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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: 'The Dukes have consistently operated large-scale campaigns against high-profile targets while concurrently engaging in smaller , more targeted campaigns with apparent coordination and no evidence of unintentional overlap or operational clashes .' [/INST] [The:O, Dukes:S-APT, have:O, consistently:O, operated:O, large-scale:O, campaigns:O, against:O, high-profile:O, targets:O, while:O, concurrently:O, engaging:O, in:O, smaller:O, ,:O, more:O, targeted:O, campaigns:O, with:O, apparent:O, coordination:O, and:O, no:O, evidence:O, of:O, unintentional:O, overlap:O, or:O, operational:O, clashes: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 therefore believe the Dukes to be a single , large , wellcoordinated organization with clear separation of responsibilities and targets .' [/INST] [We:O, therefore:O, believe:O, the:O, Dukes:S-APT, to:O, be:O, a:O, single:O, ,:O, large:O, ,:O, wellcoordinated:O, organization:O, with:O, clear:O, separation:O, of:O, responsibilities:O, and:O, targets: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 Dukes appear to prioritize the continuation of their operations over stealth .' [/INST] [The:O, Dukes:S-APT, appear:O, to:O, prioritize:O, the:O, continuation:O, of:O, their:O, operations:O, over:O, stealth: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: 'Their 2015 CozyDuke and CloudDuke campaigns take this to the extreme by apparently opting for speed and quantity over stealth and quality .' [/INST] [Their:O, 2015:O, CozyDuke:S-MAL, and:O, CloudDuke:S-MAL, campaigns:O, take:O, this:O, to:O, the:O, extreme:O, by:O, apparently:O, opting:O, for:O, speed:O, and:O, quantity:O, over:O, stealth:O, and:O, quality: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 most extreme case , the Dukes continued with their July 2015 CloudDuke campaign even after their activity had been outed by multiple security vendors .' [/INST] [In:O, the:O, most:O, extreme:O, case:O, ,:O, the:O, Dukes:S-APT, continued:O, with:O, their:O, July:B-TIME, 2015:E-TIME, CloudDuke:S-MAL, campaign:O, even:O, after:O, their:O, activity:O, had:O, been:O, outed:O, by:O, multiple:O, security:O, vendors: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 therefore believe the Dukes ’ primary mission to be so valuable to their benefactors that its continuation outweighs everything else .' [/INST] [We:O, therefore:O, believe:O, the:O, Dukes:S-APT, ’:O, primary:O, mission:O, to:O, be:O, so:O, valuable:O, to:O, their:O, benefactors:O, that:O, its:O, continuation:O, outweighs:O, everything:O, else: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 apparent disregard for publicity suggests , in our opinion , that the benefactors of the Dukes is so powerful and so tightly connected to the group that the Dukes are able to operate with no apparent fear of repercussions on getting caught .' [/INST] [This:O, apparent:O, disregard:O, for:O, publicity:O, suggests:O, ,:O, in:O, our:O, opinion:O, ,:O, that:O, the:O, benefactors:O, of:O, the:O, Dukes:S-APT, is:O, so:O, powerful:O, and:O, so:O, tightly:O, connected:O, to:O, the:O, group:O, that:O, the:O, Dukes:S-APT, are:O, able:O, to:O, operate:O, with:O, no:O, apparent:O, fear:O, of:O, repercussions:O, on:O, getting:O, caught: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 the only benefactor with the power to offer such comprehensive protection would be the government of the nation from which the group operates .' [/INST] [We:O, believe:O, the:O, only:O, benefactor:O, with:O, the:O, power:O, to:O, offer:O, such:O, comprehensive:O, protection:O, would:O, be:O, the:O, government:O, of:O, the:O, nation:O, from:O, which:O, the:O, group:O, operates: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 therefore believe the Dukes to work either within or directly for a government , thus ruling out the possibility of a criminal gang or another third party .' [/INST] [We:O, therefore:O, believe:O, the:O, Dukes:S-APT, to:O, work:O, either:O, within:O, or:O, directly:O, for:O, a:O, government:O, ,:O, thus:O, ruling:O, out:O, the:O, possibility:O, of:O, a:O, criminal:O, gang:O, or:O, another:O, third:O, party: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: 'Kaspersky Labs has previously noted the presence of Russian-language artefacts in some of the Duke malware samples .' [/INST] [Kaspersky:B-SECTEAM, Labs:E-SECTEAM, has:O, previously:O, noted:O, the:O, presence:O, of:O, Russian-language:O, artefacts:O, in:O, some:O, of:O, the:O, Duke:S-APT, malware:O, samples: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 also found a Russian-language error message in many PinchDuke samples which translates as , “ There is an error in the module ’s name ! The length of the data section name must be 4 bytes! ” Additionally , Kaspersky noted that based on the compilation timestamps , the authors of the Duke malware appear to primarily work from Monday to Friday between the times of 6am and 4pm UTC+0 .' [/INST] [We:O, have:O, also:O, found:O, a:O, Russian-language:O, error:O, message:O, in:O, many:O, PinchDuke:S-MAL, samples:O, which:O, translates:O, as:O, ,:O, “:O, There:O, is:O, an:O, error:O, in:O, the:O, module:O, ’s:O, name:O, !:O, The:O, length:O, of:O, the:O, data:O, section:O, name:O, must:O, be:O, 4:O, bytes!:O, ”:O, Additionally:O, ,:O, Kaspersky:S-SECTEAM, noted:O, that:O, based:O, on:O, the:O, compilation:O, timestamps:O, ,:O, the:O, authors:O, of:O, the:O, Duke:S-APT, malware:O, appear:O, to:O, primarily:O, work:O, from:O, Monday:S-TIME, to:O, Friday:S-TIME, between:O, the:O, times:O, of:O, 6am:S-TIME, and:O, 4pm:S-TIME, UTC+0: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 corresponds to working hours between 9am and 7pm in the UTC+3 time zone , also known as Moscow Standard Time , which covers , among others , much of western Russia , including Moscow and St. Petersburg .' [/INST] [This:O, corresponds:O, to:O, working:O, hours:O, between:O, 9am:S-TIME, and:O, 7pm:S-TIME, in:O, the:O, UTC+3:O, time:O, zone:O, ,:O, also:O, known:O, as:O, Moscow:S-TIME, Standard:B-TOOL, Time:E-TOOL, ,:O, which:O, covers:O, ,:O, among:O, others:O, ,:O, much:O, of:O, western:O, Russia:S-LOC, ,:O, including:O, Moscow:S-LOC, and:O, St.:B-LOC, Petersburg:E-LOC, .: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 Kaspersky Labs analysis of the Duke malware authors ’ working times is supported by our own analysis , as well as that performed by FireEye .' [/INST] [The:O, Kaspersky:B-SECTEAM, Labs:E-SECTEAM, analysis:O, of:O, the:O, Duke:S-APT, malware:O, authors:O, ’:O, working:O, times:O, is:O, supported:O, by:O, our:O, own:O, analysis:O, ,:O, as:O, well:O, as:O, that:O, performed:O, by:O, FireEye:S-SECTEAM, .: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 assertion of time zone is also supported by timestamps found in many GeminiDuke samples , which similarly suggest the group work in the Moscow Standard Time timezone , as further detailed in the section on the technical analysis of GeminiDuke .' [/INST] [This:O, assertion:O, of:O, time:O, zone:O, is:O, also:O, supported:O, by:O, timestamps:O, found:O, in:O, many:O, GeminiDuke:S-MAL, samples:O, ,:O, which:O, similarly:O, suggest:O, the:O, group:O, work:O, in:O, the:O, Moscow:S-LOC, Standard:B-TOOL, Time:E-TOOL, timezone:O, ,:O, as:O, further:O, detailed:O, in:O, the:O, section:O, on:O, the:O, technical:O, analysis:O, of:O, GeminiDuke:S-MAL, .: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: 'Finally , the known targets of the Dukes - Eastern European foreign ministries , western think tanks and governmental organizations , even Russian-speaking drug dealers - conform to publiclyknown Russian foreign policy and security policy interests .' [/INST] [Finally:O, ,:O, the:O, known:O, targets:O, of:O, the:O, Dukes:S-APT, -:O, Eastern:O, European:O, foreign:O, ministries:O, ,:O, western:O, think:O, tanks:O, and:O, governmental:O, organizations:O, ,:O, even:O, Russian-speaking:O, drug:O, dealers:O, -:O, conform:O, to:O, publiclyknown:O, Russian:O, foreign:O, policy:O, and:O, security:O, policy:O, interests: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: 'Even though the Dukes appear to have targeted governments all over the world , we are unaware of them ever targeting the Russian government .' [/INST] [Even:O, though:O, the:O, Dukes:S-APT, appear:O, to:O, have:O, targeted:O, governments:O, all:O, over:O, the:O, world:O, ,:O, we:O, are:O, unaware:O, of:O, them:O, ever:O, targeting:O, the:O, Russian:O, 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: 'While absence of evidence is not evidence of absence , it is an interesting detail to note .' [/INST] [While:O, absence:O, of:O, evidence:O, is:O, not:O, evidence:O, of:O, absence:O, ,:O, it:O, is:O, an:O, interesting:O, detail:O, to:O, note: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: 'Threat Actor Profile : TA505 , From Dridex to GlobeImposter .' [/INST] [Threat:O, Actor:O, Profile:O, ::O, TA505:S-APT, ,:O, From:O, Dridex:S-MAL, to:O, GlobeImposter:S-MAL, .: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 track a wide range of threat actors involved in both financially motivated cybercrime and state-sponsored actions .' [/INST] [Proofpoint:S-SECTEAM, researchers:O, track:O, a:O, wide:O, range:O, of:O, threat:O, actors:O, involved:O, in:O, both:O, financially:O, motivated:O, cybercrime:O, and:O, state-sponsored:O, actions: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 of the more prolific actors that we track - referred to as TA505 - is responsible for the largest malicious spam campaigns we have ever observed , distributing instances of the Dridex banking Trojan , Locky ransomware , Jaff ransomware , The Trick banking Trojan , and several others in very high volumes .' [/INST] [One:O, of:O, the:O, more:O, prolific:O, actors:O, that:O, we:O, track:O, -:O, referred:O, to:O, as:O, TA505:S-APT, -:O, is:O, responsible:O, for:O, the:O, largest:O, malicious:O, spam:O, campaigns:O, we:O, have:O, ever:O, observed:O, ,:O, distributing:O, instances:O, of:O, the:O, Dridex:S-MAL, banking:O, Trojan:S-MAL, ,:O, Locky:S-MAL, ransomware:O, ,:O, Jaff:S-MAL, ransomware:O, ,:O, The:O, Trick:S-MAL, banking:O, Trojan:S-MAL, ,:O, and:O, several:O, others:O, in:O, very:O, high:O, volumes: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 TA505 is such a significant part of the email threat landscape , this blog provides a retrospective on the shifting malware , payloads , and campaigns associated with this actor .' [/INST] [Because:O, TA505:S-APT, is:O, such:O, a:O, significant:O, part:O, of:O, the:O, email:S-TOOL, threat:O, landscape:O, ,:O, this:O, blog:O, provides:O, a:O, retrospective:O, on:O, the:O, shifting:O, malware:O, ,:O, payloads:O, ,:O, and:O, campaigns:O, associated:O, with:O, this:O, actor: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 examine their use malware such as Jaff , Bart , and Rockloader that appear to be exclusive to this group as well as more widely distributed malware like Dridex and Pony .' [/INST] [We:O, examine:O, their:O, use:O, malware:O, such:O, as:O, Jaff:S-MAL, ,:O, Bart:S-MAL, ,:O, and:O, Rockloader:S-MAL, that:O, appear:O, to:O, be:O, exclusive:O, to:O, this:O, group:O, as:O, well:O, as:O, more:O, widely:O, distributed:O, malware:O, like:O, Dridex:S-MAL, and:O, Pony:S-MAL, .: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: 'Where possible , we detail the affiliate models with which they are involved and outline the current state of TA505 campaigns .' [/INST] [Where:O, possible:O, ,:O, we:O, detail:O, the:O, affiliate:O, models:O, with:O, which:O, they:O, are:O, involved:O, and:O, outline:O, the:O, current:O, state:O, of:O, TA505:S-APT, campaigns: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 infographic in Figure 1 traces the earliest known dates on which TA505 began distributing particular malware strains , beginning with Dridex in 2014 and most recently when they elevated GlobeImposter and Philadelphia from small , regionally targeted ransomware variants to global threats .' [/INST] [The:O, infographic:O, in:O, Figure:O, 1:O, traces:O, the:O, earliest:O, known:O, dates:O, on:O, which:O, TA505:S-APT, began:O, distributing:O, particular:O, malware:O, strains:O, ,:O, beginning:O, with:O, Dridex:S-MAL, in:O, 2014:S-TIME, and:O, most:O, recently:O, when:O, they:O, elevated:O, GlobeImposter:S-MAL, and:O, Philadelphia:S-MAL, from:O, small:O, ,:O, regionally:O, targeted:O, ransomware:O, variants:O, to:O, global: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: 'Of note is TA505 ’s use of the Necurs botnet to drive their massive spam campaigns .' [/INST] [Of:O, note:O, is:O, TA505:S-APT, ’s:O, use:O, of:O, the:O, Necurs:S-MAL, botnet:O, to:O, drive:O, their:O, massive:O, spam:O, campaigns: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 we saw in both 2016 and 2017 , disruptions to Necurs went hand-in-hand with quiet periods from TA505 .' [/INST] [As:O, we:O, saw:O, in:O, both:O, 2016:S-TIME, and:O, 2017:S-TIME, ,:O, disruptions:O, to:O, Necurs:S-MAL, went:O, hand-in-hand:O, with:O, quiet:O, periods:O, from:O, TA505:S-APT, .: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 the botnet came back online , TA505 campaigns quickly returned , usually at even greater scale than before the disruption .' [/INST] [When:O, the:O, botnet:O, came:O, back:O, online:O, ,:O, TA505:S-APT, campaigns:O, quickly:O, returned:O, ,:O, usually:O, at:O, even:O, greater:O, scale:O, than:O, before:O, the:O, disruption: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 following is a more detailed description of the malware and notable campaign attributes associated with TA505 .' [/INST] [The:O, following:O, is:O, a:O, more:O, detailed:O, description:O, of:O, the:O, malware:O, and:O, notable:O, campaign:O, attributes:O, associated:O, with:O, TA505:S-APT, .: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 now infamous Dridex banking Trojan can trace much of its DNA to Cridex and Bugat .' [/INST] [The:O, now:O, infamous:O, Dridex:S-MAL, banking:O, Trojan:S-MAL, can:O, trace:O, much:O, of:O, its:O, DNA:O, to:O, Cridex:S-MAL, and:O, Bugat:S-MAL, .: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: 'Dridex itself appeared shortly after the Zeus banking Trojan was taken down .' [/INST] [Dridex:S-MAL, itself:O, appeared:O, shortly:O, after:O, the:O, Zeus:S-MAL, banking:O, Trojan:S-MAL, was:O, taken:O, down: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: 'It was originally documented on July 25 , 2014 ( or June 22 , 2014 , according to Kaspersky ) and the first campaign we observed in which TA505 distributed Dridex occurred three days later on July 28 .' [/INST] [It:O, was:O, originally:O, documented:O, on:O, July:B-TIME, 25:I-TIME, ,:I-TIME, 2014:E-TIME, (:O, or:O, June:B-TIME, 22:I-TIME, ,:I-TIME, 2014:E-TIME, ,:O, according:O, to:O, Kaspersky:S-SECTEAM, ):O, and:O, the:O, first:O, campaign:O, we:O, observed:O, in:O, which:O, TA505:S-APT, distributed:O, Dridex:S-MAL, occurred:O, three:O, days:O, later:O, on:O, July:B-TIME, 28:E-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: 'Although a number of actors have distributed Dridex , TA505 operates multiple affiliate IDs , including what appears to be the earliest recorded affiliate , botnet ID 125 .' [/INST] [Although:O, a:O, number:O, of:O, actors:O, have:O, distributed:O, Dridex:S-MAL, ,:O, TA505:S-APT, operates:O, multiple:O, affiliate:O, IDs:O, ,:O, including:O, what:O, appears:O, to:O, be:O, the:O, earliest:O, recorded:O, affiliate:O, ,:O, botnet:O, ID:O, 125: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: 'These early campaigns were distributed via the Lerspeng downloader while later campaigns occasionally used Pony or Andromeda as intermediate loaders to distribute various instances of Dridex .' [/INST] [These:O, early:O, campaigns:O, were:O, distributed:O, via:O, the:O, Lerspeng:S-MAL, downloader:S-TOOL, while:O, later:O, campaigns:O, occasionally:O, used:O, Pony:S-MAL, or:O, Andromeda:S-MAL, as:O, intermediate:O, loaders:O, to:O, distribute:O, various:O, instances:O, of:O, Dridex:S-MAL, .: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 TA505 initially distributed Dridex botnet ID 125 , they were observed using botnet ID 220 in March 2015 and botnet ID 223 in December of that year .' [/INST] [Although:O, TA505:S-APT, initially:O, distributed:O, Dridex:S-MAL, botnet:O, ID:O, 125:O, ,:O, they:O, were:O, observed:O, using:O, botnet:O, ID:O, 220:O, in:O, March:B-TIME, 2015:E-TIME, and:O, botnet:O, ID:O, 223:O, in:O, December:B-TIME, of:I-TIME, that:I-TIME, year:E-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: 'Later , they were also associated with botnet IDs 7200 and 7500 .' [/INST] [Later:O, ,:O, they:O, were:O, also:O, associated:O, with:O, botnet:O, IDs:O, 7200:O, and:O, 7500: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: 'These botnets generally target the following regions :' [/INST] [These:O, botnets:O, generally:O, target:O, the:O, following:O, regions: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: '125: UK , US , and Canada 220: UK and Australia 223: Germany 7200: UK 7500: Australia .' [/INST] [125::O, UK:S-LOC, ,:O, US:S-LOC, ,:O, and:O, Canada:S-LOC, 220::O, UK:S-LOC, and:O, Australia:S-LOC, 223::O, Germany:S-LOC, 7200::O, UK:S-LOC, 7500::O, Australia:S-LOC, .: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: 'TA505 continued distributing Dridex through early June 2017 using a range of email attachments .' [/INST] [TA505:S-APT, continued:O, distributing:O, Dridex:S-MAL, through:O, early:B-TIME, June:I-TIME, 2017:E-TIME, using:O, a:O, range:O, of:O, email:S-TOOL, attachments: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: 'Most recently these included PDF attachments with embedded Microsoft Word documents bearing malicious macros that call PowerShell commands that install Dridex .' [/INST] [Most:O, recently:O, these:O, included:O, PDF:S-TOOL, attachments:O, with:O, embedded:O, Microsoft:S-IDTY, Word:S-TOOL, documents:O, bearing:O, malicious:O, macros:S-TOOL, that:O, call:O, PowerShell:S-TOOL, commands:O, that:O, install:O, Dridex:S-MAL, .: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 , because of the length of time for which the group has been distributing Dridex , distribution mechanisms trace the state of the art for the last two years of email campaigns with techniques ranging from straight macro documents to a variety of zipped scripts .' [/INST] [However:O, ,:O, because:O, of:O, the:O, length:O, of:O, time:O, for:O, which:O, the:O, group:O, has:O, been:O, distributing:O, Dridex:S-MAL, ,:O, distribution:O, mechanisms:O, trace:O, the:O, state:O, of:O, the:O, art:O, for:O, the:O, last:O, two:O, years:O, of:O, email:S-TOOL, campaigns:O, with:O, techniques:O, ranging:O, from:O, straight:O, macro:S-TOOL, documents:O, to:O, a:O, variety:O, of:O, zipped:S-TOOL, scripts: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 October 2015 , we observed several campaigns in which TA505 targeted Japanese and UK organizations with the Shifu banking Trojan .' [/INST] [In:O, October:B-TIME, 2015:E-TIME, ,:O, we:O, observed:O, several:O, campaigns:O, in:O, which:O, TA505:S-APT, targeted:O, Japanese:O, and:O, UK:S-LOC, organizations:O, with:O, the:O, Shifu:S-MAL, banking:O, Trojan:S-MAL, .: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: 'Shifu is relatively common in Japan but was a new addition to TA505 ’s toolbox .' [/INST] [Shifu:S-MAL, is:O, relatively:O, common:O, in:O, Japan:S-LOC, but:O, was:O, a:O, new:O, addition:O, to:O, TA505:S-APT, ’s:O, toolbox: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: 'It appears that they introduced Shifu after high-profile law enforcement actions impacted Dridex distribution .' [/INST] [It:O, appears:O, that:O, they:O, introduced:O, Shifu:S-MAL, after:O, high-profile:O, law:O, enforcement:O, actions:O, impacted:O, Dridex:S-MAL, distribution: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: 'However , TA505 was also among the first actors to return to high-volume Dridex distribution this same month , even as they demonstrated their ability to diversify and deliver threats beyond Dridex .' [/INST] [However:O, ,:O, TA505:S-APT, was:O, also:O, among:O, the:O, first:O, actors:O, to:O, return:O, to:O, high-volume:O, Dridex:S-MAL, distribution:O, this:O, same:O, month:O, ,:O, even:O, as:O, they:O, demonstrated:O, their:O, ability:O, to:O, diversify:O, and:O, deliver:O, threats:O, beyond:O, Dridex:S-MAL, .: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 of their other campaigns , TA505 delivered Shifu through macro laden Microsoft Office document attachments .' [/INST] [As:O, with:O, many:O, of:O, their:O, other:O, campaigns:O, ,:O, TA505:S-APT, delivered:O, Shifu:S-MAL, through:O, macro:S-TOOL, laden:O, Microsoft:S-IDTY, Office:S-TOOL, document:O, attachments: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: 'TA505 introduced Locky ransomware in February 2016 .' [/INST] [TA505:S-APT, introduced:O, Locky:S-MAL, ransomware:O, in:O, February:B-TIME, 2016:E-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: 'After alternating for over four months with Dridex , Locky became the payload of choice for TA505 , eclipsing earlier campaigns in terms of volume and reach .' [/INST] [After:O, alternating:O, for:O, over:O, four:O, months:O, with:O, Dridex:S-MAL, ,:O, Locky:S-MAL, became:O, the:O, payload:O, of:O, choice:O, for:O, TA505:S-APT, ,:O, eclipsing:O, earlier:O, campaigns:O, in:O, terms:O, of:O, volume:O, and:O, reach: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: 'TA505 stopped distributing Dridex in July 2016 , relying almost exclusively on Locky through December of that year .' [/INST] [TA505:S-APT, stopped:O, distributing:O, Dridex:S-MAL, in:O, July:B-TIME, 2016:E-TIME, ,:O, relying:O, almost:O, exclusively:O, on:O, Locky:S-MAL, through:O, December:B-TIME, of:I-TIME, that:I-TIME, year:E-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: 'Like Dridex , Locky is also distributed in an affiliate model ; TA505 exclusively distributes Locky Affid=3 .' [/INST] [Like:O, Dridex:S-MAL, ,:O, Locky:S-MAL, is:O, also:O, distributed:O, in:O, an:O, affiliate:O, model:O, ;:O, TA505:S-APT, exclusively:O, distributes:O, Locky:S-MAL, Affid=3: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: 'Low-volume campaigns distributed Dridex during much of 2015 Moderate volumes of Dridex appeared from the end of 2015 through February 2016 ; it is worth noting that these “ moderate volume ” campaigns were , at the time , the largest campaigns ever observed .' [/INST] [Low-volume:O, campaigns:O, distributed:O, Dridex:S-MAL, during:O, much:B-TIME, of:I-TIME, 2015:E-TIME, Moderate:O, volumes:O, of:O, Dridex:S-MAL, appeared:O, from:O, the:O, end:B-TIME, of:I-TIME, 2015:I-TIME, through:I-TIME, February:I-TIME, 2016:E-TIME, ;:O, it:O, is:O, worth:O, noting:O, that:O, these:O, “:O, moderate:O, volume:O, ”:O, campaigns:O, were:O, ,:O, at:O, the:O, time:O, ,:O, the:O, largest:O, campaigns:O, ever:O, observed: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: 'Alternating Dridex and Locky campaigns of varying volumes appeared through May 2016 .' [/INST] [Alternating:O, Dridex:S-MAL, and:O, Locky:S-MAL, campaigns:O, of:O, varying:O, volumes:O, appeared:O, through:O, May:B-TIME, 2016:E-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: 'A lull in June 2016 associated with a disruption in the Necurs botnet ; TA505 is heavily reliant on this massive botnet to send out high-volume malicious spam campaigns and disappearances of TA505 activity frequently accompany disruptions in Necurs .' [/INST] [A:O, lull:O, in:O, June:B-TIME, 2016:E-TIME, associated:O, with:O, a:O, disruption:O, in:O, the:O, Necurs:S-MAL, botnet:O, ;:O, TA505:S-APT, is:O, heavily:O, reliant:O, on:O, this:O, massive:O, botnet:O, to:O, send:O, out:O, high-volume:O, malicious:O, spam:O, campaigns:O, and:O, disappearances:O, of:O, TA505:S-APT, activity:O, frequently:O, accompany:O, disruptions:O, in:O, Necurs:S-MAL, .: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: 'Extremely high-volume campaigns distributing Locky exclusively in July 2016 , consistently delivering tens of millions of messages .' [/INST] [Extremely:O, high-volume:O, campaigns:O, distributing:O, Locky:S-MAL, exclusively:O, in:O, July:B-TIME, 2016:E-TIME, ,:O, consistently:O, delivering:O, tens:O, of:O, millions:O, of: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: 'Another lull in November 2016 saw the complete absence of Locky and Dridex , while high-volume campaigns reappeared in December , albeit at lower volumes than during the Q3 2016 peak .' [/INST] [Another:O, lull:O, in:O, November:B-TIME, 2016:E-TIME, saw:O, the:O, complete:O, absence:O, of:O, Locky:S-MAL, and:O, Dridex:S-MAL, ,:O, while:O, high-volume:O, campaigns:O, reappeared:O, in:O, December:S-TIME, ,:O, albeit:O, at:O, lower:O, volumes:O, than:O, during:O, the:O, Q3:O, 2016:S-TIME, peak: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: 'An expected break following the 2016-2017 winter holidays turned into an unexplained three-month hiatus for TA505 .' [/INST] [An:O, expected:O, break:O, following:O, the:O, 2016-2017:B-TIME, winter:E-TIME, holidays:O, turned:O, into:O, an:O, unexplained:O, three-month:O, hiatus:O, for:O, TA505:S-APT, .: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: 'Large-scale Dridex and Locky campaigns returned in Q2 2017 , although none reached the volumes we observed in mid-2016 .' [/INST] [Large-scale:O, Dridex:S-MAL, and:O, Locky:S-MAL, campaigns:O, returned:O, in:O, Q2:O, 2017:S-TIME, ,:O, although:O, none:O, reached:O, the:O, volumes:O, we:O, observed:O, in:O, mid-2016:S-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: 'Later campaigns saw new attachment types , even as Dridex and Locky payloads remained largely unchanged .' [/INST] [Later:O, campaigns:O, saw:O, new:O, attachment:O, types:O, ,:O, even:O, as:O, Dridex:S-MAL, and:O, Locky:S-MAL, payloads:O, remained:O, largely:O, unchanged: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: 'Locky distribution ceased in June and July but returned in August with volumes rivaling the peaks of 2016 .' [/INST] [Locky:S-MAL, distribution:O, ceased:O, in:O, June:S-TIME, and:O, July:S-TIME, but:O, returned:O, in:O, August:S-TIME, with:O, volumes:O, rivaling:O, the:O, peaks:O, of:O, 2016:S-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: 'TA505 turned to URLs in early August 2017 to distribute Locky , finally eschewing the document or zipped script attachments that have characterized the majority of their Locky campaigns since February 2016 ; most of these URLs linked to malicious documents and scripts .' [/INST] [TA505:S-APT, turned:O, to:O, URLs:O, in:O, early:O, August:B-TIME, 2017:E-TIME, to:O, distribute:O, Locky:S-MAL, ,:O, finally:O, eschewing:O, the:O, document:O, or:O, zipped:S-TOOL, script:O, attachments:O, that:O, have:O, characterized:O, the:O, majority:O, of:O, their:O, Locky:S-MAL, campaigns:O, since:O, February:B-TIME, 2016:E-TIME, ;:O, most:O, of:O, these:O, URLs:O, linked:O, to:O, malicious:O, documents:O, and:O, scripts: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: 'By later August , TA505 had turned back to large attachment campaigns , primarily distributing various zipped scripts that downloaded Locky .' [/INST] [By:O, later:O, August:S-TIME, ,:O, TA505:S-APT, had:O, turned:O, back:O, to:O, large:O, attachment:O, campaigns:O, ,:O, primarily:O, distributing:O, various:O, zipped:S-TOOL, scripts:O, that:O, downloaded:O, Locky:S-MAL, .: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 continued this pattern with occasional URL campaigns and attached HTML files bearing malicious links .' [/INST] [The:O, group:O, continued:O, this:O, pattern:O, with:O, occasional:O, URL:O, campaigns:O, and:O, attached:O, HTML:S-TOOL, files:O, bearing:O, malicious:O, links: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: 'TA505 first introduced Rockloader in April 2016 as an intermediate loader for Locky .' [/INST] [TA505:S-APT, first:O, introduced:O, Rockloader:S-MAL, in:O, April:B-TIME, 2016:E-TIME, as:O, an:O, intermediate:O, loader:S-TOOL, for:O, Locky:S-MAL, .: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 that time , Rockloader was the initial payload downloaded by malicious attached JavaScript files .' [/INST] [At:O, that:O, time:O, ,:O, Rockloader:S-MAL, was:O, the:O, initial:O, payload:O, downloaded:O, by:O, malicious:O, attached:O, JavaScript:S-TOOL, 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: 'Once Rockloader was installed , it downloaded Locky and , in some cases , Pony and Kegotip .' [/INST] [Once:O, Rockloader:S-MAL, was:O, installed:O, ,:O, it:O, downloaded:O, Locky:S-MAL, and:O, ,:O, in:O, some:O, cases:O, ,:O, Pony:S-MAL, and:O, Kegotip:S-MAL, .: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: 'Pony is another loader with information stealing capabilities while Kegotip is an credential and email address harvesting malware strain that would appear in a small number of TA505 campaigns the following year as the primary payload .' [/INST] [Pony:S-MAL, is:O, another:O, loader:S-TOOL, with:O, information:O, stealing:O, capabilities:O, while:O, Kegotip:S-MAL, is:O, an:O, credential:O, and:O, email:S-TOOL, address:O, harvesting:O, malware:O, strain:O, that:O, would:O, appear:O, in:O, a:O, small:O, number:O, of:O, TA505:S-APT, campaigns:O, the:O, following:O, year:O, as:O, the:O, primary: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: 'Bart ransomware appeared for exactly one day on June 24 , 2016 .' [/INST] [Bart:S-MAL, ransomware:O, appeared:O, for:O, exactly:O, one:O, day:O, on:O, June:B-TIME, 24:I-TIME, ,:I-TIME, 2016:E-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: 'It was a secondary payload downloaded by Rockloader , the initial payload in a large email campaign using zipped JavaScript attachments .' [/INST] [It:O, was:O, a:O, secondary:O, payload:O, downloaded:O, by:O, Rockloader:S-MAL, ,:O, the:O, initial:O, payload:O, in:O, a:O, large:O, email:S-TOOL, campaign:O, using:O, zipped:S-TOOL, JavaScript:S-TOOL, attachments: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 Bart ransom screen was visually similar to Locky ’s but Bart had one important distinction : it could encrypt files without contacting a command and control server .' [/INST] [The:O, Bart:S-MAL, ransom:O, screen:O, was:O, visually:O, similar:O, to:O, Locky:S-MAL, ’s:O, but:O, Bart:S-MAL, had:O, one:O, important:O, distinction:O, ::O, it:O, could:O, encrypt:O, files:O, without:O, contacting:O, a:O, command:O, and:O, control:O, server: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: 'However , we have not seen Bart since , suggesting that this was either an experiment or that the ransomware did not function as expected for TA505 .' [/INST] [However:O, ,:O, we:O, have:O, not:O, seen:O, Bart:S-MAL, since:O, ,:O, suggesting:O, that:O, this:O, was:O, either:O, an:O, experiment:O, or:O, that:O, the:O, ransomware:O, did:O, not:O, function:O, as:O, expected:O, for:O, TA505:S-APT, .: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: 'TA505 briefly distributed the Kegotip information stealer in April 2017 .' [/INST] [TA505:S-APT, briefly:O, distributed:O, the:O, Kegotip:S-MAL, information:B-TOOL, stealer:E-TOOL, in:O, April:B-TIME, 2017:E-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: 'Across two campaigns of several million messages each , the actor used both macro laden Microsoft Word documents and zipped VBScript attachments to install the Trojan on potential victim PCs .' [/INST] [Across:O, two:O, campaigns:O, of:O, several:O, million:O, messages:O, each:O, ,:O, the:O, actor:O, used:O, both:O, macro:S-TOOL, laden:O, Microsoft:S-IDTY, Word:S-TOOL, documents:O, and:O, zipped:S-TOOL, VBScript:S-TOOL, attachments:O, to:O, install:O, the:O, Trojan:S-MAL, on:O, potential:O, victim:O, PCs:S-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: 'Kegotip is an infostealer ( credentials and email addresses ) used to facilitate other crimeware activities .' [/INST] [Kegotip:S-MAL, is:O, an:O, infostealer:S-TOOL, (:O, credentials:O, and:O, email:S-TOOL, addresses:O, ):O, used:O, to:O, facilitate:O, other:O, crimeware:O, activities: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: 'It steals credentials from various FTP clients , Outlook , and Internet Explorer .' [/INST] [It:O, steals:O, credentials:O, from:O, various:O, FTP:S-PROT, clients:O, ,:O, Outlook:S-TOOL, ,:O, and:O, Internet:B-TOOL, Explorer:E-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 also will gather email addresses scraped from files stored on the computer .' [/INST] [It:O, also:O, will:O, gather:O, email:S-TOOL, addresses:O, scraped:O, from:O, files:O, stored:O, on:O, the:O, computer: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 information can be used to facilitate future spam campaigns by the perpetrator or may be sold to other actors .' [/INST] [This:O, information:O, can:O, be:O, used:O, to:O, facilitate:O, future:O, spam:O, campaigns:O, by:O, the:O, perpetrator:O, or:O, may:O, be:O, sold:O, to:O, other: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: 'TA505 introduced Jaff ransomware in May 2017 .' [/INST] [TA505:S-APT, introduced:O, Jaff:S-MAL, ransomware:O, in:O, May:B-TIME, 2017:E-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: 'Jaff was not dramatically different from other ransomware strains .' [/INST] [Jaff:S-MAL, was:O, not:O, dramatically:O, different:O, from:O, other:O, ransomware:O, strains: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 payment portal was initially similar to the one used by Locky and Bart .' [/INST] [The:O, payment:O, portal:O, was:O, initially:O, similar:O, to:O, the:O, one:O, used:O, by:O, Locky:S-MAL, and:O, Bart:S-MAL, .: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 was primarily notable for its high-volume campaigns and its association with TA505 , given the actor ’s propensity for massive campaigns and ability to dominate the email landscape .' [/INST] [It:O, was:O, primarily:O, notable:O, for:O, its:O, high-volume:O, campaigns:O, and:O, its:O, association:O, with:O, TA505:S-APT, ,:O, given:O, the:O, actor:O, ’s:O, propensity:O, for:O, massive:O, campaigns:O, and:O, ability:O, to:O, dominate:O, the:O, email:S-TOOL, landscape: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: 'Jaff appeared in multi-million message campaigns for roughly a month and then promptly disappeared as soon as a decryptor was released in mid-June 2017 .' [/INST] [Jaff:S-MAL, appeared:O, in:O, multi-million:O, message:O, campaigns:O, for:O, roughly:O, a:O, month:O, and:O, then:O, promptly:O, disappeared:O, as:O, soon:O, as:O, a:O, decryptor:S-TOOL, was:O, released:O, in:O, mid-June:B-TIME, 2017:E-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 Trick , also known as Trickbot , is another banking Trojan that TA505 first began distributing in June of 2017 , although we have observed The Trick in the wild since fall 2016 , usually in regionally targeted campaigns .' [/INST] [The:O, Trick:S-MAL, ,:O, also:O, known:O, as:O, Trickbot:S-MAL, ,:O, is:O, another:O, banking:O, Trojan:S-MAL, that:O, TA505:S-APT, first:O, began:O, distributing:O, in:O, June:B-TIME, of:I-TIME, 2017:E-TIME, ,:O, although:O, we:O, have:O, observed:O, The:O, Trick:S-MAL, in:O, the:O, wild:O, since:O, fall:B-TIME, 2016:E-TIME, ,:O, usually:O, in:O, regionally:O, targeted:O, campaigns: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: 'It is generally considered a descendant of the Dyreza banking Trojan and features mutliple modules .' [/INST] [It:O, is:O, generally:O, considered:O, a:O, descendant:O, of:O, the:O, Dyreza:S-MAL, banking:O, Trojan:S-MAL, and:O, features:O, mutliple:O, modules: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 main bot is responsible for persistence , the downloading of additional modules , loading affiliate payloads , and loading updates for the malware .' [/INST] [The:O, main:O, bot:O, is:O, responsible:O, for:O, persistence:O, ,:O, the:O, downloading:O, of:O, additional:O, modules:O, ,:O, loading:O, affiliate:O, payloads:O, ,:O, and:O, loading:O, updates:O, for:O, the: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: 'As with much of the malware distributed by TA505 , The Trick has appeared in frequent , high-volume campaigns .' [/INST] [As:O, with:O, much:O, of:O, the:O, malware:O, distributed:O, by:O, TA505:S-APT, ,:O, The:O, Trick:S-MAL, has:O, appeared:O, in:O, frequent:O, ,:O, high-volume:O, campaigns: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 campaigns used a mix of attached zipped scripts ( WSF , VBS ) , malicious Microsoft Office documents ( Word , Excel ) , HTML attachments , password-protected Microsoft Word documents , links to malicious JavaScript , and other vectors .' [/INST] [The:O, campaigns:O, used:O, a:O, mix:O, of:O, attached:O, zipped:S-TOOL, scripts:O, (:O, WSF:S-TOOL, ,:O, VBS:S-TOOL, ):O, ,:O, malicious:O, Microsoft:S-IDTY, Office:S-TOOL, documents:O, (:O, Word:S-TOOL, ,:O, Excel:S-TOOL, ):O, ,:O, HTML:S-TOOL, attachments:O, ,:O, password-protected:O, Microsoft:S-IDTY, Word:S-TOOL, documents:O, ,:O, links:O, to:O, malicious:O, JavaScript:S-TOOL, ,:O, and:O, other:O, vectors: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 last TA505 campaigns featuring The Trick appeared in mid-September 2017 with payloads alternating between Locky and The Trick .' [/INST] [The:O, last:O, TA505:S-APT, campaigns:O, featuring:O, The:O, Trick:S-MAL, appeared:O, in:O, mid-September:B-TIME, 2017:E-TIME, with:O, payloads:O, alternating:O, between:O, Locky:S-MAL, and:O, The:O, Trick:S-MAL, .: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: 'Philadelphia ransomware has been circulating since September 2016 .' [/INST] [Philadelphia:S-MAL, ransomware:O, has:O, been:O, circulating:O, since:O, September:B-TIME, 2016:E-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: 'It first attracted our attention in April of this year when we observed an actor customizing the malware for use in highly targeted campaigns .' [/INST] [It:O, first:O, attracted:O, our:O, attention:O, in:O, April:B-TIME, of:I-TIME, this:I-TIME, year:E-TIME, when:O, we:O, observed:O, an:O, actor:O, customizing:O, the:O, malware:O, for:O, use:O, in:O, highly:O, targeted:O, campaigns: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 a brief stint , TA505 distributed it in one large campaign in July , but we have not seen them use it since .' [/INST] [In:O, a:O, brief:O, stint:O, ,:O, TA505:S-APT, distributed:O, it:O, in:O, one:O, large:O, campaign:O, in:O, July:S-TIME, ,:O, but:O, we:O, have:O, not:O, seen:O, them:O, use:O, it:O, since: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: 'GlobeImposter is another ransomware strain that saw relatively small-scale distribution until TA505 began including it in malicious spam campaigns at the end of July 2017 .' [/INST] [GlobeImposter:S-MAL, is:O, another:O, ransomware:O, strain:O, that:O, saw:O, relatively:O, small-scale:O, distribution:O, until:O, TA505:S-APT, began:O, including:O, it:O, in:O, malicious:O, spam:O, campaigns:O, at:O, the:O, end:B-TIME, of:I-TIME, July:I-TIME, 2017:E-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: 'TA505 primarily distributed GlobeImposter in zipped script attachments through the beginning of September 2017 .' [/INST] [TA505:S-APT, primarily:O, distributed:O, GlobeImposter:S-MAL, in:O, zipped:S-TOOL, script:O, attachments:O, through:O, the:O, beginning:O, of:O, September:B-TIME, 2017:E-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: 'Again , GlobeImposter is not particularly innovative but TA505 elevated the ransomware from a regional variant to a major landscape feature during roughly six weeks of large campaigns .' [/INST] [Again:O, ,:O, GlobeImposter:S-MAL, is:O, not:O, particularly:O, innovative:O, but:O, TA505:S-APT, elevated:O, the:O, ransomware:O, from:O, a:O, regional:O, variant:O, to:O, a:O, major:O, landscape:O, feature:O, during:O, roughly:O, six:O, weeks:O, of:O, large:O, campaigns: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: 'TA505 is arguably one of the most significant financially motivated threat actors because of the extraordinary volumes of messages they send .' [/INST] [TA505:S-APT, is:O, arguably:O, one:O, of:O, the:O, most:O, significant:O, financially:O, motivated:O, threat:O, actors:O, because:O, of:O, the:O, extraordinary:O, volumes:O, of:O, messages:O, they:O, send: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 variety of malware delivered by the group also demonstrates their deep connections to the underground malware scene .' [/INST] [The:O, variety:O, of:O, malware:O, delivered:O, by:O, the:O, group:O, also:O, demonstrates:O, their:O, deep:O, connections:O, to:O, the:O, underground:O, malware:O, scene: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: 'At the time of writing , Locky ransomware remains their malware of choice , even as the group continues to experiment with a variety of additional malware .' [/INST] [At:O, the:O, time:O, of:O, writing:O, ,:O, Locky:S-MAL, ransomware:O, remains:O, their:O, malware:O, of:O, choice:O, ,:O, even:O, as:O, the:O, group:O, continues:O, to:O, experiment:O, with:O, a:O, variety:O, of:O, additional: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 history of TA505 is instructive because they: Have proven to be highly adaptable , shifting techniques and malware frequently to “ follow the money ” , while largely sticking to successful strategies where possible Are flexible , using largely interchangeable components , innovating where necessary on the malware front and using off-the-shelf malware where possible Operate at massive scale , consistently driving global trends in malware distribution and message volume .' [/INST] [The:O, history:O, of:O, TA505:S-APT, is:O, instructive:O, because:O, they::O, Have:O, proven:O, to:O, be:O, highly:O, adaptable:O, ,:O, shifting:O, techniques:O, and:O, malware:O, frequently:O, to:O, “:O, follow:O, the:O, money:O, ”:O, ,:O, while:O, largely:O, sticking:O, to:O, successful:O, strategies:O, where:O, possible:O, Are:O, flexible:O, ,:O, using:O, largely:O, interchangeable:O, components:O, ,:O, innovating:O, where:O, necessary:O, on:O, the:O, malware:O, front:O, and:O, using:O, off-the-shelf:O, malware:O, where:O, possible:O, Operate:O, at:O, massive:O, scale:O, ,:O, consistently:O, driving:O, global:O, trends:O, in:O, malware:O, distribution:O, and:O, message:O, volume: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: 'Each of these elements makes TA505 a magnifying lens through which to consider the framework employed by many modern threat actors .' [/INST] [Each:O, of:O, these:O, elements:O, makes:O, TA505:S-APT, a:O, magnifying:O, lens:O, through:O, which:O, to:O, consider:O, the:O, framework:O, employed:O, by:O, many:O, modern: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: 'Such a framework typically consists of five elements :' [/INST] [Such:O, a:O, framework:O, typically:O, consists:O, of:O, five:O, elements: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: 'Actor : The attacker organization ; real humans driven by various motivations -- In the case of TA505 , the motivations are financial .' [/INST] [Actor:O, ::O, The:O, attacker:O, organization:O, ;:O, real:O, humans:O, driven:O, by:O, various:O, motivations:O, --:O, In:O, the:O, case:O, of:O, TA505:S-APT, ,:O, the:O, motivations:O, are:O, financial: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: 'Vector : The delivery mechanism ; email via attacker-controlled or leased spam botnet -- Necurs for TA505 -- remains a dominant vector , and certainly the vector of choice for this actor .' [/INST] [Vector:O, ::O, The:O, delivery:O, mechanism:O, ;:O, email:S-TOOL, via:O, attacker-controlled:O, or:O, leased:O, spam:O, botnet:O, --:O, Necurs:S-MAL, for:O, TA505:S-APT, --:O, remains:O, a:O, dominant:O, vector:O, ,:O, and:O, certainly:O, the:O, vector:O, of:O, choice:O, for:O, this:O, actor:O, .:O] </s> |