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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: 'It appeared to be geared exclusively towards high profile targets .' [/INST] [It:O, appeared:O, to:O, be:O, geared:O, exclusively:O, towards:O, high:O, profile: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: 'Sofacy ’s reported presence in the DNC network alongside APT29 brought possibly the highest level of public attention to the group ’s activities in 2016 , especially when data from the compromise was leaked and “ weaponized ” .' [/INST] [Sofacy:S-APT, ’s:O, reported:O, presence:O, in:O, the:O, DNC:S-TOOL, network:O, alongside:O, APT29:S-APT, brought:O, possibly:O, the:O, highest:O, level:O, of:O, public:O, attention:O, to:O, the:O, group:O, ’s:O, activities:O, in:O, 2016:S-TIME, ,:O, especially:O, when:O, data:O, from:O, the:O, compromise:O, was:O, leaked:O, and:O, “:O, weaponized: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: 'And later 2016 , their focus turned towards the Olympics ’ and the World Anti-Doping Agency ( WADA ) and Court of Arbitration for Sports ( CAS ) , when individuals and servers in these organizations were phished and compromised .' [/INST] [And:O, later:B-TIME, 2016:E-TIME, ,:O, their:O, focus:O, turned:O, towards:O, the:O, Olympics:S-IDTY, ’:O, and:O, the:O, World:B-IDTY, Anti-Doping:I-IDTY, Agency:E-IDTY, (:O, WADA:S-IDTY, ):O, and:O, Court:B-IDTY, of:I-IDTY, Arbitration:I-IDTY, for:I-IDTY, Sports:E-IDTY, (:O, CAS:S-IDTY, ):O, ,:O, when:O, individuals:O, and:O, servers:O, in:O, these:O, organizations:O, were:O, phished:O, and:O, compromised: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 similar vein with past CyberBerkut activity , attackers hid behind anonymous activist groups like “ anonpoland ” , and data from victimized organizations were similarly leaked and “ weaponized ” .' [/INST] [In:O, a:O, similar:O, vein:O, with:O, past:O, CyberBerkut:S-ACT, activity:O, ,:O, attackers:O, hid:O, behind:O, anonymous:O, activist:O, groups:O, like:O, “:O, anonpoland:O, ”:O, ,:O, and:O, data:O, from:O, victimized:O, organizations:O, were:O, similarly:O, leaked:O, and:O, “:O, weaponized: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 write-up will survey notables in the past year of 2017 Sofacy activity , including their targeting , technology , and notes on their infrastructure .' [/INST] [This:O, write-up:O, will:O, survey:O, notables:O, in:O, the:O, past:O, year:O, of:O, 2017:S-TIME, Sofacy:S-APT, activity:O, ,:O, including:O, their:O, targeting:O, ,:O, technology:O, ,:O, and:O, notes:O, on:O, their:O, infrastructure: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: 'No one research group has 100% global visibility , and our collected data is presented accordingly .' [/INST] [No:O, one:O, research:O, group:O, has:O, 100%:O, global:O, visibility:O, ,:O, and:O, our:O, collected:O, data:O, is:O, presented:O, accordingly: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: 'Here , external APT28 reports on 2017 Darkhotel-style activity in Europe and Dealer ’s Choice spearphishing are of interest .' [/INST] [Here:O, ,:O, external:O, APT28:S-APT, reports:O, on:O, 2017:S-TIME, Darkhotel-style:S-ACT, activity:O, in:O, Europe:S-LOC, and:O, Dealer:O, ’s:O, Choice:O, spearphishing:S-ACT, are: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: 'From where we sit , 2017 Sofacy activity starts with a heavy focus on NATO and Ukrainian partners , coinciding with lighter interest in Central Asian targets , and finishing the second half of the year with a heavy focus on Central Asian targets and some shift further East .' [/INST] [From:O, where:O, we:O, sit:O, ,:O, 2017:S-TIME, Sofacy:S-APT, activity:O, starts:O, with:O, a:O, heavy:O, focus:O, on:O, NATO:S-IDTY, and:O, Ukrainian:O, partners:O, ,:O, coinciding:O, with:O, lighter:O, interest:O, in:O, Central:B-LOC, Asian:E-LOC, targets:O, ,:O, and:O, finishing:O, the:O, second:O, half:O, of:O, the:O, year:O, with:O, a:O, heavy:O, focus:O, on:O, Central:B-LOC, Asian:E-LOC, targets:O, and:O, some:O, shift:O, further:O, East: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: 'Sofacy kicked off the year deploying two 0day in a spearphish document , both a Microsoft Office encapsulated postscript type confusion exploit ( abusing CVE-2017-0262 ) and an escalation of privilege use-after-free exploit ( abusing CVE-2017-0263 ) .' [/INST] [Sofacy:S-APT, kicked:O, off:O, the:O, year:O, deploying:O, two:O, 0day:S-VULNAME, in:O, a:O, spearphish:O, document:O, ,:O, both:O, a:O, Microsoft:S-IDTY, Office:S-TOOL, encapsulated:O, postscript:O, type:O, confusion:O, exploit:O, (:O, abusing:O, CVE-2017-0262:S-VULID, ):O, and:O, an:O, escalation:O, of:O, privilege:O, use-after-free:O, exploit:O, (:O, abusing:O, CVE-2017-0263:S-VULID, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The group attempted to deploy this spearphish attachment to push a small 30kb backdoor known as GAMEFISH to targets in Europe at the beginning of 2017 .' [/INST] [The:O, group:O, attempted:O, to:O, deploy:O, this:O, spearphish:O, attachment:O, to:O, push:O, a:O, small:O, 30kb:O, backdoor:O, known:O, as:O, GAMEFISH:S-MAL, to:O, targets:O, in:O, Europe:S-LOC, at:O, the:O, beginning:B-TIME, of: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: 'They took advantage of the Syrian military conflict for thematic content and file naming “ Trump ’s_Attack_on_Syria_English.docx ” .' [/INST] [They:O, took:O, advantage:O, of:O, the:O, Syrian:O, military:O, conflict:O, for:O, thematic:O, content:O, and:O, file:O, naming:O, “:O, Trump:B-FILE, ’s_Attack_on_Syria_English.docx:E-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: 'Again , this deployment was likely a part of their focus on NATO targets .' [/INST] [Again:O, ,:O, this:O, deployment:O, was:O, likely:O, a:O, part:O, of:O, their:O, focus:O, on:O, NATO:S-IDTY, 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: 'Meanwhile in early-to-mid 2017 , SPLM / CHOPSTICK / XAgent detections in Central Asia provided a glimpse into ongoing focus on ex-Soviet republics in Central Asia .' [/INST] [Meanwhile:O, in:O, early-to-mid:B-TIME, 2017:E-TIME, ,:O, SPLM:S-MAL, /:O, CHOPSTICK:S-MAL, /:O, XAgent:S-MAL, detections:O, in:O, Central:B-LOC, Asia:E-LOC, provided:O, a:O, glimpse:O, into:O, ongoing:O, focus:O, on:O, ex-Soviet:O, republics:O, in:O, Central:B-LOC, Asia: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: 'These particular detections are interesting because they indicate an attempted selective 2nd stage deployment of a backdoor maintaining filestealer , keylogger , and remoteshell functionality to a system of interest .' [/INST] [These:O, particular:O, detections:O, are:O, interesting:O, because:O, they:O, indicate:O, an:O, attempted:O, selective:O, 2nd:O, stage:O, deployment:O, of:O, a:O, backdoor:O, maintaining:O, filestealer:O, ,:O, keylogger:O, ,:O, and:O, remoteshell:O, functionality:O, to:O, a:O, system: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: 'As the latest revision of the backdoor , portions of SPLM didn’t match previous reports on SPLM / XAgent while other similarities were maintained .' [/INST] [As:O, the:O, latest:O, revision:O, of:O, the:O, backdoor:O, ,:O, portions:O, of:O, SPLM:S-MAL, didn’t:O, match:O, previous:O, reports:O, on:O, SPLM:S-MAL, /:O, XAgent:S-MAL, while:O, other:O, similarities:O, were:O, maintained: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: 'SPLM 64-bit modules already appeared to be at version 4 of the software by May of the year .' [/INST] [SPLM:S-MAL, 64-bit:O, modules:O, already:O, appeared:O, to:O, be:O, at:O, version:O, 4:O, of:O, the:O, software:O, by:O, May:B-TIME, of:I-TIME, the: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: 'Targeting profiles included defense related commercial and military organizations , and telecommunications .' [/INST] [Targeting:O, profiles:O, included:O, defense:O, related:O, commercial:O, and:O, military:O, organizations:O, ,:O, and:O, telecommunications: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 mid-November 2015 , the threat actor referred to as “ Sofacy ” or “ APT28 ” has been utilizing a unique payload and delivery mechanism written in Delphi and AutoIT .' [/INST] [Since:O, mid-November:B-TIME, 2015:E-TIME, ,:O, the:O, threat:O, actor:O, referred:O, to:O, as:O, “:O, Sofacy:S-APT, ”:O, or:O, “:O, APT28:S-APT, ”:O, has:O, been:O, utilizing:O, a:O, unique:O, payload:O, and:O, delivery:O, mechanism:O, written:O, in:O, Delphi:S-TOOL, and:O, AutoIT: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: 'We collectively refer to this package and related activity as “ Zebrocy ” and had written a few reports on its usage and development by June 2017 – Sofacy developers modified and redeployed incremented versions of the malware .' [/INST] [We:O, collectively:O, refer:O, to:O, this:O, package:O, and:O, related:O, activity:O, as:O, “:O, Zebrocy:S-MAL, ”:O, and:O, had:O, written:O, a:O, few:O, reports:O, on:O, its:O, usage:O, and:O, development:O, by:O, June:B-TIME, 2017:E-TIME, –:O, Sofacy:S-APT, developers:O, modified:O, and:O, redeployed:O, incremented:O, versions:O, of: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: 'The Zebrocy chain follows a pattern : spearphish attachment -> compiled Autoit script ( downloader ) -> Zebrocy payload .' [/INST] [The:O, Zebrocy:S-MAL, chain:O, follows:O, a:O, pattern:O, ::O, spearphish:S-ACT, attachment:O, ->:O, compiled:O, Autoit:S-TOOL, script:O, (:O, downloader:O, ):O, ->:O, Zebrocy:S-MAL, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In some deployments , we observed Sofacy actively developing and deploying a new package to a much smaller , specific subset of targets within the broader set .' [/INST] [In:O, some:O, deployments:O, ,:O, we:O, observed:O, Sofacy:S-APT, actively:O, developing:O, and:O, deploying:O, a:O, new:O, package:O, to:O, a:O, much:O, smaller:O, ,:O, specific:O, subset:O, of:O, targets:O, within:O, the:O, broader:O, set: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: 'Targeting profiles , spearphish filenames , and lures carry thematic content related to visa applications and scanned images , border control administration , and various administrative notes .' [/INST] [Targeting:O, profiles:O, ,:O, spearphish:S-ACT, filenames:O, ,:O, and:O, lures:O, carry:O, thematic:O, content:O, related:O, to:O, visa:O, applications:O, and:O, scanned:O, images:O, ,:O, border:O, control:O, administration:O, ,:O, and:O, various:O, administrative:O, notes: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: 'Targeting appears to be widely spread across the Middle East , Europe , and Asia .' [/INST] [Targeting:O, appears:O, to:O, be:O, widely:O, spread:O, across:O, the:O, Middle:B-LOC, East:E-LOC, ,:O, Europe:S-LOC, ,:O, and:O, Asia: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: 'We identified new MSIL components deployed by Zebrocy .' [/INST] [We:O, identified:O, new:O, MSIL:S-TOOL, components:O, deployed:O, by:O, Zebrocy: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: 'While recent Zebrocy versioning was 7.1 , some of the related Zebrocy modules that drop file-stealing MSIL modules we call Covfacy were v7.0 .' [/INST] [While:O, recent:O, Zebrocy:S-MAL, versioning:O, was:O, 7.1:O, ,:O, some:O, of:O, the:O, related:O, Zebrocy:S-MAL, modules:O, that:O, drop:O, file-stealing:O, MSIL:S-TOOL, modules:O, we:O, call:O, Covfacy:S-TOOL, were:O, v7.0: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: 'The components were an unexpected inclusion in this particular toolset .' [/INST] [The:O, components:O, were:O, an:O, unexpected:O, inclusion:O, in:O, this:O, particular:O, toolset: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 example , one sent out to a handful of countries identifies network drives when they are added to target systems , and then RC4 like-encrypts and writes certain file metadata and contents to a local path for later Exfiltration .' [/INST] [For:O, example:O, ,:O, one:O, sent:O, out:O, to:O, a:O, handful:O, of:O, countries:O, identifies:O, network:O, drives:O, when:O, they:O, are:O, added:O, to:O, target:O, systems:O, ,:O, and:O, then:O, RC4:S-ENCR, like-encrypts:O, and:O, writes:O, certain:O, file:O, metadata:O, and:O, contents:O, to:O, a:O, local:O, path:O, for:O, later:O, Exfiltration:S-ACT, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 stealer searches for files 60mb and less with these extensions : .doc , .docx , .xls , .xlsx , .ppt , .pptx , .exe , .zip , .rar .' [/INST] [The:O, stealer:O, searches:O, for:O, files:O, 60mb:O, and:O, less:O, with:O, these:O, extensions:O, ::O, .doc:S-FILE, ,:O, .docx:S-FILE, ,:O, .xls:S-FILE, ,:O, .xlsx:S-FILE, ,:O, .ppt:S-FILE, ,:O, .pptx:S-FILE, ,:O, .exe:S-FILE, ,:O, .zip:S-FILE, ,:O, .rar:S-FILE, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 execution , it installs an application-defined Windows hook .' [/INST] [At:O, execution:O, ,:O, it:O, installs:O, an:O, application-defined:O, Windows:S-OS, hook: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 hook gets windows messages indicating when a network drive has been attached .' [/INST] [The:O, hook:O, gets:O, windows:S-OS, messages:O, indicating:O, when:O, a:O, network:O, drive:O, has:O, been:O, attached: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: 'Upon adding a network drive , the hook calls its “ RecordToFile ” file stealer method .' [/INST] [Upon:O, adding:O, a:O, network:O, drive:O, ,:O, the:O, hook:O, calls:O, its:O, “:O, RecordToFile:O, ”:O, file:O, stealer:O, method: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: 'SPLM / CHOPSTICK components deployed throughout 2017 were native 64-bit modular C++ Windows COM backdoors supporting http over fully encrypted TLSv1 and TLSv1.2 communications , mostly deployed in the second half of 2017 by Sofacy .' [/INST] [SPLM:S-MAL, /:O, CHOPSTICK:S-MAL, components:O, deployed:O, throughout:O, 2017:S-TIME, were:O, native:O, 64-bit:O, modular:O, C++:S-TOOL, Windows:S-OS, COM:S-TOOL, backdoors:O, supporting:O, http:S-PROT, over:O, fully:O, encrypted:O, TLSv1:S-PROT, and:O, TLSv1.2:S-PROT, communications:O, ,:O, mostly:O, deployed:O, in:O, the:O, second:B-TIME, half:I-TIME, of:I-TIME, 2017:E-TIME, by:O, Sofacy: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: 'Earlier SPLM activity deployed 32-bit modules over unencrypted http ( and sometimes smtp ) sessions .' [/INST] [Earlier:O, SPLM:S-MAL, activity:O, deployed:O, 32-bit:O, modules:O, over:O, unencrypted:O, http:S-PROT, (:O, and:O, sometimes:O, smtp:S-PROT, ):O, sessions: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 2016 we saw fully functional , very large SPLM / X-Agent modules supporting OS X .' [/INST] [In:O, 2016:S-TIME, we:O, saw:O, fully:O, functional:O, ,:O, very:O, large:O, SPLM:S-MAL, /:O, X-Agent:S-MAL, modules:O, supporting:O, OS:B-OS, X:E-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: 'The executable module continues to be part of a framework supporting various internal and external components communicating over internal and external channels , maintaining slightly morphed encryption and functionality per deployment .' [/INST] [The:O, executable:O, module:O, continues:O, to:O, be:O, part:O, of:O, a:O, framework:O, supporting:O, various:O, internal:O, and:O, external:O, components:O, communicating:O, over:O, internal:O, and:O, external:O, channels:O, ,:O, maintaining:O, slightly:O, morphed:O, encryption:O, and:O, functionality:O, per:O, deployment: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: 'Sofacy selectively used SPLM / CHOPSTICK modules as second stage implants to high interest targets for years now .' [/INST] [Sofacy:S-APT, selectively:O, used:O, SPLM:S-MAL, /:O, CHOPSTICK:S-MAL, modules:O, as:O, second:O, stage:O, implants:O, to:O, high:O, interest:O, targets:O, for:O, years:O, now: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 newer SPLM modules are deployed mostly to Central Asian based targets that may have a tie to NATO in some form .' [/INST] [The:O, newer:O, SPLM:S-MAL, modules:O, are:O, deployed:O, mostly:O, to:O, Central:B-LOC, Asian:E-LOC, based:O, targets:O, that:O, may:O, have:O, a:O, tie:O, to:O, NATO:S-IDTY, in:O, some:O, form: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 targets include foreign affairs government organizations both localized and abroad , and defense organizations ’ presence localized , located in Europe and also located in Afghanistan .' [/INST] [These:O, targets:O, include:O, foreign:O, affairs:O, government:O, organizations:O, both:O, localized:O, and:O, abroad:O, ,:O, and:O, defense:O, organizations:O, ’:O, presence:O, localized:O, ,:O, located:O, in:O, Europe:S-LOC, and:O, also:O, located:O, in:O, Afghanistan: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: 'One outlier SPLM target profile within our visibility includes an audit and consulting firm in Bosnia and Herzegovina .' [/INST] [One:O, outlier:O, SPLM:S-MAL, target:O, profile:O, within:O, our:O, visibility:O, includes:O, an:O, audit:O, and:O, consulting:O, firm:O, in:O, Bosnia:S-LOC, and:O, Herzegovina: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: 'Minor changes and updates to the code were released with these deployments , including a new mutex format and the exclusive use of encrypted HTTP communications over TLS .' [/INST] [Minor:O, changes:O, and:O, updates:O, to:O, the:O, code:O, were:O, released:O, with:O, these:O, deployments:O, ,:O, including:O, a:O, new:O, mutex:O, format:O, and:O, the:O, exclusive:O, use:O, of:O, encrypted:O, HTTP:S-PROT, communications:O, over:O, TLS:S-PROT, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 compiled code itself already is altered per deployment in multiple subtle ways , in order to stymie identification and automated analysis and accommodate targeted environments .' [/INST] [The:O, compiled:O, code:O, itself:O, already:O, is:O, altered:O, per:O, deployment:O, in:O, multiple:O, subtle:O, ways:O, ,:O, in:O, order:O, to:O, stymie:O, identification:O, and:O, automated:O, analysis:O, and:O, accommodate:O, targeted:O, environments: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: 'Strings ( c2 domains and functionality , error messages , etc ) are custom encrypted per deployment .' [/INST] [Strings:O, (:O, c2:S-TOOL, domains:O, and:O, functionality:O, ,:O, error:O, messages:O, ,:O, etc:O, ):O, are:O, custom:O, encrypted:O, per:O, deployment: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 subset of SPLM / CHOPSTICK activity leads into several small surprises that take us into 2018 , to be discussed in further detail at SAS 2018 .' [/INST] [This:O, subset:O, of:O, SPLM:S-MAL, /:O, CHOPSTICK:S-MAL, activity:O, leads:O, into:O, several:O, small:O, surprises:O, that:O, take:O, us:O, into:O, 2018:S-TIME, ,:O, to:O, be:O, discussed:O, in:O, further:O, detail:O, at:O, SAS:S-IDTY, 2018: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: 'The group demonstrates malleability and innovation in maintaining and producing familiar SPLM functionality , but the pragmatic and systematic approach towards producing undetected or difficult-to-detect malware continues .' [/INST] [The:O, group:O, demonstrates:O, malleability:O, and:O, innovation:O, in:O, maintaining:O, and:O, producing:O, familiar:O, SPLM:S-MAL, functionality:O, ,:O, but:O, the:O, pragmatic:O, and:O, systematic:O, approach:O, towards:O, producing:O, undetected:O, or:O, difficult-to-detect:O, malware:O, continues: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: 'Changes in the second stage SPLM backdoor are refined , making the code reliably modular .' [/INST] [Changes:O, in:O, the:O, second:O, stage:O, SPLM:B-MAL, backdoor:E-MAL, are:O, refined:O, ,:O, making:O, the:O, code:O, reliably:O, modular: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 ’s interesting to note that this version of SPLM implements communications that are fully encrypted over HTTPS .' [/INST] [It:O, ’s:O, interesting:O, to:O, note:O, that:O, this:O, version:O, of:O, SPLM:S-MAL, implements:O, communications:O, that:O, are:O, fully:O, encrypted:O, over:O, HTTPS:S-PROT, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 an example , we might see extraneous data in their SSL / TLS certificates that give away information about their provider or resources .' [/INST] [As:O, an:O, example:O, ,:O, we:O, might:O, see:O, extraneous:O, data:O, in:O, their:O, SSL:S-PROT, /:O, TLS:S-PROT, certificates:O, that:O, give:O, away:O, information:O, about:O, their:O, provider:O, or:O, resources: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: 'Leading up to summer 2017 , infrastructure mostly was created with PDR and Internet Domain Service BS Corp , and their resellers .' [/INST] [Leading:O, up:O, to:O, summer:B-TIME, 2017:E-TIME, ,:O, infrastructure:O, mostly:O, was:O, created:O, with:O, PDR:O, and:O, Internet:O, Domain:O, Service:O, BS:O, Corp:O, ,:O, and:O, their:O, resellers: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: 'Hosting mostly was provided at Fast Serv Inc and resellers , in all likelihood related to bitcoin payment processing .' [/INST] [Hosting:O, mostly:O, was:O, provided:O, at:O, Fast:O, Serv:O, Inc:O, and:O, resellers:O, ,:O, in:O, all:O, likelihood:O, related:O, to:O, bitcoin:O, payment:O, processing:O, .:O] </s> |