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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: 'Our investigation of APT28 's compromise of WADA 's network , and our observations of the surrounding events reveal how Russia sought to counteract a damaging narrative and delegitimize the institutions leveling criticism .' [/INST] [Our:O, investigation:O, of:O, APT28:B-HackOrg, 's:O, compromise:O, of:O, WADA:O, 's:O, network:O, ,:O, and:O, our:O, observations:O, of:O, the:O, surrounding:O, events:O, reveal:O, how:O, Russia:B-Area, sought:O, to:O, counteract:O, a:O, damaging:O, narrative:O, and:O, delegitimize:O, the:O, institutions:O, leveling:O, criticism:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 releasing our 2014 report , we continue to assess that APT28 is sponsored by the Russian Government .' [/INST] [Since:O, releasing:O, our:O, 2014:B-Time, report:O, ,:O, we:O, continue:O, to:O, assess:O, that:O, APT28:B-HackOrg, is:O, sponsored:O, by:O, the:O, Russian:B-Area, Government:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In our 2014 report , we identified APT28 as a suspected Russian government-sponsored espionage actor .' [/INST] [In:O, our:O, 2014:B-Time, report:O, ,:O, we:O, identified:O, APT28:B-HackOrg, as:O, a:O, suspected:O, Russian:B-Area, government-sponsored:O, espionage:B-HackOrg, actor:I-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'For full details , please reference our 2014 report , APT28 : A Window into Russia 's Cyber Espionage Operations .' [/INST] [For:O, full:O, details:O, ,:O, please:O, reference:O, our:O, 2014:B-Time, report:O, ,:O, APT28:B-HackOrg, ::O, A:O, Window:O, into:O, Russia:B-Area, 's:O, Cyber:B-OffAct, Espionage:I-OffAct, Operations:I-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The espionage group , which according to the U.S. Department of Homeland Security ( DHS ) and the Federal Bureau of Investigation ( FBI ) is linked to the Russian government , returned to low-key intelligence-gathering operations during 2017 and into 2018 , targeting a range of military and government targets in Europe and South America .' [/INST] [The:O, espionage:B-HackOrg, group:I-HackOrg, ,:O, which:O, according:O, to:O, the:O, U.S.:B-Area, Department:B-SecTeam, of:I-SecTeam, Homeland:I-SecTeam, Security:I-SecTeam, (:O, DHS:B-SecTeam, ):O, and:O, the:O, Federal:O, Bureau:O, of:O, Investigation:O, (:O, FBI:B-SecTeam, ):O, is:O, linked:O, to:O, the:O, Russian:B-Area, government:O, ,:O, returned:O, to:O, low-key:O, intelligence-gathering:B-Purp, operations:O, during:O, 2017:B-Time, and:O, into:O, 2018:B-Time, ,:O, targeting:O, a:O, range:O, of:O, military:B-Idus, and:O, government:B-Idus, targets:O, in:O, Europe:B-Area, and:O, South:B-Area, America:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The APT28 , which is linked to the Russian government , returned to low-key intelligence-gathering operations during 2017 and into 2018 , targeting a range of military and government targets in Europe and South America .' [/INST] [The:O, APT28:B-HackOrg, ,:O, which:O, is:O, linked:O, to:O, the:O, Russian:B-Area, government:O, ,:O, returned:O, to:O, low-key:O, intelligence-gathering:B-Purp, operations:O, during:O, 2017:B-Time, and:O, into:O, 2018:B-Time, ,:O, targeting:O, a:O, range:O, of:O, military:B-Idus, and:O, government:B-Idus, targets:O, in:O, Europe:B-Area, and:O, South:B-Area, America:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Another attack group , Earworm ( aka Zebrocy ) , has been active since at least May 2016 and is involved in what appears to be intelligence gathering operations against military targets in Europe , Central Asia , and Eastern Asia .' [/INST] [Another:O, attack:B-HackOrg, group:I-HackOrg, ,:O, Earworm:B-HackOrg, (:O, aka:O, Zebrocy:B-HackOrg, ):O, ,:O, has:O, been:O, active:O, since:O, at:O, least:O, May:B-Time, 2016:I-Time, and:O, is:O, involved:O, in:O, what:O, appears:O, to:O, be:O, intelligence:B-Purp, gathering:I-Purp, operations:O, against:O, military:O, targets:O, in:O, Europe:B-Area, ,:O, Central:B-Area, Asia:I-Area, ,:O, and:O, Eastern:B-Area, Asia:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Several sources consider APT28 a group of CyberMercs based in Russia .' [/INST] [Several:O, sources:O, consider:O, APT28:B-HackOrg, a:O, group:B-HackOrg, of:O, CyberMercs:O, based:O, in:O, Russia:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The primary targets of APT28 are potential victims in several countries such as Ukraine , Spain , Russia , Romania , the United States and Canada .' [/INST] [The:O, primary:O, targets:O, of:O, APT28:B-HackOrg, are:O, potential:O, victims:O, in:O, several:O, countries:O, such:O, as:O, Ukraine:B-Area, ,:O, Spain:B-Area, ,:O, Russia:B-Area, ,:O, Romania:B-Area, ,:O, the:O, United:B-Area, States:I-Area, and:O, Canada:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We have reasons to believe that the operators of the APT28 network are either Russian citizens or citizens of a neighboring country that speak Russian .' [/INST] [We:O, have:O, reasons:O, to:O, believe:O, that:O, the:O, operators:B-HackOrg, of:O, the:O, APT28:B-HackOrg, network:O, are:O, either:O, Russian:B-Area, citizens:B-Org, or:O, citizens:B-Org, of:O, a:O, neighboring:O, country:O, that:O, speak:O, Russian:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Previous work published by security vendor FireEye in October 2014 suggests the group might be of Russian origin .' [/INST] [Previous:O, work:O, published:O, by:O, security:O, vendor:O, FireEye:B-SecTeam, in:O, October:B-Time, 2014:I-Time, suggests:O, the:O, group:B-HackOrg, might:O, be:O, of:O, Russian:B-Area, origin:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Finally , the use of recent domestic events and a prominent US military exercise focused on deterring Russian aggression highlight APT28 's ability and interest in exploiting geopolitical events for their operations .' [/INST] [Finally:O, ,:O, the:O, use:O, of:O, recent:O, domestic:O, events:O, and:O, a:O, prominent:O, US:B-Area, military:B-Idus, exercise:O, focused:O, on:O, deterring:O, Russian:B-Area, aggression:O, highlight:O, APT28:B-HackOrg, 's:O, ability:O, and:O, interest:O, in:O, exploiting:O, geopolitical:B-Idus, events:O, for: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: 'In 2013 , the Sofacy group expanded their arsenal and added more backdoors and tools , including CORESHELL , SPLM , JHUHUGIT , AZZY and a few others .' [/INST] [In:O, 2013:B-Time, ,:O, the:O, Sofacy:B-HackOrg, group:I-HackOrg, expanded:O, their:O, arsenal:O, and:O, added:O, more:O, backdoors:O, and:O, tools:O, ,:O, including:O, CORESHELL:B-Tool, ,:O, SPLM:B-Tool, ,:O, JHUHUGIT:B-Tool, ,:O, AZZY:B-Tool, and:O, a:O, few:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In 2013 , the Sofacy group expanded their arsenal and added more backdoors and tools , including CORESHELL , SPLM ( aka Xagent , aka CHOPSTICK ) , JHUHUGIT ( which is built with code from the Carberp sources ) , AZZY ( aka ADVSTORESHELL , NETUI , EVILTOSS , and spans across 4-5 generations ) and a few others .' [/INST] [In:O, 2013:B-Time, ,:O, the:O, Sofacy:B-HackOrg, group:I-HackOrg, expanded:O, their:O, arsenal:O, and:O, added:O, more:O, backdoors:O, and:O, tools:O, ,:O, including:O, CORESHELL:B-Tool, ,:O, SPLM:B-Tool, (:O, aka:O, Xagent:B-Tool, ,:O, aka:O, CHOPSTICK:B-Tool, ):O, ,:O, JHUHUGIT:B-Tool, (:O, which:O, is:O, built:O, with:O, code:O, from:O, the:O, Carberp:B-Tool, sources:O, ):O, ,:O, AZZY:B-Tool, (:O, aka:O, ADVSTORESHELL:O, ,:O, NETUI:O, ,:O, EVILTOSS:B-Tool, ,:O, and:O, spans:O, across:O, 4-5:O, generations:O, ):O, and:O, a:O, few:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Sofacy group spearphished targets in several waves with Flash exploits leading to their Carberp based JHUHUGIT downloaders and further stages of malware .' [/INST] [The:O, Sofacy:B-HackOrg, group:I-HackOrg, spearphished:O, targets:O, in:O, several:O, waves:O, with:O, Flash:B-Exp, exploits:I-Exp, leading:O, to:O, their:O, Carberp:B-Tool, based:O, JHUHUGIT:B-Tool, downloaders:I-Tool, and:O, further:O, stages:O, of: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: 'APT28 spearphished targets in several waves with Flash exploits leading to their Carberp based JHUHUGIT downloaders and further stages of malware .' [/INST] [APT28:B-HackOrg, spearphished:O, targets:O, in:O, several:O, waves:O, with:O, Flash:B-Exp, exploits:I-Exp, leading:O, to:O, their:O, Carberp:B-Tool, based:O, JHUHUGIT:B-Tool, downloaders:I-Tool, and:O, further:O, stages:O, of: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 group spearphished targets in several waves with Flash exploits leading to their Carberp based JHUHUGIT downloaders and further stages of malware .' [/INST] [The:O, group:B-HackOrg, spearphished:O, targets:O, in:O, several:O, waves:O, with:O, Flash:B-Exp, exploits:I-Exp, leading:O, to:O, their:O, Carberp:B-Tool, based:O, JHUHUGIT:B-Tool, downloaders:I-Tool, and:O, further:O, stages:O, of: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: 'Their evolving and modified SPLM , CHOPSTICK , XAgent code is a long-standing part of Sofacy activity , however much of it is changing .' [/INST] [Their:O, evolving:O, and:O, modified:O, SPLM:B-Tool, ,:O, CHOPSTICK:B-Tool, ,:O, XAgent:B-Tool, code:O, is:O, a:O, long-standing:O, part:O, of:O, Sofacy:B-OffAct, activity:I-OffAct, ,:O, however:O, much:O, of:O, it:O, is:O, changing:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye has moderate confidence that a campaign targeting the hospitality sector is attributed to Russian actor APT28 .' [/INST] [FireEye:B-SecTeam, has:O, moderate:O, confidence:O, that:O, a:O, campaign:B-OffAct, targeting:O, the:O, hospitality:B-Org, sector:I-Org, is:O, attributed:O, to:O, Russian:B-Area, actor:B-HackOrg, APT28:I-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT28 is using novel techniques involving the EternalBlue exploit and the open source tool Responder to spread laterally through networks and likely target travelers .' [/INST] [APT28:B-HackOrg, is:O, using:O, novel:O, techniques:O, involving:O, the:O, EternalBlue:B-Exp, exploit:I-Exp, and:O, the:O, open:B-Tool, source:I-Tool, tool:I-Tool, Responder:B-Tool, to:O, spread:B-Purp, laterally:I-Purp, through:I-Purp, networks:I-Purp, and:O, likely:O, target:O, travelers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 gaining access to the machines connected to corporate and guest Wi-Fi networks , APT28 deployed Responder .' [/INST] [Upon:O, gaining:O, access:O, to:O, the:O, machines:O, connected:O, to:O, corporate:O, and:O, guest:O, Wi-Fi:O, networks:O, ,:O, APT28:B-HackOrg, deployed:O, Responder:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Compared to other backdoor tools associated with the Sofacy group , the use of Zebrocy in attack campaigns is far more widespread .' [/INST] [Compared:O, to:O, other:O, backdoor:B-Tool, tools:I-Tool, associated:O, with:O, the:O, Sofacy:B-HackOrg, group:I-HackOrg, ,:O, the:O, use:O, of:O, Zebrocy:B-Tool, in:O, attack:B-OffAct, campaigns:I-OffAct, is:O, far:O, more:O, widespread:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 alluded to in our previous blog regarding the Cannon tool , the Sofacy group ( AKA Fancy Bear , APT28 , STRONTIUM , Pawn Storm , Sednit ) has persistently attacked various government and private organizations around the world from mid-October 2018 through mid-November 2018 .' [/INST] [As:O, alluded:O, to:O, in:O, our:O, previous:O, blog:O, regarding:O, the:O, Cannon:B-Tool, tool:I-Tool, ,:O, the:O, Sofacy:B-HackOrg, group:I-HackOrg, (:O, AKA:O, Fancy:B-HackOrg, Bear:I-HackOrg, ,:O, APT28:B-HackOrg, ,:O, STRONTIUM:B-HackOrg, ,:O, Pawn:B-HackOrg, Storm:I-HackOrg, ,:O, Sednit:B-HackOrg, ):O, has:O, persistently:O, attacked:O, various:O, government:B-Idus, and:O, private:O, organizations:O, around:O, the:O, world:O, from:O, mid-October:B-Time, 2018:I-Time, through:O, mid-November:B-Time, 2018:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Russian citizens—journalists , software developers , politicians , researchers at universities , and artists are also targeted by Pawn Storm .' [/INST] [Russian:B-Area, citizens—journalists:B-Org, ,:O, software:B-Org, developers:I-Org, ,:O, politicians:B-Org, ,:O, researchers:B-Org, at:I-Org, universities:I-Org, ,:O, and:O, artists:B-Org, are:O, also:O, targeted:O, by:O, Pawn:B-HackOrg, Storm:I-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The JHUHUGIT implant became a relatively popular first stage for the Sofacy attacks and was used again with a Java zero-day ( CVE-2015-2590 ) in July 2015 .' [/INST] [The:O, JHUHUGIT:B-Tool, implant:O, became:O, a:O, relatively:O, popular:O, first:O, stage:O, for:O, the:O, Sofacy:B-OffAct, attacks:I-OffAct, and:O, was:O, used:O, again:O, with:O, a:O, Java:B-Exp, zero-day:I-Exp, (:O, CVE-2015-2590:B-Exp, ):O, in:O, July:B-Time, 2015:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While the JHUHUGIT ( and more recently , , JKEYSKW , ) implant used in most of the Sofacy attacks , high profile victims are being targeted with another first level implant , representing the latest evolution of their AZZY Trojan .' [/INST] [While:O, the:O, JHUHUGIT:B-Tool, (:O, and:O, more:O, recently:O, ,:O, ,:O, JKEYSKW:B-Tool, ,:O, ):O, implant:O, used:O, in:O, most:O, of:O, the:O, Sofacy:B-OffAct, attacks:I-OffAct, ,:O, high:O, profile:O, victims:O, are:O, being:O, targeted:O, with:O, another:O, first:O, level:O, implant:O, ,:O, representing:O, the:O, latest:O, evolution:O, of:O, their:O, AZZY:B-Tool, Trojan:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once a foothold is established , Sofacy trys to upload more backdoors , USB stealers as well as other hacking tools such as , Mimikatz , for lateral movement .' [/INST] [Once:O, a:O, foothold:O, is:O, established:O, ,:O, Sofacy:B-HackOrg, trys:O, to:O, upload:O, more:O, backdoors:B-Tool, ,:O, USB:B-Tool, stealers:I-Tool, as:O, well:O, as:O, other:O, hacking:O, tools:O, such:O, as:O, ,:O, Mimikatz:B-Tool, ,:O, for:O, lateral:O, movement:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once a foothold is established , they try to upload more backdoors , USB stealers as well as other hacking tools such as , Mimikatz , for lateral movement .' [/INST] [Once:O, a:O, foothold:O, is:O, established:O, ,:O, they:O, try:O, to:O, upload:O, more:O, backdoors:B-Tool, ,:O, USB:B-Tool, stealers:I-Tool, as:O, well:O, as:O, other:O, hacking:O, tools:O, such:O, as:O, ,:O, Mimikatz:B-Tool, ,:O, for:O, lateral:O, movement:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Sofacy threat group continues to target government organizations in the EU , US , and former Soviet states to deliver the Zebrocy tool as a payload .' [/INST] [The:O, Sofacy:B-HackOrg, threat:I-HackOrg, group:I-HackOrg, continues:O, to:O, target:O, government:B-Org, organizations:I-Org, in:O, the:O, EU:B-Area, ,:O, US:B-Area, ,:O, and:O, former:B-Area, Soviet:I-Area, states:O, to:O, deliver:O, the:O, Zebrocy:B-Tool, tool:I-Tool, as:O, a:O, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Of note , we also discovered the Sofacy group using a very similar delivery document to deliver a new Trojan called Cannon .' [/INST] [Of:O, note:O, ,:O, we:O, also:O, discovered:O, the:O, Sofacy:B-HackOrg, group:I-HackOrg, using:O, a:O, very:O, similar:O, delivery:O, document:O, to:O, deliver:O, a:O, new:O, Trojan:B-Tool, called:O, Cannon:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Komplex shares a significant amount of functionality and traits with another tool used by Sofacy – the Carberp variant that Sofacy had used in previous attack campaigns on systems running Windows .' [/INST] [Komplex:B-Tool, shares:O, a:O, significant:O, amount:O, of:O, functionality:O, and:O, traits:O, with:O, another:O, tool:O, used:O, by:O, Sofacy:B-HackOrg, –:O, the:O, Carberp:B-Tool, variant:O, that:O, Sofacy:B-HackOrg, had:O, used:O, in:O, previous:O, attack:B-OffAct, campaigns:I-OffAct, on:O, systems:O, running:O, Windows:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Sofacy group created the Komplex Trojan to use in attack campaigns targeting the OS X operating system – a move that showcases their continued evolution toward multi-platform attacks .' [/INST] [The:O, Sofacy:B-HackOrg, group:I-HackOrg, created:O, the:O, Komplex:B-Tool, Trojan:I-Tool, to:O, use:O, in:O, attack:B-OffAct, campaigns:I-OffAct, targeting:O, the:O, OS:O, X:O, operating:O, system:O, –:O, a:O, move:O, that:O, showcases:O, their:O, continued:O, evolution:O, toward:O, multi-platform:O, attacks:B-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Komplex Trojan revealed a design similar to Sofacy 's Carberp variant Trojan , which we believe may have been done in order to handle compromised Windows and OS X systems using the same C2 server application with relative ease .' [/INST] [The:O, Komplex:B-Tool, Trojan:I-Tool, revealed:O, a:O, design:O, similar:O, to:O, Sofacy:B-HackOrg, 's:O, Carberp:B-Tool, variant:O, Trojan:O, ,:O, which:O, we:O, believe:O, may:O, have:O, been:O, done:O, in:O, order:O, to:O, handle:O, compromised:O, Windows:O, and:O, OS:O, X:O, systems:O, using:O, the:O, same:O, C2:O, server:O, application:O, with:O, relative:O, ease:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 whitepaper explores the tools - such as MiniDuke , CosmicDuke , OnionDuke , CozyDuke , etc- of the Dukes , a well-resourced , highly dedicated and organized cyberespionage group that we believe has been working for the Russian Federation since at least 2008 to collect intelligence in support of foreign and security policy decision-making .' [/INST] [This:O, whitepaper:O, explores:O, the:O, tools:O, -:O, such:O, as:O, MiniDuke:B-Tool, ,:O, CosmicDuke:B-Tool, ,:O, OnionDuke:B-Tool, ,:O, CozyDuke:B-Tool, ,:O, etc-:O, of:O, the:O, Dukes:B-HackOrg, ,:O, a:O, well-resourced:O, ,:O, highly:O, dedicated:O, and:O, organized:O, cyberespionage:B-HackOrg, group:I-HackOrg, that:O, we:O, believe:O, has:O, been:O, working:O, for:O, the:O, Russian:B-Area, Federation:O, since:O, at:O, least:O, 2008:B-Time, to:O, collect:B-Purp, intelligence:I-Purp, in:O, support:O, of:O, foreign:O, and:O, security:O, policy:O, decision-making:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Dukes are a well-resourced , highly dedicated and organized cyberespionage group that we believe has been working for the Russian Federation since at least 2008 to collect intelligence in support of foreign and security policy decision-making .' [/INST] [The:O, Dukes:B-HackOrg, are:O, a:O, well-resourced:O, ,:O, highly:O, dedicated:O, and:O, organized:O, cyberespionage:B-HackOrg, group:I-HackOrg, that:O, we:O, believe:O, has:O, been:O, working:O, for:O, the:O, Russian:B-Area, Federation:O, since:O, at:O, least:O, 2008:B-Time, to:O, collect:B-Purp, intelligence:I-Purp, in:O, support:O, of:O, foreign:O, and:O, security:O, policy:O, decision-making:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Dukes are known to employ a vast arsenal of malware toolsets , which we identify as MiniDuke , CosmicDuke , OnionDuke , CozyDuke , CloudDuke , SeaDuke , HammerDuke , PinchDuke , and GeminiDuke .' [/INST] [The:O, Dukes:B-HackOrg, are:O, known:O, to:O, employ:O, a:O, vast:O, arsenal:O, of:O, malware:O, toolsets:O, ,:O, which:O, we:O, identify:O, as:O, MiniDuke:B-Tool, ,:O, CosmicDuke:B-Tool, ,:O, OnionDuke:B-Tool, ,:O, CozyDuke:B-Tool, ,:O, CloudDuke:B-Tool, ,:O, SeaDuke:B-Tool, ,:O, HammerDuke:B-Tool, ,:O, PinchDuke:B-Tool, ,:O, and:O, GeminiDuke:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The origins of the Duke toolset names can be traced back to when researchers at Kaspersky Labs coined the term , MiniDuke , to identify the first Duke-related malware they found .' [/INST] [The:O, origins:O, of:O, the:O, Duke:O, toolset:O, names:O, can:O, be:O, traced:O, back:O, to:O, when:O, researchers:O, at:O, Kaspersky:B-SecTeam, Labs:I-SecTeam, coined:O, the:O, term:O, ,:O, MiniDuke:B-Tool, ,:O, to:O, identify:O, the:O, first:O, Duke-related:B-Tool, malware:I-Tool, they:O, found:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 researchers continued discovering new toolsets that were created and used by the same group that had been operating MiniDuke , and thus the threat actor operating the toolsets started to be commonly referred to as , Dukes , .' [/INST] [As:O, researchers:O, continued:O, discovering:O, new:O, toolsets:O, that:O, were:O, created:O, and:O, used:O, by:O, the:O, same:O, group:B-HackOrg, that:O, had:O, been:O, operating:O, MiniDuke:B-Tool, ,:O, and:O, thus:O, the:O, threat:B-HackOrg, actor:I-HackOrg, operating:O, the:O, toolsets:O, started:O, to:O, be:O, commonly:O, referred:O, to:O, as:O, ,:O, Dukes:B-HackOrg, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Based on the campaign identifiers found in PinchDuke samples discovered from 2009 , the targets of the Dukes group during that year included organizations such as the Ministry of Defense of Georgia and the ministries of foreign affairs of Turkey and Uganda .' [/INST] [Based:O, on:O, the:O, campaign:B-OffAct, identifiers:O, found:O, in:O, PinchDuke:B-Tool, samples:I-Tool, discovered:O, from:O, 2009:B-Time, ,:O, the:O, targets:O, of:O, the:O, Dukes:B-HackOrg, group:I-HackOrg, during:O, that:O, year:O, included:O, organizations:O, such:O, as:O, the:O, Ministry:B-Idus, of:I-Idus, Defense:I-Idus, of:O, Georgia:O, and:O, the:O, ministries:B-Org, of:I-Org, foreign:I-Org, affairs:I-Org, of:O, Turkey:B-Area, and:O, Uganda:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Importantly , PinchDuke trojan samples always contain a notable text string , which we believe is used as a campaign identifier by the Dukes group to distinguish between multiple attack campaigns that are run in parallel .' [/INST] [Importantly:O, ,:O, PinchDuke:B-Tool, trojan:I-Tool, samples:I-Tool, always:O, contain:O, a:O, notable:O, text:O, string:O, ,:O, which:O, we:O, believe:O, is:O, used:O, as:O, a:O, campaign:B-OffAct, identifier:O, by:O, the:O, Dukes:B-HackOrg, group:I-HackOrg, to:O, distinguish:O, between:O, multiple:O, attack:B-OffAct, campaigns:I-OffAct, that:O, are:O, run:O, in:O, parallel:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 neatly ties together many of the tools used by the Dukes group , as versions of this one loader have been used to load malware from three different Dukes-related toolsets CosmicDuke , PinchDuke , and MiniDuke – over the course of five years .' [/INST] [This:O, neatly:O, ties:O, together:O, many:O, of:O, the:O, tools:O, used:O, by:O, the:O, Dukes:B-HackOrg, group:I-HackOrg, ,:O, as:O, versions:O, of:O, this:O, one:O, loader:O, have:O, been:O, used:O, to:O, load:O, malware:O, from:O, three:O, different:O, Dukes-related:O, toolsets:O, CosmicDuke:B-Tool, ,:O, PinchDuke:B-Tool, ,:O, and:O, MiniDuke:B-Tool, –:O, over:O, the:O, course:O, of:O, five:O, years:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Dukes continued the expansion of their arsenal in 2011 with the addition of two more toolsets : MiniDuke and CozyDuke .' [/INST] [The:O, Dukes:B-HackOrg, continued:O, the:O, expansion:O, of:O, their:O, arsenal:O, in:O, 2011:B-Time, with:O, the:O, addition:O, of:O, two:O, more:O, toolsets:O, ::O, MiniDuke:B-Tool, and:O, CozyDuke:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'As we now know , by February 2013 the Dukes group had been operating MiniDuke and other toolsets for at least 4 and a half years .' [/INST] [As:O, we:O, now:O, know:O, ,:O, by:O, February:B-Time, 2013:I-Time, the:O, Dukes:B-HackOrg, group:I-HackOrg, had:O, been:O, operating:O, MiniDuke:B-Tool, and:O, other:O, toolsets:O, for:O, at:O, least:O, 4:O, and:O, a:O, half:O, years:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Secondly , the value the Dukes intended to gain from these MiniDuke campaigns may have been so great that they deemed it worth the risk of getting noticed .' [/INST] [Secondly:O, ,:O, the:O, value:O, the:O, Dukes:B-HackOrg, intended:O, to:O, gain:O, from:O, these:O, MiniDuke:B-OffAct, campaigns:I-OffAct, may:O, have:O, been:O, so:O, great:O, that:O, they:O, deemed:O, it:O, worth:O, the:O, risk:O, of:O, getting:O, noticed:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This is in stark contrast to some other suspected Russian threat actors ( such as Operation Pawn Storm ) who appear to have increased their targeting of Ukraine following the crisis .' [/INST] [This:O, is:O, in:O, stark:O, contrast:O, to:O, some:O, other:O, suspected:O, Russian:B-Area, threat:B-HackOrg, actors:I-HackOrg, (:O, such:O, as:O, Operation:B-OffAct, Pawn:I-OffAct, Storm:I-OffAct, ):O, who:O, appear:O, to:O, have:O, increased:O, their:O, targeting:O, of:O, Ukraine:B-Area, following:O, the:O, crisis:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Dukes actively targeted Ukraine before the crisis , at a time when Russia was still weighing her options , but once Russia moved from diplomacy to direct action , Ukraine was no longer relevant to the Dukes in the same way .' [/INST] [The:O, Dukes:B-HackOrg, actively:O, targeted:O, Ukraine:B-Area, before:O, the:O, crisis:O, ,:O, at:O, a:O, time:O, when:O, Russia:B-Area, was:O, still:O, weighing:O, her:O, options:O, ,:O, but:O, once:O, Russia:B-Area, moved:O, from:O, diplomacy:O, to:O, direct:O, action:O, ,:O, Ukraine:B-Area, was:O, no:O, longer:O, relevant:O, to:O, the:O, Dukes:B-HackOrg, in:O, the:O, same:O, way:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 latter case however , the Dukes group appear to have also simultaneously developed an entirely new loader , which we first observed being used in conjunction with CosmicDuke during the spring of 2015 .' [/INST] [In:O, the:O, latter:O, case:O, however:O, ,:O, the:O, Dukes:B-HackOrg, group:I-HackOrg, appear:O, to:O, have:O, also:O, simultaneously:O, developed:O, an:O, entirely:O, new:O, loader:O, ,:O, which:O, we:O, first:O, observed:O, being:O, used:O, in:O, conjunction:O, with:O, CosmicDuke:B-Tool, during:O, the:O, spring:B-Time, of:I-Time, 2015:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Dukes could have ceased all use of CosmicDuke ( at least until they had developed a new loader ) or retired it entirely , since they still had other toolsets available .' [/INST] [The:O, Dukes:B-HackOrg, could:O, have:O, ceased:O, all:O, use:O, of:O, CosmicDuke:B-Tool, (:O, at:O, least:O, until:O, they:O, had:O, developed:O, a:O, new:O, loader:O, ):O, or:O, retired:O, it:O, entirely:O, ,:O, since:O, they:O, still:O, had:O, other:O, toolsets:O, available:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 these CozyDuke campaigns however , the Dukes appear to have employed two particular later-stage toolsets , SeaDuke and HammerDuke .' [/INST] [For:O, these:O, CozyDuke:B-OffAct, campaigns:I-OffAct, however:O, ,:O, the:O, Dukes:B-HackOrg, appear:O, to:O, have:O, employed:O, two:O, particular:O, later-stage:O, toolsets:O, ,:O, SeaDuke:B-Tool, and:O, HammerDuke:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Firstly , as with the MiniDuke campaigns of February 2013 and CosmicDuke campaigns in the summer of 2014 , again the group clearly prioritized the continuation of their operations over maintaining stealth .' [/INST] [Firstly:O, ,:O, as:O, with:O, the:O, MiniDuke:B-OffAct, campaigns:I-OffAct, of:O, February:B-Time, 2013:I-Time, and:O, CosmicDuke:B-OffAct, campaigns:I-OffAct, in:O, the:O, summer:B-Time, of:I-Time, 2014:I-Time, ,:O, again:O, the:O, group:B-HackOrg, clearly:O, prioritized:O, the:O, continuation:O, of:O, their:O, operations:O, over:O, maintaining:O, stealth:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition to the notably overt and large-scale campaigns with CozyDuke and CloudDuke , the Dukes also continued to engage in more covert , surgical campaigns using CosmicDuke .' [/INST] [In:O, addition:O, to:O, the:O, notably:O, overt:O, and:O, large-scale:O, campaigns:B-OffAct, with:O, CozyDuke:B-OffAct, and:O, CloudDuke:B-OffAct, ,:O, the:O, Dukes:B-HackOrg, also:O, continued:O, to:O, engage:O, in:O, more:O, covert:O, ,:O, surgical:O, campaigns:B-OffAct, using:O, CosmicDuke:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We are however only aware of one instance - the exploitation of CVE-2013-0640 to deploy MiniDuke - where we believe the exploited vulnerability was a zero-day at the time that the group acquired the exploit .' [/INST] [We:O, are:O, however:O, only:O, aware:O, of:O, one:O, instance:O, -:O, the:O, exploitation:O, of:O, CVE-2013-0640:B-Exp, to:O, deploy:O, MiniDuke:B-Tool, -:O, where:O, we:O, believe:O, the:O, exploited:O, vulnerability:O, was:O, a:O, zero-day:B-Exp, at:O, the:O, time:O, that:O, the:O, group:B-HackOrg, acquired:O, the:O, exploit:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'All of the available evidence however does in our opinion suggest that the group operates on behalf of the Russian Federation .' [/INST] [All:O, of:O, the:O, available:O, evidence:O, however:O, does:O, in:O, our:O, opinion:O, suggest:O, that:O, the:O, group:B-HackOrg, operates:O, on:O, behalf:O, of:O, the:O, Russian:B-Area, Federation:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This assertion of time zone is also supported by timestamps found in many GeminiDuke samples , which similarly suggest the group work in the Moscow Standard Time timezone , as further detailed in the section on the technical analysis of GeminiDuke .' [/INST] [This:O, assertion:O, of:O, time:O, zone:O, is:O, also:O, supported:O, by:O, timestamps:O, found:O, in:O, many:O, GeminiDuke:B-Tool, samples:I-Tool, ,:O, which:O, similarly:O, suggest:O, the:O, group:B-HackOrg, work:O, in:O, the:O, Moscow:O, Standard:O, Time:O, timezone:O, ,:O, as:O, further:O, detailed:O, in:O, the:O, section:O, on:O, the:O, technical:O, analysis:O, of:O, GeminiDuke:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Mandiant has observed Russian nation-state attackers APT29 employing domain fronting techniques for stealthy backdoor access to victim environments for at least two years .' [/INST] [Mandiant:B-SecTeam, has:O, observed:O, Russian:B-Area, nation-state:O, attackers:B-HackOrg, APT29:B-HackOrg, employing:O, domain:O, fronting:O, techniques:O, for:O, stealthy:O, backdoor:O, access:O, to:O, victim:O, environments:O, for:O, at:O, least:O, two:O, years:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT29 has used The Onion Router and the TOR domain fronting plugin meek to create a hidden , encrypted network tunnel that appeared to connect to Google services over TLS .' [/INST] [APT29:B-HackOrg, has:O, used:O, The:B-Tool, Onion:I-Tool, Router:I-Tool, and:O, the:O, TOR:B-Tool, domain:I-Tool, fronting:I-Tool, plugin:I-Tool, meek:I-Tool, to:O, create:O, a:O, hidden:O, ,:O, encrypted:O, network:O, tunnel:O, that:O, appeared:O, to:O, connect:O, to:O, Google:B-Org, services:O, over:O, TLS:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Mandiant has observed APT29 using a stealthy backdoor that we call POSHSPY .' [/INST] [Mandiant:B-SecTeam, has:O, observed:O, APT29:B-HackOrg, using:O, a:O, stealthy:O, backdoor:O, that:O, we:O, call:O, POSHSPY:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Mandiant has since identified POSHSPY in several other environments compromised by APT29 over the past two years .' [/INST] [Mandiant:B-SecTeam, has:O, since:O, identified:O, POSHSPY:B-Tool, in:O, several:O, other:O, environments:O, compromised:O, by:O, APT29:B-HackOrg, over:O, the:O, past:O, two:O, years:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 investigations Mandiant has conducted , it appeared that APT29 deployed POSHSPY as a secondary backdoor for use if they lost access to their primary backdoors .' [/INST] [In:O, the:O, investigations:O, Mandiant:B-SecTeam, has:O, conducted:O, ,:O, it:O, appeared:O, that:O, APT29:B-HackOrg, deployed:O, POSHSPY:B-Tool, as:O, a:O, secondary:O, backdoor:O, for:O, use:O, if:O, they:O, lost:O, access:O, to:O, their:O, primary:O, backdoors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'POSHSPY is an excellent example of the skill and craftiness of APT29 .' [/INST] [POSHSPY:B-Tool, is:O, an:O, excellent:O, example:O, of:O, the:O, skill:O, and:O, craftiness:O, of:O, APT29:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye assesses that APT32 leverages a unique suite of fully-featured malware , in conjunction with commercially-available tools , to conduct targeted operations that are aligned with Vietnamese state interests .' [/INST] [FireEye:B-SecTeam, assesses:O, that:O, APT32:B-HackOrg, leverages:O, a:O, unique:O, suite:O, of:O, fully-featured:O, malware:O, ,:O, in:O, conjunction:O, with:O, commercially-available:O, tools:O, ,:O, to:O, conduct:O, targeted:O, operations:O, that:O, are:O, aligned:O, with:O, Vietnamese:B-Area, state:O, interests:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition to focused targeting of the private sector with ties to Vietnam , APT32 has also targeted foreign governments , as well as Vietnamese dissidents and journalists since at least 2013 .' [/INST] [In:O, addition:O, to:O, focused:O, targeting:O, of:O, the:O, private:O, sector:O, with:O, ties:O, to:O, Vietnam:B-Area, ,:O, APT32:B-HackOrg, has:O, also:O, targeted:O, foreign:O, governments:B-Idus, ,:O, as:O, well:O, as:O, Vietnamese:B-Area, dissidents:B-Org, and:O, journalists:B-Org, since:O, at:O, least:O, 2013:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'From 2016 through 2017 , two subsidiaries of U.S. and Philippine consumer products corporations , located inside Vietnam , were the target of APT32 intrusion operations .' [/INST] [From:O, 2016:B-Time, through:O, 2017:B-Time, ,:O, two:O, subsidiaries:O, of:O, U.S.:B-Area, and:O, Philippine:O, consumer:B-Org, products:I-Org, corporations:I-Org, ,:O, located:O, inside:O, Vietnam:B-Area, ,:O, were:O, the:O, target:O, of:O, APT32:B-HackOrg, intrusion: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: 'From 2016 through 2017 , two consumer products corporations , located inside Vietnam , were the target of APT32 intrusion operations .' [/INST] [From:O, 2016:B-Time, through:O, 2017:B-Time, ,:O, two:O, consumer:B-Org, products:I-Org, corporations:I-Org, ,:O, located:O, inside:O, Vietnam:B-Area, ,:O, were:O, the:O, target:O, of:O, APT32:B-HackOrg, intrusion: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: 'In 2014 , APT32 leveraged a spear-phishing attachment titled , Plans to crackdown on protesters at the Embassy of Vietnam.exe , , which targeted dissident activity among the Vietnamese diaspora in Southeast Asia .' [/INST] [In:O, 2014:B-Time, ,:O, APT32:B-HackOrg, leveraged:O, a:O, spear-phishing:B-Way, attachment:I-Way, titled:O, ,:O, Plans:O, to:O, crackdown:O, on:O, protesters:O, at:O, the:O, Embassy:O, of:O, Vietnam.exe:B-SamFile, ,:O, ,:O, which:O, targeted:O, dissident:O, activity:B-OffAct, among:O, the:O, Vietnamese:B-Area, diaspora:B-Org, in:O, Southeast:B-Area, Asia:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In 2015 and 2016 , two Vietnamese media outlets were targeted with malware that FireEye assesses to be unique to APT32 .' [/INST] [In:O, 2015:B-Time, and:O, 2016:B-Time, ,:O, two:O, Vietnamese:B-Area, media:B-Idus, outlets:O, were:O, targeted:O, with:O, malware:O, that:O, FireEye:B-SecTeam, assesses:O, to:O, be:O, unique:O, to:O, APT32:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In 2014 , APT32 leveraged a spear-phishing attachment titled , Plans to crackdown on protesters at the Embassy of Vietnam.exe , .' [/INST] [In:O, 2014:B-Time, ,:O, APT32:B-HackOrg, leveraged:O, a:O, spear-phishing:B-Way, attachment:I-Way, titled:O, ,:O, Plans:O, to:O, crackdown:O, on:O, protesters:O, at:O, the:O, Embassy:O, of:O, Vietnam.exe:B-SamFile, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Since at least 2014 , FireEye has observed APT32 targeting foreign corporations with a vested interest in Vietnam 's manufacturing , consumer products , and hospitality sectors .' [/INST] [Since:O, at:O, least:O, 2014:B-Time, ,:O, FireEye:B-SecTeam, has:O, observed:O, APT32:B-HackOrg, targeting:O, foreign:B-Idus, corporations:I-Idus, with:O, a:O, vested:O, interest:O, in:O, Vietnam:B-Area, 's:O, manufacturing:B-Idus, ,:O, consumer:B-Idus, products:I-Idus, ,:O, and:O, hospitality:B-Org, sectors:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT32 operations are characterized through deployment of signature malware payloads including WINDSHIELD , KOMPROGO , SOUNDBITE , and PHOREAL .' [/INST] [APT32:B-HackOrg, operations:O, are:O, characterized:O, through:O, deployment:O, of:O, signature:O, malware:O, payloads:O, including:O, WINDSHIELD:B-Tool, ,:O, KOMPROGO:B-Tool, ,:O, SOUNDBITE:B-Tool, ,:O, and:O, PHOREAL:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In 2017 , social engineering content in lures used by the actor provided evidence that they were likely used to target members of the Vietnam diaspora in Australia as well as government employees in the Philippines .' [/INST] [In:O, 2017:B-Time, ,:O, social:B-Idus, engineering:I-Idus, content:O, in:O, lures:O, used:O, by:O, the:O, actor:B-HackOrg, provided:O, evidence:O, that:O, they:O, were:O, likely:O, used:O, to:O, target:O, members:O, of:O, the:O, Vietnam:B-Area, diaspora:B-Org, in:O, Australia:B-Area, as:O, well:O, as:O, government:B-Org, employees:I-Org, in:O, the:O, Philippines:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT32 often deploys these backdoors along with the commercially-available Cobalt Strike BEACON backdoor .' [/INST] [APT32:B-HackOrg, often:O, deploys:O, these:O, backdoors:O, along:O, with:O, the:O, commercially-available:O, Cobalt:B-Tool, Strike:I-Tool, BEACON:I-Tool, backdoor:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT32 often deploys these backdoors along with the commercially-available Cobalt Strike backdoor .' [/INST] [APT32:B-HackOrg, often:O, deploys:O, these:O, backdoors:O, along:O, with:O, the:O, commercially-available:O, Cobalt:B-Tool, Strike:I-Tool, backdoor:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Based on incident response investigations , product detections , and intelligence observations along with additional publications on the same operators , FireEye assesses that APT32 is a cyber espionage group aligned with Vietnamese government interests .' [/INST] [Based:O, on:O, incident:O, response:O, investigations:O, ,:O, product:O, detections:O, ,:O, and:O, intelligence:O, observations:O, along:O, with:O, additional:O, publications:O, on:O, the:O, same:O, operators:B-HackOrg, ,:O, FireEye:B-SecTeam, assesses:O, that:O, APT32:B-HackOrg, is:O, a:O, cyber:B-HackOrg, espionage:I-HackOrg, group:I-HackOrg, aligned:O, with:O, Vietnamese:B-Area, government:O, interests:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'OceanLotus , also known as APT32 , is believed to be a Vietnam-based APT group that has become increasingly sophisticated in its attack tactics , techniques , and procedures ( TTPs ) .' [/INST] [OceanLotus:B-HackOrg, ,:O, also:O, known:O, as:O, APT32:B-HackOrg, ,:O, is:O, believed:O, to:O, be:O, a:O, Vietnam-based:B-Area, APT:B-HackOrg, group:I-HackOrg, that:O, has:O, become:O, increasingly:O, sophisticated:O, in:O, its:O, attack:O, tactics:O, ,:O, techniques:O, ,:O, and:O, procedures:O, (:O, TTPs: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: 'While Volexity does not typically engage in attempting attribution of any threat actor , Volexity does agree with previously reported assessments that OceanLotus is likely operating out of Vietnam .' [/INST] [While:O, Volexity:B-SecTeam, does:O, not:O, typically:O, engage:O, in:O, attempting:O, attribution:O, of:O, any:O, threat:B-HackOrg, actor:I-HackOrg, ,:O, Volexity:B-SecTeam, does:O, agree:O, with:O, previously:O, reported:O, assessments:O, that:O, OceanLotus:B-HackOrg, is:O, likely:O, operating:O, out:O, of:O, Vietnam:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'During that phase , the APT32 operated a fileless PowerShell-based infrastructure , using customized PowerShell payloads taken from known offensive frameworks such as Cobalt Strike , PowerSploit and Nishang .' [/INST] [During:O, that:O, phase:O, ,:O, the:O, APT32:B-HackOrg, operated:O, a:O, fileless:O, PowerShell-based:O, infrastructure:O, ,:O, using:O, customized:B-Tool, PowerShell:I-Tool, payloads:O, taken:O, from:O, known:O, offensive:O, frameworks:O, such:O, as:O, Cobalt:B-Tool, Strike:I-Tool, ,:O, PowerSploit:B-Tool, and:O, Nishang:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , over the past few years , we have been tracking a separate , less widely known suspected Iranian group with potential destructive capabilities , whom we call APT33 .' [/INST] [However:O, ,:O, over:O, the:O, past:O, few:O, years:O, ,:O, we:O, have:O, been:O, tracking:O, a:O, separate:O, ,:O, less:O, widely:O, known:O, suspected:O, Iranian:B-Area, group:B-HackOrg, with:O, potential:O, destructive:O, capabilities:O, ,:O, whom:O, we:O, call:O, APT33:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Our analysis reveals that APT33 is a capable group that has carried out cyber espionage operations since at least 2013 .' [/INST] [Our:O, analysis:O, reveals:O, that:O, APT33:B-HackOrg, is:O, a:O, capable:O, group:B-HackOrg, that:O, has:O, carried:O, out:O, cyber:B-OffAct, espionage:I-OffAct, operations:I-OffAct, since:O, at:O, least:O, 2013:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We assess APT33 works at the behest of the Iranian government .' [/INST] [We:O, assess:O, APT33:B-HackOrg, works:O, at:O, the:O, behest:O, of:O, the:O, Iranian:B-Area, government:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT33 has targeted organizations – spanning multiple industries – headquartered in the United States , Saudi Arabia and South Korea .' [/INST] [APT33:B-HackOrg, has:O, targeted:O, organizations:O, –:O, spanning:B-Idus, multiple:I-Idus, industries:I-Idus, –:O, headquartered:O, in:O, the:O, United:B-Area, States:I-Area, ,:O, Saudi:B-Area, Arabia:I-Area, and:O, South:B-Area, Korea:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Cybereason also attributes the recently reported Backdoor.Win32.Denis to the OceanLotus Group , which at the time of this report 's writing , had not been officially linked to this threat actor .' [/INST] [Cybereason:B-SecTeam, also:O, attributes:O, the:O, recently:O, reported:O, Backdoor.Win32.Denis:B-Tool, to:O, the:O, OceanLotus:B-HackOrg, Group:I-HackOrg, ,:O, which:O, at:O, the:O, time:O, of:O, this:O, report:O, 's:O, writing:O, ,:O, had:O, not:O, been:O, officially:O, linked:O, to:O, this:O, threat:B-HackOrg, actor:I-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT33 has shown particular interest in organizations in the aviation sector , as well as organizations in the energy sector with ties to petrochemical production .' [/INST] [APT33:B-HackOrg, has:O, shown:O, particular:O, interest:O, in:O, organizations:O, in:O, the:O, aviation:B-Org, sector:I-Org, ,:O, as:O, well:O, as:O, organizations:O, in:O, the:O, energy:B-Org, sector:I-Org, with:O, ties:O, to:O, petrochemical:B-Idus, production:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 mid-2016 through early 2017 , APT33 compromised a U.S. organization in the aerospace sector and targeted a business conglomerate located in Saudi Arabia with aviation holdings .' [/INST] [From:O, mid-2016:B-Time, through:O, early:B-Time, 2017:I-Time, ,:O, APT33:B-HackOrg, compromised:O, a:O, U.S.:B-Area, organization:B-Org, in:O, the:O, aerospace:B-Org, sector:I-Org, and:O, targeted:O, a:O, business:B-Org, conglomerate:I-Org, located:O, in:O, Saudi:B-Area, Arabia:I-Area, with:O, aviation:O, holdings:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 mid-2016 through early 2017 , APT33 compromised organizations located in Saudi Arabia and U.S. in the aerospace sector .' [/INST] [From:O, mid-2016:B-Time, through:O, early:B-Time, 2017:I-Time, ,:O, APT33:B-HackOrg, compromised:O, organizations:O, located:O, in:O, Saudi:B-Area, Arabia:I-Area, and:O, U.S.:B-Area, in:O, the:O, aerospace:B-Org, sector:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'During the same time period , APT33 also targeted companies in South Korea involved in oil refining and petrochemicals .' [/INST] [During:O, the:O, same:O, time:O, period:O, ,:O, APT33:B-HackOrg, also:O, targeted:O, companies:O, in:O, South:B-Area, Korea:I-Area, involved:O, in:O, oil:B-Idus, refining:I-Idus, and:O, petrochemicals:B-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'More recently , in May 2017 , APT33 appeared to target a Saudi organization and a South Korean business conglomerate using a malicious file that attempted to entice victims with job vacancies for a Saudi Arabian petrochemical company .' [/INST] [More:O, recently:O, ,:O, in:O, May:B-Time, 2017:I-Time, ,:O, APT33:B-HackOrg, appeared:O, to:O, target:O, a:O, Saudi:B-Area, organization:B-Org, and:O, a:O, South:B-Area, Korean:I-Area, business:B-Org, conglomerate:I-Org, using:O, a:O, malicious:B-SamFile, file:I-SamFile, that:O, attempted:O, to:O, entice:O, victims:O, with:O, job:O, vacancies:O, for:O, a:O, Saudi:B-Area, Arabian:I-Area, petrochemical:B-Org, company:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'More recently , in May 2017 , APT33 appeared to target organizations in Saudi and South Korea using a malicious file that attempted to entice victims with job vacancies .' [/INST] [More:O, recently:O, ,:O, in:O, May:B-Time, 2017:I-Time, ,:O, APT33:B-HackOrg, appeared:O, to:O, target:O, organizations:O, in:O, Saudi:B-Area, and:O, South:B-Area, Korea:I-Area, using:O, a:O, malicious:B-SamFile, file:I-SamFile, that:O, attempted:O, to:O, entice:O, victims:O, with:O, job:O, vacancies:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We assess the targeting of multiple companies with aviation-related partnerships to Saudi Arabia indicates that APT33 may possibly be looking to gain insights on Saudi Arabia 's military aviation capabilities to enhance Iran 's domestic aviation capabilities or to support Iran 's military and strategic decision making vis a vis Saudi Arabia .' [/INST] [We:O, assess:O, the:O, targeting:O, of:O, multiple:O, companies:O, with:O, aviation-related:O, partnerships:O, to:O, Saudi:B-Area, Arabia:I-Area, indicates:O, that:O, APT33:B-HackOrg, may:O, possibly:O, be:O, looking:O, to:O, gain:O, insights:O, on:O, Saudi:B-Area, Arabia:I-Area, 's:O, military:B-Purp, aviation:I-Purp, capabilities:I-Purp, to:O, enhance:O, Iran:B-Area, 's:O, domestic:B-Purp, aviation:I-Purp, capabilities:I-Purp, or:O, to:O, support:O, Iran:B-Area, 's:O, military:B-Idus, and:O, strategic:O, decision:O, making:O, vis:O, a:O, vis:O, Saudi:B-Area, Arabia:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT33 may possibly be looking to gain insights on Saudi Arabia 's military aviation capabilities to enhance Iran 's domestic aviation capabilities or to support Iran 's military and strategic decision making vis a vis Saudi Arabia .' [/INST] [APT33:B-HackOrg, may:O, possibly:O, be:O, looking:O, to:O, gain:O, insights:O, on:O, Saudi:B-Area, Arabia:I-Area, 's:O, military:B-Purp, aviation:I-Purp, capabilities:I-Purp, to:O, enhance:O, Iran:B-Area, 's:O, domestic:B-Purp, aviation:I-Purp, capabilities:I-Purp, or:O, to:O, support:O, Iran:B-Area, 's:O, military:B-Idus, and:O, strategic:O, decision:O, making:O, vis:O, a:O, vis:O, Saudi:B-Area, Arabia:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The generalized targeting of organizations involved in energy and petrochemicals mirrors previously observed targeting by other suspected Iranian threat groups , indicating a common interest in the sectors across Iranian actors .' [/INST] [The:O, generalized:O, targeting:O, of:O, organizations:O, involved:O, in:O, energy:B-Idus, and:O, petrochemicals:B-Idus, mirrors:O, previously:O, observed:O, targeting:O, by:O, other:O, suspected:O, Iranian:B-Area, threat:B-HackOrg, groups:I-HackOrg, ,:O, indicating:O, a:O, common:O, interest:O, in:O, the:O, sectors:O, across:O, Iranian:B-Area, actors:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT33 sent spear phishing emails to employees whose jobs related to the aviation industry .' [/INST] [APT33:B-HackOrg, sent:O, spear:B-Way, phishing:I-Way, emails:I-Way, to:O, employees:B-Org, whose:O, jobs:O, related:O, to:O, the:O, aviation:B-Idus, industry:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT33 registered multiple domains that masquerade as Saudi Arabian aviation companies and Western organizations that together have partnerships to provide training , maintenance and support for Saudi 's military and commercial fleet .' [/INST] [APT33:B-HackOrg, registered:O, multiple:O, domains:O, that:O, masquerade:O, as:O, Saudi:B-Area, Arabian:I-Area, aviation:B-Org, companies:I-Org, and:O, Western:B-Area, organizations:O, that:O, together:O, have:O, partnerships:O, to:O, provide:O, training:O, ,:O, maintenance:O, and:O, support:O, for:O, Saudi:B-Area, 's:O, military:B-Purp, and:O, commercial:B-Purp, fleet:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We identified APT33 malware tied to an Iranian persona who may have been employed by the Iranian government to conduct cyber threat activity against its adversaries .' [/INST] [We:O, identified:O, APT33:B-Tool, malware:I-Tool, tied:O, to:O, an:O, Iranian:B-Area, persona:O, who:O, may:O, have:O, been:O, employed:O, by:O, the:O, Iranian:B-Area, government:O, to:O, conduct:O, cyber:B-OffAct, threat:I-OffAct, activity:I-OffAct, against:O, its:O, adversaries:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT33 's targeting of organizations involved in aerospace and energy most closely aligns with nation-state interests , implying that the threat actor is most likely government sponsored .' [/INST] [APT33:B-HackOrg, 's:O, targeting:O, of:O, organizations:O, involved:O, in:O, aerospace:B-Idus, and:O, energy:B-Idus, most:O, closely:O, aligns:O, with:O, nation-state:O, interests:O, ,:O, implying:O, that:O, the:O, threat:B-HackOrg, actor:I-HackOrg, is:O, most:O, likely:O, government:O, sponsored:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT33 leverages popular Iranian hacker tools and DNS servers used by other suspected Iranian threat groups .' [/INST] [APT33:B-HackOrg, leverages:O, popular:O, Iranian:B-Area, hacker:O, tools:O, and:O, DNS:O, servers:O, used:O, by:O, other:O, suspected:O, Iranian:B-Area, threat:B-HackOrg, groups:I-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This coupled with the timing of operations – which coincides with Iranian working hours – and the use of multiple Iranian hacker tools and name servers bolsters our assessment that APT33 may have operated on behalf of the Iranian government .' [/INST] [This:O, coupled:O, with:O, the:O, timing:O, of:O, operations:O, –:O, which:O, coincides:O, with:O, Iranian:B-Area, working:O, hours:O, –:O, and:O, the:O, use:O, of:O, multiple:O, Iranian:B-Area, hacker:O, tools:O, and:O, name:B-Tool, servers:I-Tool, bolsters:O, our:O, assessment:O, that:O, APT33:B-HackOrg, may:O, have:O, operated:O, on:O, behalf:O, of:O, the:O, Iranian:B-Area, government:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The publicly available backdoors and tools utilized by APT33 – including NANOCORE , NETWIRE , and ALFA Shell – are all available on Iranian hacking websites , associated with Iranian hackers , and used by other suspected Iranian threat groups .' [/INST] [The:O, publicly:O, available:O, backdoors:O, and:O, tools:O, utilized:O, by:O, APT33:B-HackOrg, –:O, including:O, NANOCORE:B-Tool, ,:O, NETWIRE:B-Tool, ,:O, and:O, ALFA:B-Tool, Shell:I-Tool, –:O, are:O, all:O, available:O, on:O, Iranian:B-Area, hacking:O, websites:O, ,:O, associated:O, with:O, Iranian:B-Area, hackers:B-HackOrg, ,:O, and:O, used:O, by:O, other:O, suspected:O, Iranian:B-Area, threat:B-HackOrg, groups:I-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT33 's focus on aviation may indicate the group 's desire to gain insight into regional military capabilities to enhance Iran 's aviation capabilities or to support Iran 's military and strategic decision making .' [/INST] [APT33:B-HackOrg, 's:O, focus:O, on:O, aviation:B-Idus, may:O, indicate:O, the:O, group:O, 's:O, desire:O, to:O, gain:O, insight:O, into:O, regional:O, military:B-Idus, capabilities:O, to:O, enhance:O, Iran:B-Area, 's:O, aviation:B-Purp, capabilities:I-Purp, or:O, to:O, support:O, Iran:B-Area, 's:O, military:B-Idus, and:O, strategic:B-Purp, decision:I-Purp, making:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Specifically , the targeting of organizations in the aerospace and energy sectors indicates that the APT33 is likely in search of strategic intelligence capable of benefitting a government or military sponsor .' [/INST] [Specifically:O, ,:O, the:O, targeting:O, of:O, organizations:O, in:O, the:O, aerospace:B-Idus, and:O, energy:B-Org, sectors:I-Org, indicates:O, that:O, the:O, APT33:B-HackOrg, is:O, likely:O, in:O, search:O, of:O, strategic:O, intelligence:O, capable:O, of:O, benefitting:O, a:O, government:B-Idus, or:O, military:B-Idus, sponsor:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT33 's focus on aviation may indicate the group 's desire to gain insight into regional military aviation capabilities to enhance Iran 's aviation capabilities or to support Iran 's military and strategic decision making .' [/INST] [APT33:B-HackOrg, 's:O, focus:O, on:O, aviation:B-Idus, may:O, indicate:O, the:O, group:O, 's:O, desire:O, to:O, gain:O, insight:O, into:O, regional:O, military:B-Purp, aviation:I-Purp, capabilities:I-Purp, to:O, enhance:O, Iran:B-Area, 's:O, aviation:B-Idus, capabilities:O, or:O, to:O, support:O, Iran:B-Area, 's:O, military:B-Idus, and:O, strategic:O, decision:O, making:O, .:O] </s> |