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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: 'Trojanized versions of the utility were then signed with legitimate certificates and were hosted on and distributed from official ASUS update servers – which made them mostly invisible to the vast majority of protection solutions , according to Kaspersky Lab .' [/INST] [Trojanized:O, versions:O, of:O, the:O, utility:O, were:O, then:O, signed:O, with:O, legitimate:O, certificates:O, and:O, were:O, hosted:O, on:O, and:O, distributed:O, from:O, official:O, ASUS:O, update:O, servers:O, –:O, which:O, made:O, them:O, mostly:O, invisible:O, to:O, the:O, vast:O, majority:O, of:O, protection:O, solutions:O, ,:O, according:O, to:O, Kaspersky:B-SecTeam, Lab: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: 'Kaspersky Lab To compromise the utility , Kaspersky Lab determined that the cyberattackers used stolen digital certificates used by ASUS to sign legitimate binaries , and altered older versions of ASUS software to inject their own malicious code .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, To:O, compromise:O, the:O, utility:O, ,:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, determined:O, that:O, the:O, cyberattackers:O, used:O, stolen:O, digital:O, certificates:O, used:O, by:O, ASUS:O, to:O, sign:O, legitimate:O, binaries:O, ,:O, and:O, altered:O, older:O, versions:O, of:O, ASUS:O, software:O, to:O, inject:O, their:O, own:O, malicious: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: 'To compromise the utility , Kaspersky Lab determined that Barium used stolen digital certificates used by ASUS to sign legitimate binaries , and altered older versions of ASUS software to inject their own malicious code .' [/INST] [To:O, compromise:O, the:O, utility:O, ,:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, determined:O, that:O, Barium:O, used:O, stolen:O, digital:O, certificates:O, used:O, by:O, ASUS:O, to:O, sign:O, legitimate:O, binaries:O, ,:O, and:O, altered:O, older:O, versions:O, of:O, ASUS:O, software:O, to:O, inject:O, their:O, own:O, malicious: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: 'BARIUM , a Chinese state player that also goes by APT17 , Axiom and Deputy Dog , was previously linked to the ShadowPad and CCleaner incidents , which were also supply-chain attacks that used software updates to sneak onto machines .' [/INST] [BARIUM:B-HackOrg, ,:O, a:O, Chinese:B-Area, state:I-Area, player:O, that:O, also:O, goes:O, by:O, APT17:B-HackOrg, ,:O, Axiom:B-HackOrg, and:O, Deputy:B-HackOrg, Dog:B-HackOrg, ,:O, was:O, previously:O, linked:O, to:O, the:O, ShadowPad:B-Tool, and:O, CCleaner:B-Tool, incidents:O, ,:O, which:O, were:O, also:O, supply-chain:B-OffAct, attacks:I-OffAct, that:O, used:O, software:B-Tool, updates:I-Tool, to:O, sneak:O, onto:O, machines:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'That said , the , fingerprints , left on the samples by the attackers – including techniques used to achieve unauthorized code execution – suggest that the BARIUM APT is behind the effort , according to the researchers .' [/INST] [That:O, said:O, ,:O, the:O, ,:O, fingerprints:O, ,:O, left:O, on:O, the:O, samples:O, by:O, the:O, attackers:O, –:O, including:O, techniques:O, used:O, to:O, achieve:O, unauthorized:O, code:O, execution:O, –:O, suggest:O, that:O, the:O, BARIUM:B-HackOrg, APT:I-HackOrg, is:O, behind:O, the:O, effort:O, ,:O, according:O, to:O, the:O, researchers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 2017 ShadowPad attack , the update mechanism for Korean server management software provider NetSarang was compromised to serve up an eponymous backdoor .' [/INST] [In:O, the:O, 2017:B-Time, ShadowPad:B-OffAct, attack:I-OffAct, ,:O, the:O, update:O, mechanism:O, for:O, Korean:B-Area, server:B-Org, management:I-Org, software:I-Org, provider:I-Org, NetSarang:O, was:O, compromised:O, to:O, serve:O, up:O, an:O, eponymous:O, backdoor:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 next incident , also in 2017 , software updates for the legitimate computer cleanup tool CCleaner was found to have been compromised by hackers to taint them with the same ShadowPad backdoor .' [/INST] [In:O, the:O, next:O, incident:O, ,:O, also:O, in:O, 2017:B-Time, ,:O, software:B-Tool, updates:I-Tool, for:O, the:O, legitimate:O, computer:O, cleanup:O, tool:O, CCleaner:O, was:O, found:O, to:O, have:O, been:O, compromised:O, by:O, hackers:O, to:O, taint:O, them:O, with:O, the:O, same:O, ShadowPad:B-Tool, backdoor:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'NetSarang , which has headquarters in South Korea and the United States , removed the backdoored update , but not before it was activated on at least one victim 's machine in Hong Kong .' [/INST] [NetSarang:O, ,:O, which:O, has:O, headquarters:O, in:O, South:B-Area, Korea:I-Area, and:O, the:O, United:B-Area, States:I-Area, ,:O, removed:O, the:O, backdoored:O, update:O, ,:O, but:O, not:O, before:O, it:O, was:O, activated:O, on:O, at:O, least:O, one:O, victim:O, 's:O, machine:O, in:O, Hong:B-Area, Kong: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: 'Given our increased confidence that Bahamut was responsible for targeting of Qatari labor rights advocates and its focus on the foreign policy institutions other Gulf states , Bahamut 's interests are seemingly too expansive to be limited one sponsor or customer .' [/INST] [Given:O, our:O, increased:O, confidence:O, that:O, Bahamut:O, was:O, responsible:O, for:O, targeting:O, of:O, Qatari:B-Area, labor:B-Org, rights:I-Org, advocates:I-Org, and:O, its:O, focus:O, on:O, the:O, foreign:B-Org, policy:I-Org, institutions:I-Org, other:O, Gulf:O, states:O, ,:O, Bahamut:O, 's:O, interests:O, are:O, seemingly:O, too:O, expansive:O, to:O, be:O, limited:O, one:O, sponsor:O, or:O, customer:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Barium specializes in targeting high value organizations holding sensitive data , by gathering extensive information about their employees through publicly available information and social media , using that information to fashion phishing attacks intended to trickthose employees into compromising their computers and networks .' [/INST] [Barium:O, specializes:O, in:O, targeting:O, high:O, value:O, organizations:O, holding:O, sensitive:O, data:O, ,:O, by:O, gathering:O, extensive:O, information:O, about:O, their:O, employees:B-Org, through:O, publicly:O, available:O, information:O, and:O, social:B-Idus, media:I-Idus, ,:O, using:O, that:O, information:O, to:O, fashion:O, phishing:B-OffAct, attacks:I-OffAct, intended:O, to:O, trickthose:O, employees:B-Org, into:O, compromising:O, their:O, computers:O, and:O, networks:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 an overlap in the domain voguextra.com , which was used by Bahamut within their , Devoted To Humanity , app to host an image file and as C2 server by the PrayTime iOS app mentioned in our first post .' [/INST] [We:O, identified:O, an:O, overlap:O, in:O, the:O, domain:O, voguextra.com:O, ,:O, which:O, was:O, used:O, by:O, Bahamut:B-HackOrg, within:O, their:O, ,:O, Devoted:B-SamFile, To:I-SamFile, Humanity:I-SamFile, ,:O, app:O, to:O, host:O, an:O, image:O, file:O, and:O, as:O, C2:O, server:O, by:O, the:O, PrayTime:O, iOS:O, app:O, mentioned:O, in:O, our:O, first:O, post:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Althoughthe BariumDefendants have relied on differentand distinct infrastructures in an effortto evade detection , Bariumused the same e-mail address (hostay88@gmail.com ) to register malicious domains used in connection with at least two toolsets that Barium has employed to compromise victim computers .' [/INST] [Althoughthe:O, BariumDefendants:O, have:O, relied:O, on:O, differentand:O, distinct:O, infrastructures:O, in:O, an:O, effortto:O, evade:O, detection:O, ,:O, Bariumused:O, the:O, same:O, e-mail:B-Way, address:O, (hostay88@gmail.com:O, ):O, to:O, register:O, malicious:O, domains:O, used:O, in:O, connection:O, with:O, at:O, least:O, two:O, toolsets:O, that:O, Barium:B-HackOrg, has:O, employed:O, to:O, compromise:O, victim:O, computers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 method , described in Part D.2 , below , involves the , ShadowPad , malware , which the Barium Defendants have distributed via a third-party software provider 's compromised update .' [/INST] [The:O, second:O, method:O, ,:O, described:O, in:O, Part:O, D.2:O, ,:O, below:O, ,:O, involves:O, the:O, ,:O, ShadowPad:B-Tool, ,:O, malware:O, ,:O, which:O, the:O, Barium:B-HackOrg, Defendants:O, have:O, distributed:O, via:O, a:O, third-party:B-Org, software:I-Org, provider:I-Org, 's:O, compromised:O, update:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 enhance the effectiveness of phishing attacks into the organization , Barium will collect additional background informationfrom social media sites .' [/INST] [To:O, enhance:O, the:O, effectiveness:O, of:O, phishing:B-OffAct, attacks:I-OffAct, into:O, the:O, organization:O, ,:O, Barium:B-HackOrg, will:O, collect:O, additional:O, background:O, informationfrom:O, social:B-Idus, media:I-Idus, sites:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Employing a technique known as , spear phishing , , Barium has heavily targeted individuals within HumanResources or Business Developmentdepartments ofthe targeted organizations in order to compromise the computers ofsuch individuals .' [/INST] [Employing:O, a:O, technique:O, known:O, as:O, ,:O, spear:B-Way, phishing:I-Way, ,:O, ,:O, Barium:B-HackOrg, has:O, heavily:O, targeted:O, individuals:O, within:O, HumanResources:O, or:O, Business:O, Developmentdepartments:O, ofthe:O, targeted:O, organizations:O, in:O, order:O, to:O, compromise:O, the:O, computers:O, ofsuch:O, individuals:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 first method , described in Part D.l , below , involves the , Barlaiy , and , PlugXL , malware , which the Barium Defendants propagate using phishing techniques .' [/INST] [The:O, first:O, method:O, ,:O, described:O, in:O, Part:O, D.l:O, ,:O, below:O, ,:O, involves:O, the:O, ,:O, Barlaiy:B-Tool, ,:O, and:O, ,:O, PlugXL:B-Tool, ,:O, malware:O, ,:O, which:O, the:O, Barium:O, Defendants:O, propagate:O, using:O, phishing:B-Way, techniques: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: 'Using the information gathered from its reconnaissance on social media sites , Barium packages the phishing e-mail in a way that gives the e-mail credibility to the target user , often by making the e-mail appear as ifit were sent from an organization known to and trusted by the victim or concerning a topic of interest to the victim .' [/INST] [Using:O, the:O, information:O, gathered:O, from:O, its:O, reconnaissance:O, on:O, social:B-Idus, media:I-Idus, sites:O, ,:O, Barium:B-HackOrg, packages:O, the:O, phishing:B-Way, e-mail:I-Way, in:O, a:O, way:O, that:O, gives:O, the:O, e-mail:B-Way, credibility:O, to:O, the:O, target:O, user:O, ,:O, often:O, by:O, making:O, the:O, e-mail:B-Way, appear:O, as:O, ifit:O, were:O, sent:O, from:O, an:O, organization:O, known:O, to:O, and:O, trusted:O, by:O, the:O, victim:O, or:O, concerning:O, a:O, topic:O, of:O, interest:O, to: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: 'Barium Defendants install the malicious , Win32/Barlaiy , malware and the malicious , Win32/PlugX.L , malware on victim computers using the means described above .' [/INST] [Barium:B-HackOrg, Defendants:O, install:O, the:O, malicious:O, ,:O, Win32/Barlaiy:B-Tool, ,:O, malware:O, and:O, the:O, malicious:O, ,:O, Win32/PlugX.L:B-Tool, ,:O, malware:O, on:O, victim:O, computers:O, using:O, the:O, means:O, described:O, above:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Win32/Barlaiy & Win32/PlugX.L are remote access , trojans , , which allow Barium to gather a victim 's information , control a victim 's device , install additional malware , and exfiltrate information fi-om a victim 's device .' [/INST] [Both:O, Win32/Barlaiy:B-Tool, &:O, Win32/PlugX.L:B-Tool, are:O, remote:O, access:O, ,:O, trojans:O, ,:O, ,:O, which:O, allow:O, Barium:B-HackOrg, to:O, gather:O, a:O, victim:O, 's:O, information:O, ,:O, control:O, a:O, victim:O, 's:O, device:O, ,:O, install:O, additional:O, malware:O, ,:O, and:O, exfiltrate:O, information:O, fi-om:O, a:O, victim:O, 's:O, device:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Barium Defendants install the malicious credential stealing and injection tool known as , Win32/RibDoor.A!dha , .' [/INST] [Barium:B-HackOrg, Defendants:O, install:O, the:O, malicious:O, credential:O, stealing:O, and:O, injection:O, tool:O, known:O, as:O, ,:O, Win32/RibDoor.A!dha: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: 'While not detected at the time , Microsoft 's antivirus and security products now detect this Barium malicious file and flag the file as , Win32/ShadowPad.A , .' [/INST] [While:O, not:O, detected:O, at:O, the:O, time:O, ,:O, Microsoft:B-Org, 's:O, antivirus:O, and:O, security:O, products:O, now:O, detect:O, this:O, Barium:B-HackOrg, malicious:O, file:O, and:O, flag:O, the:O, file:O, as:O, ,:O, Win32/ShadowPad.A:B-SamFile, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'MXI Player appears to be a version of the Bahamut agent , designed to record the phone calls and collect other information about the user ( com.mxi.videoplay ) .' [/INST] [MXI:B-SamFile, Player:I-SamFile, appears:O, to:O, be:O, a:O, version:O, of:O, the:O, Bahamut:O, agent:O, ,:O, designed:O, to:O, record:B-Features, the:I-Features, phone:I-Features, calls:I-Features, and:O, collect:B-Features, other:I-Features, information:I-Features, about:O, the:O, user:O, (:O, com.mxi.videoplay: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: 'Figure 9a , below , shows detections of encounters with the Barium actors and their infrastructure , including infected computers located in Virginia , and Figure 9b , below , shows detections of encounters throughout the United States .' [/INST] [Figure:O, 9a:O, ,:O, below:O, ,:O, shows:O, detections:O, of:O, encounters:O, with:O, the:O, Barium:O, actors:O, and:O, their:O, infrastructure:O, ,:O, including:O, infected:O, computers:O, located:O, in:O, Virginia:O, ,:O, and:O, Figure:O, 9b:O, ,:O, below:O, ,:O, shows:O, detections:O, of:O, encounters:O, throughout:O, the:O, United:B-Area, States: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: 'Barium has targeted Microsoft customers both in Virginia , the United States , and around the world .' [/INST] [Barium:B-HackOrg, has:O, targeted:O, Microsoft:B-Org, customers:I-Org, both:O, in:O, Virginia:O, ,:O, the:O, United:O, States:O, ,:O, and: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: 'Once the Barium Defendants have access to a victim computer through the malware described above , they monitor the victim 's activity and ultimately search for and steal sensitive documents ( for example , exfiltration of intellectual property regarding technology has been seen ) , and personal information fi"om the victim 's network .' [/INST] [Once:O, the:O, Barium:O, Defendants:O, have:O, access:O, to:O, a:O, victim:O, computer:O, through:O, the:O, malware:O, described:O, above:O, ,:O, they:O, monitor:O, the:O, victim:O, 's:O, activity:B-OffAct, and:O, ultimately:O, search:O, for:O, and:O, steal:B-Purp, sensitive:I-Purp, documents:I-Purp, (:O, for:O, example:O, ,:O, exfiltration:O, of:O, intellectual:B-Purp, property:I-Purp, regarding:O, technology:B-Idus, has:O, been:O, seen:O, ):O, ,:O, and:O, personal:O, information:O, fi"om:O, the:O, victim: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: 'According to a 49-page report published Thursday , all of the attacks are the work of Chinese government 's intelligence apparatus , which the report 's authors dub the Winnti Umbrella .' [/INST] [According:O, to:O, a:O, 49-page:O, report:O, published:O, Thursday:O, ,:O, all:O, of:O, the:O, attacks:O, are:O, the:O, work:B-Area, of:I-Area, Chinese:I-Area, government:I-Area, 's:I-Area, intelligence:I-Area, apparatus:I-Area, ,:O, which:O, the:O, report:O, 's:O, authors:O, dub:O, the:O, Winnti:B-HackOrg, Umbrella: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: 'Researchers from various security organizations have used a variety of names to assign responsibility for the hacks , including LEAD , BARIUM , Wicked Panda , GREF , PassCV , Axiom , and Winnti .' [/INST] [Researchers:O, from:O, various:O, security:O, organizations:O, have:O, used:O, a:O, variety:O, of:O, names:O, to:O, assign:O, responsibility:O, for:O, the:O, hacks:O, ,:O, including:O, LEAD:B-HackOrg, ,:O, BARIUM:B-HackOrg, ,:O, Wicked:B-HackOrg, Panda:I-HackOrg, ,:O, GREF:B-HackOrg, ,:O, PassCV:B-HackOrg, ,:O, Axiom:B-HackOrg, ,:O, and:O, Winnti: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: 'It targets organizations in Japan , South Korea , and Taiwan , leveling its attacks on public sector agencies and telecommunications and other high-technology industries .' [/INST] [It:O, targets:O, organizations:O, in:O, Japan:I-Area, ,:O, South:B-Area, Korea:I-Area, ,:O, and:O, Taiwan:B-Area, ,:O, leveling:O, its:O, attacks:B-OffAct, on:O, public:B-Org, sector:I-Org, agencies:I-Org, and:O, telecommunications:B-Idus, and:O, other:O, high-technology:B-Idus, industries: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: 'In 2016 , for instance , we found their campaigns attacking Japanese organizations with various malware tools , notably the Elirks backdoor .' [/INST] [In:O, 2016:B-Time, ,:O, for:O, instance:O, ,:O, we:O, found:O, their:O, campaigns:B-OffAct, attacking:O, Japanese:O, organizations:O, with:O, various:O, malware:O, tools:O, ,:O, notably:O, the:O, Elirks:B-Tool, backdoor:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Blackgear has been targeting various industries since its emergence a decade ago .' [/INST] [Blackgear:O, has:O, been:O, targeting:O, various:O, industries:O, since:O, its:O, emergence:O, a:O, decade:O, ago:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Blackgear 's campaigns also use email as an entry point , which is why it's important to secure the email gateway .' [/INST] [Blackgear:O, 's:O, campaigns:B-OffAct, also:O, use:O, email:B-Way, as:O, an:O, entry:O, point:O, ,:O, which:O, is:O, why:O, it's:O, important:O, to:O, secure:O, the:O, email:B-Way, gateway: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: 'BLACKGEAR is an espionage campaign which has targeted users in Taiwan for many years .' [/INST] [BLACKGEAR:B-OffAct, is:O, an:O, espionage:B-OffAct, campaign:I-OffAct, which:O, has:O, targeted:O, users:B-Org, in:O, Taiwan:B-Area, for:O, many:O, years:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Our research indicates that it has started targeting Japanese users .' [/INST] [Our:O, research:O, indicates:O, that:O, it:O, has:O, started:O, targeting:O, Japanese:B-Org, users: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 malware tools used by BLACKGEAR can be categorized into three categories : binders , downloaders and backdoors .' [/INST] [The:O, malware:O, tools:O, used:O, by:O, BLACKGEAR:B-OffAct, can:O, be:O, categorized:O, into:O, three:O, categories:O, ::O, binders:B-Tool, ,:O, downloaders:B-Tool, and:O, backdoors: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: 'Binders are delivered by attack vectors ( such as phishing and watering hole attacks ) onto a machine .' [/INST] [Binders:B-Tool, are:O, delivered:O, by:O, attack:B-OffAct, vectors:O, (:O, such:O, as:O, phishing:B-Way, and:O, watering:B-OffAct, hole:I-OffAct, attacks:I-OffAct, ):O, onto:O, a:O, machine:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 mutexes and domain names of some of their C&C servers , BlackTech 's campaigns are likely designed to steal their target 's technology .' [/INST] [Based:O, on:O, the:O, mutexes:O, and:O, domain:O, names:O, of:O, some:O, of:O, their:O, C&C:O, servers:O, ,:O, BlackTech:O, 's:O, campaigns:B-OffAct, are:O, likely:O, designed:O, to:O, steal:B-Purp, their:I-Purp, target:I-Purp, 's:I-Purp, technology: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: 'Following their activities and evolving tactics and techniques helped us uncover the proverbial red string of fate that connected three seemingly disparate campaigns : PLEAD , Shrouded Crossbow , and of late , Waterbear .' [/INST] [Following:O, their:O, activities:B-OffAct, and:O, evolving:O, tactics:O, and:O, techniques:O, helped:O, us:O, uncover:O, the:O, proverbial:O, red:O, string:O, of:O, fate:O, that:O, connected:O, three:O, seemingly:O, disparate:O, campaigns:B-OffAct, ::O, PLEAD:B-OffAct, ,:O, Shrouded:B-OffAct, Crossbow:I-OffAct, ,:O, and:O, of:O, late:O, ,:O, Waterbear: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: 'Active since 2012 , it has so far targeted Taiwanese government agencies and private organizations .' [/INST] [Active:O, since:O, 2012:B-Time, ,:O, it:O, has:O, so:O, far:O, targeted:O, Taiwanese:O, government:B-Org, agencies:I-Org, and:O, private:O, organizations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'PLEAD uses spear-phishing emails to deliver and install their backdoor , either as an attachment or through links to cloud storage services .' [/INST] [PLEAD:B-OffAct, uses:O, spear-phishing:B-Way, emails:I-Way, to:O, deliver:O, and:O, install:O, their:O, backdoor:O, ,:O, either:O, as:O, an:O, attachment:O, or:O, through:O, links:O, to:O, cloud:B-Tool, storage:I-Tool, services: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: 'PLEAD also dabbled with a short-lived , fileless version of their malware when it obtained an exploit for a Flash vulnerability ( CVE-2015-5119 ) that was leaked during the Hacking Team breach .' [/INST] [PLEAD:B-OffAct, also:O, dabbled:O, with:O, a:O, short-lived:O, ,:O, fileless:O, version:O, of:O, their:O, malware:O, when:O, it:O, obtained:O, an:O, exploit:O, for:O, a:O, Flash:B-Exp, vulnerability:I-Exp, (:O, CVE-2015-5119:B-Exp, ):O, that:O, was:O, leaked:O, during:O, the:O, Hacking:O, Team:O, breach:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'PLEAD also uses CVE-2017-7269 , a buffer overflow vulnerability Microsoft Internet Information Services ( IIS ) 6.0 to compromise the victim 's server .' [/INST] [PLEAD:B-OffAct, also:O, uses:O, CVE-2017-7269:B-Exp, ,:O, a:O, buffer:O, overflow:O, vulnerability:O, Microsoft:O, Internet:O, Information:O, Services:O, (:O, IIS:O, ):O, 6.0:O, to:O, compromise:O, the:O, victim:O, 's:O, server:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 campaign , first observed in 2010 , is believed to be operated by a well-funded group given how it appeared to have purchased the source code of the BIFROST backdoor , which the operators enhanced and created other tools from .' [/INST] [This:O, campaign:B-OffAct, ,:O, first:O, observed:O, in:O, 2010:B-Time, ,:O, is:O, believed:O, to:O, be:O, operated:O, by:O, a:O, well-funded:O, group:O, given:O, how:O, it:O, appeared:O, to:O, have:O, purchased:O, the:O, source:O, code:O, of:O, the:O, BIFROST:O, backdoor:O, ,:O, which:O, the:O, operators:O, enhanced:O, and:O, created:O, other:O, tools:O, from:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Shrouded Crossbow targeted privatized agencies and government contractors as well as enterprises in the consumer electronics , computer , healthcare , and financial industries .' [/INST] [Shrouded:B-OffAct, Crossbow:I-OffAct, targeted:O, privatized:B-Org, agencies:I-Org, and:O, government:B-Org, contractors:I-Org, as:O, well:O, as:O, enterprises:B-Idus, in:O, the:O, consumer:B-Idus, electronics:I-Idus, ,:O, computer:B-Idus, ,:O, healthcare:B-Idus, ,:O, and:O, financial:B-Idus, industries: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: 'Shrouded Crossbow employs three BIFROST-derived backdoors : BIFROSE , KIVARS , and XBOW .' [/INST] [Shrouded:B-OffAct, Crossbow:I-OffAct, employs:O, three:O, BIFROST-derived:B-Tool, backdoors:I-Tool, ::O, BIFROSE:B-Tool, ,:O, KIVARS:B-Tool, ,:O, and:O, XBOW: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: 'Like PLEAD , Shrouded Crossbow uses spear-phishing emails with backdoor-laden attachments that utilize the RTLO technique and accompanied by decoy documents .' [/INST] [Like:O, PLEAD:B-OffAct, ,:O, Shrouded:B-OffAct, Crossbow:I-OffAct, uses:O, spear-phishing:B-Way, emails:I-Way, with:O, backdoor-laden:O, attachments:O, that:O, utilize:O, the:O, RTLO:B-Tool, technique:I-Tool, and:O, accompanied:O, by:O, decoy:B-SamFile, documents: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: 'XBOW 's capabilities are derived from BIFROSE and KIVARS ; Shrouded Crossbow gets its name from its unique mutex format .' [/INST] [XBOW:B-Tool, 's:O, capabilities:O, are:O, derived:O, from:O, BIFROSE:B-Tool, and:O, KIVARS:B-Tool, ;:O, Shrouded:B-OffAct, Crossbow:I-OffAct, gets:O, its:O, name:O, from:O, its:O, unique:O, mutex:O, format:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While PLEAD and KIVARS are most likely to be used in first phase attacks , Waterbear can be seen as a secondary backdoor installed after attackers have gained a certain level of privilege .' [/INST] [While:O, PLEAD:B-Tool, and:O, KIVARS:B-Tool, are:O, most:O, likely:O, to:O, be:O, used:O, in:O, first:O, phase:O, attacks:B-OffAct, ,:O, Waterbear:B-OffAct, can:O, be:O, seen:O, as:O, a:O, secondary:O, backdoor:O, installed:O, after:O, attackers:O, have:O, gained:O, a:O, certain:O, level:O, of:O, privilege:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , the JPCERT published a thorough analysis of the Plead backdoor , which , according to Trend Micro , is used by the cyberespionage group BlackTech .' [/INST] [Recently:O, ,:O, the:O, JPCERT:B-SecTeam, published:O, a:O, thorough:O, analysis:O, of:O, the:O, Plead:B-Tool, backdoor:I-Tool, ,:O, which:O, ,:O, according:O, to:O, Trend:B-SecTeam, Micro:I-SecTeam, ,:O, is:O, used:O, by:O, the:O, cyberespionage:O, group:O, BlackTech:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the fact that the Changing Information Technology Inc. certificate was revoked on July 4 , 2017 , the BlackTech group is still using it to sign their malicious tools .' [/INST] [Despite:O, the:O, fact:O, that:O, the:O, Changing:B-Area, Information:I-Area, Technology:I-Area, Inc.:I-Area, certificate:O, was:O, revoked:O, on:O, July:B-Time, 4:I-Time, ,:O, 2017:B-Time, ,:O, the:O, BlackTech:O, group:O, is:O, still:O, using:O, it:O, to:O, sign:O, their:O, malicious:O, tools:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The BlackTech group is primarily focused on cyberespionage in Asia .' [/INST] [The:O, BlackTech:O, group:O, is:O, primarily:O, focused:O, on:O, cyberespionage:O, in:O, Asia: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 new activity described in this blogpost was detected by ESET in Taiwan , where the Plead malware has always been most actively deployed .' [/INST] [The:O, new:O, activity:B-OffAct, described:O, in:O, this:O, blogpost:O, was:O, detected:O, by:O, ESET:B-SecTeam, in:O, Taiwan:B-Area, ,:O, where:O, the:O, Plead:B-Tool, malware:I-Tool, has:O, always:O, been:O, most:O, actively:O, deployed:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 are targeting Windows platform and aiming at government institutions as well as big companies in Colombia .' [/INST] [Attackers:O, are:O, targeting:O, Windows:O, platform:O, and:O, aiming:O, at:O, government:B-Org, institutions:I-Org, as:O, well:O, as:O, big:O, companies:O, in:O, Colombia: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: 'Attackers like to use spear-fishing email with password protected RAR attachment to avoid being detected by the email gateway .' [/INST] [Attackers:O, like:O, to:O, use:O, spear-fishing:B-Way, email:I-Way, with:O, password:O, protected:O, RAR:B-Tool, attachment:O, to:O, avoid:O, being:O, detected:O, by:O, the:O, email:B-Way, gateway: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: 'The first sample being captured was in April 2018 and since that we observed a lot more related ones .' [/INST] [The:O, first:O, sample:O, being:O, captured:O, was:O, in:O, April:B-Time, 2018:I-Time, and:O, since:O, that:O, we:O, observed:O, a:O, lot:O, more:O, related:O, ones:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'After performing investigations on the classified victims , we find the attacker targets big companies and government agencies in Colombia .' [/INST] [After:O, performing:O, investigations:O, on:O, the:O, classified:O, victims:O, ,:O, we:O, find:O, the:O, attacker:O, targets:O, big:O, companies:O, and:O, government:B-Org, agencies:I-Org, in:O, Colombia: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: 'After monitoring and correlating the APT attack , 360 Threat Intelligence Center discovered multiple related emails to attack Colombian government agencies , financial institutions and large enterprises .' [/INST] [After:O, monitoring:O, and:O, correlating:O, the:O, APT:B-OffAct, attack:I-OffAct, ,:O, 360:B-SecTeam, Threat:I-SecTeam, Intelligence:I-SecTeam, Center:I-SecTeam, discovered:O, multiple:O, related:O, emails:B-Way, to:O, attack:O, Colombian:O, government:B-Org, agencies:I-Org, ,:O, financial:B-Org, institutions:I-Org, and:O, large:O, enterprises: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 oldest sample we've seen up to now is from November 2013 .' [/INST] [The:O, oldest:O, sample:O, we've:O, seen:O, up:O, to:O, now:O, is:O, from:O, November:B-Time, 2013: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: 'One of the top targets is the Japan Pension Service , but the list of targeted industries includes government and government agencies , local governments , public interest groups , universities , banks , financial services , energy and so on .' [/INST] [One:O, of:O, the:O, top:O, targets:O, is:O, the:O, Japan:B-Area, Pension:B-Org, Service:I-Org, ,:O, but:O, the:O, list:O, of:O, targeted:O, industries:O, includes:O, government:B-Idus, and:O, government:B-Idus, agencies:I-Idus, ,:O, local:B-Idus, governments:I-Idus, ,:O, public:B-Idus, interest:I-Idus, groups:I-Idus, ,:O, universities:B-Idus, ,:O, banks:B-Idus, ,:O, financial:B-Idus, services:I-Idus, ,:O, energy:B-Idus, and:O, so:O, on:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , the attack is different in two respects : unlike other APTs , the main focus of Blue Termite is to attack Japanese organizations ; and most of their C2s are located in Japan .' [/INST] [However:O, ,:O, the:O, attack:B-OffAct, is:O, different:O, in:O, two:O, respects:O, ::O, unlike:O, other:O, APTs:O, ,:O, the:O, main:O, focus:O, of:O, Blue:B-Tool, Termite:I-Tool, is:O, to:O, attack:O, Japanese:B-Area, organizations:O, ;:O, and:O, most:O, of:O, their:O, C2s:O, are:O, located: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: 'Originally , the main infection vector of Blue Termite was spear-phishing emails .' [/INST] [Originally:O, ,:O, the:O, main:O, infection:O, vector:O, of:O, Blue:B-Tool, Termite:I-Tool, was:O, spear-phishing:B-Way, emails: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: 'Kaspersky Lab has detected a new method of first infection that uses a drive-by-download with a flash exploit ( CVE-2015-5119 , the one leaked from The Hacking Team incident ) .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, has:O, detected:O, a:O, new:O, method:O, of:O, first:O, infection:O, that:O, uses:O, a:O, drive-by-download:O, with:O, a:O, flash:B-Exp, exploit:I-Exp, (:O, CVE-2015-5119:B-Exp, ,:O, the:O, one:O, leaked:O, from:O, The:O, Hacking:O, Team:O, incident: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: 'Kaspersky Lab also found some watering hole attacks , including one on a website belonging to a prominent member of the Japanese government .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, also:O, found:O, some:O, watering:B-OffAct, hole:I-OffAct, attacks:I-OffAct, ,:O, including:O, one:O, on:O, a:O, website:O, belonging:O, to:O, a:O, prominent:O, member:O, of:O, the:O, Japanese:B-Area, government:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In early July 2015 , however , Kaspersky Lab found a sample that creates a decryption key with Salt1 , Salt2 , and Salt3 .' [/INST] [In:O, early:O, July:B-Time, 2015:I-Time, ,:O, however:O, ,:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, found:O, a:O, sample:O, that:O, creates:O, a:O, decryption:O, key:O, with:O, Salt1:O, ,:O, Salt2:O, ,:O, and:O, Salt3:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'From early June , when the cyber-attack on the Japan Pension Service started to be reported widely , various Japanese organizations would have started to deploy protection measures .' [/INST] [From:O, early:O, June:B-Time, ,:O, when:O, the:O, cyber-attack:B-OffAct, on:O, the:O, Japan:B-Area, Pension:B-Org, Service:I-Org, started:O, to:O, be:O, reported:O, widely:O, ,:O, various:O, Japanese:B-Area, organizations:O, would:O, have:O, started:O, to:O, deploy:O, protection:O, measures:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 employs AES in addition to SID tricks , making it difficult to decrypt sensitive data .' [/INST] [It:O, employs:O, AES:B-Tool, in:O, addition:O, to:O, SID:B-Tool, tricks:O, ,:O, making:O, it:O, difficult:O, to:O, decrypt: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: 'In order to fight back against this cyber-espionage , Kaspersky Lab will continue its research .' [/INST] [In:O, order:O, to:O, fight:O, back:O, against:O, this:O, cyber-espionage:O, ,:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, will:O, continue:O, its:O, research:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Bookworm 's functional code is radically different from PlugX and has a rather unique modular architecture that warranted additional analysis by Unit 42 .' [/INST] [Bookworm:B-Tool, 's:O, functional:O, code:O, is:O, radically:O, different:O, from:O, PlugX:B-Tool, and:O, has:O, a:O, rather:O, unique:O, modular:O, architecture:O, that:O, warranted:O, additional:O, analysis:O, by:O, Unit:B-SecTeam, 42: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: 'Bookworm has little malicious functionality built-in , with its only core ability involving stealing keystrokes and clipboard contents .' [/INST] [Bookworm:B-Tool, has:O, little:O, malicious:O, functionality:O, built-in:O, ,:O, with:O, its:O, only:O, core:O, ability:O, involving:O, stealing:B-Purp, keystrokes:I-Purp, and:I-Purp, clipboard:I-Purp, contents: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: 'The Plead malware is a backdoor which , according to Trend Micro , is used by the BlackTech group in targeted attacks .' [/INST] [The:O, Plead:B-Tool, malware:I-Tool, is:O, a:O, backdoor:B-Tool, which:O, ,:O, according:O, to:O, Trend:B-SecTeam, Micro:I-SecTeam, ,:O, is:O, used:O, by:O, the:O, BlackTech:O, group:O, in:O, targeted:B-OffAct, attacks: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: 'So far , it appears threat actors have deployed the Bookworm Trojan primarily in attacks on targets in Thailand .' [/INST] [So:O, far:O, ,:O, it:O, appears:O, threat:O, actors:O, have:O, deployed:O, the:O, Bookworm:B-Tool, Trojan:I-Tool, primarily:O, in:O, attacks:B-OffAct, on:O, targets:O, in:O, Thailand: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 threat actors use a commercial installation tool called Smart Installer Maker to encapsulate and execute a self-extracting RAR archive and in some cases a decoy slideshow or Flash installation application .' [/INST] [The:O, threat:O, actors:O, use:O, a:O, commercial:O, installation:O, tool:O, called:O, Smart:B-Tool, Installer:I-Tool, Maker:I-Tool, to:O, encapsulate:O, and:O, execute:O, a:O, self-extracting:B-Tool, RAR:I-Tool, archive:O, and:O, in:O, some:O, cases:O, a:O, decoy:B-Tool, slideshow:I-Tool, or:O, Flash:B-Tool, installation:I-Tool, application: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 self-extracting RAR writes a legitimate executable , an actor-created DLL called Loader.dll and a file named readme.txt to the filesystem and then executes the legitimate executable .' [/INST] [The:O, self-extracting:B-Tool, RAR:I-Tool, writes:O, a:O, legitimate:O, executable:O, ,:O, an:O, actor-created:O, DLL:O, called:O, Loader.dll:B-SamFile, and:O, a:O, file:O, named:O, readme.txt:B-SamFile, to:O, the:O, filesystem:O, and:O, then:O, executes:O, the:O, legitimate:O, executable:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 attacks .' [/INST] [targeted:B-OffAct, attacks: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: 'Using XREFs during static analysis is a common technique to quickly find where functions of interest are called .' [/INST] [Using:O, XREFs:B-Tool, during:O, static:O, analysis:O, is:O, a:O, common:O, technique:O, to:O, quickly:O, find:B-Features, where:I-Features, functions:I-Features, of:I-Features, interest:I-Features, are:O, called:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 developers designed Bookworm to be a modular Trojan not limited to just the initial architecture of the Trojan , as Bookworm can also load additional modules provided by the C2 server .' [/INST] [The:O, developers:O, designed:O, Bookworm:B-Tool, to:O, be:O, a:O, modular:B-Tool, Trojan:I-Tool, not:O, limited:O, to:O, just:O, the:O, initial:O, architecture:O, of:O, the:O, Trojan:O, ,:O, as:O, Bookworm:B-Tool, can:O, also:O, load:O, additional:O, modules:O, provided:O, by:O, the:O, C2:O, server:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Although the developers of Bookworm have included only keylogging functionality in Bookworm as a core ability , as suggested in Table 1 , several of the embedded DLLs provide Leader with cryptographic and hashing functions , while others support Leader 's ability to communicate with its C2 server .' [/INST] [Although:O, the:O, developers:O, of:O, Bookworm:B-Tool, have:O, included:O, only:O, keylogging:O, functionality:O, in:O, Bookworm:B-Tool, as:O, a:O, core:O, ability:O, ,:O, as:O, suggested:O, in:O, Table:O, 1:O, ,:O, several:O, of:O, the:O, embedded:O, DLLs:O, provide:B-Features, Leader:I-Features, with:O, cryptographic:O, and:O, hashing:O, functions:O, ,:O, while:O, others:O, support:O, Leader:B-Tool, 's:O, ability:O, to:O, communicate:B-Features, with:I-Features, its:I-Features, C2:I-Features, server: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: 'While we did not discuss the surrounding attacks using Bookworm in detail , we have observed threat actors deploying Bookworm primarily in attacks on targets in Thailand .' [/INST] [While:O, we:O, did:O, not:O, discuss:O, the:O, surrounding:B-OffAct, attacks:I-OffAct, using:O, Bookworm:B-Tool, in:O, detail:O, ,:O, we:O, have:O, observed:O, threat:O, actors:O, deploying:O, Bookworm:B-Tool, primarily:O, in:O, attacks:B-OffAct, on:O, targets:O, in:O, Thailand: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: 'Also , Bookworm uses a combination of encryption and compression algorithms to obfuscate the traffic between the system and C2 server .' [/INST] [Also:O, ,:O, Bookworm:B-Tool, uses:O, a:O, combination:O, of:O, encryption:O, and:O, compression:O, algorithms:O, to:O, obfuscate:B-Purp, the:I-Purp, traffic:I-Purp, between:O, the:O, system:O, and:O, C2:O, server:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 developers of Bookworm have gone to great lengths to create a modular framework that is very flexible through its ability to run additional modules directly from its C2 server .' [/INST] [The:O, developers:O, of:O, Bookworm:B-Tool, have:O, gone:O, to:O, great:O, lengths:O, to:O, create:O, a:O, modular:O, framework:O, that:O, is:O, very:O, flexible:O, through:O, its:O, ability:O, to:O, run:O, additional:O, modules:O, directly:O, from:O, its:O, C2:O, server:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Unit 42 recently published a blog on a newly identified Trojan called Bookworm , which discussed the architecture and capabilities of the malware and alluded to Thailand being the focus of the threat actors' campaigns .' [/INST] [Unit:B-SecTeam, 42:I-SecTeam, recently:O, published:O, a:O, blog:O, on:O, a:O, newly:O, identified:O, Trojan:O, called:O, Bookworm:B-Tool, ,:O, which:O, discussed:O, the:O, architecture:O, and:O, capabilities:O, of:O, the:O, malware:O, and:O, alluded:O, to:O, Thailand:B-Area, being:O, the:O, focus:O, of:O, the:O, threat:O, actors':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: 'Leader is Bookworm 's main module and controls all of the activities of the Trojan , but relies on the additional DLLs to provide specific functionality .' [/INST] [Leader:B-Tool, is:O, Bookworm:B-Tool, 's:O, main:O, module:O, and:O, controls:O, all:O, of:O, the:O, activities:B-OffAct, of:O, the:O, Trojan:O, ,:O, but:O, relies:O, on:O, the:O, additional:O, DLLs:B-SamFile, to:O, provide:O, specific:O, functionality:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 developers of Bookworm use these modules in a rather unique way , as the other embedded DLLs provide API functions for Leader to carry out its tasks .' [/INST] [The:O, developers:O, of:O, Bookworm:B-Tool, use:O, these:O, modules:O, in:O, a:O, rather:O, unique:O, way:O, ,:O, as:O, the:O, other:O, embedded:O, DLLs:O, provide:O, API:O, functions:O, for:O, Leader:B-Tool, to:O, carry:O, out:O, its:O, tasks:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Unit 42 does not have detailed targeting information for all known Bookworm samples , but we are aware of attempted attacks on at least two branches of government in Thailand .' [/INST] [Unit:B-SecTeam, 42:I-SecTeam, does:O, not:O, have:O, detailed:O, targeting:O, information:O, for:O, all:O, known:O, Bookworm:B-Tool, samples:I-Tool, ,:O, but:O, we:O, are:O, aware:O, of:O, attempted:O, attacks:B-OffAct, on:O, at:O, least:O, two:O, branches:O, of:O, government:B-Idus, in:O, Thailand:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 speculate that other attacks delivering Bookworm were also targeting organizations in Thailand based on the contents of the associated decoys documents , as well as several of the dynamic DNS domain names used to host C2 servers that contain the words , Thai , or , Thailand , .' [/INST] [We:O, speculate:O, that:O, other:O, attacks:B-OffAct, delivering:O, Bookworm:B-Tool, were:O, also:O, targeting:O, organizations:O, in:O, Thailand:B-Area, based:O, on:O, the:O, contents:O, of:O, the:O, associated:O, decoys:B-SamFile, documents:I-SamFile, ,:O, as:O, well:O, as:O, several:O, of:O, the:O, dynamic:B-Tool, DNS:I-Tool, domain:I-Tool, names:O, used:O, to:O, host:O, C2:O, servers:O, that:O, contain:O, the:O, words:O, ,:O, Thai:B-Area, ,:O, or:O, ,:O, Thailand:B-Area, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 believe that it is likely threat actors will continue development Bookworm , and will continue to use it for the foreseeable future .' [/INST] [We:O, believe:O, that:O, it:O, is:O, likely:O, threat:O, actors:O, will:O, continue:O, development:O, Bookworm:B-Tool, ,:O, and:O, will:O, continue:O, to:O, use:O, it:O, for:O, the:O, foreseeable:O, future:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Threat actors have delivered Bookworm as a payload in attacks on targets in Thailand .' [/INST] [Threat:O, actors:O, have:O, delivered:O, Bookworm:B-Tool, as:O, a:O, payload:O, in:O, attacks:B-OffAct, on:O, targets:O, in:O, Thailand: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: 'Analysis of compromised systems seen communicating with Bookworm C2 servers also confirms our speculation on targeting with a majority of systems existing within Thailand .' [/INST] [Analysis:O, of:O, compromised:O, systems:O, seen:O, communicating:O, with:O, Bookworm:B-Tool, C2:I-Tool, servers:I-Tool, also:O, confirms:O, our:O, speculation:O, on:O, targeting:O, with:O, a:O, majority:O, of:O, systems:O, existing:O, within:O, Thailand: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: 'As mentioned in our previous blog on Bookworm , the Trojan sends a static date string to the C2 server that we referred to as a campaign code .' [/INST] [As:O, mentioned:O, in:O, our:O, previous:O, blog:O, on:O, Bookworm:B-Tool, ,:O, the:O, Trojan:B-Tool, sends:B-Features, a:I-Features, static:I-Features, date:I-Features, string:I-Features, to:O, the:O, C2:O, server:O, that:O, we:O, referred:O, to:O, as:O, a:O, campaign: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: 'We believed that the actors would use this date code to track their attack campaigns ; however , after continued analysis of the malware , we think these static dates could also be a build identifier for the Trojan .' [/INST] [We:O, believed:O, that:O, the:O, actors:O, would:O, use:O, this:O, date:B-Tool, code:I-Tool, to:O, track:O, their:O, attack:B-OffAct, campaigns:I-OffAct, ;:O, however:O, ,:O, after:O, continued:O, analysis:O, of:O, the:O, malware:O, ,:O, we:O, think:O, these:O, static:O, dates:O, could:O, also:O, be:O, a:O, build:B-Features, identifier:I-Features, for:O, the:O, Trojan:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Threat actors may use the date string hardcoded into each Bookworm sample as a build identifier .' [/INST] [Threat:O, actors:O, may:O, use:O, the:O, date:B-SamFile, string:I-SamFile, hardcoded:I-SamFile, into:O, each:O, Bookworm:B-Tool, sample:I-Tool, as:O, a:O, build:B-Features, identifier: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: 'A Trojan sending a build identifier to its C2 server is quite common , as it notifies the threat actors of the specific version of the Trojan in which they are interacting .' [/INST] [A:O, Trojan:O, sending:O, a:O, build:B-Features, identifier:I-Features, to:O, its:O, C2:O, server:O, is:O, quite:O, common:O, ,:O, as:O, it:O, notifies:B-Features, the:O, threat:O, actors:O, of:O, the:O, specific:O, version:O, of:O, the:O, Trojan:O, in:O, which:O, they:O, are:O, interacting:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 these changes without a new date string , we believe the date codes are used for campaign tracking rather than a Bookworm build identifier .' [/INST] [Due:O, to:O, these:O, changes:O, without:O, a:O, new:O, date:B-SamFile, string:I-SamFile, ,:O, we:O, believe:O, the:O, date:B-SamFile, codes:I-SamFile, are:O, used:O, for:O, campaign:B-Features, tracking:I-Features, rather:O, than:O, a:O, Bookworm:B-Tool, build:O, identifier:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 believe that Bookworm samples use the static date string as campaign codes , which we used to determine the approximate date of each attack that we did not have detailed targeting information .' [/INST] [We:O, believe:O, that:O, Bookworm:B-Tool, samples:I-Tool, use:B-Features, the:I-Features, static:I-Features, date:I-Features, string:I-Features, as:O, campaign:O, codes:O, ,:O, which:O, we:O, used:O, to:O, determine:O, the:O, approximate:O, date:O, of:O, each:O, attack:B-OffAct, that:O, we:O, did:O, not:O, have:O, detailed:O, targeting: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: 'Another decoy slideshow associated with the Bookworm attack campaign contains photos of an event called Bike for Dad 2015 .' [/INST] [Another:O, decoy:B-SamFile, slideshow:I-SamFile, associated:O, with:O, the:O, Bookworm:B-OffAct, attack:I-OffAct, campaign:I-OffAct, contains:O, photos:O, of:O, an:O, event:O, called:O, Bike:O, for:O, Dad:O, 2015: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: 'The campaign code , 20150920 , is associated with this decoy , which is a week prior to media articles announcing that the Crown Price of Thailand Maha Vajiralongkorn will lead the Bike for Dad 2015 event .' [/INST] [The:O, campaign:O, code:O, ,:O, 20150920:O, ,:O, is:O, associated:O, with:O, this:O, decoy:O, ,:O, which:O, is:O, a:O, week:O, prior:O, to:O, media:B-Idus, articles:O, announcing:O, that:O, the:O, Crown:O, Price:O, of:O, Thailand:O, Maha:O, Vajiralongkorn:O, will:O, lead:O, the:O, Bike:O, for:O, Dad:O, 2015:B-Time, 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: 'Chitpas is heavily involved with Thailand politics and was a core leader of the People's Committee for Absolute Democracy ( PCAD ) , which is an organization that staged anti-government campaigns in 2013 and 2014 .' [/INST] [Chitpas:O, is:O, heavily:O, involved:O, with:O, Thailand:O, politics:B-Idus, and:O, was:O, a:O, core:O, leader:O, of:O, the:O, People's:O, Committee:O, for:O, Absolute:O, Democracy:O, (:O, PCAD:O, ):O, ,:O, which:O, is:O, an:O, organization:O, that:O, staged:O, anti-government:B-OffAct, campaigns:I-OffAct, in:O, 2013:B-Time, and:O, 2014: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: 'The final remaining known decoy includes photos of Chitpas Tant Kridakon ( Figure 7 ) , who is known as heiress to the largest brewery in Thailand .' [/INST] [The:O, final:O, remaining:O, known:O, decoy:B-Tool, includes:O, photos:O, of:O, Chitpas:B-Tool, Tant:I-Tool, Kridakon:I-Tool, (:O, Figure:O, 7:O, ):O, ,:O, who:O, is:O, known:O, as:O, heiress:O, to:O, the:O, largest:O, brewery:O, in:O, Thailand:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 images were associated with the Bookworm campaign code , 20150905 , .' [/INST] [These:O, images:O, were:O, associated:O, with:O, the:O, Bookworm:B-OffAct, campaign:I-OffAct, code:O, ,:O, 20150905: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: 'Unit 42 analyzed the systems communicating with the Bookworm C2 domains and found that a majority of the IP addresses existed within autonomous systems ( ASN ) located in Thailand .' [/INST] [Unit:B-SecTeam, 42:I-SecTeam, analyzed:O, the:O, systems:O, communicating:O, with:O, the:O, Bookworm:B-Tool, C2:O, domains:O, and:O, found:O, that:O, a:O, majority:O, of:O, the:O, IP:O, addresses:O, existed:O, within:O, autonomous:O, systems:O, (:O, ASN:O, ):O, located:O, in:O, Thailand: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 pie chart in Figure 8 shows that the vast majority ( 73% ) of the hosts are geographically located in Thailand , which matches the known targeting of this threat group .' [/INST] [The:O, pie:O, chart:O, in:O, Figure:O, 8:O, shows:O, that:O, the:O, vast:O, majority:O, (:O, 73%:O, ):O, of:O, the:O, hosts:O, are:O, geographically:O, located:O, in:O, Thailand:O, ,:O, which:O, matches:O, the:O, known:O, targeting:O, of:O, this:O, threat:O, group:O, .:O] </s> |
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