TEMP.Hermit are associated with Lab 110 , an organization subordinate to or synonymous with the 6th Technical Bureau in North Korea .' [/INST] [Based:O, on:O, details:O, published:O, in:O, the:O, DOJ:O, complaint:O, against:O, North:B-Area, Korean:I-Area, programmer:O, Park:O, Jin:O, Hyok:O, ,:O, we:O, know:O, that:O, APT38:B-HackOrg, and:O, other:O, cyber:B-HackOrg, operators:I-HackOrg, linked:O, to:O, TEMP.Hermit:B-HackOrg, are:O, associated:O, with:O, Lab:B-Org, 110:I-Org, ,:O, an:O, organization:O, subordinate:O, to:O, or:O, synonymous:O, with:O, the:O, 6th:O, Technical:O, Bureau:O, in:O, North:B-Area, Korea: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: 'As detailed in the DOJ complaint , a sample of WHITEOUT ( aka Contopee ) malware we attribute to APT38 was used between 2015 and 2016 against a Southeast Asian bank .' [/INST] [As:O, detailed:O, in:O, the:O, DOJ:O, complaint:O, ,:O, a:O, sample:O, of:O, WHITEOUT:B-Tool, (:O, aka:O, Contopee:B-Tool, ):O, malware:O, we:O, attribute:O, to:O, APT38:B-HackOrg, was:O, used:O, between:O, 2015:B-Time, and:O, 2016:B-Time, against:O, a:O, Southeast:B-Area, Asian:I-Area, bank: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: 'Based on details published in the DOJ complaint against North Korean programmer Park Jin Hyok , we know that APT38 and other cyber operators linked to TEMP.Hermit are associated with Lab 110 , an organization subordinate to or synonymous with the 6th Technical Bureau in North Korea 's Reconnaissance General Bureau ( RGB ) .' [/INST] [Based:O, on:O, details:O, published:O, in:O, the:O, DOJ:O, complaint:O, against:O, North:B-Area, Korean:I-Area, programmer:O, Park:O, Jin:O, Hyok:O, ,:O, we:O, know:O, that:O, APT38:B-HackOrg, and:O, other:O, cyber:B-HackOrg, operators:I-HackOrg, linked:O, to:O, TEMP.Hermit:B-HackOrg, are:O, associated:O, with:O, Lab:B-Org, 110:I-Org, ,:O, an:O, organization:O, subordinate:O, to:O, or:O, synonymous:O, with:O, the:O, 6th:O, Technical:O, Bureau:O, in:O, North:B-Area, Korea:I-Area, 's:O, Reconnaissance:O, General:O, Bureau:O, (:O, RGB:O, ):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: 'APT38 .' [/INST] [APT38:B-HackOrg, .: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 detailed in the DOJ complaint , a sample of WHITEOUT ( aka Contopee ) malware we attribute to APT38 was used between 2015 and 2016 against a Southeast Asian bank .' [/INST] [As:O, detailed:O, in:O, the:O, DOJ:O, complaint:O, ,:O, a:O, sample:O, of:O, WHITEOUT:B-Tool, (:O, aka:O, Contopee:B-Tool, ):O, malware:O, we:O, attribute:O, to:O, APT38:B-HackOrg, was:O, used:O, between:O, 2015:B-Time, and:O, 2016:B-Time, against:O, a:O, Southeast:B-Area, Asian:I-Area, bank: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: 'APT38 's targeting of financial institutions is most likely an effort by the North Korean government to supplement their heavily-sanctioned economy .' [/INST] [APT38:B-HackOrg, 's:O, targeting:O, of:O, financial:B-Org, institutions:I-Org, is:O, most:O, likely:O, an:O, effort:O, by:O, the:O, North:B-Area, Korean:I-Area, government:O, to:O, supplement:O, their:O, heavily-sanctioned:O, economy: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 have moderate confidence APT39 operations are conducted in support of Iranian national interests based on regional targeting patterns focused in the Middle East .' [/INST] [We:O, have:O, moderate:O, confidence:O, APT39:B-HackOrg, operations:O, are:O, conducted:O, in:O, support:O, of:O, Iranian:B-Area, national:O, interests:O, based:O, on:O, regional:O, targeting:O, patterns:O, focused:O, in: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: 'APT39 's focus on the widespread theft of personal information sets it apart from other Iranian groups FireEye tracks , which have been linked to influence operations , disruptive attacks , and other threats .' [/INST] [APT39:B-HackOrg, 's:O, focus:O, on:O, the:O, widespread:O, theft:O, of:O, personal:B-Purp, information:I-Purp, sets:I-Purp, it:O, apart:O, from:O, other:O, Iranian:B-Area, groups:B-HackOrg, FireEye:B-SecTeam, tracks:O, ,:O, which:O, have:O, been:O, linked:O, to:O, influence:O, operations:O, ,:O, disruptive:O, attacks:B-OffAct, ,:O, and:O, other:O, threats: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: 'APT39 's focus on the telecommunications and travel industries suggests intent to perform monitoring , tracking , or surveillance operations against specific individuals , collect proprietary or customer data for commercial or operational purposes that serve strategic requirements related to national priorities , or create additional accesses and vectors to facilitate future campaigns .' [/INST] [APT39:B-HackOrg, 's:O, focus:O, on:O, the:O, telecommunications:B-Idus, and:I-Idus, travel:I-Idus, industries:I-Idus, suggests:O, intent:O, to:O, perform:O, monitoring:O, ,:O, tracking:O, ,:O, or:O, surveillance:O, operations:O, against:O, specific:B-Org, individuals:I-Org, ,:O, collect:B-Purp, proprietary:I-Purp, or:I-Purp, customer:I-Purp, data:I-Purp, for:O, commercial:B-Purp, or:I-Purp, operational:I-Purp, purposes:I-Purp, that:O, serve:O, strategic:O, requirements:O, related:O, to:O, national:O, priorities:O, ,:O, or:O, create:B-Purp, additional:I-Purp, accesses:I-Purp, and:I-Purp, vectors:I-Purp, to:O, facilitate: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: 'Other groups attributed to Iranian attackers , such as Rocket Kitten , have targeted Iranian individuals in the past , including anonymous proxy users , researchers , journalists , and dissidents .' [/INST] [Other:O, groups:B-HackOrg, attributed:O, to:O, Iranian:B-Area, attackers:B-HackOrg, ,:O, such:O, as:O, Rocket:B-HackOrg, Kitten:I-HackOrg, ,:O, have:O, targeted:O, Iranian:B-Area, individuals:O, in:O, the:O, past:O, ,:O, including:O, anonymous:B-Org, proxy:I-Org, users:I-Org, ,:O, researchers:B-Org, ,:O, journalists:B-Org, ,:O, and:O, 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: 'Remexi is a basic back door Trojan that allows Cadelle to open a remote shell on the computer and execute commands .' [/INST] [Remexi:B-Tool, is:O, a:O, basic:O, back:O, door:O, Trojan:O, that:O, allows:O, Cadelle:B-HackOrg, to:O, open:O, a:O, remote:O, shell:O, on:O, the:O, computer:O, and:O, execute:O, commands: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: 'Remexi is a basic back door Trojan that allows attackers to open a remote shell on the computer and execute commands .' [/INST] [Remexi:B-Tool, is:O, a:O, basic:O, back:O, door:O, Trojan:O, that:O, allows:O, attackers:B-HackOrg, to:O, open:O, a:O, remote:O, shell:O, on:O, the:O, computer:O, and:O, execute:O, commands: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: 'One group , which we call Cadelle , uses Backdoor.Cadelspy , while the other , which we've named Chafer , uses Backdoor.Remexi and Backdoor.Remexi.B .' [/INST] [One:O, group:B-HackOrg, ,:O, which:O, we:O, call:O, Cadelle:B-HackOrg, ,:O, uses:O, Backdoor.Cadelspy:B-Tool, ,:O, while:O, the:O, other:O, ,:O, which:O, we've:O, named:O, Chafer:B-HackOrg, ,:O, uses:O, Backdoor.Remexi:B-Tool, and:O, Backdoor.Remexi.B: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: 'APT39 facilitates lateral movement through myriad tools such as Remote Desktop Protocol ( RDP ) , Secure Shell ( SSH ) , PsExec , RemCom , and xCmdSvc .' [/INST] [APT39:B-HackOrg, facilitates:O, lateral:O, movement:O, through:O, myriad:O, tools:O, such:O, as:O, Remote:B-Tool, Desktop:I-Tool, Protocol:I-Tool, (:O, RDP:B-Tool, ):O, ,:O, Secure:B-Tool, Shell:I-Tool, (:O, SSH:B-Tool, ):O, ,:O, PsExec:B-Tool, ,:O, RemCom:B-Tool, ,:O, and:O, xCmdSvc: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: 'The APT39 were using an improved version of Remexi in what the victimology suggests might be a domestic cyber-espionage operation .' [/INST] [The:O, APT39:B-HackOrg, were:O, using:O, an:O, improved:O, version:O, of:O, Remexi:O, in:O, what:O, the:O, victimology:O, suggests:O, might:O, be:O, a:O, domestic:O, cyber-espionage:O, operation:O, .:O] </s> |