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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: 'RedDrip Team (formerly SkyEye Team) has been to OceanLotus to keep track of high strength , groupactivity , found it in the near future to Indochinese Peninsula countries since 2019 On April 1 , 2019 , RedDrip discovered a Vietnamese file name Hop dong sungroup.rar in the process of daily monitoring the attack activities of the OceanLotus .' [/INST] [RedDrip:O, Team:O, (formerly:O, SkyEye:O, Team):O, has:O, been:O, to:O, OceanLotus:B-HackOrg, to:O, keep:O, track:O, of:O, high:O, strength:O, ,:O, groupactivity:O, ,:O, found:O, it:O, in:O, the:O, near:O, future:O, to:O, Indochinese:O, Peninsula:O, countries:O, since:O, 2019:B-Time, On:O, April:B-Time, 1:I-Time, ,:O, 2019:O, ,:O, RedDrip:B-SecTeam, discovered:O, a:O, Vietnamese:O, file:O, name:O, Hop:O, dong:O, sungroup.rar:O, in:O, the:O, process:O, of:O, daily:O, monitoring:O, the:O, attack:O, activities:O, of:O, the:O, OceanLotus: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: 'COCCOC is a Vietnam was founded in 2013 .' [/INST] [COCCOC:B-HackOrg, is:O, a:O, Vietnam:O, was:O, founded:O, in:O, 2013:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In fact , according to reports of various security vendors , OceanLotus also attacked several countries , including Cambodia , Thailand , Laos , even some victims in Vietnam , like opinion leaders , media , real estate companies , foreign enterprises and banks .' [/INST] [In:O, fact:O, ,:O, according:O, to:O, reports:O, of:O, various:O, security:O, vendors:O, ,:O, OceanLotus:B-HackOrg, also:O, attacked:O, several:O, countries:O, ,:O, including:O, Cambodia:B-Area, ,:O, Thailand:B-Area, ,:O, Laos:B-Area, ,:O, even:O, some:O, victims:O, in:O, Vietnam:B-Area, ,:O, like:O, opinion:O, leaders:O, ,:O, media:B-Idus, ,:O, real:B-Idus, estate:I-Idus, companies:I-Idus, ,:O, foreign:B-Idus, enterprises:I-Idus, and:O, banks: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: 'Unlike the 2016 variants of Ratsnif that stored all packets to a PCAP file .' [/INST] [Unlike:O, the:O, 2016:B-Time, variants:O, of:O, Ratsnif:B-HackOrg, that:O, stored:O, all:O, packets:O, to:O, a:O, PCAP: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: 'these threat actors targeted a number of government agencies Threat actors targeted a number of government agencies in East Asia .' [/INST] [these:O, threat:O, actors:O, targeted:O, a:O, number:O, of:O, government:O, agencies:O, Threat:B-HackOrg, actors:I-HackOrg, targeted:O, a:O, number:O, of:O, government:B-Idus, agencies:B-Idus, in:O, East:O, Asia: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 relied on Microsoft Equation Editor exploit CVE-2018-0798 to deliver a custom malware that Proofpoint researchers have dubbed Cotx RAT .' [/INST] [Attackers:B-HackOrg, relied:O, on:O, Microsoft:O, Equation:O, Editor:O, exploit:O, CVE-2018-0798:B-Exp, to:O, deliver:O, a:O, custom:O, malware:O, that:O, Proofpoint:O, researchers:O, have:O, dubbed:O, Cotx:O, RAT: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: 'Maudi Surveillance Operation which was previously reported in 2013 .' [/INST] [Maudi:B-HackOrg, Surveillance:O, Operation:O, which:O, was:O, previously:O, reported:O, in:O, 2013:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'specifically CVE-2018-0798 , before downloading subsequent payloads .' [/INST] [specifically:O, CVE-2018-0798:B-Exp, ,:O, before:O, downloading:O, subsequent: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: 'The dropped PE file has the distinctive file name 8.t” .' [/INST] [The:O, dropped:O, PE:B-Tool, file:O, has:O, the:O, distinctive:O, file:O, name:O, 8.t”:B-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: 'The last process is utilized as part of the loading process for Cotx RAT and involves the legitimate Symantec binary noted above .' [/INST] [The:O, last:O, process:O, is:O, utilized:O, as:O, part:O, of:O, the:O, loading:O, process:O, for:O, Cotx:B-HackOrg, RAT:I-HackOrg, and:O, involves:O, the:O, legitimate:O, Symantec:B-SecTeam, binary:O, noted: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: 'These conflicts have even resulted in Haftar leading an attack on the capital city in April .' [/INST] [These:O, conflicts:O, have:O, even:O, resulted:O, in:O, Haftar:B-HackOrg, leading:O, an:O, attack:O, on:O, the:O, capital:O, city:O, in:O, April: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 attackers have targeted a large number of organizations globally since early 2017 .' [/INST] [The:O, attackers:B-HackOrg, have:O, targeted:O, a:O, large:O, number:O, of:O, organizations:O, globally:O, since:O, early: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: 'Attackers were initially discovered while investigating a phishing attack that targeted political figures in the MENA region .' [/INST] [Attackers:B-HackOrg, were:O, initially:O, discovered:O, while:O, investigating:O, a:O, phishing:B-Way, attack:I-Way, that:O, targeted:O, political:B-Idus, figures:O, in:O, the:O, MENA:B-Area, region: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: 'Group's targets include high-profile entities such as parliaments , senates , top state offices and officials , political science scholars , military and intelligence agencies , ministries , media outlets , research centers , election commissions , Olympic organizations , large trading companies , and other unknown entities .' [/INST] [Group's:B-HackOrg, targets:O, include:O, high-profile:O, entities:O, such:O, as:O, parliaments:B-Org, ,:O, senates:B-Org, ,:O, top:B-Org, state:I-Org, offices:I-Org, and:O, officials:B-Org, ,:O, political:B-Org, science:I-Org, scholars:I-Org, ,:O, military:B-Idus, and:O, intelligence:B-Org, agencies:I-Org, ,:O, ministries:B-Idus, ,:O, media:B-Idus, outlets:I-Idus, ,:O, research:B-Idus, centers:I-Idus, ,:O, election:B-Org, commissions:I-Org, ,:O, Olympic:B-Org, organizations:I-Org, ,:O, large:O, trading:B-Org, companies:I-Org, ,:O, and:O, other:O, unknown:B-Org, entities: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: 'Cisco Talos recently published a blogpost describing targeted attacks in the Middle East region which we believe may be connected .' [/INST] [Cisco:B-SecTeam, Talos:I-SecTeam, recently:O, published:O, a:O, blogpost:O, describing:O, targeted:O, attacks:O, in:O, the:O, Middle:B-Area, East:I-Area, region:O, which:O, we:O, believe:O, may:O, be:O, connected: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: 'Operation Parliament appears to be another symptom of escalating tensions in the Middle East region .' [/INST] [Operation:B-HackOrg, Parliament:I-HackOrg, appears:O, to:O, be:O, another:O, symptom:O, of:O, escalating:O, tensions:O, in:O, the:O, Middle:B-Area, East:I-Area, region: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 have taken great care to stay under the radar , imitating another attack group in the region .' [/INST] [The:O, attackers:B-HackOrg, have:O, taken:O, great:O, care:O, to:O, stay:O, under:O, the:O, radar:O, ,:O, imitating:B-Way, another:O, attack:O, group:O, in:O, the:O, region: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: 'With deception and false flags increasingly being employed by threat actors , attribution is a hard and complicated task that requires solid evidence , especially in complex regions such as the Middle East .' [/INST] [With:O, deception:O, and:O, false:O, flags:O, increasingly:O, being:O, employed:O, by:O, threat:B-HackOrg, actors:I-HackOrg, ,:O, attribution:O, is:O, a:O, hard:O, and:O, complicated:O, task:O, that:O, requires:O, solid:O, evidence:O, ,:O, especially:O, in:O, complex:O, regions:O, such:O, as:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The malware was first seen packed with VMProtect; when unpacked the sample didn’t show any similarities with previously known malware .' [/INST] [The:O, malware:B-SamFile, was:O, first:O, seen:O, packed:O, with:O, VMProtect;:B-Features, when:O, unpacked:O, the:O, sample:O, didn’t:O, show:O, any:O, similarities:O, with:O, previously:O, known:O, malware:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The malware starts communicating with the C&C server by sending basic information about the infected machine .' [/INST] [The:O, malware:B-SamFile, starts:O, communicating:B-Features, with:I-Features, the:I-Features, C&C:I-Features, server:O, by:O, sending:O, basic:O, information:O, about:O, the:O, infected: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: 'The malware basically provides a remote CMD/PowerShell terminal for the attackers , enabling them to execute scripts/commands and receive the results via HTTP requests .' [/INST] [The:O, malware:B-SamFile, basically:O, provides:B-Features, a:O, remote:O, CMD/PowerShell:B-Tool, terminal:O, for:O, the:O, attackers:B-HackOrg, ,:O, enabling:O, them:O, to:O, execute:B-Purp, scripts/commands:I-Purp, and:O, receive:O, the:O, results:O, via:O, HTTP:O, requests: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: 'What lied beneath this facade was a well-engineered campaign of phishing attacks designed to steal credentials and spy on the activity of dozens of journalists , human rights defenders , trade unions and labour rights activists , many of whom are seemingly involved in the issue of migrants’ rights in Qatar and Nepal .' [/INST] [What:O, lied:O, beneath:O, this:O, facade:O, was:O, a:O, well-engineered:O, campaign:O, of:O, phishing:O, attacks:O, designed:O, to:O, steal:B-Purp, credentials:I-Purp, and:O, spy:O, on:O, the:O, activity:O, of:O, dozens:O, of:O, journalists:O, ,:O, human:B-Purp, rights:I-Purp, defenders:I-Purp, ,:O, trade:B-Purp, unions:I-Purp, and:O, labour:O, rights:O, activists:O, ,:O, many:O, of:O, whom:O, are:O, seemingly:O, involved:O, in:O, the:O, issue:O, of:O, migrants’:O, rights:O, in:O, Qatar:O, and:O, Nepal: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 refer to this campaign and the associated actor as Operation Kingphish Malik” , in one of its written forms in Arabic , translates to King” .' [/INST] [We:O, refer:O, to:O, this:O, campaign:O, and:O, the:O, associated:O, actor:O, as:O, Operation:B-HackOrg, Kingphish:I-HackOrg, Malik”:O, ,:O, in:O, one:O, of:O, its:O, written:O, forms:O, in:O, Arabic:B-Area, ,:O, translates:O, to:O, King”: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 is worth noting that in December 2016 , Amnesty International published an investigation into another social engineering campaign perpetrated by a seemingly fake human rights organization known as Voiceless Victims , which targeted international human rights and labour rights organizations campaigning on migrant workers’ rights in Qatar .' [/INST] [It:O, is:O, worth:O, noting:O, that:O, in:O, December:B-Time, 2016:I-Time, ,:O, Amnesty:O, International:O, published:O, an:O, investigation:O, into:O, another:O, social:O, engineering:O, campaign:O, perpetrated:O, by:O, a:O, seemingly:O, fake:O, human:O, rights:O, organization:O, known:O, as:O, Voiceless:B-HackOrg, Victims:O, ,:O, which:O, targeted:O, international:O, human:O, rights:O, and:O, labour:O, rights:O, organizations:O, campaigning:O, on:O, migrant:O, workers’:O, rights:O, in:O, Qatar: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 appears that the attackers may have impersonated the identity of a real young woman and stole her pictures to construct the fake profile , along with a professional biography also stolen from yet another person .' [/INST] [It:O, appears:O, that:O, the:O, attackers:B-HackOrg, may:O, have:O, impersonated:O, the:O, identity:O, of:O, a:O, real:O, young:O, woman:O, and:O, stole:B-Purp, her:I-Purp, pictures:I-Purp, to:O, construct:B-Purp, the:I-Purp, fake:I-Purp, profile:I-Purp, ,:O, along:O, with:O, a:O, professional:O, biography:O, also:O, stolen:O, from:O, yet:O, another:O, person: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 course of this email correspondence , the attacker — Safeena” — then sent what appeared to be invitations to access several documents on Google Drive .' [/INST] [In:O, the:O, course:O, of:O, this:O, email:O, correspondence:O, ,:O, the:O, attacker:B-HackOrg, —:O, Safeena”:O, —:O, then:O, sent:O, what:O, appeared:O, to:O, be:O, invitations:B-Way, to:O, access:O, several:O, documents:O, on:O, Google:O, Drive: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 were meticulous in making their phishing page as credible as possible .' [/INST] [The:O, attackers:B-HackOrg, were:O, meticulous:O, in:O, making:O, their:O, phishing:B-Way, page:I-Way, as:O, credible:O, as: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: 'Among the targets of this campaign is the International Trade Union Confederation (ITUC) .' [/INST] [Among:O, the:O, targets:O, of:O, this:O, campaign:B-OffAct, is:O, the:O, International:O, Trade:B-Org, Union:I-Org, Confederation:I-Org, (ITUC):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 in the attacks against ITUC and in other occasions , Operation Kingphish approached selected targets over social media , prominently Facebook , and engaged in chat conversations with them on and off , sometimes over a period of several months .' [/INST] [Both:O, in:O, the:O, attacks:O, against:O, ITUC:B-Org, and:O, in:O, other:O, occasions:O, ,:O, Operation:B-HackOrg, Kingphish:I-HackOrg, approached:O, selected:O, targets:O, over:O, social:B-Tool, media:I-Tool, ,:O, prominently:B-Tool, Facebook:I-Tool, ,:O, and:O, engaged:O, in:O, chat:O, conversations:O, with:O, them:O, on:O, and:O, off:O, ,:O, sometimes:O, over:O, a:O, period:O, of:O, several:O, months: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 time the document purported to be about the involvement of the Emir of Qatar in funding ISIS , which was seemingly copied from a website critical of Qatar .' [/INST] [This:O, time:O, the:O, document:B-SamFile, purported:O, to:O, be:O, about:O, the:O, involvement:O, of:O, the:O, Emir:B-Area, of:O, Qatar:B-Area, in:O, funding:O, ISIS:B-Area, ,:O, which:O, was:O, seemingly:O, copied:O, from:O, a:O, website:O, critical:O, of:O, Qatar: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 there is a clear underlying Qatar migrant workers theme in Operation Sheep , it is also hypothetically possible that these attacks could have been perpetrated by a malicious actor affiliated to a different government with an interest in damaging the reputation of the State of Qatar .' [/INST] [While:O, there:O, is:O, a:O, clear:O, underlying:O, Qatar:B-Area, migrant:O, workers:O, theme:O, in:O, Operation:B-HackOrg, Sheep:I-HackOrg, ,:O, it:O, is:O, also:O, hypothetically:O, possible:O, that:O, these:O, attacks:O, could:O, have:O, been:O, perpetrated:O, by:O, a:O, malicious:O, actor:O, affiliated:O, to:O, a:O, different:O, government:O, with:O, an:O, interest:O, in:O, damaging:O, the:O, reputation:O, of:O, the:O, State:O, of:O, Qatar: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: 'Dubbed ‘Operation Sheep’ , this massive data stealing campaign is the first known campaign seen in the wild to exploit the Man-in-the-Disk vulnerability revealed by Check Point Research earlier last year .' [/INST] [Dubbed:O, ‘Operation:B-HackOrg, Sheep’:I-HackOrg, ,:O, this:O, massive:B-Purp, data:I-Purp, stealing:I-Purp, campaign:O, is:O, the:O, first:O, known:O, campaign:O, seen:O, in:O, the:O, wild:O, to:O, exploit:O, the:O, Man-in-the-Disk:B-Exp, vulnerability:O, revealed:O, by:O, Check:O, Point:O, Research:O, earlier:O, last:O, year: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 SDK , named SWAnalytics is integrated into seemingly innocent Android applications published on major 3rd party Chinese app stores such as Tencent MyApp , Wandoujia , Huawei App Store , and Xiaomi App Store .' [/INST] [The:O, SDK:B-Tool, ,:O, named:O, SWAnalytics:B-SamFile, is:O, integrated:O, into:O, seemingly:O, innocent:O, Android:O, applications:O, published:B-Way, on:I-Way, major:O, 3rd:O, party:O, Chinese:O, app:O, stores:O, such:O, as:O, Tencent:B-Idus, MyApp:I-Idus, ,:O, Wandoujia:B-Idus, ,:O, Huawei:B-Idus, App:I-Idus, Store:I-Idus, ,:O, and:O, Xiaomi:B-Idus, App:I-Idus, Store: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: 'After app installation , whenever SWAnalytics senses victims opening up infected applications or rebooting their phones , it silently uploads their entire contacts list to Hangzhou Shun Wang Technologies controlled servers .' [/INST] [After:O, app:O, installation:O, ,:O, whenever:O, SWAnalytics:B-SamFile, senses:O, victims:O, opening:O, up:O, infected:O, applications:O, or:O, rebooting:O, their:O, phones:O, ,:O, it:O, silently:O, uploads:B-Features, their:O, entire:O, contacts:O, list:O, to:O, Hangzhou:O, Shun:O, Wang:O, Technologies:O, controlled:O, servers: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 theory , Shun Wang Technologies could have collected a third of China’s population names and contact numbers if not more .' [/INST] [In:O, theory:O, ,:O, Shun:B-HackOrg, Wang:I-HackOrg, Technologies:O, could:O, have:O, collected:B-Purp, a:O, third:O, of:O, China’s:B-Area, population:O, names:O, and:O, contact:O, numbers:O, if:O, not:O, more: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: 'With no clear declaration of usage from Shun Wang , nor proper regulatory supervision , such data could circulate into underground markets for further exploit , ranging from rogue marketing , targeted telephone scams or even friend referral program abuse during November’s Single’s Day and December’s Asian online shopping fest .' [/INST] [With:O, no:O, clear:O, declaration:O, of:O, usage:O, from:O, Shun:B-HackOrg, Wang:I-HackOrg, ,:O, nor:O, proper:O, regulatory:O, supervision:O, ,:O, such:O, data:O, could:O, circulate:O, into:O, underground:O, markets:O, for:O, further:O, exploit:O, ,:O, ranging:O, from:O, rogue:O, marketing:O, ,:O, targeted:O, telephone:B-Purp, scams:I-Purp, or:O, even:O, friend:O, referral:O, program:B-Purp, abuse:I-Purp, during:O, November’s:O, Single’s:O, Day:O, and:O, December’s:O, Asian:O, online:O, shopping:O, fest: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 paper will cover the discovery of this campaign , dubbed ‘Operation Sheep’ , and an analysis of SWAnalytics .' [/INST] [This:O, paper:O, will:O, cover:O, the:O, discovery:O, of:O, this:O, campaign:O, ,:O, dubbed:O, ‘Operation:B-HackOrg, Sheep’:I-HackOrg, ,:O, and:O, an:O, analysis:O, of:O, SWAnalytics:B-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: 'In mid-September , an app named ‘Network Speed Master’ stood out on our radar with its rather unusual behavior patterns .' [/INST] [In:O, mid-September:O, ,:O, an:O, app:O, named:O, ‘Network:B-HackOrg, Speed:I-HackOrg, Master’:I-HackOrg, stood:O, out:O, on:O, our:O, radar:O, with:O, its:O, rather:O, unusual:O, behavior:O, patterns: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 module monitors a wide range of device activities including application installation / remove / update , phone restart and battery charge .' [/INST] [This:O, module:B-SamFile, monitors:O, a:O, wide:O, range:O, of:O, device:O, activities:O, including:O, application:B-Features, installation:I-Features, /:O, remove:B-Features, /:O, update:B-Features, ,:O, phone:B-Features, restart:I-Features, and:O, battery:B-Features, charge: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: 'It turns out that contacts data isn’t the only unusual data SWAnalytics is interested in .' [/INST] [It:O, turns:O, out:O, that:O, contacts:B-Features, data:I-Features, isn’t:O, the:O, only:O, unusual:O, data:O, SWAnalytics:B-SamFile, is:O, interested:O, in: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: 'With default settings , SWAnalytics will scan through an Android device’s external storage , looking for directory tencent/MobileQQ/WebViewCheck” .' [/INST] [With:O, default:O, settings:O, ,:O, SWAnalytics:B-SamFile, will:O, scan:B-Features, through:O, an:O, Android:O, device’s:O, external:O, storage:O, ,:O, looking:O, for:O, directory:O, tencent/MobileQQ/WebViewCheck”: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 our first malicious sample encounter back in mid-September until now , we have observed 12 infected applications , the majority of which are in the system utility category .' [/INST] [From:O, our:O, first:O, malicious:B-SamFile, sample:I-SamFile, encounter:O, back:O, in:O, mid-September:B-Time, until:O, now:O, ,:O, we:O, have:O, observed:O, 12:O, infected:O, applications:O, ,:O, the:O, majority:O, of:O, which:O, are:O, in:O, the:O, system:O, utility:O, category: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: 'By listing sub-folders , SWAnalytics is able to infer QQ accounts which have never been used on the device .' [/INST] [By:O, listing:B-Features, sub-folders:I-Features, ,:O, SWAnalytics:B-SamFile, is:O, able:O, to:O, infer:B-Features, QQ:I-Features, accounts:I-Features, which:O, have:O, never:O, been:O, used:O, on:O, the: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: 'Operation Sheep is the first campaign we have observed in the wild that abuses similar concept since our MitD publication .' [/INST] [Operation:B-HackOrg, Sheep:I-HackOrg, is:O, the:O, first:O, campaign:O, we:O, have:O, observed:O, in:O, the:O, wild:O, that:O, abuses:B-Way, similar:I-Way, concept:I-Way, since:O, our:O, MitD: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: 'To make this data harvesting operation flexible , SWAnalytics equips the ability to receive and process configuration files from a remote Command-and-Control .' [/INST] [To:O, make:O, this:O, data:O, harvesting:O, operation:O, flexible:O, ,:O, SWAnalytics:B-SamFile, equips:O, the:O, ability:O, to:O, receive:B-Features, and:O, process:B-Features, configuration:I-Features, files:I-Features, from:O, a:O, remote:B-Features, Command-and-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: 'Whenever users reboot their device or open up Network Speed Master , SWAnalytics will fetch the latest configuration file from http[:]//mbl[.]shunwang[.]com/cfg/config[.]json” .' [/INST] [Whenever:O, users:O, reboot:O, their:O, device:O, or:O, open:O, up:O, Network:B-Way, Speed:I-Way, Master:I-Way, ,:O, SWAnalytics:B-SamFile, will:O, fetch:O, the:O, latest:O, configuration:O, file:O, from:O, http[:]//mbl[.]shunwang[.]com/cfg/config[.]json”: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 understand SWAnalytics’ impact , we turned to public download volume data available on Chandashi , one of the app store optimization vendors specialized in Chinese mobile application markets .' [/INST] [In:O, order:O, to:O, understand:O, SWAnalytics’:B-SamFile, impact:O, ,:O, we:O, turned:O, to:O, public:O, download:O, volume:O, data:O, available:O, on:O, Chandashi:O, ,:O, one:O, of:O, the:O, app:O, store:O, optimization:O, vendors:O, specialized:O, in:O, Chinese:B-Area, mobile:O, application:O, markets: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 points span from September 2018 to January 2019 where we observed over 17 million downloads in just five months .' [/INST] [Data:O, points:O, span:O, from:O, September:B-Time, 2018:I-Time, to:O, January:B-Time, 2019:I-Time, where:O, we:B-SecTeam, observed:O, over:O, 17:O, million:O, downloads:O, in:O, just:O, five:O, months: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 China alone , we have seen underground market sheep shavers” ported SMS rogue marketing strategy to spread Alipay Red Packet referral URL links .' [/INST] [In:O, China:B-Area, alone:O, ,:O, we:O, have:O, seen:O, underground:O, market:O, sheep:B-HackOrg, shavers”:I-HackOrg, ported:O, SMS:O, rogue:O, marketing:O, strategy:O, to:O, spread:O, Alipay:O, Red:O, Packet:O, referral:O, URL:O, links: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 Operation Sheep’s case , Shun Wang likely harvests end user contact lists without application developer acknowledgement .' [/INST] [In:O, Operation:O, Sheep’s:O, case:O, ,:O, Shun:B-HackOrg, Wang:I-HackOrg, likely:O, harvests:B-Purp, end:O, user:O, contact:O, lists:O, without:O, application:O, developer:O, acknowledgement: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 Cheetah Mobile’s follow-up investigation , fraudulent behaviors came from two 3rd party SDKs Batmobi , Duapps integrated inside Cheetah SDK .' [/INST] [According:O, to:O, Cheetah:O, Mobile’s:O, follow-up:O, investigation:O, ,:O, fraudulent:O, behaviors:O, came:O, from:O, two:O, 3rd:O, party:O, SDKs:O, Batmobi:B-SamFile, ,:O, Duapps:B-SamFile, integrated:O, inside:O, Cheetah:B-SamFile, SDK: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: 'It is likely a new campaign or actor started using Panda Banker since in addition to the previously unseen Japanese targeting , Arbor has not seen any indicator of compromise (IOC) overlaps with previous Panda Banker campaigns .' [/INST] [It:O, is:O, likely:O, a:O, new:O, campaign:O, or:O, actor:B-HackOrg, started:O, using:O, Panda:B-Tool, Banker:I-Tool, since:O, in:O, addition:O, to:O, the:O, previously:O, unseen:O, Japanese:B-Area, targeting:O, ,:O, Arbor:B-SecTeam, has:O, not:O, seen:O, any:O, indicator:O, of:O, compromise:O, (IOC):O, overlaps:O, with:O, previous:O, Panda:B-SamFile, Banker:I-SamFile, campaigns: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: 'Webinjects targeting Japan , a country we haven’t seen targeted by Panda Banker before .' [/INST] [Webinjects:O, targeting:O, Japan:B-Area, ,:O, a:O, country:O, we:O, haven’t:O, seen:O, targeted:O, by:O, Panda:B-SamFile, Banker:I-SamFile, before: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: 'Japan is no stranger to banking malware .' [/INST] [Japan:B-Area, is:O, no:O, stranger:O, to:O, banking:B-SamFile, malware:B-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: 'Based on recent reports , the country has been plagued by attacks using the Ursnif and Urlzone banking malware .' [/INST] [Based:O, on:O, recent:O, reports:O, ,:O, the:O, country:B-Area, has:O, been:O, plagued:O, by:O, attacks:O, using:O, the:O, Ursnif:B-SamFile, and:O, Urlzone:B-SamFile, banking: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: 'This post was our first analysis of the first Panda Banker campaign that we’ve seen to target financial institutions in Japan .' [/INST] [This:O, post:O, was:O, our:O, first:O, analysis:O, of:O, the:O, first:O, Panda:B-SamFile, Banker:I-SamFile, campaign:O, that:O, we’ve:O, seen:O, to:O, target:O, financial:B-Idus, institutions:I-Idus, 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: 'Operation Pawn Storm is an active economic and political cyber-espionage operation that targets a wide range of entities , like the military , governments , defense industries , and the media .' [/INST] [Operation:B-HackOrg, Pawn:I-HackOrg, Storm:I-HackOrg, is:O, an:O, active:O, economic:B-Idus, and:O, political:B-Idus, cyber-espionage:O, operation:O, that:O, targets:O, a:O, wide:O, range:O, of:O, entities:O, ,:O, like:O, the:O, military:B-Idus, ,:O, governments:B-Idus, ,:O, defense:B-Idus, industries:I-Idus, ,:O, and:O, the: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: 'We believe the iOS malware gets installed on already compromised systems , and it is very similar to next stage SEDNIT malware we have found for Microsoft Windows’ systems .' [/INST] [We:B-SecTeam, believe:O, the:O, iOS:O, malware:O, gets:O, installed:O, on:O, already:O, compromised:O, systems:O, ,:O, and:O, it:O, is:O, very:O, similar:O, to:O, next:O, stage:O, SEDNIT:B-SamFile, malware:O, we:O, have:O, found:O, for:O, Microsoft:O, Windows’:O, systems:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We found two malicious iOS applications in Operation Pawn Storm .' [/INST] [We:B-SecTeam, found:O, two:O, malicious:O, iOS:O, applications:O, in:O, Operation:O, Pawn:B-OffAct, Storm: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: 'One is called XAgent detected as IOS_XAGENT.A and the other one uses the name of a legitimate iOS game , MadCap detected as IOS_ XAGENT.B .' [/INST] [One:O, is:O, called:O, XAgent:B-SamFile, detected:O, as:O, IOS_XAGENT.A:B-SamFile, and:O, the:O, other:O, one:O, uses:O, the:O, name:O, of:O, a:O, legitimate:O, iOS:O, game:O, ,:O, MadCap:B-SamFile, detected:O, as:O, IOS_:O, XAGENT.B:B-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: 'The obvious goal of the SEDNIT-related spyware is to steal personal data , record audio , make screenshots , and send them to a remote command-and-control (C&C) server .' [/INST] [The:O, obvious:O, goal:O, of:O, the:O, SEDNIT-related:B-HackOrg, spyware:O, is:O, to:O, steal:O, personal:B-Org, data:I-Org, ,:O, record:O, audio:O, ,:O, make:O, screenshots:O, ,:O, and:O, send:O, them:O, to:O, a:O, remote:O, command-and-control:O, (C&C):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: 'Madcap” is similar to the XAgent malware , but the former is focused on recording audio .' [/INST] [Madcap”:B-SamFile, is:O, similar:O, to:O, the:O, XAgent:B-SamFile, malware:O, ,:O, but:O, the:O, former:O, is:O, focused:O, on:O, recording:O, audio: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 learn more about this campaign , you may refer to our report , Operation Pawn Storm Using Decoys to Evade Detection .' [/INST] [To:O, learn:O, more:O, about:O, this:O, campaign:O, ,:O, you:O, may:O, refer:O, to:O, our:O, report:O, ,:O, Operation:O, Pawn:B-OffAct, Storm:I-OffAct, Using:O, Decoys:O, to:O, Evade:B-HackOrg, Detection: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: 'Additionally , we discovered a new DNS hijacking technique that we assess with moderate confidence is connected to the actors behind Sea Turtle .' [/INST] [Additionally:O, ,:O, we:O, discovered:O, a:O, new:O, DNS:O, hijacking:O, technique:O, that:O, we:O, assess:O, with:O, moderate:O, confidence:O, is:O, connected:O, to:O, the:O, actors:B-HackOrg, behind:O, Sea:B-OffAct, Turtle: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: 'Talos now has moderate confidence that the threat actors behind Sea Turtle have been using another DNS hijacking technique .' [/INST] [Talos:B-SecTeam, now:O, has:O, moderate:O, confidence:O, that:O, the:O, threat:O, actors:O, behind:O, Sea:B-OffAct, Turtle:I-OffAct, have:O, been:O, using:O, another:O, DNS:O, hijacking:O, technique: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 technique was also observed against a government organizations in the Middle East and North African region .' [/INST] [This:O, technique:B-OffAct, was:O, also:O, observed:O, against:O, a:O, government:O, organizations:O, in:O, the:O, Middle:B-Area, East:I-Area, and:O, North:B-Area, African:I-Area, region: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: 'Cisco telemetry confirmed that the actors behind Sea Turtle maintained access to the ICS-Forth network from an operational command and control (C2) node .' [/INST] [Cisco:B-SecTeam, telemetry:O, confirmed:O, that:O, the:O, actors:O, behind:O, Sea:B-OffAct, Turtle:I-OffAct, maintained:O, access:O, to:O, the:O, ICS-Forth:O, network:O, from:O, an:O, operational:O, command:O, and:O, control:B-Tool, (C2):I-Tool, node: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 telemetry indicates that the actors maintained access in the ICS-Forth network through at least April 24 , five days after the statement was publicly released .' [/INST] [Our:O, telemetry:O, indicates:O, that:O, the:O, actors:B-HackOrg, maintained:O, access:O, in:O, the:O, ICS-Forth:O, network:O, through:O, at:O, least:O, April:B-Time, 24:I-Time, ,:O, five:O, days:O, after:O, the:O, statement:O, was:O, publicly:O, released: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 full-blown spying framework consists of two packages named ‘Tokyo’ and ‘Yokohama’ .' [/INST] [This:O, full-blown:O, spying:O, framework:O, consists:O, of:O, two:O, packages:O, named:O, ‘Tokyo’:B-SamFile, and:O, ‘Yokohama’:B-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: 'Just to highlight its capabilities , TajMahal is able to steal data from a CD burnt by a victim as well as from the printer queue .' [/INST] [Just:O, to:O, highlight:O, its:O, capabilities:O, ,:O, TajMahal:B-SamFile, is:O, able:O, to:O, steal:B-Features, data:I-Features, from:O, a:O, CD:O, burnt:O, by:O, a:O, victim:O, as:O, well:O, as:O, from:O, the:O, printer:O, queue: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 confirmed date when TajMahal samples were seen on a victim’s machine is August 2014 .' [/INST] [The:O, first:O, confirmed:O, date:O, when:O, TajMahal:B-SamFile, samples:O, were:O, seen:O, on:O, a:O, victim’s:O, machine:O, is:O, August:B-Time, 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: 'More details about TajMahal are available to customers of the Kaspersky Intelligence Reporting service (contact intelreports@kaspersky.com) .' [/INST] [More:O, details:O, about:O, TajMahal:B-SamFile, are:O, available:O, to:O, customers:O, of:O, the:O, Kaspersky:B-SecTeam, Intelligence:O, Reporting:O, service:O, (contact:O, intelreports@kaspersky.com):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 dropper first appeared in mid-July , suggesting that this APT activity is potentially ongoing , with Turla actively targeting G20 participants and/or those with interest in the G20 , including member nations , journalists , and policymakers .' [/INST] [The:O, dropper:B-OffAct, first:O, appeared:O, in:O, mid-July:B-Time, ,:O, suggesting:O, that:O, this:O, APT:O, activity:O, is:O, potentially:O, ongoing:O, ,:O, with:O, Turla:B-HackOrg, actively:O, targeting:O, G20:B-Idus, participants:O, and/or:O, those:O, with:O, interest:O, in:O, the:O, G20:O, ,:O, including:O, member:O, nations:O, ,:O, journalists:O, ,:O, and:O, policymakers: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: 'Turla is a well-documented , long operating APT group that is widely believed to be a Russian state-sponsored organization .' [/INST] [Turla:B-HackOrg, is:O, a:O, well-documented:O, ,:O, long:O, operating:O, APT:O, group:O, that:O, is:O, widely:O, believed:O, to:O, be:O, a:O, Russian:B-Area, state-sponsored:O, organization: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: 'Turla is perhaps most notoriously suspected as responsible for the breach of the United States Central Command in 2008 .' [/INST] [Turla:B-HackOrg, is:O, perhaps:O, most:O, notoriously:O, suspected:O, as:O, responsible:O, for:O, the:O, breach:O, of:O, the:O, United:O, States:O, Central:O, Command:O, in:O, 2008: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: 'More recently Turla was accused of breaching RUAG , a Swiss technology company , in a public report published by GovCERT.ch .' [/INST] [More:O, recently:O, Turla:B-HackOrg, was:O, accused:O, of:O, breaching:O, RUAG:B-Org, ,:O, a:O, Swiss:O, technology:O, company:O, ,:O, in:O, a:O, public:O, report:O, published:O, by:O, GovCERT.ch:B-SecTeam, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The delivery of KopiLuwak in this instance is currently unknown as the MSIL dropper has only been observed by Proofpoint researchers on a public malware repository .' [/INST] [The:O, delivery:O, of:O, KopiLuwak:O, in:O, this:O, instance:O, is:O, currently:O, unknown:O, as:O, the:O, MSIL:B-SamFile, dropper:I-SamFile, has:O, only:O, been:O, observed:O, by:O, Proofpoint:B-SecTeam, researchers:O, on:O, a:O, public:O, malware:O, repository: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: 'Assuming this variant of KopiLuwak has been observed in the wild , there are a number of ways it may have been delivered including some of Turla’s previous attack methods such as spear phishing or via a watering hole .' [/INST] [Assuming:O, this:O, variant:O, of:O, KopiLuwak:O, has:O, been:O, observed:O, in:O, the:O, wild:O, ,:O, there:O, are:O, a:O, number:O, of:O, ways:O, it:O, may:O, have:O, been:O, delivered:O, including:O, some:O, of:O, Turla’s:B-HackOrg, previous:O, attack:O, methods:O, such:O, as:O, spear:B-Way, phishing:I-Way, or:O, via:O, a:O, watering:B-Way, hole: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: 'This could include diplomats , experts in the areas of interest related to the Digital Economy Task Force , or possibly even journalists .' [/INST] [This:O, could:O, include:O, diplomats:B-Org, ,:O, experts:O, in:O, the:O, areas:O, of:O, interest:O, related:O, to:O, the:O, Digital:O, Economy:O, Task:O, Force:O, ,:O, or:O, possibly:O, even:O, journalists:B-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Turla's goal could include diplomats , experts in the areas of interest related to the Digital Economy Task Force , or possibly even journalists .' [/INST] [Turla's:B-HackOrg, goal:O, could:O, include:O, diplomats:O, ,:O, experts:O, in:O, the:O, areas:O, of:O, interest:O, related:O, to:O, the:O, Digital:B-Idus, Economy:I-Idus, Task:O, Force:O, ,:O, or:O, possibly:O, even:O, journalists: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 earliest step in any possible attack(s) involving this variant of KopiLuwak of which Proofpoint researchers are currently aware begin with the MSIL dropper .' [/INST] [The:O, earliest:O, step:O, in:O, any:O, possible:O, attack(s):O, involving:O, this:O, variant:O, of:O, KopiLuwak:B-SamFile, of:O, which:O, Proofpoint:O, researchers:O, are:O, currently:O, aware:O, begin:O, with:O, the:O, MSIL:B-SamFile, dropper: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: 'The basic chain of events upon execution of the MSIL dropper include dropping and executing both a PDF decoy and a Javascript (JS) dropper .' [/INST] [The:O, basic:O, chain:O, of:O, events:O, upon:O, execution:O, of:O, the:O, MSIL:B-SamFile, dropper:I-SamFile, include:O, dropping:O, and:O, executing:O, both:O, a:O, PDF:O, decoy:O, and:O, a:O, Javascript:B-SamFile, (JS):I-SamFile, dropper: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: 'As explained in further detail below , the JS dropper ultimately installs a JS decryptor onto an infected machine that will then finally decrypt and execute the actual KopiLuwak backdoor in memory only .' [/INST] [As:O, explained:O, in:O, further:O, detail:O, below:O, ,:O, the:O, JS:B-SamFile, dropper:I-SamFile, ultimately:O, installs:O, a:O, JS:B-SamFile, decryptor:I-SamFile, onto:O, an:O, infected:O, machine:O, that:O, will:O, then:O, finally:O, decrypt:O, and:O, execute:O, the:O, actual:O, KopiLuwak:B-SamFile, backdoor:O, in:O, memory:O, only: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 Proofpoint has not yet observed this attack in the wild it is likely that there is an additional component that leads to the execution of the MSIL payload .' [/INST] [As:O, Proofpoint:B-SecTeam, has:O, not:O, yet:O, observed:O, this:O, attack:O, in:O, the:O, wild:O, it:O, is:O, likely:O, that:O, there:O, is:O, an:O, additional:O, component:O, that:O, leads:O, to:O, the:O, execution:O, of:O, the:O, MSIL:B-SamFile, payload: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: 'The newer variant of KopiLuwak is now capable of exfiltrating files to the C&C as well as downloading files and saving them to the infected machine .' [/INST] [The:O, newer:O, variant:O, of:O, KopiLuwak:B-SamFile, is:O, now:O, capable:O, of:O, exfiltrating:B-Features, files:I-Features, to:O, the:O, C&C:O, as:O, well:O, as:O, downloading:B-Features, files:I-Features, and:O, saving:O, them:O, to:O, the:O, infected: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: 'Despite the added capabilities , we still agree with Kaspersky that this backdoor is likely used as an initial reconnaissance tool and would probably be used as a staging point to deploy one of Turla’s more fully featured implants .' [/INST] [Despite:O, the:O, added:O, capabilities:O, ,:O, we:O, still:O, agree:O, with:O, Kaspersky:B-SecTeam, that:O, this:O, backdoor:O, is:O, likely:O, used:O, as:O, an:O, initial:O, reconnaissance:O, tool:O, and:O, would:O, probably:O, be:O, used:O, as:O, a:O, staging:O, point:O, to:O, deploy:O, one:O, of:O, Turla’s:B-HackOrg, more:O, fully:O, featured:O, implants: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: 'Turla is a complex cyberattack platform focused predominantly on diplomatic and government-related targets , particularly in the Middle East , Central and Far East Asia , Europe , North and South America and former Soviet bloc nations .' [/INST] [Turla:B-HackOrg, is:O, a:O, complex:O, cyberattack:O, platform:O, focused:O, predominantly:O, on:O, diplomatic:O, and:O, government-related:O, targets:O, ,:O, particularly:O, in:O, the:O, Middle:B-Area, East:I-Area, ,:O, Central:B-Area, and:O, Far:B-Area, East:I-Area, Asia:I-Area, ,:O, Europe:B-Area, ,:O, North:B-Area, and:I-Area, South:I-Area, America:I-Area, and:O, former:B-Area, Soviet:I-Area, bloc:O, nations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We didn’t choose to name it after a vegetable; the .NET malware developers named it Topinambour themselves .' [/INST] [We:O, didn’t:O, choose:O, to:O, name:O, it:O, after:O, a:O, vegetable;:O, the:O, .NET:B-SamFile, malware:I-SamFile, developers:O, named:O, it:O, Topinambour:B-SamFile, themselves: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 role of the .NET module is to deliver the known KopiLuwak JavaScript Trojan .' [/INST] [The:O, role:O, of:O, the:O, .NET:B-SamFile, module:I-SamFile, is:O, to:O, deliver:O, the:O, known:O, KopiLuwak:B-SamFile, JavaScript:I-SamFile, 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: 'Moreover , Turla now also has a heavily obfuscated PowerShell Trojan that is similar to KopiLuwak .' [/INST] [Moreover:O, ,:O, Turla:B-HackOrg, now:O, also:O, has:O, a:O, heavily:O, obfuscated:O, PowerShell:B-Way, Trojan:I-Way, that:O, is:O, similar:O, to:O, KopiLuwak: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: 'RocketMan!” (probably a reference to Donald Trump’s nickname for Kim Jong Un) and MiamiBeach” serve as the first beacon messages from the victim to the control server .' [/INST] [RocketMan!”:B-SamFile, (probably:O, a:O, reference:O, to:O, Donald:O, Trump’s:O, nickname:O, for:O, Kim:O, Jong:O, Un):O, and:O, MiamiBeach”:B-SamFile, serve:O, as:O, the:O, first:O, beacon:O, messages:O, from:O, the:O, victim:O, to:O, the:O, control: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: 'These could be tools to circumvent internet censorship , such as Softether VPN 4.12” and psiphon3” , or Microsoft Office activators” .' [/INST] [These:O, could:O, be:O, tools:O, to:O, circumvent:O, internet:O, censorship:O, ,:O, such:O, as:O, Softether:B-SamFile, VPN:I-SamFile, 4.12”:I-SamFile, and:O, psiphon3”:B-SamFile, ,:O, or:O, Microsoft:B-SamFile, Office:I-SamFile, activators”: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: 'These campaign-related VPSs are located in South Africa .' [/INST] [These:O, campaign-related:O, VPSs:B-HackOrg, are:O, located:O, in:O, South:B-Area, Africa: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 tool does all that a typical Trojan needs to accomplish: upload , download and execute files , fingerprint target systems .' [/INST] [The:O, tool:O, does:O, all:O, that:O, a:O, typical:O, Trojan:B-SamFile, needs:O, to:O, accomplish::O, upload:B-Features, ,:O, download:B-Features, and:O, execute:B-Features, files:I-Features, ,:O, fingerprint:B-Features, target:I-Features, systems: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: 'The PowerShell version of the Trojan also has the ability to get screenshots .' [/INST] [The:O, PowerShell:B-SamFile, version:O, of:O, the:O, Trojan:O, also:O, has:O, the:O, ability:O, to:O, get:B-Features, screenshots:B-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: 'The Trojan is quite similar to the .NET RocketMan Trojan and can handle the same commands; additionally , it includes the #screen” command to take a screenshot .' [/INST] [The:O, Trojan:B-SamFile, is:O, quite:O, similar:O, to:O, the:O, .NET:B-SamFile, RocketMan:I-SamFile, Trojan:I-SamFile, and:O, can:O, handle:O, the:O, same:O, commands;:O, additionally:O, ,:O, it:O, includes:O, the:O, #screen”:O, command:O, to:O, take:O, a:O, screenshot: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 usage of KopiLuwak , a well-known and exclusive artefact previously used by the Turla group , makes us attribute this campaign to this actor with high confidence .' [/INST] [The:O, usage:O, of:O, KopiLuwak:B-Tool, ,:O, a:O, well-known:O, and:O, exclusive:O, artefact:O, previously:O, used:O, by:O, the:O, Turla:B-HackOrg, group:O, ,:O, makes:O, us:O, attribute:O, this:O, campaign:O, to:O, this:O, actor:O, with:O, high:O, confidence: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: 'Winnti's mode of operation: to collect information on the organizational charts of companies , on cooperating departments , on the IT systems of individual business units , and on trade secrets , obviously .' [/INST] [Winnti's:B-HackOrg, mode:O, of:O, operation::O, to:O, collect:O, information:O, on:O, the:O, organizational:O, charts:B-Idus, of:I-Idus, companies:I-Idus, ,:O, on:O, cooperating:O, departments:O, ,:O, on:O, the:O, IT:O, systems:O, of:O, individual:B-Idus, business:I-Idus, units:I-Idus, ,:O, and:O, on:O, trade:O, secrets:O, ,:O, obviously: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: 'Hackers usually take precautions , which experts refer to as Opsec .' [/INST] [Hackers:B-HackOrg, usually:O, take:O, precautions:O, ,:O, which:O, experts:O, refer:O, to:O, as:O, Opsec:B-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 Winnti group’s Opsec was dismal to say the least .' [/INST] [The:O, Winnti:B-HackOrg, group’s:O, Opsec:B-Way, was:O, dismal:O, to:O, say:O, the:O, least:O, .:O] </s> |
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