Datasets:
pritamdeka
/
dataset_dnrti_train

Dataset card Data Studio Files
xet
Community
1
text
stringlengths
306
1.51k
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'First released in 2005 , the tool has gone unchanged since 2008 with v ersion 2.3.2 .' [/INST] [First:O, released:O, in:O, 2005:B-Time, ,:O, the:O, tool:O, has:O, gone:O, unchanged:O, since:O, 2008:B-Time, with:O, v:O, ersion:O, 2.3.2:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Poison Ivy includes features common to most Windows-based RATs , including key logging , screen capturing , video capturing , file transfers , system administration , password theft , and traffic relaying .' [/INST] [Poison:B-Tool, Ivy:I-Tool, includes:O, features:O, common:O, to:O, most:O, Windows-based:O, RATs:B-Tool, ,:O, including:O, key:B-Features, logging:I-Features, ,:O, screen:B-Features, capturing:I-Features, ,:O, video:B-Features, capturing:I-Features, ,:O, file:B-Features, transfers:I-Features, ,:O, system:B-Features, administration:I-Features, ,:O, password:B-Features, theft:I-Features, ,:O, and:O, traffic:B-Features, relaying:I-Features, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT40 was previously reported as TEMP.Periscope and TEMP.Jumper .' [/INST] [APT40:B-HackOrg, was:O, previously:O, reported:O, as:O, TEMP.Periscope:B-HackOrg, and:O, TEMP.Jumper: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: 'They move laterally and escalate system privileges to extract sensitive information — whenever the attacker wants to do so.4 ,5 Because some RATs used in targeted attacks are widely available , determining whether an attack is part of a broader APT campaign can be difficult .' [/INST] [They:O, move:O, laterally:O, and:O, escalate:O, system:O, privileges:O, to:O, extract:B-Purp, sensitive:I-Purp, information:I-Purp, —:O, whenever:O, the:O, attacker:B-HackOrg, wants:O, to:O, do:O, so.4:O, ,5:O, Because:O, some:O, RATs:B-Tool, used:O, in:O, targeted:B-OffAct, attacks:I-OffAct, are:O, widely:O, available:O, ,:O, determining:O, whether:O, an:O, attack:B-OffAct, is:O, part:O, of:O, a:O, broader:O, APT:B-OffAct, campaign:I-OffAct, can:O, be:O, difficult:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 2011 , three years after the most recent release of PIVY , attackers used the RAT to compromise security firm RSA and steal data about its SecureID authentication system .' [/INST] [In:O, 2011:B-Time, ,:O, three:O, years:O, after:O, the:O, most:O, recent:O, release:O, of:O, PIVY:B-Tool, ,:O, attackers:B-HackOrg, used:O, the:O, RAT:B-Tool, to:O, compromise:O, security:B-Org, firm:I-Org, RSA:I-Org, and:O, steal:B-Purp, data:I-Purp, about:O, its:O, SecureID:O, authentication:O, system:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'PIVY also played a key role in the 2011 campaign known as Nitro that targeted chemical makers , government agencies , defense contractors , and human rights groups.10,11 Still active a year later , the Nitro attackers used a zero-day vulnerability in Java to deploy PIVY in 2012 .' [/INST] [PIVY:B-Tool, also:O, played:O, a:O, key:O, role:O, in:O, the:O, 2011:B-OffAct, campaign:I-OffAct, known:O, as:O, Nitro:O, that:O, targeted:O, chemical:B-Org, makers:I-Org, ,:O, government:B-Org, agencies:I-Org, ,:O, defense:B-Org, contractors:I-Org, ,:O, and:O, human:O, rights:O, groups.10,11:O, Still:O, active:O, a:O, year:O, later:O, ,:O, the:O, Nitro:O, attackers:B-HackOrg, used:O, a:O, zero-day:B-Exp, vulnerability:I-Exp, in:O, Java:O, to:O, deploy:O, PIVY:B-Tool, in:O, 2012: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: 'Just recently , PIVY was the payload of a zero-day exploit in Internet Explorer used in what is known as a , strategic web compromise , attack against visitors to a U.S. government website and a variety of others .' [/INST] [Just:O, recently:O, ,:O, PIVY:B-Tool, was:O, the:O, payload:O, of:O, a:O, zero-day:B-Exp, exploit:I-Exp, in:O, Internet:O, Explorer:O, used:O, in:O, what:O, is:O, known:O, as:O, a:O, ,:O, strategic:O, web:O, compromise:O, ,:O, attack:B-OffAct, against:O, visitors:O, to:O, a:O, U.S.:B-Area, government:O, website:O, and:O, a:O, variety:O, of: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 Poison Ivy builder kit allows attackers to customize and build their own PIVY server , which is delivered as mobile code to a target that has been compromised , typically using social engineering .' [/INST] [The:O, Poison:B-Tool, Ivy:I-Tool, builder:O, kit:O, allows:O, attackers:B-HackOrg, to:O, customize:B-Features, and:I-Features, build:I-Features, their:I-Features, own:I-Features, PIVY:I-Features, server:I-Features, ,:O, which:O, is:O, delivered:O, as:O, mobile:O, code:O, to:O, a:O, target:O, that:O, has:O, been:O, compromised:O, ,:O, typically:O, using:O, social:B-Idus, engineering: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: 'Attackers can point and click their way through a compromised network and exfiltrate data .' [/INST] [Attackers:B-HackOrg, can:O, point:O, and:O, click:O, their:O, way:O, through:O, a:O, compromised:O, network:O, and:O, exfiltrate:B-Purp, data: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: 'Commodity RATs also complicate efforts by security professionals to correlate a threat actor 's activity over time—attackers can hide in the sea of malicious activity that also uses Poison Ivy-based malware .' [/INST] [Commodity:O, RATs:B-Tool, also:O, complicate:O, efforts:O, by:O, security:O, professionals:O, to:O, correlate:O, a:O, threat:B-HackOrg, actor:I-HackOrg, 's:O, activity:B-OffAct, over:O, time—attackers:O, can:O, hide:O, in:O, the:O, sea:O, of:O, malicious:B-OffAct, activity:I-OffAct, that:O, also:O, uses:O, Poison:B-Tool, Ivy-based:I-Tool, malware:I-Tool, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This report is an initial public release of research PwC UK and BAE Systems have conducted into new , sustained global campaigns by an established threat actor against managed IT service providers and their clients as well as several directly targeted organisations in Japan .' [/INST] [This:O, report:O, is:O, an:O, initial:O, public:O, release:O, of:O, research:O, PwC:B-SecTeam, UK:I-SecTeam, and:O, BAE:B-SecTeam, Systems:I-SecTeam, have:O, conducted:O, into:O, new:O, ,:O, sustained:O, global:O, campaigns:B-OffAct, by:O, an:O, established:O, threat:B-HackOrg, actor:I-HackOrg, against:O, managed:B-Org, IT:I-Org, service:I-Org, providers:I-Org, and:O, their:O, clients:O, as:O, well:O, as:O, several:O, directly:O, targeted:O, organisations:O, in:O, Japan: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: 'Since late 2016 , PwC UK and BAE Systems have been assisting victims of a new cyber espionage campaign conducted by APT10 .' [/INST] [Since:O, late:B-Time, 2016:I-Time, ,:O, PwC:B-SecTeam, UK:I-SecTeam, and:O, BAE:B-SecTeam, Systems:I-SecTeam, have:O, been:O, assisting:O, victims:O, of:O, a:O, new:O, cyber:B-OffAct, espionage:I-OffAct, campaign:I-OffAct, conducted:O, by:O, APT10: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: 'The campaign , which we refer to as Operation Cloud Hopper , has targeted managed IT service providers ( MSPs ) , allowing APT10 unprecedented potential access to the intellectual property and sensitive data of those MSPs and their clients globally .' [/INST] [The:O, campaign:B-OffAct, ,:O, which:O, we:O, refer:O, to:O, as:O, Operation:B-OffAct, Cloud:I-OffAct, Hopper:I-OffAct, ,:O, has:O, targeted:O, managed:B-Org, IT:I-Org, service:I-Org, providers:I-Org, (:O, MSPs:B-Org, ):O, ,:O, allowing:O, APT10:B-HackOrg, unprecedented:O, potential:O, access:O, to:O, the:O, intellectual:B-Purp, property:I-Purp, and:O, sensitive:O, data:O, of:O, those:O, MSPs:B-Org, and:O, their:O, clients:O, globally:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 ceased its use of the Poison Ivy malware family after a 2013 FireEye report , which comprehensively detailed the malware 's functionality and features , and its use by several China-based threat actors , including APT10 .' [/INST] [APT10:B-HackOrg, ceased:O, its:O, use:O, of:O, the:O, Poison:B-Tool, Ivy:I-Tool, malware:I-Tool, family:I-Tool, after:O, a:O, 2013:O, FireEye:B-SecTeam, report:O, ,:O, which:O, comprehensively:O, detailed:O, the:O, malware:O, 's:O, functionality:O, and:O, features:O, ,:O, and:O, its:O, use:O, by:O, several:O, China-based:B-Area, threat:B-HackOrg, actors:I-HackOrg, ,:O, including:O, APT10: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: 'APT10 primarily used PlugX malware from 2014 to 2016 , progressively improving and deploying newer versions , while simultaneously standardising their command and control function .' [/INST] [APT10:B-HackOrg, primarily:O, used:O, PlugX:B-Tool, malware:I-Tool, from:O, 2014:B-Time, to:O, 2016:B-Time, ,:O, progressively:O, improving:O, and:O, deploying:O, newer:O, versions:O, ,:O, while:O, simultaneously:O, standardising:O, their:O, command:O, and:O, control:O, function:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'PwC UK and BAE Systems assess it is highly likely that APT10 is a China-based threat actor with a focus on espionage and wide ranging information collection .' [/INST] [PwC:B-SecTeam, UK:I-SecTeam, and:O, BAE:B-SecTeam, Systems:I-SecTeam, assess:O, it:O, is:O, highly:O, likely:O, that:O, APT10:B-HackOrg, is:O, a:O, China-based:B-Area, threat:B-HackOrg, actor:I-HackOrg, with:O, a:O, focus:O, on:O, espionage:B-HackOrg, and:O, wide:O, ranging:O, information:B-Purp, collection: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: 'APT10 is known to have exfiltrated a high volume of data from multiple victims , exploiting compromised MSP networks , and those of their customers , to stealthily move this data around the world .' [/INST] [APT10:B-HackOrg, is:O, known:O, to:O, have:O, exfiltrated:B-Purp, a:I-Purp, high:I-Purp, volume:I-Purp, of:I-Purp, data:I-Purp, from:O, multiple:O, victims:O, ,:O, exploiting:O, compromised:O, MSP:B-Tool, networks:I-Tool, ,:O, and:O, those:O, of:O, their:O, customers:B-Org, ,:O, to:O, stealthily:O, move:O, this:O, data:O, around:O, the:O, world:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 , a name originally coined by FireEye , is also referred to as Red Apollo by PwC UK , CVNX by BAE Systems , Stone Panda by CrowdStrike , and menuPass Team more broadly in the public domain .' [/INST] [APT10:B-HackOrg, ,:O, a:O, name:O, originally:O, coined:O, by:O, FireEye:B-SecTeam, ,:O, is:O, also:O, referred:O, to:O, as:O, Red:B-HackOrg, Apollo:I-HackOrg, by:O, PwC:B-SecTeam, UK:I-SecTeam, ,:O, CVNX:B-HackOrg, by:O, BAE:B-SecTeam, Systems:I-SecTeam, ,:O, Stone:B-HackOrg, Panda:I-HackOrg, by:O, CrowdStrike:B-SecTeam, ,:O, and:O, menuPass:B-HackOrg, Team:I-HackOrg, more:O, broadly:O, in:O, the:O, public:O, domain:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The threat actor has previously been the subject of a range of open source reporting , including most notably a report by FireEye comprehensively detailing the threat actor 's use of the Poison Ivy malware family and blog posts by Trend Micro3 similarly detailing the use of EvilGrab malware .' [/INST] [The:O, threat:B-HackOrg, actor:I-HackOrg, has:O, previously:O, been:O, the:O, subject:O, of:O, a:O, range:O, of:O, open:O, source:O, reporting:O, ,:O, including:O, most:O, notably:O, a:O, report:O, by:O, FireEye:B-SecTeam, comprehensively:O, detailing:O, the:O, threat:B-HackOrg, actor:I-HackOrg, 's:O, use:O, of:O, the:O, Poison:B-Tool, Ivy:I-Tool, malware:I-Tool, family:I-Tool, and:O, blog:O, posts:O, by:O, Trend:B-SecTeam, Micro3:I-SecTeam, similarly:O, detailing:O, the:O, use:O, of:O, EvilGrab:B-Tool, malware:I-Tool, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The threat actor has previously been the subject of a range of open source reporting , including most notably a report by FireEye comprehensively detailing the threat actor 's use of the Poison Ivy malware family and blog posts by Trend Micro similarly detailing the use of EvilGrab malware .' [/INST] [The:O, threat:B-HackOrg, actor:I-HackOrg, has:O, previously:O, been:O, the:O, subject:O, of:O, a:O, range:O, of:O, open:O, source:O, reporting:O, ,:O, including:O, most:O, notably:O, a:O, report:O, by:O, FireEye:B-SecTeam, comprehensively:O, detailing:O, the:O, threat:B-HackOrg, actor:I-HackOrg, 's:O, use:O, of:O, the:O, Poison:B-Tool, Ivy:I-Tool, malware:I-Tool, family:I-Tool, and:O, blog:O, posts:O, by:O, Trend:B-SecTeam, Micro:I-SecTeam, similarly:O, detailing:O, the:O, use:O, of:O, EvilGrab:B-Tool, malware:I-Tool, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 has been in operation since at least 2009 , and has evolved its targeting from an early focus on the US defence industrial base ( DIB )1 and the technology and telecommunications sector , to a widespread compromise of multiple industries and sectors across the globe , most recently with a focus on MSPs .' [/INST] [APT10:B-HackOrg, has:O, been:O, in:O, operation:O, since:O, at:O, least:O, 2009:B-Time, ,:O, and:O, has:O, evolved:O, its:O, targeting:O, from:O, an:O, early:O, focus:O, on:O, the:O, US:B-Area, defence:O, industrial:O, base:O, (:O, DIB:O, )1:O, and:O, the:O, technology:B-Org, and:O, telecommunications:B-Org, sector:I-Org, ,:O, to:O, a:O, widespread:O, compromise:O, of:O, multiple:O, industries:O, and:O, sectors:O, across:O, the:O, globe:O, ,:O, most:O, recently:O, with:O, a:O, focus:O, on:O, MSPs:B-Org, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The research and ongoing tracking of APT10 by both PwC UK and BAE .' [/INST] [The:O, research:O, and:O, ongoing:O, tracking:O, of:O, APT10:B-HackOrg, by:O, both:O, PwC:B-SecTeam, UK:I-SecTeam, and:O, BAE:B-SecTeam, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 has been in operation since at least 2009 , and has evolved its targeting from an early focus on the US defence industrial base ( DIB ) and the technology and telecommunications sector , to a widespread compromise of multiple industries and sectors across the globe , most recently with a focus on MSPs .' [/INST] [APT10:B-HackOrg, has:O, been:O, in:O, operation:O, since:O, at:O, least:O, 2009:B-Time, ,:O, and:O, has:O, evolved:O, its:O, targeting:O, from:O, an:O, early:O, focus:O, on:O, the:O, US:B-Area, defence:O, industrial:O, base:O, (:O, DIB:O, ):O, and:O, the:O, technology:B-Org, and:O, telecommunications:B-Org, sector:I-Org, ,:O, to:O, a:O, widespread:O, compromise:O, of:O, multiple:O, industries:O, and:O, sectors:O, across:O, the:O, globe:O, ,:O, most:O, recently:O, with:O, a:O, focus:O, on:O, MSPs:B-Org, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'PwC UK has been engaged in supporting investigations linked to APT10 compromises .' [/INST] [PwC:B-SecTeam, UK:I-SecTeam, has:O, been:O, engaged:O, in:O, supporting:O, investigations:O, linked:O, to:O, APT10:B-HackOrg, compromises:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 a result of our analysis of APT10 's activities , we believe that it almost certainly benefits from significant staffing and logistical resources , which have increased over the last three years , with a significant step-change in 2016 .' [/INST] [As:O, a:O, result:O, of:O, our:O, analysis:O, of:O, APT10:B-HackOrg, 's:O, activities:B-OffAct, ,:O, we:O, believe:O, that:O, it:O, almost:O, certainly:O, benefits:O, from:O, significant:O, staffing:O, and:O, logistical:O, resources:O, ,:O, which:O, have:O, increased:O, over:O, the:O, last:O, three:O, years:O, ,:O, with:O, a:O, significant:O, step-change:O, in:O, 2016: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: 'Due to the scale of the threat actor 's operations throughout 2016 and 2017 , we similarly assess it currently comprises multiple teams , each responsible for a different section of the day-to-day operations , namely domain registration , infrastructure management , malware development , target operations , and analysis .' [/INST] [Due:O, to:O, the:O, scale:O, of:O, the:O, threat:B-HackOrg, actor:I-HackOrg, 's:O, operations:O, throughout:O, 2016:B-Time, and:O, 2017:B-Time, ,:O, we:O, similarly:O, assess:O, it:O, currently:O, comprises:O, multiple:O, teams:O, ,:O, each:O, responsible:O, for:O, a:O, different:O, section:O, of:O, the:O, day-to-day:O, operations:O, ,:O, namely:B-Way, domain:I-Way, registration:I-Way, ,:O, infrastructure:O, management:O, ,:O, malware:O, development:O, ,:O, target:O, operations:O, ,:O, and:O, analysis:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 withdrew from direct targeting using Poison Ivy in 2013 and conducted its first known retooling operation , upgrading its capabilities and replatforming to use PlugX .' [/INST] [APT10:B-HackOrg, withdrew:O, from:O, direct:O, targeting:O, using:O, Poison:B-Tool, Ivy:I-Tool, in:O, 2013:B-Time, and:O, conducted:O, its:O, first:O, known:O, retooling:O, operation:O, ,:O, upgrading:O, its:O, capabilities:O, and:O, replatforming:O, to:O, use:O, PlugX: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: 'It is highly likely that this is due to the release of the 2013 FireEye report .' [/INST] [It:O, is:O, highly:O, likely:O, that:O, this:O, is:O, due:O, to:O, the:O, release:O, of:O, the:O, 2013:O, FireEye:B-SecTeam, report:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 report will detail the most recent campaigns conducted by APT10 , including the sustained targeting of MSPs , which we have named Operation Cloud Hopper , and the targeting of a number of Japanese institutions .' [/INST] [Our:O, report:O, will:O, detail:O, the:O, most:O, recent:O, campaigns:B-OffAct, conducted:O, by:O, APT10:B-HackOrg, ,:O, including:O, the:O, sustained:O, targeting:O, of:O, MSPs:B-Org, ,:O, which:O, we:O, have:O, named:O, Operation:B-OffAct, Cloud:I-OffAct, Hopper:I-OffAct, ,:O, and:O, the:O, targeting:O, of:O, a:O, number:O, of:O, Japanese:B-Area, institutions:B-Org, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'MSPs therefore represent a high-payoff target for espionagefocused threat actors such as APT10 .' [/INST] [MSPs:B-Org, therefore:O, represent:O, a:O, high-payoff:O, target:O, for:O, espionagefocused:O, threat:B-HackOrg, actors:I-HackOrg, such:O, as:O, APT10: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: 'Given the level of client network access MSPs have , once APT10 has gained access to a MSP , it is likely to be relatively straightforward to exploit this and move laterally onto the networks of potentially thousands of other victims .' [/INST] [Given:O, the:O, level:O, of:O, client:O, network:O, access:O, MSPs:B-Org, have:O, ,:O, once:O, APT10:B-HackOrg, has:O, gained:O, access:O, to:O, a:O, MSP:B-Tool, ,:O, it:O, is:O, likely:O, to:O, be:O, relatively:O, straightforward:O, to:O, exploit:O, this:O, and:O, move:O, laterally:O, onto:O, the:O, networks:O, of:O, potentially:O, thousands:O, of:O, other:O, victims:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This , in turn , would provide access to a larger amount of intellectual property and sensitive data .' [/INST] [This:O, ,:O, in:O, turn:O, ,:O, would:O, provide:O, access:O, to:O, a:O, larger:O, amount:O, of:O, intellectual:B-Purp, property:I-Purp, and:O, sensitive:O, data:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 has been observed to exfiltrate stolen intellectual property via the MSPs , hence evading local network defences .' [/INST] [APT10:B-HackOrg, has:O, been:O, observed:O, to:O, exfiltrate:O, stolen:B-Purp, intellectual:I-Purp, property:I-Purp, via:O, the:O, MSPs:B-Org, ,:O, hence:O, evading:O, local:O, network:O, defences:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 command and control ( C2 ) infrastructure chosen by APT10 for Operation Cloud Hopper is predominantly referenced using dynamic-DNS domains .' [/INST] [The:O, command:O, and:O, control:O, (:O, C2:O, ):O, infrastructure:O, chosen:O, by:O, APT10:B-HackOrg, for:O, Operation:B-OffAct, Cloud:I-OffAct, Hopper:I-OffAct, is:O, predominantly:O, referenced:O, using:O, dynamic-DNS:B-Tool, domains: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: 'Several of these provide enterprise services or cloud hosting , supporting our assessment that APT10 are almost certainly targeting MSPs .' [/INST] [Several:O, of:O, these:O, provide:O, enterprise:O, services:O, or:O, cloud:O, hosting:O, ,:O, supporting:O, our:O, assessment:O, that:O, APT10:B-HackOrg, are:O, almost:O, certainly:O, targeting:O, MSPs:B-Org, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The 13th FYP was released in March 2016 and the sectors and organisations known to be targeted by APT10 are broadly in line with the strategic aims documented in this plan .' [/INST] [The:O, 13th:O, FYP:O, was:O, released:O, in:O, March:B-Time, 2016:I-Time, and:O, the:O, sectors:O, and:O, organisations:O, known:O, to:O, be:O, targeted:O, by:O, APT10:B-HackOrg, are:O, broadly:O, in:O, line:O, with:O, the:O, strategic:O, aims:O, documented:O, in:O, this:O, plan:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 aims outlined in the FYP will largely dictate the growth of businesses in China and are , therefore , likely to also form part of Chinese companies ' business strategies .' [/INST] [These:O, aims:O, outlined:O, in:O, the:O, FYP:O, will:O, largely:O, dictate:O, the:O, growth:O, of:O, businesses:B-Idus, in:O, China:B-Area, and:O, are:O, ,:O, therefore:O, ,:O, likely:O, to:O, also:O, form:O, part:O, of:O, Chinese:B-Area, companies:B-Org, ':O, business:O, strategies:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 has , in the past , primarily been known for its targeting of government and US defence industrial base organisations , with the earliest known date of its activity being in December 2009 .' [/INST] [APT10:B-HackOrg, has:O, ,:O, in:O, the:O, past:O, ,:O, primarily:O, been:O, known:O, for:O, its:O, targeting:O, of:O, government:B-Idus, and:O, US:B-Area, defence:O, industrial:O, base:O, organisations:O, ,:O, with:O, the:O, earliest:O, known:O, date:O, of:O, its:O, activity:B-OffAct, being:O, in:O, December:B-Time, 2009: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: 'Observed APT10 targeting is in line with many of the historic compromises we have outlined previously as originating from China .' [/INST] [Observed:O, APT10:B-HackOrg, targeting:O, is:O, in:O, line:O, with:O, many:O, of:O, the:O, historic:O, compromises:O, we:O, have:O, outlined:O, previously:O, as:O, originating:O, from:O, China: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: 'In line with commonly used APT actor methodologies , the threat actor aligns its decoy documents to a topic of interest relevant to the recipient .' [/INST] [In:O, line:O, with:O, commonly:O, used:O, APT:B-HackOrg, actor:I-HackOrg, methodologies:O, ,:O, the:O, threat:B-HackOrg, actor:I-HackOrg, aligns:O, its:O, decoy:B-Tool, documents:I-Tool, to:O, a:O, topic:O, of:O, interest:O, relevant:O, to:O, the:O, recipient:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 section details changes made to APT10 tools , techniques and procedures ( TTPs ) post-2014 , following its shift from Poison Ivy to PlugX .' [/INST] [This:O, section:O, details:O, changes:O, made:O, to:O, APT10:B-HackOrg, tools:O, ,:O, techniques:O, and:O, procedures:O, (:O, TTPs:O, ):O, post-2014:B-Time, ,:O, following:O, its:O, shift:O, from:O, Poison:B-Tool, Ivy:I-Tool, to:O, PlugX: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 have observed that in cases where APT10 has infiltrated a target via an MSP , it continues to use the MSPs credentials .' [/INST] [We:O, have:O, observed:O, that:O, in:O, cases:O, where:O, APT10:B-HackOrg, has:O, infiltrated:O, a:O, target:O, via:O, an:O, MSP:B-Tool, ,:O, it:O, continues:O, to:O, use:O, the:O, MSPs:B-Org, credentials:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 order to gain any further credentials , APT10 will usually deploy credential theft tools such as mimikatz or PwDump , sometimes using DLL load order hijacking , to use against a domain controller , explained further in Annex B .' [/INST] [In:O, order:O, to:O, gain:O, any:O, further:O, credentials:O, ,:O, APT10:B-HackOrg, will:O, usually:O, deploy:O, credential:B-Purp, theft:I-Purp, tools:O, such:O, as:O, mimikatz:B-Tool, or:O, PwDump:B-Tool, ,:O, sometimes:O, using:O, DLL:B-Tool, load:I-Tool, order:I-Tool, hijacking:I-Tool, ,:O, to:O, use:O, against:O, a:O, domain:O, controller:O, ,:O, explained:O, further:O, in:O, Annex:O, B:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 achieves persistence on its targets primarily by using scheduled tasks or Windows services in order to ensure the malware remains active regardless of system reboots .' [/INST] [APT10:B-HackOrg, achieves:O, persistence:O, on:O, its:O, targets:O, primarily:O, by:O, using:O, scheduled:B-Tool, tasks:I-Tool, or:O, Windows:B-Tool, services:I-Tool, in:O, order:O, to:O, ensure:O, the:O, malware:O, remains:O, active:O, regardless:O, of:O, system:O, reboots:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , in addition to compromising high value domain controllers and security servers , the threat actor has also been observed identifying and subsequently installing malware on low profile systems that provide non-critical support functions to the business , and are thus less likely to draw the attention of system administrators .' [/INST] [For:O, example:O, ,:O, in:O, addition:O, to:O, compromising:B-Purp, high:I-Purp, value:I-Purp, domain:I-Purp, controllers:I-Purp, and:O, security:B-Purp, servers:I-Purp, ,:O, the:O, threat:B-HackOrg, actor:I-HackOrg, has:O, also:O, been:O, observed:O, identifying:O, and:O, subsequently:O, installing:O, malware:O, on:O, low:O, profile:O, systems:O, that:O, provide:O, non-critical:O, support:O, functions:O, to:O, the:O, business:O, ,:O, and:O, are:O, thus:O, less:O, likely:O, to:O, draw:O, the:O, attention:O, of:O, system:O, administrators:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 majority of instances APT10 used either a reverse shell or RDP connection to install its malware ; the actor also uses these methods to propagate across the network .' [/INST] [In:O, the:O, majority:O, of:O, instances:O, APT10:B-HackOrg, used:O, either:O, a:O, reverse:B-Tool, shell:I-Tool, or:O, RDP:B-Tool, connection:O, to:O, install:O, its:O, malware:O, ;:O, the:O, actor:B-HackOrg, also:O, uses:O, these:O, methods:O, to:O, propagate:O, across:O, the:O, network:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 tactical malware , historically EvilGrab , and now ChChes ( and likely also RedLeaves ) , is designed to be lightweight and disposable , often being delivered through spear phishing .' [/INST] [The:O, tactical:O, malware:O, ,:O, historically:O, EvilGrab:B-Tool, ,:O, and:O, now:O, ChChes:B-Tool, (:O, and:O, likely:O, also:O, RedLeaves:B-Tool, ):O, ,:O, is:O, designed:O, to:O, be:O, lightweight:O, and:O, disposable:O, ,:O, often:O, being:O, delivered:O, through:O, spear:B-Way, phishing:I-Way, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once executed , tactical malware contains the capability to profile the network and manoeuvre through it to identify a key system of interest .' [/INST] [Once:O, executed:O, ,:O, tactical:O, malware:O, contains:O, the:O, capability:O, to:O, profile:O, the:O, network:B-Idus, and:O, manoeuvre:O, through:O, it:O, to:O, identify:O, a:O, key: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: 'We have also observed APT10 use DLL search order hijacking and sideloading , to execute some modified versions of open-source tools .' [/INST] [We:O, have:O, also:O, observed:O, APT10:B-HackOrg, use:O, DLL:B-Way, search:I-Way, order:I-Way, hijacking:I-Way, and:I-Way, sideloading:I-Way, ,:O, to:O, execute:O, some:O, modified:O, versions:O, of:O, open-source:O, tools:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'For example , PwC UK has observed APT10 compiling DLLs out of tools , such as Mimikatz and PwDump6 , and using legitimate , signed software , such as Windows Defender to load the malicious payloads .' [/INST] [For:O, example:O, ,:O, PwC:B-SecTeam, UK:I-SecTeam, has:O, observed:O, APT10:B-HackOrg, compiling:O, DLLs:O, out:O, of:O, tools:O, ,:O, such:O, as:O, Mimikatz:B-Tool, and:O, PwDump6:B-Tool, ,:O, and:O, using:O, legitimate:O, ,:O, signed:B-Tool, software:I-Tool, ,:O, such:O, as:O, Windows:O, Defender:O, to:O, load:O, the:O, malicious:O, payloads:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 our analysis of victim networks , we were able to observe APT10 once again initiate a retooling cycle in late 2016 .' [/INST] [During:O, our:O, analysis:O, of:O, victim:O, networks:O, ,:O, we:O, were:O, able:O, to:O, observe:O, APT10:B-HackOrg, once:O, again:O, initiate:O, a:O, retooling:O, cycle:O, in:O, late:B-Time, 2016: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: 'We observed the deployment and testing of multiple versions of Quasar malware , and the introduction of the bespoke malware families ChChes and RedLeaves .' [/INST] [We:O, observed:O, the:O, deployment:O, and:O, testing:O, of:O, multiple:O, versions:O, of:O, Quasar:B-Tool, malware:I-Tool, ,:O, and:O, the:O, introduction:O, of:O, the:O, bespoke:O, malware:O, families:O, ChChes:B-Tool, and:O, RedLeaves: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: 'APT10 is a constantly evolving , highly persistent China-based threat actor that has an ambitious and unprecedented collection programme against a broad spectrum of sectors , enabled by its strategic targeting .' [/INST] [APT10:B-HackOrg, is:O, a:O, constantly:O, evolving:O, ,:O, highly:O, persistent:O, China-based:B-Area, threat:B-HackOrg, actor:I-HackOrg, that:O, has:O, an:O, ambitious:O, and:O, unprecedented:O, collection:O, programme:O, against:O, a:O, broad:O, spectrum:O, of:O, sectors:O, ,:O, enabled:O, by:O, its:O, strategic:O, targeting:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 exposure of its operations in 2013 , APT10 has made a number of significant changes intended to thwart detection of its campaigns .' [/INST] [Since:O, exposure:O, of:O, its:O, operations:O, in:O, 2013:B-Time, ,:O, APT10:B-HackOrg, has:O, made:O, a:O, number:O, of:O, significant:O, changes:O, intended:O, to:O, thwart:O, detection:O, of:O, its:O, campaigns:B-OffAct, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'PwC UK and BAE Systems , working closely with industry and government , have uncovered a new , unparallelled campaign which we refer to as Operation Cloud Hopper .' [/INST] [PwC:B-SecTeam, UK:I-SecTeam, and:O, BAE:B-SecTeam, Systems:I-SecTeam, ,:O, working:O, closely:O, with:O, industry:B-Idus, and:O, government:B-Idus, ,:O, have:O, uncovered:O, a:O, new:O, ,:O, unparallelled:O, campaign:B-OffAct, which:O, we:O, refer:O, to:O, as:O, Operation:B-OffAct, Cloud:I-OffAct, Hopper: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: 'This operation has targeted managed IT service providers , the compromise of which provides APT10 with potential access to thousands of further victims .' [/INST] [This:O, operation:O, has:O, targeted:O, managed:B-Org, IT:I-Org, service:I-Org, providers:I-Org, ,:O, the:O, compromise:O, of:O, which:O, provides:O, APT10:B-HackOrg, with:O, potential:O, access:O, to:O, thousands:O, of:O, further:O, victims:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'An additional campaign has also been observed targeting Japanese entities .' [/INST] [An:O, additional:O, campaign:B-OffAct, has:O, also:O, been:O, observed:O, targeting:O, Japanese:B-Area, entities:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 's malware toolbox shows a clear evolution from malware commonly associated with China-based threat actors towards bespoke in-house malware that has been used in more recent campaigns ; this is indicative of APT10 's increasing sophistication , which is highly likely to continue .' [/INST] [APT10:B-HackOrg, 's:O, malware:O, toolbox:O, shows:O, a:O, clear:O, evolution:O, from:O, malware:O, commonly:O, associated:O, with:O, China-based:B-Area, threat:B-HackOrg, actors:I-HackOrg, towards:O, bespoke:O, in-house:O, malware:O, that:O, has:O, been:O, used:O, in:O, more:O, recent:O, campaigns:B-OffAct, ;:O, this:O, is:O, indicative:O, of:O, APT10:B-HackOrg, 's:O, increasing:O, sophistication:O, ,:O, which:O, is:O, highly:O, likely:O, to:O, continue:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The threat actor 's known working hours align to Chinese Standard Time ( CST ) and its targeting corresponds to that of other known China-based threat actors , which supports our assessment that these campaigns are conducted by APT10 .' [/INST] [The:O, threat:B-HackOrg, actor:I-HackOrg, 's:O, known:O, working:O, hours:O, align:O, to:O, Chinese:B-Area, Standard:O, Time:O, (:O, CST:O, ):O, and:O, its:O, targeting:O, corresponds:O, to:O, that:O, of:O, other:O, known:O, China-based:B-Area, threat:B-HackOrg, actors:I-HackOrg, ,:O, which:O, supports:O, our:O, assessment:O, that:O, these:O, campaigns:B-OffAct, are:O, conducted:O, by:O, APT10: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: 'APT10 ( MenuPass Group ) is a Chinese cyber espionage group that FireEye has tracked since 2009 .' [/INST] [APT10:B-HackOrg, (:O, MenuPass:B-HackOrg, Group:I-HackOrg, ):O, is:O, a:O, Chinese:B-Area, cyber:B-HackOrg, espionage:I-HackOrg, group:I-HackOrg, that:O, FireEye:B-SecTeam, has:O, tracked:O, since:O, 2009: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: 'Its targets include the military organizations and governments of countries with national interests in the South China Sea , including some within the U.S. defense industrial base .' [/INST] [Its:O, targets:O, include:O, the:O, military:B-Org, organizations:I-Org, and:O, governments:B-Idus, of:O, countries:O, with:O, national:O, interests:O, in:O, the:O, South:B-Area, China:I-Area, Sea:I-Area, ,:O, including:O, some:O, within:O, the:O, U.S.:B-Area, defense:B-Org, industrial:I-Org, base: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: 'Moafee may have chosen its targets based on the rich resources of South China Sea region – the world 's second business sea-lane , according to Wikipedia – including rare earth metals , crude oil , and natural gas .' [/INST] [Moafee:B-HackOrg, may:O, have:O, chosen:O, its:O, targets:O, based:O, on:O, the:O, rich:O, resources:O, of:O, South:B-Area, China:I-Area, Sea:I-Area, region:O, –:O, the:O, world:O, 's:O, second:O, business:O, sea-lane:O, ,:O, according:O, to:O, Wikipedia:O, –:O, including:O, rare:O, earth:O, metals:O, ,:O, crude:O, oil:B-Idus, ,:O, and:O, natural:O, gas: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: 'DragonOK appears to operate out of China 's Jiangsu Province .' [/INST] [DragonOK:B-HackOrg, appears:O, to:O, operate:O, out:O, of:O, China:B-Area, 's:O, Jiangsu:B-Area, Province: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: 'Moafee and DragonOK both use a well-known proxy tool – HUC Packet Transmit Tool ( HTRAN ) – to disguise their geographical locations .' [/INST] [Moafee:B-HackOrg, and:O, DragonOK:B-HackOrg, both:O, use:O, a:O, well-known:O, proxy:O, tool:O, –:O, HUC:B-Tool, Packet:I-Tool, Transmit:I-Tool, Tool:I-Tool, (:O, HTRAN:B-Tool, ):O, –:O, to:O, disguise:O, their:O, geographical:O, locations:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , FireEye researchers do not have enough insight to reliably report a definitive connection to the Moafee and DragonOK groups .' [/INST] [However:O, ,:O, FireEye:B-SecTeam, researchers:O, do:O, not:O, have:O, enough:O, insight:O, to:O, reliably:O, report:O, a:O, definitive:O, connection:O, to:O, the:O, Moafee:B-HackOrg, and:O, DragonOK: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: 'Both Moafee and DragonOK favor spear-phishing emails as an attack vector , often employing a decoy to deceive the victim .' [/INST] [Both:O, Moafee:B-HackOrg, and:O, DragonOK:B-HackOrg, favor:O, spear-phishing:B-Way, emails:I-Way, as:O, an:O, attack:B-OffAct, vector:O, ,:O, often:O, employing:O, a:O, decoy:O, to:O, deceive:O, the:O, victim:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Attachments are typically sent as an executable file embedded in a ZIP archive or a password-protected Microsoft Office document .' [/INST] [Attachments:B-SamFile, are:O, typically:O, sent:O, as:O, an:O, executable:O, file:O, embedded:O, in:O, a:O, ZIP:B-Way, archive:I-Way, or:O, a:O, password-protected:B-Way, Microsoft:I-Way, Office:I-Way, document:I-Way, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We observed Moafee running HTRAN proxies on their multiple Command and Control ( C2 ) servers – all operated on CHINANET , and hosted in Guangdong Province .' [/INST] [We:O, observed:O, Moafee:B-HackOrg, running:O, HTRAN:B-Tool, proxies:O, on:O, their:O, multiple:O, Command:O, and:O, Control:O, (:O, C2:O, ):O, servers:O, –:O, all:O, operated:O, on:O, CHINANET:O, ,:O, and:O, hosted:O, in:O, Guangdong:B-Area, Province: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: 'Like the Moafee group , we observed DragonOK running HTRAN to proxy their C2 servers , which are also operated on CHINANET but are hosted in the Jiangsu Province .' [/INST] [Like:O, the:O, Moafee:B-HackOrg, group:I-HackOrg, ,:O, we:O, observed:O, DragonOK:B-HackOrg, running:O, HTRAN:B-Tool, to:O, proxy:O, their:O, C2:O, servers:O, ,:O, which:O, are:O, also:O, operated:O, on:O, CHINANET:O, but:O, are:O, hosted:O, in:O, the:O, Jiangsu:B-Area, Province: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: 'Primarily focused on governments and military operations of countries with interests in the South China Sea , Moafee likely chooses its targets based on region 's rich natural resources .' [/INST] [Primarily:O, focused:O, on:O, governments:B-Idus, and:O, military:O, operations:O, of:O, countries:O, with:O, interests:O, in:O, the:O, South:B-Area, China:I-Area, Sea:I-Area, ,:O, Moafee:B-HackOrg, likely:O, chooses:O, its:O, targets:O, based:O, on:O, region:O, 's:O, rich:O, natural:B-Purp, resources: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: 'By targeting high-tech and manufacturing operations in Japan and Taiwan , DragonOK may be acquiring trade secrets for a competitive economic advantage .' [/INST] [By:O, targeting:O, high-tech:B-Idus, and:O, manufacturing:B-Idus, operations:O, in:O, Japan:B-Area, and:O, Taiwan:B-Area, ,:O, DragonOK:B-HackOrg, may:O, be:O, acquiring:B-Purp, trade:I-Purp, secrets:I-Purp, for:O, a:O, competitive:O, economic:B-Idus, advantage:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Security researchers subsequently linked these attacks to a broader , yearlong campaign that targeted not just Israelis but Palestinians as well .' [/INST] [Security:O, researchers:O, subsequently:O, linked:O, these:O, attacks:B-OffAct, to:O, a:O, broader:O, ,:O, yearlong:O, campaign:B-OffAct, that:O, targeted:O, not:O, just:O, Israelis:B-Area, but:O, Palestinians:O, as:O, well:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 as discovered later , even the U.S. and UK governments .' [/INST] [and:O, as:O, discovered:O, later:O, ,:O, even:O, the:O, U.S.:B-Area, and:O, UK:B-Area, governments:B-Idus, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The second group , known as DragonOK , targets high-tech and manufacturing companies in Japan and Taiwan .' [/INST] [The:O, second:O, group:B-HackOrg, ,:O, known:O, as:O, DragonOK:B-HackOrg, ,:O, targets:O, high-tech:B-Org, and:O, manufacturing:B-Org, companies:I-Org, in:O, Japan:B-Area, and:O, Taiwan: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: 'In 2012 , the Molerats attacks appeared to rely heavily on the XtremeRAT , a freely available tool that is popular with attackers based in the Middle East .' [/INST] [In:O, 2012:B-Time, ,:O, the:O, Molerats:B-OffAct, attacks:I-OffAct, appeared:O, to:O, rely:O, heavily:O, on:O, the:O, XtremeRAT:B-Tool, ,:O, a:O, freely:O, available:O, tool:O, that:O, is:O, popular:O, with:O, attackers:B-HackOrg, based:O, in:O, the:O, Middle:B-Area, East:I-Area, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'But the group has also used Poison Ivy ( PIVY ) , a RAT more commonly associated with threat actors in China — so much so that PIVY has , inaccurately , become synonymous with all APT attacks linked to China .' [/INST] [But:O, the:O, group:B-HackOrg, has:O, also:O, used:O, Poison:B-Tool, Ivy:I-Tool, (:O, PIVY:B-Tool, ):O, ,:O, a:O, RAT:B-Tool, more:O, commonly:O, associated:O, with:O, threat:B-HackOrg, actors:I-HackOrg, in:O, China:B-Area, —:O, so:O, much:O, so:O, that:O, PIVY:B-Tool, has:O, ,:O, inaccurately:O, ,:O, become:O, synonymous:O, with:O, all:O, APT:B-OffAct, attacks:I-OffAct, linked:O, to:O, China: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: 'This blog post analyzes several recent Molerats attacks that deployed PIVY against targets in the Middle East and in the U.S. We also examine additional PIVY attacks that leverage Arabic-language content related to the ongoing crisis in Egypt and the wider Middle East to lure targets into opening malicious files .' [/INST] [This:O, blog:O, post:O, analyzes:O, several:O, recent:O, Molerats:B-OffAct, attacks:I-OffAct, that:O, deployed:O, PIVY:B-Tool, against:O, targets:O, in:O, the:O, Middle:B-Area, East:I-Area, and:O, in:O, the:O, U.S.:B-Area, We:O, also:O, examine:O, additional:O, PIVY:B-OffAct, attacks:I-OffAct, that:O, leverage:O, Arabic-language:O, content:O, related:O, to:O, the:O, ongoing:O, crisis:O, in:O, Egypt:B-Area, and:O, the:O, wider:O, Middle:B-Area, East:I-Area, to:O, lure:O, targets:O, into:O, opening:O, malicious:B-SamFile, files:I-SamFile, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We do not know whether using PIVY is an attempt by those behind the Molerats campaign to frame China-based threat actors for their attacks or simply evidence that they have added another effective , publicly-available RAT to its arsenal .' [/INST] [We:O, do:O, not:O, know:O, whether:O, using:O, PIVY:B-Tool, is:O, an:O, attempt:O, by:O, those:O, behind:O, the:O, Molerats:B-OffAct, campaign:I-OffAct, to:O, frame:O, China-based:B-Area, threat:B-HackOrg, actors:I-HackOrg, for:O, their:O, attacks:B-OffAct, or:O, simply:O, evidence:O, that:O, they:O, have:O, added:O, another:O, effective:O, ,:O, publicly-available:O, RAT:B-Tool, to:O, its:O, arsenal:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 observed several attacks in June and July 2013 against targets in the Middle East and the U.S. that dropped a PIVY payload that connected to command-and-control ( CnC ) infrastructure used by the Molerats attackers .' [/INST] [We:O, observed:O, several:O, attacks:B-OffAct, in:O, June:B-Time, and:O, July:B-Time, 2013:I-Time, against:O, targets:O, in:O, the:O, Middle:B-Area, East:I-Area, and:O, the:O, U.S.:B-Area, that:O, dropped:O, a:O, PIVY:B-Tool, payload:O, that:O, connected:O, to:O, command-and-control:B-Tool, (:O, CnC:B-Tool, ):O, infrastructure:O, used:O, by:O, the:O, Molerats:B-HackOrg, attackers: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: 'The archive contains an .exe file , sometimes disguised as a Microsoft Word file , a video , or another file format , using the corresponding icon .' [/INST] [The:O, archive:O, contains:O, an:O, .exe:B-SamFile, file:I-SamFile, ,:O, sometimes:O, disguised:O, as:O, a:O, Microsoft:B-SamFile, Word:I-SamFile, file:I-SamFile, ,:O, a:O, video:O, ,:O, or:O, another:O, file:O, format:O, ,:O, using:O, the:O, corresponding:O, icon:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 DustySky , the attackers use publicly available tools such as the following Remote Administration Tools ( RAT ) : Poison Ivy , Nano Core , XtremeRAT , DarkComet and Spy-Net .' [/INST] [In:O, addition:O, to:O, DustySky:B-Tool, ,:O, the:O, attackers:B-HackOrg, use:O, publicly:B-Tool, available:I-Tool, tools:I-Tool, such:O, as:O, the:O, following:O, Remote:B-Tool, Administration:I-Tool, Tools:I-Tool, (:O, RAT:B-Tool, ):O, ::O, Poison:B-Tool, Ivy:I-Tool, ,:O, Nano:B-Tool, Core:I-Tool, ,:O, XtremeRAT:B-Tool, ,:O, DarkComet:B-Tool, and:O, Spy-Net: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: 'DustySky ( called , NeD Worm , by its developer ) is a multi-stage malware in use since May 2015 .' [/INST] [DustySky:B-Tool, (:O, called:O, ,:O, NeD:O, Worm:O, ,:O, by:O, its:O, developer:O, ):O, is:O, a:O, multi-stage:O, malware:O, in:O, use:O, since:O, May: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: 'It is in use by the Molerats ( aka Gaza cybergang ) , a politically motivated group whose main objective , we believe , is intelligence gathering .' [/INST] [It:O, is:O, in:O, use:O, by:O, the:O, Molerats:B-HackOrg, (:O, aka:O, Gaza:B-HackOrg, cybergang:I-HackOrg, ):O, ,:O, a:O, politically:B-Idus, motivated:O, group:B-HackOrg, whose:O, main:O, objective:O, ,:O, we:O, believe:O, ,:O, is:O, intelligence:B-Purp, gathering: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: 'Operating since 2012 , the Molerats group 's activity has been reported by Norman , Kaspersky , FireEye , and PwC .' [/INST] [Operating:O, since:O, 2012:B-Time, ,:O, the:O, Molerats:B-HackOrg, group:I-HackOrg, 's:O, activity:B-OffAct, has:O, been:O, reported:O, by:O, Norman:B-SecTeam, ,:O, Kaspersky:B-SecTeam, ,:O, FireEye:B-SecTeam, ,:O, and:O, PwC:B-SecTeam, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'DustySky has been developed and used since May 2015 by Molerats ( aka , Gaza cybergang , ) , a terrorist group whose main objective in this campaign is intelligence gathering .' [/INST] [DustySky:B-Tool, has:O, been:O, developed:O, and:O, used:O, since:O, May:B-Time, 2015:I-Time, by:O, Molerats:B-HackOrg, (:O, aka:O, ,:O, Gaza:B-HackOrg, cybergang:I-HackOrg, ,:O, ):O, ,:O, a:O, terrorist:B-HackOrg, group:I-HackOrg, whose:O, main:O, objective:O, in:O, this:O, campaign:B-OffAct, is:O, intelligence:B-Purp, gathering: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: 'Most targets are from the Middle East : Israel , Egypt , Saudi Arabia , United Arab Emirates and Iraq .' [/INST] [Most:O, targets:O, are:O, from:O, the:O, Middle:B-Area, East:I-Area, ::O, Israel:B-Area, ,:O, Egypt:B-Area, ,:O, Saudi:B-Area, Arabia:I-Area, ,:O, United:B-Area, Arab:I-Area, Emirates:I-Area, and:O, Iraq: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 United States and countries in Europe are targeted as well .' [/INST] [The:O, United:B-Area, States:I-Area, and:O, countries:O, in:O, Europe:B-Area, are:O, targeted:O, as:O, well:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 sample analyzed is f589827c4cf94662544066b80bfda6ab from late August 2015 .' [/INST] [The:O, sample:O, analyzed:O, is:O, f589827c4cf94662544066b80bfda6ab:O, from:O, late:B-Time, August: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 MuddyWater attacks are primarily against Middle Eastern nations .' [/INST] [The:O, MuddyWater:B-OffAct, attacks:I-OffAct, are:O, primarily:O, against:O, Middle:B-Area, Eastern:I-Area, nations:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , we have also observed attacks against surrounding nations and beyond , including targets in India and the USA .' [/INST] [However:O, ,:O, we:O, have:O, also:O, observed:O, attacks:B-OffAct, against:O, surrounding:O, nations:O, and:O, beyond:O, ,:O, including:O, targets:O, in:O, India:B-Area, and:O, the:O, USA: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: 'Targeted sectors of Molerats include governmental and diplomatic institutions , including embassies ; companies from the aerospace and defence Industries ; financial institutions ; journalists ; software developers .' [/INST] [Targeted:O, sectors:O, of:O, Molerats:B-HackOrg, include:O, governmental:B-Org, and:O, diplomatic:I-Org, institutions:I-Org, ,:O, including:O, embassies:B-Org, ;:O, companies:O, from:O, the:O, aerospace:B-Idus, and:O, defence:B-Idus, Industries:I-Idus, ;:O, financial:B-Org, institutions:I-Org, ;:O, journalists:B-Org, ;:O, software:B-Org, developers: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: 'The Palo Alto Networks Unit 42 research team recently came across a series of malicious files which were almost identical to those targeting the Saudi Arabian government previously discussed by MalwareBytes .' [/INST] [The:O, Palo:B-SecTeam, Alto:I-SecTeam, Networks:I-SecTeam, Unit:I-SecTeam, 42:I-SecTeam, research:O, team:O, recently:O, came:O, across:O, a:O, series:O, of:O, malicious:B-SamFile, files:I-SamFile, which:O, were:O, almost:O, identical:O, to:O, those:O, targeting:O, the:O, Saudi:B-Area, Arabian:I-Area, government:B-Idus, previously:O, discussed:O, by:O, MalwareBytes:B-SecTeam, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'MuddyWater attacks are characterized by the use of a slowly evolving PowerShell-based first stage backdoor we call , POWERSTATS , .' [/INST] [MuddyWater:B-OffAct, attacks:I-OffAct, are:O, characterized:O, by:O, the:O, use:O, of:O, a:O, slowly:O, evolving:O, PowerShell-based:B-Tool, first:I-Tool, stage:I-Tool, backdoor:I-Tool, we:O, call:O, ,:O, POWERSTATS:B-Tool, ,:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'When we looked at the cluster of activity which consisted of what appeared to be espionage-focused attacks in the Middle East , we were somewhat confused as the previous public reporting had attributed these attacks to FIN7 .' [/INST] [When:O, we:O, looked:O, at:O, the:O, cluster:O, of:O, activity:B-OffAct, which:O, consisted:O, of:O, what:O, appeared:O, to:O, be:O, espionage-focused:B-OffAct, attacks:I-OffAct, in:O, the:O, Middle:B-Area, East:I-Area, ,:O, we:O, were:O, somewhat:O, confused:O, as:O, the:O, previous:O, public:O, reporting:O, had:O, attributed:O, these:O, attacks:B-OffAct, to:O, FIN7: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: 'FIN7 is a threat actor group that is financially motivated with targets in the restaurant , services and financial sectors .' [/INST] [FIN7:B-HackOrg, is:O, a:O, threat:B-HackOrg, actor:I-HackOrg, group:I-HackOrg, that:O, is:O, financially:B-Purp, motivated:I-Purp, with:O, targets:O, in:O, the:O, restaurant:B-Idus, ,:O, services:B-Idus, and:O, financial: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: 'Following the trail of existing public reporting , the tie to FIN7 is essentially made based on a download observed from a MuddyWater C2 , of a non-public tool , DNSMessenger , .' [/INST] [Following:O, the:O, trail:O, of:O, existing:O, public:O, reporting:O, ,:O, the:O, tie:O, to:O, FIN7:B-HackOrg, is:O, essentially:O, made:O, based:O, on:O, a:O, download:O, observed:O, from:O, a:O, MuddyWater:B-Tool, C2:I-Tool, ,:O, of:O, a:O, non-public:B-Tool, tool:I-Tool, ,:O, DNSMessenger:B-Tool, ,:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'There was a mistake in the original Morphisec analysis which linked these attacks to FIN7 .' [/INST] [There:O, was:O, a:O, mistake:O, in:O, the:O, original:O, Morphisec:B-SecTeam, analysis:O, which:O, linked:O, these:O, attacks:B-OffAct, to:O, FIN7: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: 'The DNSMessenger malware is a shared tool , used by FIN7 , MuddyWater and perhaps other groups .' [/INST] [The:O, DNSMessenger:B-Tool, malware:I-Tool, is:O, a:O, shared:O, tool:O, ,:O, used:O, by:O, FIN7:B-HackOrg, ,:O, MuddyWater:B-HackOrg, and:O, perhaps:O, other:O, groups: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 September 2018 , we found evidence of Seedworm and the espionage group APT28 ( aka Swallowtail , Fancy Bear ) , on a computer within the Brazil-based embassy of an oil-producing nation .' [/INST] [In:O, September:B-Time, 2018:I-Time, ,:O, we:O, found:O, evidence:O, of:O, Seedworm:B-HackOrg, and:O, the:O, espionage:B-HackOrg, group:I-HackOrg, APT28:B-HackOrg, (:O, aka:O, Swallowtail:B-HackOrg, ,:O, Fancy:B-HackOrg, Bear:I-HackOrg, ):O, ,:O, on:O, a:O, computer:O, within:O, the:O, Brazil-based:B-Area, embassy:B-Org, of:O, an:O, oil-producing:O, nation:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 found new variants of the Powermud backdoor , a new backdoor ( Backdoor.Powemuddy ) , and custom tools for stealing passwords , creating reverse shells , privilege escalation , and the use of the native Windows cabinet creation tool , makecab.exe , probably for compressing stolen data to be uploaded .' [/INST] [We:O, found:O, new:O, variants:O, of:O, the:O, Powermud:B-Tool, backdoor:I-Tool, ,:O, a:O, new:O, backdoor:O, (:O, Backdoor.Powemuddy:B-SamFile, ):O, ,:O, and:O, custom:B-Tool, tools:I-Tool, for:O, stealing:B-Features, passwords:I-Features, ,:O, creating:B-Features, reverse:I-Features, shells:I-Features, ,:O, privilege:B-Features, escalation:I-Features, ,:O, and:O, the:O, use:B-Features, of:I-Features, the:I-Features, native:I-Features, Windows:I-Features, cabinet:I-Features, creation:I-Features, tool:I-Features, ,:O, makecab.exe:B-SamFile, ,:O, probably:O, for:O, compressing:O, stolen:O, data:O, to:O, be:O, uploaded:O, .:O] </s>