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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: 'Hoster : The sites hosting malware ; if malware is not directly attached to email , then macro enabled documents , malicious scripts , or exploit kits will pull payloads from these servers .' [/INST] [Hoster:O, ::O, The:O, sites:O, hosting:O, malware:O, ;:O, if:O, malware:O, is:O, not:O, directly:O, attached:O, to:O, email:S-TOOL, ,:O, then:O, macro:S-TOOL, enabled:O, documents:O, ,:O, malicious:O, scripts:O, ,:O, or:O, exploit:O, kits:O, will:O, pull:O, payloads:O, from:O, these:O, servers: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 almost exclusively hosts malware in this way , although they vary the means of installing their final payloads on victim machines .' [/INST] [TA505:S-APT, almost:O, exclusively:O, hosts:O, malware:O, in:O, this:O, way:O, ,:O, although:O, they:O, vary:O, the:O, means:O, of:O, installing:O, their:O, final:O, payloads:O, on:O, victim:O, machines: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: 'Payload : The malware ; software that will enable the attacker to make use of ( control , exfiltrate data from , or download more software to ) the target computer .' [/INST] [Payload:O, ::O, The:O, malware:O, ;:O, software:O, that:O, will:O, enable:O, the:O, attacker:O, to:O, make:O, use:O, of:O, (:O, control:O, ,:O, exfiltrate:O, data:O, from:O, ,:O, or:O, download:O, more:O, software:O, to:O, ):O, the:O, target: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: 'For TA505 , the payloads have shifted over the years and months of their activity , but their sending and hosting infrastructure make these changes relatively simple to implement .' [/INST] [For:O, TA505:S-APT, ,:O, the:O, payloads:O, have:O, shifted:O, over:O, the:O, years:O, and:O, months:O, of:O, their:O, activity:O, ,:O, but:O, their:O, sending:O, and:O, hosting:O, infrastructure:O, make:O, these:O, changes:O, relatively:O, simple:O, to:O, implement: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: 'C&C : The command and control channel that serves to relay commands between the installed malware and attackers .' [/INST] [C&C:S-TOOL, ::O, The:O, command:B-TOOL, and:I-TOOL, control:E-TOOL, channel:O, that:O, serves:O, to:O, relay:O, commands:O, between:O, the:O, installed:O, malware:O, and:O, attackers: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 operates a variety of C&C servers , allowing it to be resilient in the case of takedowns , sinkholes , and other defensive operations .' [/INST] [TA505:S-APT, operates:O, a:O, variety:O, of:O, C&C:S-TOOL, servers:O, ,:O, allowing:O, it:O, to:O, be:O, resilient:O, in:O, the:O, case:O, of:O, takedowns:O, ,:O, sinkholes:O, ,:O, and:O, other:O, defensive: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: 'This framework enables attackers to operate in robust , horizontally segmented ecosystems , specializing in developing certain parts of the framework , and selling or leasing to others ; such frameworks are resistant to takedowns and individual component failures .' [/INST] [This:O, framework:O, enables:O, attackers:O, to:O, operate:O, in:O, robust:O, ,:O, horizontally:O, segmented:O, ecosystems:O, ,:O, specializing:O, in:O, developing:O, certain:O, parts:O, of:O, the:O, framework:O, ,:O, and:O, selling:O, or:O, leasing:O, to:O, others:O, ;:O, such:O, frameworks:O, are:O, resistant:O, to:O, takedowns:O, and:O, individual:O, component:O, failures: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: 'But such frameworks also increase attackers' detection surface , that is , their susceptibility to discovery .' [/INST] [But:O, such:O, frameworks:O, also:O, increase:O, attackers':O, detection:O, surface:O, ,:O, that:O, is:O, ,:O, their:O, susceptibility:O, to:O, discovery: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 case of TA505 , while most elements of the framework are well-developed , their reliance on the Necurs botnet for the sending high-volume malicious spam - a key component of the Vector element above - appears to be their Achilles heel .' [/INST] [In:O, the:O, case:O, of:O, TA505:S-APT, ,:O, while:O, most:O, elements:O, of:O, the:O, framework:O, are:O, well-developed:O, ,:O, their:O, reliance:O, on:O, the:O, Necurs:S-MAL, botnet:O, for:O, the:O, sending:O, high-volume:O, malicious:O, spam:O, -:O, a:O, key:O, component:O, of:O, the:O, Vector:O, element:O, above:O, -:O, appears:O, to:O, be:O, their:O, Achilles:S-MAL, heel: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: 'A XENOTIME to Remember : Veles in the Wild .' [/INST] [A:O, XENOTIME:S-APT, to:O, Remember:O, ::O, Veles:S-TOOL, in:O, the:O, Wild: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: 'Release_Time : 2019-12-04' [/INST] [Release_Time:O, ::O, 2019-12-04:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Report_URL : https://pylos.co/2019/04/12/a-xenotime-to-remember-veles-in-the-wild/' [/INST] [Report_URL:O, ::O, https://pylos.co/2019/04/12/a-xenotime-to-remember-veles-in-the-wild/:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 I use a word , ” Humpty Dumpty said , in rather a scornful tone , “ it means just what I choose it to mean—neither more nor less. ” – Through the Looking Glass , Lewis Carroll FireEye recently published a blog covering the tactics , techniques , and procedures ( TTPs ) for the “ TRITON actor ” when preparing to deploy the malware framework in 2017 .' [/INST] [“:O, When:O, I:O, use:O, a:O, word:O, ,:O, ”:O, Humpty:O, Dumpty:O, said:O, ,:O, in:O, rather:O, a:O, scornful:O, tone:O, ,:O, “:O, it:O, means:O, just:O, what:O, I:O, choose:O, it:O, to:O, mean—neither:O, more:O, nor:O, less.:O, ”:O, –:O, Through:O, the:O, Looking:B-IDTY, Glass:E-IDTY, ,:O, Lewis:O, Carroll:O, FireEye:S-SECTEAM, recently:O, published:O, a:O, blog:O, covering:O, the:O, tactics:O, ,:O, techniques:O, ,:O, and:O, procedures:O, (:O, TTPs:O, ):O, for:O, the:O, “:O, TRITON:S-MAL, actor:O, ”:O, when:O, preparing:O, to:O, deploy:O, the:O, malware:O, framework:O, in:O, 2017: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: 'Overall , the post does a commendable job in making public findings previously only privately shared ( presumably by FireEye , and in several reports I authored for my employer , Dragos ) to threat intelligence customers .' [/INST] [Overall:O, ,:O, the:O, post:O, does:O, a:O, commendable:O, job:O, in:O, making:O, public:O, findings:O, previously:O, only:O, privately:O, shared:O, (:O, presumably:O, by:O, FireEye:S-SECTEAM, ,:O, and:O, in:O, several:O, reports:O, I:O, authored:O, for:O, my:O, employer:O, ,:O, Dragos:S-SECTEAM, ):O, to:O, threat:O, intelligence:O, customers: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 such , the blog continues to push forward the narrative of how ICS attacks are enabled through prepositioning and initial intrusion operations – an item I have discussed at length .' [/INST] [As:O, such:O, ,:O, the:O, blog:O, continues:O, to:O, push:O, forward:O, the:O, narrative:O, of:O, how:O, ICS:B-ACT, attacks:E-ACT, are:O, enabled:O, through:O, prepositioning:O, and:O, initial:O, intrusion:O, operations:O, –:O, an:O, item:O, I:O, have:O, discussed:O, at:O, length: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: 'Yet one point of confusion in the blog comes at the very start : referring to the entity responsible for TRITON as the “ TRITON actor ” .' [/INST] [Yet:O, one:O, point:O, of:O, confusion:O, in:O, the:O, blog:O, comes:O, at:O, the:O, very:O, start:O, ::O, referring:O, to:O, the:O, entity:O, responsible:O, for:O, TRITON:S-MAL, as:O, the:O, “:O, TRITON:S-MAL, actor: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: 'This seems confusing as FireEye earlier publicly declared the “ TRITON actor ” as a discrete entity , linked to a Russian research institution , and christened it as “ TEMP.Veles ” .' [/INST] [This:O, seems:O, confusing:O, as:O, FireEye:S-SECTEAM, earlier:O, publicly:O, declared:O, the:O, “:O, TRITON:S-MAL, actor:O, ”:O, as:O, a:O, discrete:O, entity:O, ,:O, linked:O, to:O, a:O, Russian:O, research:O, institution:O, ,:O, and:O, christened:O, it:O, as:O, “:O, TEMP.Veles:S-APT, ”: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 2018 public posting announcing TEMP.Veles , FireEye researchers noted that the institute in question at least supported TEMP.Veles activity in deploying TRITON , with subsequent public presentations at Cyberwarcon and the Kaspersky Lab sponsored Security Analyst Summit essentially linking TRITON and the research institute ( and therefore TEMP.Veles ) as one in the same .' [/INST] [In:O, the:O, 2018:S-TIME, public:O, posting:O, announcing:O, TEMP.Veles:S-APT, ,:O, FireEye:S-SECTEAM, researchers:O, noted:O, that:O, the:O, institute:O, in:O, question:O, at:O, least:O, supported:O, TEMP.Veles:S-APT, activity:O, in:O, deploying:O, TRITON:S-MAL, ,:O, with:O, subsequent:O, public:O, presentations:O, at:O, Cyberwarcon:S-SECTEAM, and:O, the:O, Kaspersky:B-SECTEAM, Lab:E-SECTEAM, sponsored:O, Security:B-SECTEAM, Analyst:I-SECTEAM, Summit:E-SECTEAM, essentially:O, linking:O, TRITON:S-MAL, and:O, the:O, research:O, institute:O, (:O, and:O, therefore:O, TEMP.Veles:S-APT, ):O, as:O, one:O, in:O, the:O, same: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: 'Yet the most-recent posting covering TTPs from initial access through prerequisites to enable final delivery of effects on target ( deploying ) avoids the use of the TEMP.Veles term entirely .' [/INST] [Yet:O, the:O, most-recent:O, posting:O, covering:O, TTPs:S-PROT, from:O, initial:O, access:O, through:O, prerequisites:O, to:O, enable:O, final:O, delivery:O, of:O, effects:O, on:O, target:O, (:O, deploying:O, ):O, avoids:O, the:O, use:O, of:O, the:O, TEMP.Veles:S-APT, term:O, entirely: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 subsequent discussion , FireEye personnel indicate that there was not “ an avalanche of evidence to substantiate ” anything more than “ TRITON actor ” – summing matters by indicating this term “ is the best we ’ve got for the public for now ” .' [/INST] [In:O, subsequent:O, discussion:O, ,:O, FireEye:S-SECTEAM, personnel:O, indicate:O, that:O, there:O, was:O, not:O, “:O, an:O, avalanche:O, of:O, evidence:O, to:O, substantiate:O, ”:O, anything:O, more:O, than:O, “:O, TRITON:S-MAL, actor:O, ”:O, –:O, summing:O, matters:O, by:O, indicating:O, this:O, term:O, “:O, is:O, the:O, best:O, we:O, ’ve:O, got:O, for:O, the:O, public:O, for:O, now: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: 'Meanwhile , parallel work at Dragos ( my employer , where I have performed significant work on the activity described above ) uncovered similar conclusions concerning TTPs and behaviors , for both the 2017 event and subsequent activity in other industrial sectors .' [/INST] [Meanwhile:O, ,:O, parallel:O, work:O, at:O, Dragos:S-SECTEAM, (:O, my:O, employer:O, ,:O, where:O, I:O, have:O, performed:O, significant:O, work:O, on:O, the:O, activity:O, described:O, above:O, ):O, uncovered:O, similar:O, conclusions:O, concerning:O, TTPs:S-PROT, and:O, behaviors:O, ,:O, for:O, both:O, the:O, 2017:S-TIME, event:O, and:O, subsequent:O, activity:O, in:O, other:O, industrial:O, sectors: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: 'Utilizing Diamond Model methodology for characterizing activity by behaviors attached to victims , we began tracking and immediate enabling activity as a distinct activity group ( collection of behaviors , infrastructure , and victimology ) designated XENOTIME .' [/INST] [Utilizing:O, Diamond:O, Model:O, methodology:O, for:O, characterizing:O, activity:O, by:O, behaviors:O, attached:O, to:O, victims:O, ,:O, we:O, began:O, tracking:O, and:O, immediate:O, enabling:O, activity:O, as:O, a:O, distinct:O, activity:O, group:O, (:O, collection:O, of:O, behaviors:O, ,:O, infrastructure:O, ,:O, and:O, victimology:O, ):O, designated:O, XENOTIME: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: 'Based on information gained from discussion with the initial responders and subsequent work on follow-on activity by this entity , Dragos developed a comprehensive ( public ) picture of adversary activity roughly matching FireEye ’s analysis published in April 2019 , described in various media .' [/INST] [Based:O, on:O, information:O, gained:O, from:O, discussion:O, with:O, the:O, initial:O, responders:O, and:O, subsequent:O, work:O, on:O, follow-on:O, activity:O, by:O, this:O, entity:O, ,:O, Dragos:S-SECTEAM, developed:O, a:O, comprehensive:O, (:O, public:O, ):O, picture:O, of:O, adversary:O, activity:O, roughly:O, matching:O, FireEye:S-SECTEAM, ’s:O, analysis:O, published:O, in:O, April:B-TIME, 2019:E-TIME, ,:O, described:O, in:O, various:O, media: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 this stage , we have two similar , parallel constructions of events – the how behind the immediate deployment and execution of – yet dramatically different responses in terms of attribution and labeling .' [/INST] [At:O, this:O, stage:O, ,:O, we:O, have:O, two:O, similar:O, ,:O, parallel:O, constructions:O, of:O, events:O, –:O, the:O, how:O, behind:O, the:O, immediate:O, deployment:O, and:O, execution:O, of:O, –:O, yet:O, dramatically:O, different:O, responses:O, in:O, terms:O, of:O, attribution:O, and:O, labeling: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 late 2018 , based upon the most-recent posting , FireEye appears to have “ walked back ” the previously-used terminology of TEMP.Veles and instead refers rather cryptically to the “ TRITON actor ” , while Dragos leveraged identified behaviors to consistently refer to an activity group , XENOTIME .' [/INST] [Since:O, late:B-TIME, 2018:E-TIME, ,:O, based:O, upon:O, the:O, most-recent:O, posting:O, ,:O, FireEye:S-SECTEAM, appears:O, to:O, have:O, “:O, walked:O, back:O, ”:O, the:O, previously-used:O, terminology:O, of:O, TEMP.Veles:S-APT, and:O, instead:O, refers:O, rather:O, cryptically:O, to:O, the:O, “:O, TRITON:S-MAL, actor:O, ”:O, ,:O, while:O, Dragos:S-SECTEAM, leveraged:O, identified:O, behaviors:O, to:O, consistently:O, refer:O, to:O, an:O, activity:O, group:O, ,:O, XENOTIME: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: 'Given that both organizations appear to describe similar ( if not identical ) activity , any reasonable person could ( and should ) ask – why the inconsistency in naming and identification? Aside from the competitive vendor naming landscape ( which I am not a fan of in cases on direct overlap , but which has more to say for itself when different methodologies are employed around similar observations ) , the distinction between FireEye and Dragos ’ approaches with respect to the “ TRITON actor ” comes down to fundamental philosophical differences in methodology .' [/INST] [Given:O, that:O, both:O, organizations:O, appear:O, to:O, describe:O, similar:O, (:O, if:O, not:O, identical:O, ):O, activity:O, ,:O, any:O, reasonable:O, person:O, could:O, (:O, and:O, should:O, ):O, ask:O, –:O, why:O, the:O, inconsistency:O, in:O, naming:O, and:O, identification?:O, Aside:O, from:O, the:O, competitive:O, vendor:O, naming:O, landscape:O, (:O, which:O, I:O, am:O, not:O, a:O, fan:O, of:O, in:O, cases:O, on:O, direct:O, overlap:O, ,:O, but:O, which:O, has:O, more:O, to:O, say:O, for:O, itself:O, when:O, different:O, methodologies:O, are:O, employed:O, around:O, similar:O, observations:O, ):O, ,:O, the:O, distinction:O, between:O, FireEye:S-SECTEAM, and:O, Dragos:S-SECTEAM, ’:O, approaches:O, with:O, respect:O, to:O, the:O, “:O, TRITON:S-MAL, actor:O, ”:O, comes:O, down:O, to:O, fundamental:O, philosophical:O, differences:O, in:O, methodology: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 wonderfully described in a recent public posting , FireEye adheres to a naming convention based upon extensive data collection and activity comparison , designed to yield the identification of a discrete , identifiable entity responsible for a given collection of activity .' [/INST] [As:O, wonderfully:O, described:O, in:O, a:O, recent:O, public:O, posting:O, ,:O, FireEye:S-SECTEAM, adheres:O, to:O, a:O, naming:O, convention:O, based:O, upon:O, extensive:O, data:O, collection:O, and:O, activity:O, comparison:O, ,:O, designed:O, to:O, yield:O, the:O, identification:O, of:O, a:O, discrete:O, ,:O, identifiable:O, entity:O, responsible:O, for:O, a:O, given:O, collection:O, of:O, activity: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 technique is precise and praiseworthy – yet at the same time , appears so rigorous as to impose limitations on the ability to dynamically adjust and adapt to emerging adversary activity . ( Or for that matter , even categorize otherwise well-known historical actors operating to the present day , such as Turla . ) FireEye ’s methodology may have particular limitations in instances where adversaries ( such as XENOTIME and presumably TEMP.Veles ) rely upon extensive use of publicly-available , commonly-used tools with limited amounts of customization .' [/INST] [This:O, technique:O, is:O, precise:O, and:O, praiseworthy:O, –:O, yet:O, at:O, the:O, same:O, time:O, ,:O, appears:O, so:O, rigorous:O, as:O, to:O, impose:O, limitations:O, on:O, the:O, ability:O, to:O, dynamically:O, adjust:O, and:O, adapt:O, to:O, emerging:O, adversary:O, activity:O, .:O, (:O, Or:O, for:O, that:O, matter:O, ,:O, even:O, categorize:O, otherwise:O, well-known:O, historical:O, actors:O, operating:O, to:O, the:O, present:O, day:O, ,:O, such:O, as:O, Turla:S-APT, .:O, ):O, FireEye:S-SECTEAM, ’s:O, methodology:O, may:O, have:O, particular:O, limitations:O, in:O, instances:O, where:O, adversaries:O, (:O, such:O, as:O, XENOTIME:S-APT, and:O, presumably:O, TEMP.Veles:S-APT, ):O, rely:O, upon:O, extensive:O, use:O, of:O, publicly-available:O, ,:O, commonly-used:O, tools:O, with:O, limited:O, amounts:O, of:O, customization: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 such cases , utilizing purely technical approaches for differentiation ( an issue I lightly touched on in a recent post ) becomes problematic , especially when trying to define attribution to specific , “ who-based ” entities ( such as a Russian research institute ) .' [/INST] [In:O, such:O, cases:O, ,:O, utilizing:O, purely:O, technical:O, approaches:O, for:O, differentiation:O, (:O, an:O, issue:O, I:O, lightly:O, touched:O, on:O, in:O, a:O, recent:O, post:O, ):O, becomes:O, problematic:O, ,:O, especially:O, when:O, trying:O, to:O, define:O, attribution:O, to:O, specific:O, ,:O, “:O, who-based:O, ”:O, entities:O, (:O, such:O, as:O, a:O, Russian:O, research:O, institute: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: 'My understanding is FireEye labels entities where definitive attribution is not yet possible with the “ TEMP ” moniker ( hence , TEMP.Veles ) – yet in this case FireEye developed and deployed the label , then appeared to move away from it in subsequent reporting .' [/INST] [My:O, understanding:O, is:O, FireEye:S-SECTEAM, labels:O, entities:O, where:O, definitive:O, attribution:O, is:O, not:O, yet:O, possible:O, with:O, the:O, “:O, TEMP:O, ”:O, moniker:O, (:O, hence:O, ,:O, TEMP.Veles:S-APT, ):O, –:O, yet:O, in:O, this:O, case:O, FireEye:S-SECTEAM, developed:O, and:O, deployed:O, the:O, label:O, ,:O, then:O, appeared:O, to:O, move:O, away:O, from:O, it:O, in:O, subsequent:O, reporting: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 the public blog post – which also indicated that FireEye is responding to an intrusion at a second facility featuring the same or similar observations – this is presumably not for lack of evidence , yet the “ downgrade ” occurs all the same .' [/INST] [Based:O, on:O, the:O, public:O, blog:O, post:O, –:O, which:O, also:O, indicated:O, that:O, FireEye:S-SECTEAM, is:O, responding:O, to:O, an:O, intrusion:O, at:O, a:O, second:O, facility:O, featuring:O, the:O, same:O, or:O, similar:O, observations:O, –:O, this:O, is:O, presumably:O, not:O, for:O, lack:O, of:O, evidence:O, ,:O, yet:O, the:O, “:O, downgrade:O, ”:O, occurs:O, all:O, the:O, same: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 comparison , XENOTIME was defined based on principles of infrastructure ( compromised third-party infrastructure and various networks associated with several Russian research institutions ) , capabilities ( publicly- and commercially-available tools with varying levels of customization ) and targeting ( an issue not meant for discussion in this blog ) .' [/INST] [In:O, comparison:O, ,:O, XENOTIME:S-APT, was:O, defined:O, based:O, on:O, principles:O, of:O, infrastructure:O, (:O, compromised:O, third-party:O, infrastructure:O, and:O, various:O, networks:O, associated:O, with:O, several:O, Russian:O, research:O, institutions:O, ):O, ,:O, capabilities:O, (:O, publicly-:O, and:O, commercially-available:O, tools:O, with:O, varying:O, levels:O, of:O, customization:O, ):O, and:O, targeting:O, (:O, an:O, issue:O, not:O, meant:O, for:O, discussion:O, in:O, this:O, blog: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: 'In personally responding to several incidents across multiple industry sectors since early 2018 matching TTPs from the event , these items proved consistent and supported the creation of the XENOTIME activity group .' [/INST] [In:O, personally:O, responding:O, to:O, several:O, incidents:O, across:O, multiple:O, industry:O, sectors:O, since:O, early:B-TIME, 2018:E-TIME, matching:O, TTPs:S-PROT, from:O, the:O, event:O, ,:O, these:O, items:O, proved:O, consistent:O, and:O, supported:O, the:O, creation:O, of:O, the:O, XENOTIME:S-APT, activity:O, group: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 naming decision was founded upon the underlying methodology described in the Diamond Model of intrusion analysis .' [/INST] [This:O, naming:O, decision:O, was:O, founded:O, upon:O, the:O, underlying:O, methodology:O, described:O, in:O, the:O, Diamond:O, Model:O, of:O, intrusion:O, analysis: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 such , this decision does not necessarily refer to a specific institution , but rather a collection of observations and behaviors observed across multiple , similarly-situated victims .' [/INST] [As:O, such:O, ,:O, this:O, decision:O, does:O, not:O, necessarily:O, refer:O, to:O, a:O, specific:O, institution:O, ,:O, but:O, rather:O, a:O, collection:O, of:O, observations:O, and:O, behaviors:O, observed:O, across:O, multiple:O, ,:O, similarly-situated:O, 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: 'Of note , this methodology of naming abstracts away the “ who ” element – XENOTIME may represent a single discrete entity ( such as a Russian research institution ) or several entities working in coordination in a roughly repeatable , similar manner across multiple events .' [/INST] [Of:O, note:O, ,:O, this:O, methodology:O, of:O, naming:O, abstracts:O, away:O, the:O, “:O, who:O, ”:O, element:O, –:O, XENOTIME:S-APT, may:O, represent:O, a:O, single:O, discrete:O, entity:O, (:O, such:O, as:O, a:O, Russian:O, research:O, institution:O, ):O, or:O, several:O, entities:O, working:O, in:O, coordination:O, in:O, a:O, roughly:O, repeatable:O, ,:O, similar:O, manner:O, across:O, multiple:O, events: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: 'Ultimately , the epistemic foundation of the behavior-based naming approach makes this irrelevant for tracking ( and labeling for convenience sake ) observations .' [/INST] [Ultimately:O, ,:O, the:O, epistemic:O, foundation:O, of:O, the:O, behavior-based:O, naming:O, approach:O, makes:O, this:O, irrelevant:O, for:O, tracking:O, (:O, and:O, labeling:O, for:O, convenience:O, sake:O, ):O, observations: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: 'Much like the observers watching the shadows of objects cast upon the wall of the cave , these two definitions ( XENOTIME and TEMP.Veles , both presumably referring to “ the TRITON actor ” ) describe the same phenomena , yet at the same time appear different .' [/INST] [Much:O, like:O, the:O, observers:O, watching:O, the:O, shadows:O, of:O, objects:O, cast:O, upon:O, the:O, wall:O, of:O, the:O, cave:O, ,:O, these:O, two:O, definitions:O, (:O, XENOTIME:S-APT, and:O, TEMP.Veles:S-APT, ,:O, both:O, presumably:O, referring:O, to:O, “:O, the:O, TRITON:S-MAL, actor:O, ”:O, ):O, describe:O, the:O, same:O, phenomena:O, ,:O, yet:O, at:O, the:O, same:O, time:O, appear:O, different: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 question of perception and accuracy rests upon the underlying epistemic framework and the goal conceived for that framework in defining an adversary : FireEye ’s methodology follows a deductive approach requiring the collection of significant evidence over time to yield a conclusion that will be necessary given the premises ( the totality of evidence suggests APTxx ) ; the Dragos approach instead seeks an inductive approach , where premises may all be true but the conclusion need not necessarily follow from them given changes in premises over time or other observations not contained within the set ( thus , identified behaviors strongly suggests an activity group , defined as X ) .' [/INST] [This:O, question:O, of:O, perception:O, and:O, accuracy:O, rests:O, upon:O, the:O, underlying:O, epistemic:O, framework:O, and:O, the:O, goal:O, conceived:O, for:O, that:O, framework:O, in:O, defining:O, an:O, adversary:O, ::O, FireEye:S-SECTEAM, ’s:O, methodology:O, follows:O, a:O, deductive:O, approach:O, requiring:O, the:O, collection:O, of:O, significant:O, evidence:O, over:O, time:O, to:O, yield:O, a:O, conclusion:O, that:O, will:O, be:O, necessary:O, given:O, the:O, premises:O, (:O, the:O, totality:O, of:O, evidence:O, suggests:O, APTxx:O, ):O, ;:O, the:O, Dragos:S-SECTEAM, approach:O, instead:O, seeks:O, an:O, inductive:O, approach:O, ,:O, where:O, premises:O, may:O, all:O, be:O, true:O, but:O, the:O, conclusion:O, need:O, not:O, necessarily:O, follow:O, from:O, them:O, given:O, changes:O, in:O, premises:O, over:O, time:O, or:O, other:O, observations:O, not:O, contained:O, within:O, the:O, set:O, (:O, thus:O, ,:O, identified:O, behaviors:O, strongly:O, suggests:O, an:O, activity:O, group:O, ,:O, defined:O, as:O, X: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: 'From an external analysts ’ point of view , the wonder is , which is superior to the other? And my answer for this is : neither is perfect , but both are useful – depending upon your goals and objectives .' [/INST] [From:O, an:O, external:O, analysts:O, ’:O, point:O, of:O, view:O, ,:O, the:O, wonder:O, is:O, ,:O, which:O, is:O, superior:O, to:O, the:O, other?:O, And:O, my:O, answer:O, for:O, this:O, is:O, ::O, neither:O, is:O, perfect:O, ,:O, but:O, both:O, are:O, useful:O, –:O, depending:O, upon:O, your:O, goals:O, and:O, objectives: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: 'But rather than trying to pursue some comparison between the two for identification of superiority ( an approach that will result in unproductive argument and social media warring ) , the point of this post is to highlight the distinctions between these approaches and how – in the case of “ the TRITON actor ” – they result in noticeably different conclusions from similar datasets .' [/INST] [But:O, rather:O, than:O, trying:O, to:O, pursue:O, some:O, comparison:O, between:O, the:O, two:O, for:O, identification:O, of:O, superiority:O, (:O, an:O, approach:O, that:O, will:O, result:O, in:O, unproductive:O, argument:O, and:O, social:O, media:O, warring:O, ):O, ,:O, the:O, point:O, of:O, this:O, post:O, is:O, to:O, highlight:O, the:O, distinctions:O, between:O, these:O, approaches:O, and:O, how:O, –:O, in:O, the:O, case:O, of:O, “:O, the:O, TRITON:S-MAL, actor:O, ”:O, –:O, they:O, result:O, in:O, noticeably:O, different:O, conclusions:O, from:O, similar:O, datasets: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 reason for the distinction may be differences in evidence , as FireEye ’s public reporting notes two distinct events of which they are aware of and have responded to related to “ the TRITON actor ” while Dragos has been engaged several instances – thus , Dragos would possess more evidence to cement the definition of an activity group , while FireEye ’s data collection-centric approach would require far more observations to yield an “ APT ” .' [/INST] [One:O, reason:O, for:O, the:O, distinction:O, may:O, be:O, differences:O, in:O, evidence:O, ,:O, as:O, FireEye:S-SECTEAM, ’s:O, public:O, reporting:O, notes:O, two:O, distinct:O, events:O, of:O, which:O, they:O, are:O, aware:O, of:O, and:O, have:O, responded:O, to:O, related:O, to:O, “:O, the:O, TRITON:S-MAL, actor:O, ”:O, while:O, Dragos:S-SECTEAM, has:O, been:O, engaged:O, several:O, instances:O, –:O, thus:O, ,:O, Dragos:S-SECTEAM, would:O, possess:O, more:O, evidence:O, to:O, cement:O, the:O, definition:O, of:O, an:O, activity:O, group:O, ,:O, while:O, FireEye:S-SECTEAM, ’s:O, data:O, collection-centric:O, approach:O, would:O, require:O, far:O, more:O, observations:O, to:O, yield:O, an:O, “:O, APT: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: 'Yet irrespective of this , it is confusing why the previously-declared “ TEMP ” category was walked back as this has led to not small amount of confusion – in both technical and non-technical audiences – as to just what FireEye ’s blog post refers .' [/INST] [Yet:O, irrespective:O, of:O, this:O, ,:O, it:O, is:O, confusing:O, why:O, the:O, previously-declared:O, “:O, TEMP:O, ”:O, category:O, was:O, walked:O, back:O, as:O, this:O, has:O, led:O, to:O, not:O, small:O, amount:O, of:O, confusion:O, –:O, in:O, both:O, technical:O, and:O, non-technical:O, audiences:O, –:O, as:O, to:O, just:O, what:O, FireEye:S-SECTEAM, ’s:O, blog:O, post:O, refers: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: 'Thus respected journalists ( at least by me ) conflate the “ TRITON actor is active at another site ” with “ TRITON malware was identified at another site ” .' [/INST] [Thus:O, respected:O, journalists:O, (:O, at:O, least:O, by:O, me:O, ):O, conflate:O, the:O, “:O, TRITON:S-MAL, actor:O, is:O, active:O, at:O, another:O, site:O, ”:O, with:O, “:O, TRITON:S-MAL, malware:O, was:O, identified:O, at:O, another:O, site: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: 'In this case , we ’re seeing a definite problem with the overly-conservative naming approach used as it engenders confusion in a significant subset of the intended audience .' [/INST] [In:O, this:O, case:O, ,:O, we:O, ’re:O, seeing:O, a:O, definite:O, problem:O, with:O, the:O, overly-conservative:O, naming:O, approach:O, used:O, as:O, it:O, engenders:O, confusion:O, in:O, a:O, significant:O, subset:O, of:O, the:O, intended:O, audience: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 some may dismiss adversary or activity naming as so much marketing , having a distinct label for something allows for clearer communication and more accurate discussion .' [/INST] [While:O, some:O, may:O, dismiss:O, adversary:O, or:O, activity:O, naming:O, as:O, so:O, much:O, marketing:O, ,:O, having:O, a:O, distinct:O, label:O, for:O, something:O, allows:O, for:O, clearer:O, communication:O, and:O, more:O, accurate:O, discussion: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: 'Furthermore , conflating adversaries with tools , since tools can be repurposed or used by other entities than those first observed deploying them , leads to further potential confusion as the “ X actor ” is quickly compressed in the minds of some to refer to any and all instantiations of tool “ X ” .' [/INST] [Furthermore:O, ,:O, conflating:O, adversaries:O, with:O, tools:O, ,:O, since:O, tools:O, can:O, be:O, repurposed:O, or:O, used:O, by:O, other:O, entities:O, than:O, those:O, first:O, observed:O, deploying:O, them:O, ,:O, leads:O, to:O, further:O, potential:O, confusion:O, as:O, the:O, “:O, X:S-TOOL, actor:O, ”:O, is:O, quickly:O, compressed:O, in:O, the:O, minds:O, of:O, some:O, to:O, refer:O, to:O, any:O, and:O, all:O, instantiations:O, of:O, tool:O, “:O, X:S-TOOL, ”:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Overall , the discussion above may appear so much splitting of hairs or determining how many angels can dance on the head of a pin – yet given the communicative impacts behind different naming and labeling conventions , this exploration seems not merely useful but necessary .' [/INST] [Overall:O, ,:O, the:O, discussion:O, above:O, may:O, appear:O, so:O, much:O, splitting:O, of:O, hairs:O, or:O, determining:O, how:O, many:O, angels:O, can:O, dance:O, on:O, the:O, head:O, of:O, a:O, pin:O, –:O, yet:O, given:O, the:O, communicative:O, impacts:O, behind:O, different:O, naming:O, and:O, labeling:O, conventions:O, ,:O, this:O, exploration:O, seems:O, not:O, merely:O, useful:O, but:O, necessary: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: 'Understanding the “ how ” and “ why ” behind different entity classifications of similar ( or even the same ) activity allows us to move beyond the dismissive approach of “ everyone has their names for marketing purposes ” to a more productive mindset that grasps the fundamental methodologies that ( should ) drive these decisions .' [/INST] [Understanding:O, the:O, “:O, how:O, ”:O, and:O, “:O, why:O, ”:O, behind:O, different:O, entity:O, classifications:O, of:O, similar:O, (:O, or:O, even:O, the:O, same:O, ):O, activity:O, allows:O, us:O, to:O, move:O, beyond:O, the:O, dismissive:O, approach:O, of:O, “:O, everyone:O, has:O, their:O, names:O, for:O, marketing:O, purposes:O, ”:O, to:O, a:O, more:O, productive:O, mindset:O, that:O, grasps:O, the:O, fundamental:O, methodologies:O, that:O, (:O, should:O, ):O, drive:O, these:O, decisions: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 Group 3390 Cyberespionage .' [/INST] [Threat:B-APT, Group:I-APT, 3390:E-APT, Cyberespionage: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: 'CTU researchers have observed TG-3390 actors using tools that are favored by multiple threat groups :' [/INST] [CTU:S-SECTEAM, researchers:O, have:O, observed:O, TG-3390:S-APT, actors:O, using:O, tools:O, that:O, are:O, favored:O, by:O, multiple:O, threat:O, groups: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: 'PlugX — A remote access tool notable for communications that may contain HTTP headers starting with , X- , ( e.g. , , X-Session : 0 , ) .' [/INST] [PlugX:S-MAL, —:O, A:O, remote:O, access:O, tool:O, notable:O, for:O, communications:O, that:O, may:O, contain:O, HTTP:S-PROT, headers:O, starting:O, with:O, ,:O, X-:O, ,:O, (:O, e.g.:O, ,:O, ,:O, X-Session:S-TOOL, ::O, 0:O, ,: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: 'Its presence on a compromised system allows a threat actor to execute a wide variety of commands , including uploading and downloading files , and spawning a reverse shell .' [/INST] [Its:O, presence:O, on:O, a:O, compromised:O, system:O, allows:O, a:O, threat:O, actor:O, to:O, execute:O, a:O, wide:O, variety:O, of:O, commands:O, ,:O, including:O, uploading:O, and:O, downloading:O, files:O, ,:O, and:O, spawning:O, a:O, reverse:O, shell:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The malware can be configured to use multiple network protocols to avoid network-based detection .' [/INST] [The:O, malware:O, can:O, be:O, configured:O, to:O, use:O, multiple:O, network:O, protocols:O, to:O, avoid:O, network-based:O, detection: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: 'DLL side loading is often used to maintain persistence on the compromised system .' [/INST] [DLL:S-TOOL, side:O, loading:O, is:O, often:O, used:O, to:O, maintain:O, persistence:O, on:O, the:O, compromised:O, system: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: 'HttpBrowser ( also known as TokenControl ) — A backdoor notable for HTTPS communications with the HttpBrowser User-Agent .' [/INST] [HttpBrowser:S-MAL, (:O, also:O, known:O, as:O, TokenControl:S-MAL, ):O, —:O, A:O, backdoor:O, notable:O, for:O, HTTPS:S-PROT, communications:O, with:O, the:O, HttpBrowser:S-MAL, User-Agent: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: 'HttpBrowser 's executable code may be obfuscated through structured exception handling and return-oriented programming .' [/INST] [HttpBrowser:S-MAL, 's:O, executable:O, code:O, may:O, be:O, obfuscated:O, through:O, structured:O, exception:O, handling:O, and:O, return-oriented:O, programming: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: 'Its presence on a compromised system allows a threat actor to spawn a reverse shell , upload or download files , and capture keystrokes .' [/INST] [Its:O, presence:O, on:O, a:O, compromised:O, system:O, allows:O, a:O, threat:O, actor:O, to:O, spawn:O, a:O, reverse:O, shell:O, ,:O, upload:O, or:O, download:O, files:O, ,:O, and:O, capture:O, keystrokes: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: 'Antivirus detection for HttpBrowser is extremely low and is typically based upon heuristic signatures .' [/INST] [Antivirus:O, detection:O, for:O, HttpBrowser:S-MAL, is:O, extremely:O, low:O, and:O, is:O, typically:O, based:O, upon:O, heuristic:O, signatures: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: 'DLL side loading has been used to maintain persistence on the compromised system .' [/INST] [DLL:S-TOOL, side:O, loading:O, has:O, been:O, used:O, to:O, maintain:O, persistence:O, on:O, the:O, compromised:O, system: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: 'ChinaChopper web shell — A web-based executable script that allows a threat actor to execute commands on the compromised system .' [/INST] [ChinaChopper:S-MAL, web:B-TOOL, shell:E-TOOL, —:O, A:O, web-based:O, executable:O, script:O, that:O, allows:O, a:O, threat:O, actor:O, to:O, execute:O, commands:O, on:O, the:O, compromised:O, system: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 server-side component provides a simple graphical user interface for threat actors interacting with web shells .' [/INST] [The:O, server-side:O, component:O, provides:O, a:O, simple:O, graphical:O, user:O, interface:O, for:O, threat:O, actors:O, interacting:O, with:O, web:B-TOOL, shells: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: 'Hunter — A web application scanning tool written by @tojen to identify vulnerabilities in Apache Tomcat , Red Hat JBoss Middleware , and Adobe ColdFusion .' [/INST] [Hunter:S-TOOL, —:O, A:O, web:O, application:O, scanning:O, tool:O, written:O, by:O, @tojen:O, to:O, identify:O, vulnerabilities:O, in:O, Apache:B-TOOL, Tomcat:E-TOOL, ,:O, Red:B-TOOL, Hat:I-TOOL, JBoss:I-TOOL, Middleware:E-TOOL, ,:O, and:O, Adobe:B-TOOL, ColdFusion: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 can also identify open ports , collect web banners , and download secondary files .' [/INST] [It:O, can:O, also:O, identify:O, open:O, ports:O, ,:O, collect:O, web:O, banners:O, ,:O, and:O, download:O, secondary:O, files:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The following tools appear to be exclusive to TG-3390 : OwaAuth web shell — A web shell and credential stealer deployed to Microsoft Exchange servers .' [/INST] [The:O, following:O, tools:O, appear:O, to:O, be:O, exclusive:O, to:O, TG-3390:S-APT, ::O, OwaAuth:S-MAL, web:B-TOOL, shell:E-TOOL, —:O, A:O, web:B-TOOL, shell:E-TOOL, and:O, credential:O, stealer:S-TOOL, deployed:O, to:O, Microsoft:S-IDTY, Exchange:S-TOOL, servers: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 installed as an ISAPI filter .' [/INST] [It:O, is:O, installed:O, as:O, an:O, ISAPI:B-TOOL, filter: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: 'Captured credentials are DES encrypted using the password , 12345678 , and are written to the log.txt file in the root directory .' [/INST] [Captured:O, credentials:O, are:O, DES:S-ENCR, encrypted:O, using:O, the:O, password:O, ,:O, 12345678:O, ,:O, and:O, are:O, written:O, to:O, the:O, log.txt:O, file:O, in:O, the:O, root:O, directory: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: 'Like the ChinaChopper web shell , the OwaAuth web shell requires a password .' [/INST] [Like:O, the:O, ChinaChopper:S-MAL, web:B-TOOL, shell:E-TOOL, ,:O, the:O, OwaAuth:S-MAL, web:B-TOOL, shell:E-TOOL, requires:O, a:O, password: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 , the OwaAuth web shell password contains the victim organization's name .' [/INST] [However:O, ,:O, the:O, OwaAuth:S-MAL, web:B-TOOL, shell:E-TOOL, password:O, contains:O, the:O, victim:O, organization's:O, name: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: 'ASPXTool — A modified version of the ASPXSpy web shell .' [/INST] [ASPXTool:S-MAL, —:O, A:O, modified:O, version:O, of:O, the:O, ASPXSpy:S-MAL, web:B-TOOL, shell: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 is deployed to internally accessible servers running Internet Information Services ( IIS ) .' [/INST] [It:O, is:O, deployed:O, to:O, internally:O, accessible:O, servers:O, running:O, Internet:B-TOOL, Information:I-TOOL, Services:E-TOOL, (:O, IIS:S-TOOL, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'TG-3390 actors have also used the following publicly available tools :' [/INST] [TG-3390:S-APT, actors:O, have:O, also:O, used:O, the:O, following:O, publicly:O, available:O, tools: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: 'Windows Credential Editor ( WCE ) — obtains passwords from memory . gsecdump — obtains passwords from memory . winrar — compresses data for Exfiltration . nbtscan — scans NetBIOS name servers .' [/INST] [Windows:B-TOOL, Credential:I-TOOL, Editor:E-TOOL, (:O, WCE:S-TOOL, ):O, —:O, obtains:O, passwords:O, from:O, memory:O, .:O, gsecdump:S-TOOL, —:O, obtains:O, passwords:O, from:O, memory:O, .:O, winrar:S-TOOL, —:O, compresses:O, data:O, for:O, Exfiltration:S-ACT, .:O, nbtscan:S-TOOL, —:O, scans:O, NetBIOS:S-TOOL, name:O, servers: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: 'CTU researchers have not observed TG-3390 actors performing reconnaissance prior to compromising organizations .' [/INST] [CTU:S-SECTEAM, researchers:O, have:O, not:O, observed:O, TG-3390:S-APT, actors:O, performing:O, reconnaissance:O, prior:O, to:O, compromising: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: 'As discussed in the Actions on objectives section , the threat actors appear to wait until they have established a foothold .' [/INST] [As:O, discussed:O, in:O, the:O, Actions:O, on:O, objectives:O, section:O, ,:O, the:O, threat:O, actors:O, appear:O, to:O, wait:O, until:O, they:O, have:O, established:O, a:O, foothold: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: 'TG-3390 actors use command and control ( C2 ) domains for extended periods of time but frequently change the domains' IP addresses .' [/INST] [TG-3390:S-APT, actors:O, use:O, command:B-TOOL, and:I-TOOL, control:E-TOOL, (:O, C2:S-TOOL, ):O, domains:O, for:O, extended:O, periods:O, of:O, time:O, but:O, frequently:O, change:O, the:O, domains':O, IP:O, addresses: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 new IP addresses are typically on the same subnet as the previous ones .' [/INST] [The:O, new:O, IP:O, addresses:O, are:O, typically:O, on:O, the:O, same:O, subnet:O, as:O, the:O, previous:O, ones: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: 'TG-3390 is capable of using a C2 infrastructure that spans multiple networks and registrars .' [/INST] [TG-3390:S-APT, is:O, capable:O, of:O, using:O, a:O, C2:S-TOOL, infrastructure:O, that:O, spans:O, multiple:O, networks:O, and:O, registrars:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The most common registrar used by the adversary is HiChina Zhicheng Technology Ltd .' [/INST] [The:O, most:O, common:O, registrar:O, used:O, by:O, the:O, adversary:O, is:O, HiChina:B-IDTY, Zhicheng:I-IDTY, Technology:I-IDTY, Ltd:E-IDTY, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The threat actors have a demonstrated ability to move from one network provider to another , using some infrastructure for extended periods of time and other domains for only a few days .' [/INST] [The:O, threat:O, actors:O, have:O, a:O, demonstrated:O, ability:O, to:O, move:O, from:O, one:O, network:O, provider:O, to:O, another:O, ,:O, using:O, some:O, infrastructure:O, for:O, extended:O, periods:O, of:O, time:O, and:O, other:O, domains:O, for:O, only:O, a:O, few:O, days: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: 'Seemingly random activity patterns in infrastructure deployment and usage , along with the ability to use a wide variety of geographically diverse infrastructure , help the threat actors avoid detection .' [/INST] [Seemingly:O, random:O, activity:O, patterns:O, in:O, infrastructure:O, deployment:O, and:O, usage:O, ,:O, along:O, with:O, the:O, ability:O, to:O, use:O, a:O, wide:O, variety:O, of:O, geographically:O, diverse:O, infrastructure:O, ,:O, help:O, the:O, threat:O, actors:O, avoid:O, detection: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: 'TG-3390 SWCs may be largely geographically independent , but the group's most frequently used C2 registrars and IP net blocks are located in the U.S. Using a U.S. based C2 infrastructure to compromise targets in the U.S. helps TG-3390 actors avoid geo-blocking and geo-flagging measures used in network defense .' [/INST] [TG-3390:S-APT, SWCs:S-OS, may:O, be:O, largely:O, geographically:O, independent:O, ,:O, but:O, the:O, group's:O, most:O, frequently:O, used:O, C2:S-TOOL, registrars:O, and:O, IP:O, net:O, blocks:O, are:O, located:O, in:O, the:O, U.S.:S-LOC, Using:O, a:O, U.S.:S-LOC, based:O, C2:S-TOOL, infrastructure:O, to:O, compromise:O, targets:O, in:O, the:O, U.S.:S-LOC, helps:O, TG-3390:S-APT, actors:O, avoid:O, geo-blocking:O, and:O, geo-flagging:O, measures:O, used:O, in:O, network:O, defense: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 threat actors create PlugX DLL stub loaders that will run only after a specific date .' [/INST] [The:O, threat:O, actors:O, create:O, PlugX:S-MAL, DLL:S-TOOL, stub:O, loaders:S-TOOL, that:O, will:O, run:O, only:O, after:O, a:O, specific:O, date: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 compile dates of the samples analyzed by CTU researchers are all later than the hard-coded August 8 , 2013 date , indicating that the code might be reused from previous tools .' [/INST] [The:O, compile:O, dates:O, of:O, the:O, samples:O, analyzed:O, by:O, CTU:S-SECTEAM, researchers:O, are:O, all:O, later:O, than:O, the:O, hard-coded:O, August:B-TIME, 8:I-TIME, ,:I-TIME, 2013:E-TIME, date:O, ,:O, indicating:O, that:O, the:O, code:O, might:O, be:O, reused:O, from:O, previous:O, tools: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 OwaAuth web shell is likely created with a builder , given that the PE compile time of the binary does not change between instances and the configuration fields are padded to a specific size .' [/INST] [The:O, OwaAuth:S-MAL, web:B-TOOL, shell:E-TOOL, is:O, likely:O, created:O, with:O, a:O, builder:O, ,:O, given:O, that:O, the:O, PE:S-TOOL, compile:O, time:O, of:O, the:O, binary:O, does:O, not:O, change:O, between:O, instances:O, and:O, the:O, configuration:O, fields:O, are:O, padded:O, to:O, a:O, specific:O, size: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 adversaries modify publicly available tools such as ASPXSpy to remove identifying characteristics that network defenders use to identify web shells .' [/INST] [The:O, adversaries:O, modify:O, publicly:O, available:O, tools:O, such:O, as:O, ASPXSpy:S-MAL, to:O, remove:O, identifying:O, characteristics:O, that:O, network:O, defenders:O, use:O, to:O, identify:O, web:B-TOOL, shells: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: 'TG-3390 conducts SWCs or sends spearphishing emails with ZIP archive attachments .' [/INST] [TG-3390:S-APT, conducts:O, SWCs:S-OS, or:O, sends:O, spearphishing:S-ACT, emails:S-TOOL, with:O, ZIP:S-TOOL, archive: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: 'The ZIP archives have names relevant to the targets and contain both legitimate files and malware .' [/INST] [The:O, ZIP:S-TOOL, archives:O, have:O, names:O, relevant:O, to:O, the:O, targets:O, and:O, contain:O, both:O, legitimate:O, files:O, and: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: 'One archive sample analyzed by CTU researchers contained a legitimate PDF file , a benign image of interest to targets , and an HttpBrowser installer disguised as an image file .' [/INST] [One:O, archive:O, sample:O, analyzed:O, by:O, CTU:S-SECTEAM, researchers:O, contained:O, a:O, legitimate:O, PDF:S-TOOL, file:O, ,:O, a:O, benign:O, image:O, of:O, interest:O, to:O, targets:O, ,:O, and:O, an:O, HttpBrowser:S-MAL, installer:S-TOOL, disguised:O, as:O, an:O, image:O, file: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: 'Both the redirect code on the compromised site and the exploit code appear and disappear , indicating that the adversaries add the code when they want to leverage the SWC and remove the code when it is not in use to limit the visibility of their operations .' [/INST] [Both:O, the:O, redirect:O, code:O, on:O, the:O, compromised:O, site:O, and:O, the:O, exploit:O, code:O, appear:O, and:O, disappear:O, ,:O, indicating:O, that:O, the:O, adversaries:O, add:O, the:O, code:O, when:O, they:O, want:O, to:O, leverage:O, the:O, SWC:S-OS, and:O, remove:O, the:O, code:O, when:O, it:O, is:O, not:O, in:O, use:O, to:O, limit:O, the:O, visibility:O, of:O, their: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: 'The threat actors have evolved to whitelisting IP addresses and only delivering the exploit and payload to specific targets of interest .' [/INST] [The:O, threat:O, actors:O, have:O, evolved:O, to:O, whitelisting:O, IP:S-PROT, addresses:O, and:O, only:O, delivering:O, the:O, exploit:O, and:O, payload:O, to:O, specific:O, targets:O, of:O, interest: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: 'CTU researchers have observed TG-3390 compromising a target organization's externally and internally accessible assets , such as an OWA server , and adding redirect code to point internal users to an external website that hosts an exploit and delivers malware .' [/INST] [CTU:S-SECTEAM, researchers:O, have:O, observed:O, TG-3390:S-APT, compromising:O, a:O, target:O, organization's:O, externally:O, and:O, internally:O, accessible:O, assets:O, ,:O, such:O, as:O, an:O, OWA:S-TOOL, server:O, ,:O, and:O, adding:O, redirect:O, code:O, to:O, point:O, internal:O, users:O, to:O, an:O, external:O, website:O, that:O, hosts:O, an:O, exploit:O, and:O, delivers: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: 'TG-3390 actors have used Java exploits in their SWCs .' [/INST] [TG-3390:S-APT, actors:O, have:O, used:O, Java:S-TOOL, exploits:S-TOOL, in:O, their:O, SWCs:S-OS, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 particular , the threat actors have exploited CVE-2011-3544 , a vulnerability in the Java Runtime Environment , to deliver the HttpBrowser backdoor ; and CVE-2010-0738 , a vulnerability in JBoss , to compromise internally and externally accessible assets used to redirect users' web browsers to exploit code .' [/INST] [In:O, particular:O, ,:O, the:O, threat:O, actors:O, have:O, exploited:O, CVE-2011-3544:S-VULID, ,:O, a:O, vulnerability:S-TOOL, in:O, the:O, Java:S-TOOL, Runtime:B-TOOL, Environment:E-TOOL, ,:O, to:O, deliver:O, the:O, HttpBrowser:S-MAL, backdoor:S-TOOL, ;:O, and:O, CVE-2010-0738:S-VULID, ,:O, a:O, vulnerability:S-TOOL, in:O, JBoss:S-TOOL, ,:O, to:O, compromise:O, internally:O, and:O, externally:O, accessible:O, assets:O, used:O, to:O, redirect:O, users':O, web:O, browsers:O, to:O, exploit:O, code: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 activity analyzed by CTU researchers , TG-3390 executed the Hunter web application scanning tool against a target server running IIS .' [/INST] [In:O, activity:O, analyzed:O, by:O, CTU:S-SECTEAM, researchers:O, ,:O, TG-3390:S-APT, executed:O, the:O, Hunter:S-TOOL, web:O, application:O, scanning:O, tool:O, against:O, a:O, target:O, server:O, running:O, IIS: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: 'Hunter queried the following URIs in a specific order to determine if the associated software configurations are insecure .' [/INST] [Hunter:S-TOOL, queried:O, the:O, following:O, URIs:O, in:O, a:O, specific:O, order:O, to:O, determine:O, if:O, the:O, associated:O, software:O, configurations:O, are:O, insecure: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: 'TG-3390 uses DLL side loading , a technique that involves running a legitimate , typically digitally signed , program that loads a malicious DLL .' [/INST] [TG-3390:S-APT, uses:O, DLL:S-TOOL, side:O, loading:O, ,:O, a:O, technique:O, that:O, involves:O, running:O, a:O, legitimate:O, ,:O, typically:O, digitally:O, signed:O, ,:O, program:O, that:O, loads:O, a:O, malicious:O, DLL: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: 'CTU researchers have observed the threat actors employing legitimate Kaspersky antivirus variants in analyzed samples .' [/INST] [CTU:S-SECTEAM, researchers:O, have:O, observed:O, the:O, threat:O, actors:O, employing:O, legitimate:O, Kaspersky:S-SECTEAM, antivirus:O, variants:O, in:O, analyzed: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: 'The DLL acts as a stub loader , which loads and executes the shell code .' [/INST] [The:O, DLL:S-TOOL, acts:O, as:O, a:O, stub:O, loader:S-TOOL, ,:O, which:O, loads:O, and:O, executes:O, the:O, shell:O, code: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 adversaries have used this technique to allow PlugX and HttpBrowser to persist on a system .' [/INST] [The:O, adversaries:O, have:O, used:O, this:O, technique:O, to:O, allow:O, PlugX:S-MAL, and:O, HttpBrowser:S-MAL, to:O, persist:O, on:O, a:O, system:O, .:O] </s> |