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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Taidoor attackers have been actively engaging in targeted attacks since at least March 4 , 2009 .' [/INST] [The:O, Taidoor:O, attackers:O, have:O, been:O, actively:O, engaging:O, in:O, targeted:B-OffAct, attacks:I-OffAct, since:O, at:O, least:O, March:B-Time, 4:I-Time, ,: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: 'Taidoor spoofed Taiwanese government email addresses to send out socially engineered emails in the Chinese language that typically leveraged Taiwan-themed issues .' [/INST] [Taidoor:O, spoofed:O, Taiwanese:B-Area, government:B-Idus, email:O, addresses:O, to:O, send:O, out:O, socially:B-Way, engineered:I-Way, emails:I-Way, in:O, the:O, Chinese:B-Area, language:O, that:O, typically:O, leveraged:O, Taiwan-themed:O, issues:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Despite some exceptions , the Taidoor campaign often used Taiwanese IP addresses as C&C servers and email addresses to send out socially engineered emails with malware as attachments .' [/INST] [Despite:O, some:O, exceptions:O, ,:O, the:O, Taidoor:B-OffAct, campaign:I-OffAct, often:O, used:O, Taiwanese:B-Area, IP:B-Tool, addresses:O, as:O, C&C:O, servers:O, and:O, email:O, addresses:O, to:O, send:O, out:O, socially:B-Way, engineered:I-Way, emails:I-Way, with:O, malware:O, as:O, attachments:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'One of the primary targets of the Taidoor campaign appeared to be the Taiwanese government .' [/INST] [One:O, of:O, the:O, primary:O, targets:O, of:O, the:O, Taidoor:B-OffAct, campaign:I-OffAct, appeared:O, to:O, be:O, the:O, Taiwanese:B-Area, government: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: 'Suckfly targeted one of India 's largest e-commerce companies , a major Indian shipping company , one of India 's largest financial organizations , and an IT firm that provides support for India 's largest stock exchange .' [/INST] [Suckfly:O, targeted:O, one:O, of:O, India:O, 's:O, largest:O, e-commerce:B-Org, companies:I-Org, ,:O, a:O, major:O, Indian:O, shipping:B-Org, company:I-Org, ,:O, one:O, of:O, India:O, 's:O, largest:O, financial:B-Org, organizations:I-Org, ,:O, and:O, an:O, IT:B-Org, firm:I-Org, that:O, provides:O, support:O, for:O, India:O, 's:O, largest:O, stock:O, exchange:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Data from the early part of this year shows that the Taidoor attackers rampantly used malicious.DOC files to exploit a Microsoft Common Controls vulnerability , CVE-2012-0158 .' [/INST] [Data:O, from:O, the:O, early:O, part:O, of:O, this:O, year:O, shows:O, that:O, the:O, Taidoor:O, attackers:O, rampantly:O, used:O, malicious.DOC:B-SamFile, files:O, to:O, exploit:O, a:O, Microsoft:B-Exp, Common:I-Exp, Controls:I-Exp, vulnerability:I-Exp, ,:O, CVE-2012-0158:B-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Taidoor actively sent out malicious documents and maintained several IP addresses for command and control .' [/INST] [Taidoor:O, actively:O, sent:O, out:O, malicious:B-Way, documents:I-Way, and:O, maintained:O, several:O, IP:B-Way, addresses:I-Way, for:O, command:O, and:O, control:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 attackers actively sent out malicious documents and maintained several IP addresses for command and control .' [/INST] [The:O, attackers:O, actively:O, sent:O, out:O, malicious:O, documents:O, and:O, maintained:O, several:O, IP:B-Way, addresses:I-Way, for:O, command:O, and:O, control:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 part of their social engineering ploy , the Taidoor attackers attach a decoy document to their emails that , when opened , displays the contents of a legitimate document but executes a malicious payload in the background .' [/INST] [As:O, part:O, of:O, their:O, social:B-Idus, engineering:I-Idus, ploy:O, ,:O, the:O, Taidoor:O, attackers:O, attach:O, a:O, decoy:O, document:O, to:O, their:O, emails:B-Way, that:O, ,:O, when:O, opened:O, ,:O, displays:O, the:O, contents:O, of:O, a:O, legitimate:O, document:O, but:O, executes:O, a:O, malicious:O, payload:O, in:O, the:O, background:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Sometimes , however , certain samples made use of domain names for HTTP communication .' [/INST] [Sometimes:O, ,:O, however:O, ,:O, certain:O, samples:O, made:O, use:O, of:O, domain:B-Way, names:I-Way, for:O, HTTP:O, communication:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 command capabilities of the Taidoor malware , we were able to determine that data theft and data destruction was possible .' [/INST] [Based:O, on:O, the:O, command:O, capabilities:O, of:O, the:O, Taidoor:B-Tool, malware:I-Tool, ,:O, we:O, were:O, able:O, to:O, determine:O, that:O, data:B-Features, theft:I-Features, and:O, data:B-Features, destruction:I-Features, was:O, possible:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 ultimate objective of targeted attacks is to acquire sensitive data .' [/INST] [The:O, ultimate:O, objective:O, of:O, targeted:B-OffAct, attacks:I-OffAct, is:O, to:O, acquire:B-Purp, sensitive:I-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: 'In December 2017 , FireEye publicly released our first analysis on the TRITON attack where malicious actors used the TRITON custom attack framework to manipulate industrial safety systems at a critical infrastructure facility and inadvertently caused a process shutdown .' [/INST] [In:O, December:B-Time, 2017:I-Time, ,:O, FireEye:B-SecTeam, publicly:O, released:O, our:O, first:O, analysis:O, on:O, the:O, TRITON:B-OffAct, attack:I-OffAct, where:O, malicious:O, actors:O, used:O, the:O, TRITON:B-Tool, custom:O, attack:B-OffAct, framework:I-OffAct, to:O, manipulate:O, industrial:O, safety:O, systems:O, at:O, a:O, critical:O, infrastructure:O, facility:O, and:O, inadvertently:O, caused:O, a:O, process:O, shutdown:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 most recent analysis , we attributed the intrusion activity that led to the deployment of TRITON to a Russian government-owned technical research institute in Moscow .' [/INST] [In:O, our:O, most:O, recent:O, analysis:O, ,:O, we:O, attributed:O, the:O, intrusion:B-OffAct, activity:I-OffAct, that:O, led:O, to:O, the:O, deployment:O, of:O, TRITON:B-Tool, to:O, a:O, Russian:B-Area, government-owned:O, technical:O, research:O, institute:O, in:O, Moscow: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: 'For more in-depth analysis of TRITON and other cyber threats , consider subscribing to FireEye Cyber Threat Intelligence .' [/INST] [For:O, more:O, in-depth:O, analysis:O, of:O, TRITON:B-Tool, and:O, other:O, cyber:O, threats:O, ,:O, consider:O, subscribing:O, to:O, FireEye:B-SecTeam, Cyber:I-SecTeam, Threat:I-SecTeam, Intelligence:I-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: 'During this time , the attacker must ensure continued access to the target environment or risk losing years of effort and potentially expensive custom ICS malware .' [/INST] [During:O, this:O, time:O, ,:O, the:O, attacker:O, must:O, ensure:O, continued:O, access:O, to:O, the:O, target:O, environment:O, or:O, risk:O, losing:O, years:O, of:O, effort:O, and:O, potentially:O, expensive:O, custom:O, ICS: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: 'In this report we continue our research of the actor 's operations with a specific focus on a selection of custom information technology ( IT ) tools and tactics the threat actor leveraged during the early stages of the targeted attack lifecycle .' [/INST] [In:O, this:O, report:O, we:O, continue:O, our:O, research:O, of:O, the:O, actor:O, 's:O, operations:O, with:O, a:O, specific:O, focus:O, on:O, a:O, selection:O, of:O, custom:O, information:B-Idus, technology:I-Idus, (:O, IT:B-Idus, ):O, tools:O, and:O, tactics:O, the:O, threat:O, actor:O, leveraged:O, during:O, the:O, early:O, stages:O, of:O, the:O, targeted:B-OffAct, attack:I-OffAct, lifecycle:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Additionally , the actor possibly gained a foothold on other target networks—beyond the two intrusions discussed in this post – using similar strategies .' [/INST] [Additionally:O, ,:O, the:O, actor:O, possibly:O, gained:O, a:O, foothold:O, on:O, other:O, target:O, networks—beyond:O, the:O, two:O, intrusions:O, discussed:O, in:O, this:O, post:O, –:O, using:O, similar: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: 'There is often a singular focus from the security community on ICS malware largely due to its novel nature and the fact that there are very few examples found in the wild .' [/INST] [There:O, is:O, often:O, a:O, singular:O, focus:O, from:O, the:O, security:B-SecTeam, community:I-SecTeam, on:O, ICS:B-Tool, malware:I-Tool, largely:O, due:O, to:O, its:O, novel:O, nature:O, and:O, the:O, fact:O, that:O, there:O, are:O, very:O, few:O, examples:O, found:O, in:O, the:O, wild:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'ЦНИИХМ ) , a Russian government-owned technical research institution located in Moscow .' [/INST] [ЦНИИХМ:O, ):O, ,:O, a:O, Russian:B-Area, government-owned:O, technical:O, research:B-Org, institution:I-Org, located:O, in:O, Moscow: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 this blog post we provide additional information linking TEMP.Veles and their activity surrounding the TRITON intrusion to a Russian government-owned research institute .' [/INST] [In:O, this:O, blog:O, post:O, we:O, provide:O, additional:O, information:O, linking:O, TEMP.Veles:B-HackOrg, and:O, their:O, activity:B-OffAct, surrounding:O, the:O, TRITON:B-Tool, intrusion:O, to:O, a:O, Russian:O, government-owned:O, research:O, institute:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Analysis of these cryptcat binaries indicates that the actor continually modified them to decrease AV detection rates .' [/INST] [Analysis:O, of:O, these:O, cryptcat:O, binaries:O, indicates:O, that:O, the:O, actor:O, continually:O, modified:O, them:O, to:O, decrease:O, AV:O, detection:O, rates:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'TEMP.Veles' lateral movement activities used a publicly-available PowerShell-based tool , WMImplant .' [/INST] [TEMP.Veles':B-HackOrg, lateral:O, movement:B-OffAct, activities:I-OffAct, used:O, a:O, publicly-available:O, PowerShell-based:B-Tool, tool:I-Tool, ,:O, WMImplant: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: 'On multiple dates in 2017 , TEMP.Veles struggled to execute this utility on multiple victim systems , potentially due to AV detection .' [/INST] [On:O, multiple:O, dates:O, in:O, 2017:B-Time, ,:O, TEMP.Veles:B-HackOrg, struggled:O, to:O, execute:O, this:O, utility:O, on:O, multiple:O, victim:O, systems:O, ,:O, potentially:O, due:O, to:O, AV:O, detection:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Custom payloads utilized by TEMP.Veles in investigations conducted by Mandiant are typically weaponized versions of legitimate open-source software , retrofitted with code used for command and control .' [/INST] [Custom:O, payloads:O, utilized:O, by:O, TEMP.Veles:B-HackOrg, in:O, investigations:O, conducted:O, by:O, Mandiant:B-SecTeam, are:O, typically:O, weaponized:O, versions:O, of:O, legitimate:O, open-source:O, software:O, ,:O, retrofitted:B-Way, with:I-Way, code:I-Way, used:O, for:O, command:O, and:O, control:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 file creation times for numerous files that TEMP.Veles created during lateral movement on a target 's network .' [/INST] [We:O, identified:O, file:O, creation:O, times:O, for:O, numerous:O, files:O, that:O, TEMP.Veles:B-HackOrg, created:O, during:O, lateral:O, movement:O, on:O, a:O, target:O, 's: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: 'Adversary behavioral artifacts further suggest the TEMP.Veles operators are based in Moscow , lending some further support to the scenario that CNIIHM , a Russian research organization in Moscow , has been involved in TEMP.Veles activity .' [/INST] [Adversary:O, behavioral:O, artifacts:O, further:O, suggest:O, the:O, TEMP.Veles:B-HackOrg, operators:O, are:O, based:O, in:O, Moscow:B-Area, ,:O, lending:O, some:O, further:O, support:O, to:O, the:O, scenario:O, that:O, CNIIHM:B-HackOrg, ,:O, a:O, Russian:B-Area, research:B-Org, organization:I-Org, in:O, Moscow:B-Area, ,:O, has:O, been:O, involved:O, in:O, TEMP.Veles:B-HackOrg, activity: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: 'XENOTIME is easily the most dangerous threat activity publicly known .' [/INST] [XENOTIME:B-HackOrg, is:O, easily:O, the:O, most:O, dangerous:O, threat:B-OffAct, activity:I-OffAct, publicly:O, known:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CNIIHM 's characteristics are consistent with what we might expect of an organization responsible for TEMP.Veles activity .' [/INST] [CNIIHM:B-HackOrg, 's:O, characteristics:O, are:O, consistent:O, with:O, what:O, we:O, might:O, expect:O, of:O, an:O, organization:O, responsible:O, for:O, TEMP.Veles:B-HackOrg, activity: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: 'Dragos identified several compromises of ICS vendors and manufacturers in 2018 by activity associated with XENOTIME , providing potential supply chain threat opportunities and vendor-enabled access to asset owner and operator ICS networks .' [/INST] [Dragos:B-SecTeam, identified:O, several:O, compromises:O, of:O, ICS:B-Tool, vendors:I-Tool, and:I-Tool, manufacturers:I-Tool, in:O, 2018:B-Time, by:O, activity:B-OffAct, associated:O, with:O, XENOTIME:B-HackOrg, ,:O, providing:O, potential:O, supply:O, chain:O, threat:O, opportunities:O, and:O, vendor-enabled:O, access:O, to:O, asset:O, owner:O, and:O, operator:O, ICS:B-Tool, networks: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: 'XENOTIME rose to prominence in December 2017 when Dragos and FireEye jointly published details of TRISIS destructive malware targeting Schneider Electric 's Triconex safety instrumented system .' [/INST] [XENOTIME:B-HackOrg, rose:O, to:O, prominence:O, in:O, December:B-Time, 2017:I-Time, when:O, Dragos:B-SecTeam, and:O, FireEye:B-SecTeam, jointly:O, published:O, details:O, of:O, TRISIS:B-Tool, destructive:O, malware:O, targeting:O, Schneider:O, Electric:O, 's:O, Triconex:O, safety:O, instrumented: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: 'Targeting a safety system indicates significant damage and loss of human life were either intentional or acceptable goals of the attack , a consequence not seen in previous disruptive attacks such as the 2016 CRASHOVERRIDE malware that caused a power loss in Ukraine .' [/INST] [Targeting:O, a:O, safety:O, system:O, indicates:O, significant:O, damage:O, and:O, loss:O, of:O, human:O, life:O, were:O, either:O, intentional:O, or:O, acceptable:O, goals:O, of:O, the:O, attack:B-OffAct, ,:O, a:O, consequence:O, not:O, seen:O, in:O, previous:O, disruptive:O, attacks:B-OffAct, such:O, as:O, the:O, 2016:B-Time, CRASHOVERRIDE:B-Tool, malware:I-Tool, that:O, caused:O, a:O, power:O, loss:O, in:O, Ukraine: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: 'XENOTIME used credential capture and replay to move between networks , Windows commands , standard command-line tools such as PSExec , and proprietary tools for operations on victim hosts .' [/INST] [XENOTIME:B-HackOrg, used:O, credential:B-Tool, capture:I-Tool, and:I-Tool, replay:I-Tool, to:O, move:O, between:O, networks:O, ,:O, Windows:O, commands:O, ,:O, standard:O, command-line:O, tools:O, such:O, as:O, PSExec:B-Tool, ,:O, and:O, proprietary:O, tools:O, for:O, operations:O, on:O, victim:O, hosts:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'XENOTIME configured TRISIS based on the specifics and functions of the Triconex system within the industrial control ( ICS ) environment .' [/INST] [XENOTIME:B-HackOrg, configured:O, TRISIS:B-Tool, based:O, on:O, the:O, specifics:O, and:O, functions:O, of:O, the:O, Triconex:O, system:O, within:O, the:O, industrial:O, control:O, (:O, ICS:B-Tool, ):O, environment:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Dragos' data indicates XENOTIME remains active .' [/INST] [Dragos':B-SecTeam, data:O, indicates:O, XENOTIME:B-HackOrg, remains:O, active:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'TEMP.Veles created a custom malware framework and tailormade credential gathering tools , but an apparent misconfiguration prevented the attack from executing properly .' [/INST] [TEMP.Veles:B-HackOrg, created:O, a:O, custom:B-Tool, malware:I-Tool, framework:O, and:O, tailormade:B-Tool, credential:I-Tool, gathering:I-Tool, tools:I-Tool, ,:O, but:O, an:O, apparent:O, misconfiguration:O, prevented:O, the:O, attack:B-OffAct, from:O, executing:O, properly:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Furthermore , Dragos' analysis of the TRISIS event continues as we recover additional data surrounding the incident .' [/INST] [Furthermore:O, ,:O, Dragos':B-SecTeam, analysis:O, of:O, the:O, TRISIS:B-Tool, event:O, continues:O, as:O, we:O, recover:O, additional:O, data:O, surrounding:O, the:O, incident:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'XENOTIME operates globally , impacting regions far outside of the Middle East , their initial target .' [/INST] [XENOTIME:B-HackOrg, operates:O, globally:O, ,:O, impacting:O, regions:O, far:O, outside:O, of:O, the:O, Middle:B-Area, East:I-Area, ,:O, their:O, initial:O, target:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Intelligence suggests the group has been active since at least 2014 and is presently operating in multiple facilities targeting safety systems beyond Triconex .' [/INST] [Intelligence:O, suggests:O, the:O, group:O, has:O, been:O, active:O, since:O, at:O, least:O, 2014:B-Time, and:O, is:O, presently:O, operating:O, in:O, multiple:O, facilities:O, targeting:O, safety:O, systems:O, beyond:O, Triconex:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Dragos instead focuses on threat behaviors and appropriate detection and response .' [/INST] [Dragos:B-SecTeam, instead:O, focuses:O, on:O, threat:O, behaviors:O, and:O, appropriate:O, detection:O, and:O, response:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Dragos assesses with moderate confidence that XENOTIME intends to establish required access and capability to cause a potential , future disruptive—or even destructive—event .' [/INST] [Dragos:B-SecTeam, assesses:O, with:O, moderate:O, confidence:O, that:O, XENOTIME:B-HackOrg, intends:O, to:O, establish:O, required:O, access:O, and:O, capability:O, to:O, cause:O, a:O, potential:O, ,:O, future:O, disruptive—or:O, even:O, destructive—event:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , full details on XENOTIME and other group tools , techniques , procedures , and infrastructure is available to network defenders via Dragos WorldView .' [/INST] [However:O, ,:O, full:O, details:O, on:O, XENOTIME:B-HackOrg, and:O, other:O, group:O, tools:O, ,:O, techniques:O, ,:O, procedures:O, ,:O, and:O, infrastructure:O, is:O, available:O, to:O, network:O, defenders:O, via:O, Dragos:B-SecTeam, WorldView:I-SecTeam, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This seems confusing as FireEye earlier publicly declared the TRITON as a discrete entity , linked to a Russian research institution , and christened it as , TEMP.Veles , .' [/INST] [This:O, seems:O, confusing:O, as:O, FireEye:B-SecTeam, earlier:O, publicly:O, declared:O, the:O, TRITON:B-Tool, as:O, a:O, discrete:O, entity:O, ,:O, linked:O, to:O, a:O, Russian:B-Area, research:B-Org, institution:I-Org, ,:O, and:O, christened:O, it:O, as:O, ,:O, TEMP.Veles: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: 'This seems confusing as FireEye earlier publicly declared the , TRITON actor , as a discrete entity , linked to a Russian research institution , and christened it as , TEMP.Veles , .' [/INST] [This:O, seems:O, confusing:O, as:O, FireEye:B-SecTeam, earlier:O, publicly:O, declared:O, the:O, ,:O, TRITON:B-Tool, actor:O, ,:O, as:O, a:O, discrete:O, entity:O, ,:O, linked:O, to:O, a:O, Russian:B-Area, research:B-Org, institution:I-Org, ,:O, and:O, christened:O, it:O, as:O, ,:O, TEMP.Veles: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: 'Meanwhile , parallel work at Dragos ( my employer , where I have performed significant work on the activity described above ) uncovered similar conclusions concerning TTPs and behaviors , for both the 2017 event and subsequent activity in other industrial sectors .' [/INST] [Meanwhile:O, ,:O, parallel:O, work:O, at:O, Dragos:B-SecTeam, (:O, my:O, employer:O, ,:O, where:O, I:O, have:O, performed:O, significant:O, work:O, on:O, the:O, activity:B-OffAct, described:O, above:O, ):O, uncovered:O, similar:O, conclusions:O, concerning:O, TTPs:O, and:O, behaviors:O, ,:O, for:O, both:O, the:O, 2017:B-Time, event:O, and:O, subsequent:O, activity:B-OffAct, in:O, other:O, industrial: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: 'FireEye recently published a blog covering the tactics , techniques , and procedures ( TTPs ) for the , TRITON actor , when preparing to deploy the TRITON/TRISIS malware framework in 2017 .' [/INST] [FireEye:B-SecTeam, recently:O, published:O, a:O, blog:O, covering:O, the:O, tactics:O, ,:O, techniques:O, ,:O, and:O, procedures:O, (:O, TTPs:O, ):O, for:O, the:O, ,:O, TRITON:B-Tool, actor:O, ,:O, when:O, preparing:O, to:O, deploy:O, the:O, TRITON/TRISIS:B-Tool, malware:I-Tool, framework:O, in:O, 2017: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: 'Based on information gained from discussion with the initial TRITON/TRISIS responders and subsequent work on follow-on activity by this entity , Dragos developed a comprehensive ( public ) picture of adversary activity roughly matching FireEye 's analysis published in April 2019 , described in various media .' [/INST] [Based:O, on:O, information:O, gained:O, from:O, discussion:O, with:O, the:O, initial:O, TRITON/TRISIS:B-Tool, responders:O, and:O, subsequent:O, work:O, on:O, follow-on:O, activity:B-OffAct, by:O, this:O, entity:O, ,:O, Dragos:B-SecTeam, developed:O, a:O, comprehensive:O, (:O, public:O, ):O, picture:O, of:O, adversary:O, activity:B-OffAct, roughly:O, matching:O, FireEye:B-SecTeam, 's:O, analysis:O, published:O, in:O, April:B-Time, 2019:I-Time, ,:O, described:O, in:O, various:O, media: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: 'Since late 2018 , based upon the most-recent posting , FireEye appears to have , walked back , the previously-used terminology of TEMP.Veles and instead refers rather cryptically to the , TRITON actor , , while Dragos leveraged identified behaviors to consistently refer to an activity group , XENOTIME .' [/INST] [Since:O, late:O, 2018:B-Time, ,:O, based:O, upon:O, the:O, most-recent:O, posting:O, ,:O, FireEye:B-SecTeam, appears:O, to:O, have:O, ,:O, walked:O, back:O, ,:O, the:O, previously-used:O, terminology:O, of:O, TEMP.Veles:B-HackOrg, and:O, instead:O, refers:O, rather:O, cryptically:O, to:O, the:O, ,:O, TRITON:B-Tool, actor:O, ,:O, ,:O, while:O, Dragos:B-SecTeam, leveraged:O, identified:O, behaviors:O, to:O, consistently:O, refer:O, to:O, an:O, activity:O, group:O, ,:O, XENOTIME: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: 'Dragos leveraged identified behaviors to consistently refer to an activity group , XENOTIME .' [/INST] [Dragos:B-SecTeam, leveraged:O, identified:O, behaviors:O, to:O, consistently:O, refer:O, to:O, an:O, activity:O, group:O, ,:O, XENOTIME: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: 'Aside from the competitive vendor naming landscape ( which I am not a fan of in cases on direct overlap , but which has more to say for itself when different methodologies are employed around similar observations ) , the distinction between FireEye and Dragos' approaches with respect to the , TRITON actor , comes down to fundamental philosophical differences in methodology .' [/INST] [Aside:O, from:O, the:O, competitive:O, vendor:O, naming:O, landscape:O, (:O, which:O, I:O, am:O, not:O, a:O, fan:O, of:O, in:O, cases:O, on:O, direct:O, overlap:O, ,:O, but:O, which:O, has:O, more:O, to:O, say:O, for:O, itself:O, when:O, different:O, methodologies:O, are:O, employed:O, around:O, similar:O, observations:O, ):O, ,:O, the:O, distinction:O, between:O, FireEye:B-SecTeam, and:O, Dragos':B-SecTeam, approaches:O, with:O, respect:O, to:O, the:O, ,:O, TRITON:B-Tool, actor:O, ,:O, comes:O, down:O, to:O, fundamental:O, philosophical:O, differences:O, in:O, methodology:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In the 2018 public posting announcing TEMP.Veles , FireEye researchers noted that the institute in question at least supported TEMP.Veles activity in deploying TRITON .' [/INST] [In:O, the:O, 2018:B-Time, public:O, posting:O, announcing:O, TEMP.Veles:B-HackOrg, ,:O, FireEye:B-SecTeam, researchers:O, noted:O, that:O, the:O, institute:O, in:O, question:O, at:O, least:O, supported:O, TEMP.Veles:B-HackOrg, activity:I-OffAct, in:O, deploying:O, TRITON: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: 'My understanding is FireEye labels entities where definitive attribution is not yet possible with the , TEMP , moniker ( hence , TEMP.Veles ) – yet in this case FireEye developed and deployed the label , then appeared to move away from it in subsequent reporting .' [/INST] [My:O, understanding:O, is:O, FireEye:B-SecTeam, labels:O, entities:O, where:O, definitive:O, attribution:O, is:O, not:O, yet:O, possible:O, with:O, the:O, ,:O, TEMP:O, ,:O, moniker:O, (:O, hence:O, ,:O, TEMP.Veles:B-HackOrg, ):O, –:O, yet:O, in:O, this:O, case:O, FireEye:B-SecTeam, developed:O, and:O, deployed:O, the:O, label:O, ,:O, then:O, appeared:O, to:O, move:O, away:O, from:O, it:O, in:O, subsequent:O, reporting:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In comparison , XENOTIME was defined based on principles of infrastructure ( compromised third-party infrastructure and various networks associated with several Russian research institutions ) , capabilities ( publicly- and commercially-available tools with varying levels of customization ) and targeting ( an issue not meant for discussion in this blog ) .' [/INST] [In:O, comparison:O, ,:O, XENOTIME:B-HackOrg, was:O, defined:O, based:O, on:O, principles:O, of:O, infrastructure:O, (:O, compromised:O, third-party:O, infrastructure:O, and:O, various:O, networks:O, associated:O, with:O, several:O, Russian:B-Area, research:B-Org, institutions:I-Org, ):O, ,:O, capabilities:O, (:O, publicly-:O, and:O, commercially-available:O, tools:O, with:O, varying:O, levels:O, of:O, customization:O, ):O, and:O, targeting:O, (:O, an:O, issue:O, not:O, meant:O, for:O, discussion:O, in:O, this:O, blog:O, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Of note , this methodology of naming abstracts away the , who , element – XENOTIME may represent a single discrete entity ( such as a Russian research institution ) or several entities working in coordination in a roughly repeatable , similar manner across multiple events .' [/INST] [Of:O, note:O, ,:O, this:O, methodology:O, of:O, naming:O, abstracts:O, away:O, the:O, ,:O, who:O, ,:O, element:O, –:O, XENOTIME:B-HackOrg, may:O, represent:O, a:O, single:O, discrete:O, entity:O, (:O, such:O, as:O, a:O, Russian:B-Area, research:B-Org, institution:I-Org, ):O, or:O, several:O, entities:O, working:O, in:O, coordination:O, in:O, a:O, roughly:O, repeatable:O, ,:O, similar:O, manner:O, across:O, multiple:O, events:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Much like the observers watching the shadows of objects cast upon the wall of the cave , these two definitions ( XENOTIME and TEMP.Veles , both presumably referring to , the TRITON actor , ) describe the same phenomena , yet at the same time appear different .' [/INST] [Much:O, like:O, the:O, observers:O, watching:O, the:O, shadows:O, of:O, objects:O, cast:O, upon:O, the:O, wall:O, of:O, the:O, cave:O, ,:O, these:O, two:O, definitions:O, (:O, XENOTIME:B-HackOrg, and:O, TEMP.Veles:B-HackOrg, ,:O, both:O, presumably:O, referring:O, to:O, ,:O, the:O, TRITON:B-Tool, actor:O, ,:O, ):O, describe:O, the:O, same:O, phenomena:O, ,:O, yet:O, at:O, the:O, same:O, time:O, appear:O, different:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To better understand how the adversary was operating and what other actions they had performed , CTU researchers examined cmd.exe and its supporting processes to uncover additional command line artifacts .' [/INST] [To:O, better:O, understand:O, how:O, the:O, adversary:O, was:O, operating:O, and:O, what:O, other:O, actions:O, they:O, had:O, performed:O, ,:O, CTU:B-SecTeam, researchers:O, examined:O, cmd.exe:B-SamFile, and:O, its:O, supporting:O, processes:O, to:O, uncover:O, additional:O, command:O, line:O, artifacts:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CTU researchers assess with high confidence that threat groups like Threat Group-1314 will continue to live off of the land to avoid detection and conduct their operations .' [/INST] [CTU:B-SecTeam, researchers:O, assess:O, with:O, high:O, confidence:O, that:O, threat:O, groups:O, like:O, Threat:B-HackOrg, Group-1314:I-HackOrg, will:O, continue:O, to:O, live:O, off:O, of:O, the:O, land:O, to:O, avoid:O, detection:O, and:O, conduct: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: 'Analysis of TG-3390 's operations , targeting , and tools led CTU researchers to assess with moderate confidence the group is located in the People's Republic of China .' [/INST] [Analysis:O, of:O, TG-3390:B-HackOrg, 's:O, operations:O, ,:O, targeting:O, ,:O, and:O, tools:O, led:O, CTU:B-SecTeam, researchers:O, to:O, assess:O, with:O, moderate:O, confidence:O, the:O, group:O, is:O, located:O, in:O, the:O, People's:B-Area, Republic:I-Area, of:I-Area, China: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 threat actors target a wide range of organizations : CTU researchers have observed TG-3390 actors obtaining confidential data on defense manufacturing projects , but also targeting other industry verticals and attacking organizations involved in international relations .' [/INST] [The:O, threat:O, actors:O, target:O, a:O, wide:O, range:O, of:O, organizations:O, ::O, CTU:B-SecTeam, researchers:O, have:O, observed:O, TG-3390:B-HackOrg, actors:O, obtaining:O, confidential:O, data:O, on:O, defense:O, manufacturing:O, projects:O, ,:O, but:O, also:O, targeting:O, other:O, industry:O, verticals:O, and:O, attacking:O, organizations:O, involved:O, in:O, international:O, relations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In comparison to other threat groups , TG-3390 is notable for its tendency to compromise Microsoft Exchange servers using a custom backdoor and credential logger .' [/INST] [In:O, comparison:O, to:O, other:O, threat:O, groups:O, ,:O, TG-3390:B-HackOrg, is:O, notable:O, for:O, its:O, tendency:O, to:O, compromise:O, Microsoft:O, Exchange:O, servers:O, using:O, a:O, custom:B-Tool, backdoor:I-Tool, and:O, credential:B-Tool, logger: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: 'CTU researchers have evidence that the TG-3390 compromised U.S and UK organizations in the following verticals : manufacturing ( specifically aerospace ( including defense contractors ) , automotive , technology , energy , and pharmaceuticals ) , education , and legal , as well as organizations focused on international relations .' [/INST] [CTU:B-SecTeam, researchers:O, have:O, evidence:O, that:O, the:O, TG-3390:B-HackOrg, compromised:O, U.S:O, and:O, UK:O, organizations:O, in:O, the:O, following:O, verticals:O, ::O, manufacturing:B-Idus, (:O, specifically:O, aerospace:B-Idus, (:O, including:O, defense:B-Org, contractors:I-Org, ):O, ,:O, automotive:B-Idus, ,:O, technology:B-Idus, ,:O, energy:B-Idus, ,:O, and:O, pharmaceuticals:B-Idus, ):O, ,:O, education:B-Idus, ,:O, and:O, legal:B-Idus, ,:O, as:O, well:O, as:O, organizations:O, focused:O, on:O, international:O, relations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 analysis of the group 's SWCs , TG-3390 operations likely affect organizations in other countries and verticals .' [/INST] [Based:O, on:O, analysis:O, of:O, the:O, group:O, 's:O, SWCs:B-Tool, ,:O, TG-3390:B-HackOrg, operations:O, likely:O, affect:O, organizations:O, in:O, other:O, countries:O, and:O, verticals:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'TG-3390 operates a broad and long-running campaign of SWCs and has compromised approximately 100 websites as of this publication .' [/INST] [TG-3390:B-HackOrg, operates:O, a:O, broad:O, and:O, long-running:O, campaign:B-OffAct, of:O, SWCs:B-OffAct, and:O, has:O, compromised:O, approximately:O, 100:O, websites:O, as:O, of:O, this:O, publication:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CTU researchers have evidence that the threat group compromised U.S and UK organizations in the following verticals : manufacturing ( specifically aerospace ( including defense contractors ) , automotive , technology , energy , and pharmaceuticals ) , education , and legal , as well as organizations focused on international relations .' [/INST] [CTU:B-SecTeam, researchers:O, have:O, evidence:O, that:O, the:O, threat:O, group:O, compromised:O, U.S:O, and:O, UK:O, organizations:O, in:O, the:O, following:O, verticals:O, ::O, manufacturing:B-Idus, (:O, specifically:O, aerospace:B-Idus, (:O, including:O, defense:B-Org, contractors:I-Org, ):O, ,:O, automotive:B-Idus, ,:O, technology:B-Idus, ,:O, energy:B-Idus, ,:O, and:O, pharmaceuticals:B-Idus, ):O, ,:O, education:B-Idus, ,:O, and:O, legal:B-Idus, ,:O, as:O, well:O, as:O, organizations:O, focused:O, on:O, international:O, relations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 many threat groups , TG-3390 conducts strategic web compromises ( SWCs ) , also known as watering hole attacks , on websites associated with the target organization 's vertical or demographic to increase the likelihood of finding victims with relevant information .' [/INST] [Like:O, many:O, threat:O, groups:O, ,:O, TG-3390:B-HackOrg, conducts:O, strategic:B-Way, web:I-Way, compromises:I-Way, (:O, SWCs:B-Tool, ):O, ,:O, also:O, known:O, as:O, watering:B-OffAct, hole:I-OffAct, attacks:I-OffAct, ,:O, on:O, websites:O, associated:O, with:O, the:O, target:O, organization:O, 's:O, vertical:O, or:O, demographic:O, to:O, increase:B-Purp, the:I-Purp, likelihood:I-Purp, of:O, finding:O, victims:O, with:O, relevant:O, information:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Through an IP address whitelisting process , the threat group selectively targets visitors to these websites .' [/INST] [Through:O, an:O, IP:B-Way, address:I-Way, whitelisting:I-Way, process:I-Way, ,:O, the:O, threat:O, group:O, selectively:O, targets:O, visitors:O, to:O, these:O, websites:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'After the initial compromise , TG-3390 delivers the HTTPBrowser backdoor to its victims .' [/INST] [After:O, the:O, initial:O, compromise:O, ,:O, TG-3390:B-HackOrg, delivers:O, the:O, HTTPBrowser:B-Tool, backdoor:I-Tool, to:O, its: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: 'CTU researchers assess with high confidence that TG-3390 uses information gathered from prior reconnaissance activities to selectively compromise users who visit websites under its control .' [/INST] [CTU:B-SecTeam, researchers:O, assess:O, with:O, high:O, confidence:O, that:O, TG-3390:B-HackOrg, uses:O, information:O, gathered:O, from:O, prior:O, reconnaissance:O, activities:B-OffAct, to:O, selectively:O, compromise:O, users:O, who:O, visit:O, websites:O, under:O, its:O, control:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'TG-3390 uses the PlugX remote access tool .' [/INST] [TG-3390:B-HackOrg, uses:O, the:O, PlugX:B-Tool, remote:I-Tool, access:I-Tool, tool: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 SWC of a Uyghur cultural website suggests intent to target the Uyghur ethnic group , a Muslim minority group primarily found in the Xinjiang region of China .' [/INST] [The:O, SWC:B-Tool, of:O, a:O, Uyghur:O, cultural:O, website:O, suggests:O, intent:O, to:O, target:O, the:O, Uyghur:B-Org, ethnic:I-Org, group:I-Org, ,:O, a:O, Muslim:B-Org, minority:I-Org, group:I-Org, primarily:O, found:O, in:O, the:O, Xinjiang:B-Area, region:O, of:O, China:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The threat actors have used the Baidu search engine , which is only available in Chinese , to conduct reconnaissance activities .' [/INST] [The:O, threat:O, actors:O, have:O, used:O, the:O, Baidu:B-Tool, search:I-Tool, engine:I-Tool, ,:O, which:O, is:O, only:O, available:O, in:O, Chinese:B-Area, ,:O, to:O, conduct:O, reconnaissance:O, activities: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: 'Recently , CTU researchers responded to an intrusion perpetrated by Threat Group-1314 , one of numerous threat groups that employ the , living off the land , technique to conduct their intrusions .' [/INST] [Recently:O, ,:O, CTU:B-SecTeam, researchers:O, responded:O, to:O, an:O, intrusion:O, perpetrated:O, by:O, Threat:B-HackOrg, Group-1314:I-HackOrg, ,:O, one:O, of:O, numerous:O, threat:O, groups:O, that:O, employ:O, the:O, ,:O, living:B-Way, off:I-Way, the:I-Way, land:I-Way, ,:O, technique:O, to:O, conduct:O, their:O, intrusions:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CTU researchers have observed the Threat Group-3390 obtaining information about specific U.S. defense projects that would be desirable to those operating within a country with a manufacturing base , an interest in U.S. military capability , or both .' [/INST] [CTU:B-SecTeam, researchers:O, have:O, observed:O, the:O, Threat:O, Group-3390:B-HackOrg, obtaining:O, information:O, about:O, specific:O, U.S.:B-Idus, defense:I-Idus, projects:O, that:O, would:O, be:O, desirable:O, to:O, those:O, operating:O, within:O, a:O, country:O, with:O, a:O, manufacturing:O, base:O, ,:O, an:O, interest:O, in:O, U.S.:B-Area, military:B-Idus, capability:I-Idus, ,:O, or:O, both:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CTU researchers have observed the threat group obtaining information about specific U.S. defense projects that would be desirable to those operating within a country with a manufacturing base , an interest in U.S. military capability , or both .' [/INST] [CTU:B-SecTeam, researchers:O, have:O, observed:O, the:O, threat:O, group:O, obtaining:O, information:O, about:O, specific:O, U.S.:B-Idus, defense:I-Idus, projects:O, that:O, would:O, be:O, desirable:O, to:O, those:O, operating:O, within:O, a:O, country:O, with:O, a:O, manufacturing:O, base:O, ,:O, an:O, interest:O, in:O, U.S.:B-Area, military:B-Idus, capability:I-Idus, ,:O, or:O, both:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'TG-3390 can quickly leverage compromised network infrastructure during an operation and can conduct simultaneous intrusions into multiple environments .' [/INST] [TG-3390:B-HackOrg, can:O, quickly:O, leverage:O, compromised:O, network:B-Way, infrastructure:I-Way, during:O, an:O, operation:O, and:O, can:O, conduct:O, simultaneous:O, intrusions:O, into:O, multiple:O, environments:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Malware used by the threat group can be configured to bypass network-based detection ; however , the threat actors rarely modify host-based configuration settings when deploying payloads .' [/INST] [Malware:B-Tool, used:O, by:O, the:O, threat:O, group:O, can:O, be:O, configured:O, to:O, bypass:O, network-based:O, detection:O, ;:O, however:O, ,:O, the:O, threat:O, actors:O, rarely:O, modify:O, host-based:O, configuration:O, settings:O, when:O, deploying: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: 'TG-3390 uses older exploits to compromise targets , and CTU researchers have not observed the threat actors using zero-day exploits as of this publication .' [/INST] [TG-3390:B-HackOrg, uses:O, older:O, exploits:O, to:O, compromise:O, targets:O, ,:O, and:O, CTU:B-SecTeam, researchers:O, have:O, not:O, observed:O, the:O, threat:O, actors:O, using:O, zero-day:B-Exp, exploits:I-Exp, as:O, of:O, this:O, publication:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 using SWCs to target specific types of organizations , TG-3390 uses spearphishing emails to target specific victims .' [/INST] [In:O, addition:O, to:O, using:O, SWCs:B-Tool, to:O, target:O, specific:O, types:O, of:O, organizations:O, ,:O, TG-3390:B-HackOrg, uses:O, spearphishing:B-Way, emails:I-Way, to:O, target:O, specific: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: 'After gaining access to a target network in one intrusion analyzed by CTU researchers , TG-3390 actors identified and exfiltrated data for specific projects run by the target organization , indicating that they successfully obtained the information they sought .' [/INST] [After:O, gaining:O, access:O, to:O, a:O, target:O, network:O, in:O, one:O, intrusion:O, analyzed:O, by:O, CTU:B-SecTeam, researchers:O, ,:O, TG-3390:B-HackOrg, actors:O, identified:O, and:O, exfiltrated:O, data:O, for:O, specific:O, projects:O, run:O, by:O, the:O, target:O, organization:O, ,:O, indicating:O, that:O, they:O, successfully:O, obtained:O, the:O, information:O, they:O, sought:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 this information , CTU researchers assess that TG-3390 aims to collect defense technology and capability intelligence , other industrial intelligence , and political intelligence from governments and NGOs .' [/INST] [Based:O, on:O, this:O, information:O, ,:O, CTU:B-SecTeam, researchers:O, assess:O, that:O, TG-3390:B-HackOrg, aims:O, to:O, collect:O, defense:B-Purp, technology:I-Purp, and:O, capability:B-Purp, intelligence:I-Purp, ,:O, other:O, industrial:O, intelligence:O, ,:O, and:O, political:B-Idus, intelligence:I-Idus, from:O, governments:B-Idus, and:O, NGOs: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: 'Incident response engagements have given CTU researchers insight into the tactics TG-3390 employs during intrusions .' [/INST] [Incident:O, response:O, engagements:O, have:O, given:O, CTU:B-SecTeam, researchers:O, insight:O, into:O, the:O, tactics:O, TG-3390:B-HackOrg, employs:O, during:O, intrusions:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CTU researchers have not observed TG-3390 actors performing reconnaissance prior to compromising organizations .' [/INST] [CTU:B-SecTeam, researchers:O, have:O, not:O, observed:O, TG-3390:B-HackOrg, actors:O, performing:O, reconnaissance:O, prior:O, to:O, compromising:B-Org, organizations: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: 'CTU researchers have observed the threat actors installing a credential logger and backdoor on Microsoft Exchange servers , which requires a technical grasp of Internet Information Services ( IIS ) .' [/INST] [CTU:B-SecTeam, researchers:O, have:O, observed:O, the:O, threat:O, actors:O, installing:O, a:O, credential:B-Tool, logger:I-Tool, and:O, backdoor:O, on:O, Microsoft:O, Exchange:O, servers:O, ,:O, which:O, requires:O, a:O, technical:O, grasp:O, of:O, Internet:O, Information:O, Services:O, (:O, IIS: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: 'TG-3390 is capable of using a C2 infrastructure that spans multiple networks and registrars .' [/INST] [TG-3390:B-HackOrg, is:O, capable:O, of:O, using:O, a:O, C2:B-Way, infrastructure:I-Way, that:O, spans:O, multiple:O, networks:O, and:O, registrars:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'TG-3390 SWCs may be largely geographically independent , but the group 's most frequently used C2 registrars and IP net blocks are located in the U.S .' [/INST] [TG-3390:B-HackOrg, SWCs:O, may:O, be:O, largely:O, geographically:O, independent:O, ,:O, but:O, the:O, group:O, 's:O, most:O, frequently:O, used:O, C2:O, registrars:O, and:O, IP:O, net:O, blocks:O, are:O, located:O, in:O, the:O, U.S: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: 'Using a U.S.-based C2 infrastructure ( see Figure 7 ) to compromise targets in the U.S. helps TG-3390 actors avoid geo-blocking and geo-flagging measures used in network defense .' [/INST] [Using:O, a:O, U.S.-based:B-Tool, C2:I-Tool, infrastructure:I-Tool, (:O, see:O, Figure:O, 7:O, ):O, to:O, compromise:O, targets:O, in:O, the:O, U.S.:B-Area, helps:O, TG-3390:B-HackOrg, actors:O, avoid:O, geo-blocking:O, and:O, geo-flagging:O, measures:O, used:O, in:O, network:O, defense:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The threat actors create PlugX DLL stub loaders that will run only after a specific date .' [/INST] [The:O, threat:O, actors:O, create:O, PlugX:B-Tool, DLL:I-Tool, stub:O, loaders:O, that:O, will:O, run:O, only:O, after:O, a:O, specific:O, date:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The compile dates of the samples analyzed by CTU researchers are all later than the hard-coded August 8 , 2013 date , indicating that the code might be reused from previous tools .' [/INST] [The:O, compile:O, dates:O, of:O, the:O, samples:O, analyzed:O, by:O, CTU:B-SecTeam, researchers:O, are:O, all:O, later:O, than:O, the:O, hard-coded:O, August:B-Time, 8:I-Time, ,:O, 2013:B-Time, date:O, ,:O, indicating:O, that:O, the:O, code:O, might:O, be:O, reused:O, from:O, previous:O, tools:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'One archive sample analyzed by CTU researchers contained a legitimate PDF file , a benign image of interest to targets ( see Figure 8 ) , and an HTTPBrowser installer disguised as an image file .' [/INST] [One:O, archive:O, sample:O, analyzed:O, by:O, CTU:B-SecTeam, researchers:O, contained:O, a:O, legitimate:O, PDF:B-Tool, file:I-Tool, ,:O, a:O, benign:O, image:O, of:O, interest:O, to:O, targets:O, (:O, see:O, Figure:O, 8:O, ):O, ,:O, and:O, an:O, HTTPBrowser:B-Tool, installer:I-Tool, disguised:O, as:O, an:O, image:O, file:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CTU researchers have observed TG-3390 activity between 04:00 and 09:00 UTC , which is 12:00 to 17:00 local time in China ( UTC +8 ) .' [/INST] [CTU:B-SecTeam, researchers:O, have:O, observed:O, TG-3390:B-OffAct, activity:I-OffAct, between:O, 04:00:O, and:O, 09:00:O, UTC:O, ,:O, which:O, is:O, 12:00:O, to:O, 17:00:O, local:O, time:O, in:O, China:B-Area, (:O, UTC:O, +8: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: 'TG-3390 sends spearphishing emails with ZIP archive attachments .' [/INST] [TG-3390:B-HackOrg, sends:O, spearphishing:B-Way, emails:I-Way, with:O, ZIP:O, archive:O, attachments:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CTU researchers have observed TG-3390 compromising a target organization 's externally and internally accessible assets , such as an OWA server , and adding redirect code to point internal users to an external website that hosts an exploit and delivers malware .' [/INST] [CTU:B-SecTeam, researchers:O, have:O, observed:O, TG-3390:B-HackOrg, compromising:O, a:O, target:O, organization:O, 's:O, externally:O, and:O, internally:O, accessible:O, assets:O, ,:O, such:O, as:O, an:O, OWA:O, server:O, ,:O, and:O, adding:B-Way, redirect:I-Way, code:I-Way, to:O, point:O, internal:O, users:O, to:O, an:O, external:O, website:O, that:O, hosts:O, an:O, exploit:O, and:O, delivers:O, malware:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'TG-3390 actors have used Java exploits in their SWCs .' [/INST] [TG-3390:B-HackOrg, actors:O, have:O, used:O, Java:B-Exp, exploits:I-Exp, in:O, their:O, SWCs: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 particular , TG-3390 has exploited CVE-2011-3544 , a vulnerability in the Java Runtime Environment , to deliver the HTTPBrowser backdoor ; and CVE-2010-0738 , a vulnerability in JBoss , to compromise internally and externally accessible assets used to redirect users' web browsers to exploit code .' [/INST] [In:O, particular:O, ,:O, TG-3390:B-HackOrg, has:O, exploited:O, CVE-2011-3544:B-Exp, ,:O, a:O, vulnerability:O, in:O, the:O, Java:O, Runtime:O, Environment:O, ,:O, to:O, deliver:O, the:O, HTTPBrowser:B-Tool, backdoor:I-Tool, ;:O, and:O, CVE-2010-0738:B-Exp, ,:O, a:O, vulnerability:O, in:O, JBoss:B-Tool, ,:O, to:O, compromise:O, internally:O, and:O, externally:O, accessible:O, assets:O, used:O, to:O, redirect:O, users':O, web:O, browsers:O, to:O, exploit:O, code:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In activity analyzed by CTU researchers , TG-3390 executed the Hunter web application scanning tool against a target server running IIS .' [/INST] [In:O, activity:B-OffAct, analyzed:O, by:O, CTU:B-SecTeam, researchers:O, ,:O, TG-3390:B-HackOrg, executed:O, the:O, Hunter:B-Tool, web:I-Tool, application:I-Tool, scanning:I-Tool, tool:I-Tool, against:O, a:O, target:O, server:O, running:O, IIS:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In particular , the threat actors have exploited CVE-2011-3544 , a vulnerability in the Java Runtime Environment , to deliver the HTTPBrowser backdoor ; and CVE-2010-0738 , a vulnerability in JBoss , to compromise internally and externally accessible assets used to redirect users' web browsers to exploit code .' [/INST] [In:O, particular:O, ,:O, the:O, threat:O, actors:O, have:O, exploited:O, CVE-2011-3544:B-Exp, ,:O, a:O, vulnerability:O, in:O, the:O, Java:O, Runtime:O, Environment:O, ,:O, to:O, deliver:O, the:O, HTTPBrowser:B-Tool, backdoor:I-Tool, ;:O, and:O, CVE-2010-0738:B-Exp, ,:O, a:O, vulnerability:O, in:O, JBoss:B-Tool, ,:O, to:O, compromise:O, internally:O, and:O, externally:O, accessible:O, assets:O, used:O, to:O, redirect:O, users':O, web:O, browsers:O, to:O, exploit:O, code:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'TG-3390 uses DLL side loading , a technique that involves running a legitimate , typically digitally signed , program that loads a malicious DLL .' [/INST] [TG-3390:B-HackOrg, uses:O, DLL:B-Way, side:I-Way, loading:I-Way, ,:O, a:O, technique:O, that:O, involves:O, running:O, a:O, legitimate:O, ,:O, typically:O, digitally:O, signed:O, ,:O, program:O, that:O, loads:O, a:O, malicious:O, DLL:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CTU researchers have observed the Threat Group-3390 employing legitimate Kaspersky antivirus variants in analyzed samples .' [/INST] [CTU:B-SecTeam, researchers:O, have:O, observed:O, the:O, Threat:B-HackOrg, Group-3390:I-HackOrg, employing:O, legitimate:O, Kaspersky:B-SecTeam, antivirus:O, variants:O, in:O, analyzed:O, samples:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The adversaries have used this technique to allow PlugX and HTTPBrowser to persist on a system .' [/INST] [The:O, adversaries:O, have:O, used:O, this:O, technique:O, to:O, allow:O, PlugX:B-Tool, and:O, HTTPBrowser:B-Tool, to:O, persist:O, on:O, a: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: 'CTU researchers have observed the TG-3390 employing legitimate Kaspersky antivirus variants in analyzed samples .' [/INST] [CTU:B-SecTeam, researchers:O, have:O, observed:O, the:O, TG-3390:B-HackOrg, employing:O, legitimate:O, Kaspersky:B-SecTeam, antivirus:O, variants:O, in:O, analyzed:O, samples:O, .:O] </s> |
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