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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: 'BlackEnergy is a highly dynamic threat actor and the current attacks in Ukraine indicate that destructive actions are on their main agenda , in addition to compromising industrial control installations and espionage activities .' [/INST] [BlackEnergy:B-HackOrg, is:O, a:O, highly:O, dynamic:O, threat:O, actor:O, and:O, the:O, current:O, attacks:O, in:O, Ukraine:B-Area, indicate:O, that:O, destructive:O, actions:O, are:O, on:O, their:O, main:O, agenda:O, ,:O, in:O, addition:O, to:O, compromising:O, industrial:O, control:O, installations:O, and:O, espionage:O, activities:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 will continue to monitor the BlackEnergy attacks in Ukraine and update our readers with more data when available .' [/INST] [Kaspersky:B-SecTeam, will:O, continue:O, to:O, monitor:O, the:O, BlackEnergy:B-HackOrg, attacks:O, in:O, Ukraine:B-Area, and:O, update:O, our:O, readers:O, with:O, more:O, data:O, when:O, available:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'From Buhtrap perpetrating cybercrime for financial gain , its toolset has been expanded with malware used to conduct espionage in Eastern Europe and Central Asia .' [/INST] [From:O, Buhtrap:B-HackOrg, perpetrating:O, cybercrime:O, for:O, financial:O, gain:O, ,:O, its:O, toolset:O, has:O, been:O, expanded:O, with:O, malware:O, used:O, to:O, conduct:O, espionage:O, in:O, Eastern:B-Area, Europe:I-Area, and:O, Central:B-Area, Asia:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Throughout our tracking , we've seen this group deploy its main backdoor as well as other tools against various victims , but June 2019 was the first time we saw the Buhtrap group use a zero-day exploit as part of a campaign .' [/INST] [Throughout:O, our:O, tracking:O, ,:O, we've:B-SecTeam, seen:O, this:B-HackOrg, group:I-HackOrg, deploy:O, its:O, main:O, backdoor:B-Way, as:O, well:O, as:O, other:O, tools:O, against:O, various:O, victims:O, ,:O, but:O, June:B-Time, 2019:I-Time, was:O, the:O, first:O, time:O, we:O, saw:O, the:O, Buhtrap:B-HackOrg, group:O, use:O, a:O, zero-day:B-OffAct, exploit:I-OffAct, as:O, part:O, of:O, a:O, campaign:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 that case , we observed Buhtrap using a local privilege escalation exploit , CVE-2019-1132 , against one of its victims .' [/INST] [In:O, that:O, case:O, ,:O, we:O, observed:O, Buhtrap:B-HackOrg, using:O, a:O, local:O, privilege:O, escalation:O, exploit:O, ,:O, CVE-2019-1132:B-Exp, ,:O, against:O, one:O, of:O, its:O, victims:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , as the shift in targets occurred before the source code leak , we assess with high confidence that the same people behind the first Buhtrap malware attacks against businesses and banks are also involved in targeting governmental institutions .' [/INST] [However:O, ,:O, as:O, the:O, shift:O, in:O, targets:O, occurred:O, before:O, the:O, source:O, code:O, leak:O, ,:O, we:O, assess:O, with:O, high:O, confidence:O, that:O, the:O, same:O, people:O, behind:O, the:O, first:O, Buhtrap:B-HackOrg, malware:O, attacks:O, against:O, businesses:B-Idus, and:O, banks:B-Idus, are:O, also:O, involved:O, in:O, targeting:O, governmental:B-Idus, institutions: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: 'When Buhtrap was targeting businesses , the decoy documents would typically be contracts or invoices .' [/INST] [When:O, Buhtrap:B-HackOrg, was:O, targeting:O, businesses:B-Idus, ,:O, the:O, decoy:O, documents:O, would:O, typically:O, be:O, contracts:O, or:O, invoices:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Buhtrap group is well known for its targeting of financial institutions and businesses in Russia .' [/INST] [The:O, Buhtrap:B-HackOrg, group:O, is:O, well:O, known:O, for:O, its:O, targeting:O, of:O, financial:B-Idus, institutions:I-Idus, and:O, businesses:O, in:O, Russia:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Figure 2 is a typical example of a generic invoice the group used in a campaign in 2014 .' [/INST] [Figure:O, 2:O, is:O, a:O, typical:O, example:O, of:O, a:O, generic:O, invoice:O, the:O, group:B-HackOrg, used:O, in:O, a:O, campaign:O, in: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: 'When the group's focus shifted to banks , the decoy documents were related to banking system regulations or advisories from FinCERT , an organization created by the Russian government to provide help and guidance to its financial institutions .' [/INST] [When:O, the:O, group's:B-HackOrg, focus:O, shifted:O, to:O, banks:O, ,:O, the:O, decoy:O, documents:O, were:O, related:O, to:O, banking:O, system:O, regulations:O, or:O, advisories:O, from:O, FinCERT:B-SecTeam, ,:O, an:O, organization:O, created:O, by:O, the:O, Russian:O, government:O, to:O, provide:O, help:O, and:O, guidance:O, to:O, its:O, financial:O, institutions:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 confirmed that this is a DarkHydrus Group's new attack targeting Middle East region .' [/INST] [We:O, confirmed:O, that:O, this:O, is:O, a:O, DarkHydrus:B-HackOrg, Group's:O, new:O, attack:O, targeting:O, Middle:B-Area, East:I-Area, region: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 July 2018 , Palo Alto disclosed DarkHydrus Group which showed its special interest to governments in Middle East .' [/INST] [In:O, July:O, 2018:O, ,:O, Palo:B-SecTeam, Alto:I-SecTeam, disclosed:O, DarkHydrus:B-HackOrg, Group:O, which:O, showed:O, its:O, special:O, interest:O, to:O, governments:B-Idus, in:O, Middle:O, East:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Prior to that report , we published detail analysis on malware exploiting CVE-2018-8414 vulnerability (remote code execution in SettingContent-ms) , which is believed a work of DarkHydrus .' [/INST] [Prior:O, to:O, that:O, report:O, ,:O, we:O, published:O, detail:O, analysis:O, on:O, malware:O, exploiting:O, CVE-2018-8414:B-Exp, vulnerability:O, (remote:O, code:O, execution:O, in:O, SettingContent-ms):O, ,:O, which:O, is:O, believed:O, a:O, work:O, of:O, DarkHydrus: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: 'However , the final payload is something that welivesecurity have never seen associated with Buhtrap .' [/INST] [However:O, ,:O, the:O, final:O, payload:O, is:O, something:O, that:O, welivesecurity:B-SecTeam, have:O, never:O, seen:O, associated:O, with:O, Buhtrap: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's coincident that both 'darkhydrus' APT group name and ‘Williams’ user name in PDB path found in this Twitter user .' [/INST] [It's:O, coincident:O, that:O, both:O, 'darkhydrus':B-HackOrg, APT:O, group:O, name:O, and:O, ‘Williams’:B-HackOrg, user:O, name:O, in:O, PDB:O, path:O, found:O, in:O, this:O, Twitter:B-Org, user: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: 'In recent APT incidents , Dark Hydruns tend to adopt Office VBA macro instead of Office 0day vulnerability in the consideration of cost reduction .' [/INST] [In:O, recent:O, APT:O, incidents:O, ,:O, Dark:B-HackOrg, Hydruns:I-HackOrg, tend:O, to:O, adopt:O, Office:B-Tool, VBA:I-Tool, macro:I-Tool, instead:O, of:O, Office:O, 0day:O, vulnerability:O, in:O, the:O, consideration:O, of:O, cost:O, reduction:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'ASERT uncovered a credential theft campaign we call LUCKY ELEPHANT where attackers masquerade as legitimate entities such as foreign government , telecommunications , and military .' [/INST] [ASERT:B-SecTeam, uncovered:O, a:O, credential:O, theft:O, campaign:O, we:O, call:O, LUCKY:B-HackOrg, ELEPHANT:I-HackOrg, where:O, attackers:B-OffAct, masquerade:I-OffAct, as:O, legitimate:O, entities:O, such:O, as:O, foreign:B-Idus, government:I-Idus, ,:O, telecommunications:B-Idus, ,:O, and:O, military: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: 'From at least February 2019 to present , the actors in the LUCKY ELEPHANT campaign copied webpages to mimic South Asian government websites as well as Microsoft Outlook 365 login pages and hosted them on their own doppelganger domains , presumably to trick victims into providing login credentials .' [/INST] [From:O, at:O, least:O, February:B-Time, 2019:I-Time, to:O, present:O, ,:O, the:O, actors:O, in:O, the:O, LUCKY:B-HackOrg, ELEPHANT:I-HackOrg, campaign:O, copied:O, webpages:O, to:O, mimic:O, South:B-Idus, Asian:I-Idus, government:I-Idus, websites:I-Idus, as:O, well:O, as:O, Microsoft:B-Org, Outlook:I-Org, 365:O, login:O, pages:O, and:O, hosted:B-OffAct, them:I-OffAct, on:O, their:O, own:O, doppelganger:O, domains:O, ,:O, presumably:O, to:O, trick:O, victims:O, into:O, providing:O, login:O, credentials:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'ASERT suspects that the Actors use phishing emails to lure victims to the doppelganger websites and entice users to enter their credentials .' [/INST] [ASERT:B-SecTeam, suspects:O, that:O, the:O, Actors:O, use:O, phishing:B-OffAct, emails:I-OffAct, to:O, lure:O, victims:O, to:O, the:O, doppelganger:O, websites:O, and:O, entice:O, users:O, to:O, enter:O, their:O, credentials:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'It is important to note that one domain , yahoomail[.]cf is only associated with this group from February 2019 onward .' [/INST] [It:O, is:O, important:O, to:O, note:O, that:O, one:O, domain:O, ,:O, yahoomail[.]cf:O, is:O, only:O, associated:O, with:O, this:O, group:B-HackOrg, from:O, February:B-Time, 2019:I-Time, onward:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 late 2018 , the domain was associated with a different APT group / campaign of Chinese origin .' [/INST] [In:O, late:O, 2018:O, ,:O, the:O, domain:O, was:O, associated:O, with:O, a:O, different:O, APT:B-HackOrg, group:I-HackOrg, /:O, campaign:O, of:O, Chinese:B-Area, origin: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: 'Based on our analysis into the activity , ASERT deems with moderate confidence that an Indian APT group is behind the LUCKY ELEPHANT campaign .' [/INST] [Based:O, on:O, our:O, analysis:O, into:O, the:O, activity:O, ,:O, ASERT:O, deems:O, with:O, moderate:O, confidence:O, that:O, an:O, Indian:B-HackOrg, APT:I-HackOrg, group:I-HackOrg, is:O, behind:O, the:O, LUCKY:B-OffAct, ELEPHANT:I-OffAct, campaign:I-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The targets are typical of known Indian APT activity and the infrastructure was previously used by an Indian APT group .' [/INST] [The:O, targets:O, are:O, typical:O, of:O, known:O, Indian:B-Area, APT:O, activity:O, and:O, the:O, infrastructure:O, was:O, previously:O, used:O, by:O, an:O, Indian:O, APT:B-HackOrg, group: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: 'DoNot Team has a history of heavily targeting Pakistan , in addition to other neighboring countries .' [/INST] [DoNot:B-HackOrg, Team:I-HackOrg, has:O, a:O, history:O, of:O, heavily:O, targeting:O, Pakistan:B-Area, ,:O, in:O, addition:O, to:O, other:O, neighboring:B-Area, countries: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 360 Intelligence Center observed four distinct campaigns against Pakistan since 2017 (link) , recently targeting Pakistani businessmen working in China .' [/INST] [The:O, 360:O, Intelligence:O, Center:O, observed:O, four:O, distinct:O, campaigns:O, against:O, Pakistan:B-Area, since:O, 2017:O, (link):O, ,:O, recently:O, targeting:O, Pakistani:B-Org, businessmen:I-Org, working:O, in:O, China:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'DoNot Team’s confirmed use of this IP dates back to September 2018 , with a six-month gap until it was used to host doppelganger domains for the LUCKY ELEPHANT campaign in early February .' [/INST] [DoNot:B-HackOrg, Team’s:O, confirmed:O, use:O, of:O, this:O, IP:O, dates:O, back:O, to:O, September:B-Time, 2018:I-Time, ,:O, with:O, a:O, six-month:O, gap:O, until:O, it:O, was:O, used:O, to:O, host:O, doppelganger:O, domains:O, for:O, the:O, LUCKY:O, ELEPHANT:O, campaign:O, in:O, early:O, February:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 IP addresses , 128.127.105.13 , was previously used by the DoNot Team (aka APT-C-35) , a suspected Indian APT group .' [/INST] [One:O, of:O, the:O, IP:O, addresses:O, ,:O, 128.127.105.13:O, ,:O, was:O, previously:O, used:O, by:O, the:O, DoNot:B-HackOrg, Team:I-HackOrg, (aka:O, APT-C-35):O, ,:O, a:O, suspected:O, Indian:B-Area, APT:O, group:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 actors behind LUCKY ELEPHANT recognize the effectiveness and use doppelganger webpages nearly identical to legitimate sites , enticing users to input their credentials .' [/INST] [The:O, actors:O, behind:O, LUCKY:B-HackOrg, ELEPHANT:I-HackOrg, recognize:O, the:O, effectiveness:O, and:O, use:O, doppelganger:B-Tool, webpages:I-Tool, nearly:O, identical:O, to:O, legitimate:O, sites:O, ,:O, enticing:O, users:O, to:O, input:O, their:O, credentials:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The heavier targeting in Pakistan adheres to historical targeting and the ongoing tension between the two countries , which has escalated since a terrorist attack in Kashmir on 14 February 2019 .' [/INST] [The:O, heavier:O, targeting:O, in:O, Pakistan:O, adheres:O, to:O, historical:O, targeting:O, and:O, the:O, ongoing:O, tension:O, between:O, the:O, two:O, countries:O, ,:O, which:O, has:O, escalated:O, since:O, a:O, terrorist:B-OffAct, attack:I-OffAct, in:O, Kashmir:O, on:O, 14:B-Time, February:I-Time, 2019:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The targeting of Pakistan , Bangladesh , Sri Lanka , Maldives , Myanmar , Nepal , and the Shanghai Cooperation Organization are all historical espionage targets by India .' [/INST] [The:O, targeting:O, of:O, Pakistan:B-Area, ,:O, Bangladesh:B-Area, ,:O, Sri:B-Area, Lanka:I-Area, ,:O, Maldives:B-Area, ,:O, Myanmar:B-Area, ,:O, Nepal:B-Area, ,:O, and:O, the:O, Shanghai:B-Idus, Cooperation:I-Idus, Organization:I-Idus, are:O, all:O, historical:O, espionage:B-HackOrg, targets:O, by:O, India: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: 'However , it is clear is that Donot are actively establishing infrastructure and are targeting governments in South Asia .' [/INST] [However:O, ,:O, it:O, is:O, clear:O, is:O, that:O, Donot:B-HackOrg, are:O, actively:O, establishing:O, infrastructure:O, and:O, are:O, targeting:O, governments:O, in:O, South:B-Area, Asia:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'First attack of this campaign took place in May 2018 .' [/INST] [First:B-OffAct, attack:I-OffAct, of:O, this:O, campaign:O, took:O, place:O, in:O, May:B-Time, 2018:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Arbor also published APT research on this group , and named it ‘Donot’ .' [/INST] [Arbor:B-SecTeam, also:O, published:O, APT:O, research:O, on:O, this:O, group:O, ,:O, and:O, named:O, it:O, ‘Donot’: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: 'Donot attacked government agencies , aiming for classified intelligence .' [/INST] [Donot:B-HackOrg, attacked:O, government:B-Idus, agencies:I-Idus, ,:O, aiming:O, for:O, classified:B-Purp, intelligence:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 this APT group coded as ‘APT-C-35’ in 2017 , who is mainly targeting Pakistan and other South Asian countries for cyber espionage .' [/INST] [We:O, identified:O, this:O, APT:O, group:O, coded:O, as:O, ‘APT-C-35’:B-HackOrg, in:O, 2017:O, ,:O, who:O, is:O, mainly:O, targeting:O, Pakistan:B-Area, and:O, other:O, South:B-Area, Asian:I-Area, countries:O, for:O, cyber:O, espionage:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'At least 4 attack campaigns against Pakistan have been observed by us since 2017 .' [/INST] [At:O, least:O, 4:O, attack:O, campaigns:O, against:O, Pakistan:O, have:O, been:O, observed:O, by:O, us:O, since:B-Time, 2017: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: 'Spear phishing emails with vulnerable Office documents or malicious macros are sent to victims .' [/INST] [Spear:B-Tool, phishing:I-Tool, emails:O, with:O, vulnerable:O, Office:O, documents:O, or:O, malicious:O, macros:O, are:O, sent:O, to:O, victims:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In the latest attack , Donot group is targeting Pakistani businessman working in China .' [/INST] [In:O, the:O, latest:O, attack:O, ,:O, Donot:B-HackOrg, group:I-HackOrg, is:O, targeting:O, Pakistani:B-Org, businessman:I-Org, working:O, in:O, China:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Two unique malware frameworks , EHDevel and yty , are developed by attackers .' [/INST] [Two:O, unique:O, malware:O, frameworks:O, ,:O, EHDevel:B-Tool, and:O, yty:B-Tool, ,:O, are:O, developed:O, by:O, attackers:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'wuaupdt.exe is a CMD backdoor , which can receive and execute CMD commands sent from C2 .' [/INST] [wuaupdt.exe:B-SamFile, is:O, a:O, CMD:B-Tool, backdoor:O, ,:O, which:O, can:O, receive:B-Features, and:O, execute:B-Features, CMD:I-Features, commands:I-Features, sent:O, from:O, C2:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Furthermore , it has similar code logic as previous ones wuaupdt.exe in this attack appears in previous Donot attack , and C2 addresses are same to previous ones .' [/INST] [Furthermore:O, ,:O, it:O, has:O, similar:O, code:O, logic:O, as:O, previous:O, ones:O, wuaupdt.exe:B-SamFile, in:O, this:O, attack:O, appears:O, in:O, previous:O, Donot:O, attack:O, ,:O, and:O, C2:O, addresses:O, are:O, same:O, to:O, previous: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: 'From the attack activity captured this time , it is obvious that Donot APT group is still keen on Pakistan as primary target of attack , and even expands scope of attack to include Pakistani staffs and institutions in China .' [/INST] [From:O, the:O, attack:O, activity:O, captured:O, this:O, time:O, ,:O, it:O, is:O, obvious:O, that:O, Donot:B-HackOrg, APT:I-HackOrg, group:I-HackOrg, is:O, still:O, keen:O, on:O, Pakistan:B-Area, as:O, primary:O, target:O, of:O, attack:O, ,:O, and:O, even:O, expands:O, scope:O, of:O, attack:O, to:O, include:O, Pakistani:O, staffs:O, and:O, institutions:O, in:O, China:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Buhtrap still make extensive use of NSIS installers as droppers and these are mainly delivered through malicious documents .' [/INST] [Buhtrap:B-HackOrg, still:O, make:O, extensive:O, use:O, of:O, NSIS:B-HackOrg, installers:I-HackOrg, as:O, droppers:O, and:O, these:O, are:O, mainly:O, delivered:O, through:O, malicious:O, documents:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'They first came to light in 2016 , when they managed to steal sensitive information from the US Democratic National Committee (DNC) .' [/INST] [They:O, first:O, came:O, to:O, light:O, in:O, 2016:B-Time, ,:O, when:O, they:O, managed:O, to:O, steal:O, sensitive:O, information:O, from:O, the:O, US:O, Democratic:O, National:O, Committee:O, (DNC):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: 'Earworm first came to light in 2016 , when they managed to steal sensitive information from the US Democratic National Committee (DNC) .' [/INST] [Earworm:B-HackOrg, first:O, came:O, to:O, light:O, in:O, 2016:B-Time, ,:O, when:O, they:O, managed:O, to:O, steal:O, sensitive:O, information:O, from:O, the:O, US:O, Democratic:O, National:O, Committee:O, (DNC):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: 'They were also behind an attack on the World Anti-Doping Agency (WADA) , in which they leaked confidential information about several drug tests .' [/INST] [They:B-HackOrg, were:O, also:O, behind:O, an:O, attack:O, on:O, the:O, World:O, Anti-Doping:O, Agency:O, (WADA):B-Idus, ,:O, in:O, which:O, they:O, leaked:O, confidential:O, information:O, about:O, several:O, drug:O, tests:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'SPLM , GAMEFISH , and Zebrocy delivery all maintain their own clusters , but frequently overlap later .' [/INST] [SPLM:B-HackOrg, ,:O, GAMEFISH:B-HackOrg, ,:O, and:O, Zebrocy:B-HackOrg, delivery:O, all:O, maintain:O, their:O, own:O, clusters:O, ,:O, but:O, frequently:O, overlap:O, later:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 previous post on Sofacy's 2017 activity stepped away from the previously covered headline buzz presenting their association with previously known political hacks and interest in Europe and the US , and examines their under-reported ongoing activity in middle east , central asia , and now a shift in targeting further east , including China , along with an overlap surprise .' [/INST] [Our:O, previous:O, post:O, on:O, Sofacy's:B-HackOrg, 2017:O, activity:O, stepped:O, away:O, from:O, the:O, previously:O, covered:O, headline:O, buzz:O, presenting:O, their:O, association:O, with:O, previously:O, known:O, political:O, hacks:O, and:O, interest:O, in:O, Europe:B-Area, and:O, the:O, US:B-Area, ,:O, and:O, examines:O, their:O, under-reported:O, ongoing:O, activity:O, in:O, middle:B-Area, east:I-Area, ,:O, central:B-Area, asia:I-Area, ,:O, and:O, now:O, a:O, shift:O, in:O, targeting:O, further:O, east:O, ,:O, including:O, China:B-Area, ,:O, along:O, with:O, an:O, overlap:O, surprise:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 larger , 300kb+ SPLM backdoors deployed in 2016 and 2017 are not observed any longer at targets in 2018 .' [/INST] [The:O, larger:O, ,:O, 300kb+:O, SPLM:B-HackOrg, backdoors:O, deployed:O, in:O, 2016:B-Time, and:I-Time, 2017:I-Time, are:O, not:O, observed:O, any:O, longer:O, at:O, targets:O, in:O, 2018:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 previous , removed , report from another vendor claimed non-specific information about the groups' interest in Chinese universities , but that report has been removed – most likely detections were related to students’ and researchers’ scanning known collected samples and any incidents” remain unconfirmed and unknown .' [/INST] [A:O, previous:O, ,:O, removed:O, ,:O, report:O, from:O, another:O, vendor:O, claimed:O, non-specific:O, information:O, about:O, the:O, groups':B-HackOrg, interest:O, in:O, Chinese:B-Org, universities:I-Org, ,:O, but:O, that:O, report:O, has:O, been:O, removed:O, –:O, most:O, likely:O, detections:O, were:O, related:O, to:O, students’:O, and:O, researchers’:O, scanning:O, known:O, collected:O, samples:O, and:O, any:O, incidents”:O, remain:O, unconfirmed:O, and:O, unknown:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Either way , the group's consistent activity throughout central and eastern asia seems to be poorly represented in the public discussion .' [/INST] [Either:O, way:O, ,:O, the:O, group's:B-HackOrg, consistent:O, activity:O, throughout:O, central:B-Area, and:I-Area, eastern:I-Area, asia:I-Area, seems:O, to:O, be:O, poorly:O, represented:O, in:O, the:O, public:O, discussion:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 actors behind this campaign we call LUCKY ELEPHANT use doppelganger webpages to mimic legitimate entities such as foreign governments , telecommunications , and military .' [/INST] [The:O, actors:O, behind:O, this:O, campaign:O, we:O, call:O, LUCKY:B-HackOrg, ELEPHANT:I-HackOrg, use:O, doppelganger:B-Tool, webpages:I-Tool, to:O, mimic:O, legitimate:O, entities:O, such:O, as:O, foreign:B-Idus, governments:I-Idus, ,:O, telecommunications:B-Idus, ,:O, and:O, military: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: 'Currently , Sofacy targets large air-defense related commercial organizations in China with SPLM , and moves Zebrocy focus across Armenia , Turkey , Kazahkstan , Tajikistan , Afghanistan , Mongolia , China , and Japan .' [/INST] [Currently:O, ,:O, Sofacy:O, targets:O, large:O, air-defense:B-OffAct, related:O, commercial:O, organizations:O, in:O, China:B-Area, with:O, SPLM:O, ,:O, and:O, moves:O, Zebrocy:O, focus:O, across:O, Armenia:B-Area, ,:O, Turkey:B-Area, ,:O, Kazahkstan:B-Area, ,:O, Tajikistan:B-Area, ,:O, Afghanistan:B-Area, ,:O, Mongolia:B-Area, ,:O, China:B-Area, ,:O, and: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: 'Either way , Sofacy's consistent activity throughout central and eastern asia seems to be poorly represented in the public discussion .' [/INST] [Either:O, way:O, ,:O, Sofacy's:B-HackOrg, consistent:O, activity:O, throughout:O, central:B-Area, and:I-Area, eastern:I-Area, asia:I-Area, seems:O, to:O, be:O, poorly:O, represented:O, in:O, the:O, public:O, discussion:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 this new alert , Hidden Cobra the U.S government’s code name for Lazarus has been conducting FASTCash attacks stealing money from Automated Teller Machines (ATMs) from banks in Asia and Africa since at least 2016 .' [/INST] [According:O, to:O, this:O, new:O, alert:O, ,:O, Hidden:B-HackOrg, Cobra:I-HackOrg, the:O, U.S:O, government’s:O, code:O, name:O, for:O, Lazarus:O, has:O, been:O, conducting:O, FASTCash:B-OffAct, attacks:O, stealing:O, money:O, from:O, Automated:O, Teller:O, Machines:O, (ATMs):O, from:O, banks:B-Idus, in:O, Asia:B-Area, and:O, Africa:B-Area, since:O, at:O, least:O, 2016:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Lazarus is a very active attack group involved in both cyber crime and espionage .' [/INST] [Lazarus:B-HackOrg, is:O, a:O, very:O, active:O, attack:O, group:O, involved:O, in:O, both:O, cyber:B-Purp, crime:I-Purp, and:O, espionage:B-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 group was initially known for its espionage operations and a number of high-profile disruptive attacks , including the 2014 attack on Sony Pictures .' [/INST] [The:O, group:B-HackOrg, was:O, initially:O, known:O, for:O, its:O, espionage:O, operations:O, and:O, a:O, number:O, of:O, high-profile:O, disruptive:O, attacks:O, ,:O, including:O, the:O, 2014:B-OffAct, attack:I-OffAct, on:O, Sony:O, Pictures:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 US-CERTs report , Symantec's research uncovered the key component used in Lazarus's recent wave of financial attacks .' [/INST] [Following:O, US-CERTs:O, report:O, ,:O, Symantec's:O, research:O, uncovered:O, the:O, key:O, component:O, used:O, in:O, Lazarus's:B-HackOrg, recent:O, wave:O, of:O, financial:B-Idus, attacks:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , Lazarus has also become involved in financially motivated attacks , including an US$81 million dollar theft from the Bangladesh Central Bank and the WannaCry ransomware .' [/INST] [More:O, recently:O, ,:O, Lazarus:B-HackOrg, has:O, also:O, become:O, involved:O, in:O, financially:O, motivated:O, attacks:O, ,:O, including:O, an:O, US$81:O, million:O, dollar:O, theft:O, from:O, the:O, Bangladesh:B-Idus, Central:I-Idus, Bank:I-Idus, and:O, the:O, WannaCry:B-Tool, ransomware:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Other open source and semi-legitimate pen-testing tools like nbtscan and powercat are being used for mapping available resources and lateral movement as well .' [/INST] [Other:O, open:O, source:O, and:O, semi-legitimate:O, pen-testing:O, tools:O, like:O, nbtscan:B-SamFile, and:O, powercat:B-SamFile, are:O, being:O, used:O, for:O, mapping:O, available:O, resources:O, and:O, lateral:O, movement:O, as:O, well:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To make the fraudulent withdrawals , Lazarus first breaches targeted banks' networks and compromises the switch application servers handling ATM transactions .' [/INST] [To:O, make:O, the:O, fraudulent:B-Purp, withdrawals:I-Purp, ,:O, Lazarus:B-HackOrg, first:O, breaches:O, targeted:O, banks':B-Idus, networks:O, and:O, compromises:O, the:O, switch:O, application:O, servers:O, handling:O, ATM:O, transactions:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 operation , known as FASTCash” has enabled Lazarus to fraudulently empty ATMs of cash .' [/INST] [The:O, operation:O, ,:O, known:O, as:O, FASTCash”:O, has:O, enabled:O, Lazarus:B-HackOrg, to:O, fraudulently:O, empty:B-Purp, ATMs:I-Purp, of:O, cash:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 permit their fraudulent withdrawals from ATMs , Lazarus inject a malicious Advanced Interactive eXecutive (AIX) executable into a running , legitimate process on the switch application server of a financial transaction network , in this case a network handling ATM transactions .' [/INST] [In:O, order:O, to:O, permit:O, their:O, fraudulent:O, withdrawals:O, from:O, ATMs:O, ,:O, Lazarus:B-HackOrg, inject:O, a:O, malicious:O, Advanced:O, Interactive:O, eXecutive:O, (AIX):B-Tool, executable:O, into:O, a:O, running:O, ,:O, legitimate:O, process:O, on:O, the:O, switch:O, application:O, server:O, of:O, a:O, financial:O, transaction:O, network:O, ,:O, in:O, this:O, case:O, a:O, network:O, handling:O, ATM:O, transactions:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 was previously believed that the attackers used scripts to manipulate legitimate software on the server into enabling the fraudulent activity .' [/INST] [It:O, was:O, previously:O, believed:O, that:O, the:O, attackers:B-HackOrg, used:O, scripts:B-Tool, to:O, manipulate:O, legitimate:O, software:O, on:O, the:O, server:O, into:O, enabling:O, the:O, fraudulent:O, activity:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 recent years , Lazarus has also become involved in financially motivated attacks .' [/INST] [In:O, recent:B-Time, years:I-Time, ,:O, Lazarus:B-HackOrg, has:O, also:O, become:O, involved:O, in:O, financially:B-Idus, motivated:O, attacks:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 malware in turn intercepts fraudulent Lazarus cash withdrawal requests and sends fake approval responses , allowing the attackers to steal cash from ATMs .' [/INST] [This:O, malware:B-Tool, in:O, turn:O, intercepts:O, fraudulent:O, Lazarus:B-HackOrg, cash:O, withdrawal:O, requests:O, and:O, sends:O, fake:O, approval:O, responses:O, ,:O, allowing:O, the:O, attackers:O, to:O, steal:B-Purp, cash:I-Purp, from:O, ATMs:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Lazarus was linked to the $81 million theft from the Bangladesh central bank in 2016 , along with a number of other bank heists .' [/INST] [Lazarus:B-HackOrg, was:O, linked:O, to:O, the:O, $81:O, million:O, theft:O, from:O, the:O, Bangladesh:B-Idus, central:I-Idus, bank:I-Idus, in:O, 2016:B-Time, ,:O, along:O, with:O, a:O, number:O, of:O, other:O, bank:O, heists:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Lazarus was also linked to the WannaCry ransomware outbreak in May 2017 .' [/INST] [Lazarus:B-HackOrg, was:O, also:O, linked:O, to:O, the:O, WannaCry:B-OffAct, ransomware:I-OffAct, outbreak:O, in:O, May:O, 2017:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'WannaCry incorporated the leaked EternalBlue exploit that used two known vulnerabilities in Windows CVE-2017-0144 and CVE-2017-0145 to turn the ransomware into a worm , capable of spreading itself to any unpatched computers on the victim's network and also to other vulnerable computers connected to the internet .' [/INST] [WannaCry:B-OffAct, incorporated:O, the:O, leaked:O, EternalBlue:O, exploit:O, that:O, used:O, two:O, known:O, vulnerabilities:O, in:O, Windows:O, CVE-2017-0144:B-Exp, and:O, CVE-2017-0145:B-Exp, to:O, turn:O, the:O, ransomware:O, into:O, a:O, worm:O, ,:O, capable:O, of:O, spreading:O, itself:O, to:O, any:O, unpatched:O, computers:O, on:O, the:O, victim's:O, network:O, and:O, also:O, to:O, other:O, vulnerable:O, computers:O, connected:O, to:O, the:O, internet:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Lazarus was initially known for its involvement in espionage operations and a number of high-profile disruptive attacks , including the 2014 attack on Sony Pictures that saw large amounts of information being stolen and computers wiped by malware .' [/INST] [Lazarus:B-HackOrg, was:O, initially:O, known:O, for:O, its:O, involvement:O, in:O, espionage:O, operations:O, and:O, a:O, number:O, of:O, high-profile:O, disruptive:O, attacks:O, ,:O, including:O, the:O, 2014:B-Time, attack:O, on:O, Sony:O, Pictures:O, that:O, saw:O, large:O, amounts:O, of:O, information:O, being:O, stolen:O, and:O, computers:O, wiped:O, by: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: 'In short , Lazarus continues to pose a serious threat to the financial sector and organizations should take all necessary steps to ensure that their payment systems are fully up to date and secured .' [/INST] [In:O, short:O, ,:O, Lazarus:B-HackOrg, continues:O, to:O, pose:O, a:O, serious:O, threat:O, to:O, the:O, financial:B-Idus, sector:I-Idus, and:O, organizations:O, should:O, take:O, all:O, necessary:O, steps:O, to:O, ensure:O, that:O, their:O, payment:O, systems:O, are:O, fully:O, up:O, to:O, date:O, and:O, secured:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 with the 2016 series of virtual bank heists , including the Bangladesh Bank heist , FASTCash illustrates that Lazarus possesses an in-depth knowledge of banking systems and transaction processing protocols and has the expertise to leverage that knowledge in order to steal large sums from vulnerable banks .' [/INST] [As:O, with:O, the:O, 2016:B-Time, series:O, of:O, virtual:O, bank:O, heists:O, ,:O, including:O, the:O, Bangladesh:O, Bank:O, heist:O, ,:O, FASTCash:B-SecTeam, illustrates:O, that:O, Lazarus:B-HackOrg, possesses:O, an:O, in-depth:O, knowledge:O, of:O, banking:O, systems:O, and:O, transaction:O, processing:O, protocols:O, and:O, has:O, the:O, expertise:O, to:O, leverage:O, that:O, knowledge:O, in:O, order:O, to:O, steal:O, large:O, sums:O, from:O, vulnerable:O, banks:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 attack , which starts with a malicious attachment disguised as a top secret US document , weaponizes TeamViewer , the popular remote access and desktop sharing software , to gain full control of the infected computer .' [/INST] [The:O, attack:B-HackOrg, ,:O, which:O, starts:O, with:O, a:O, malicious:O, attachment:O, disguised:O, as:O, a:O, top:O, secret:O, US:O, document:O, ,:O, weaponizes:O, TeamViewer:B-Tool, ,:O, the:O, popular:O, remote:O, access:O, and:O, desktop:O, sharing:O, software:O, ,:O, to:O, gain:O, full:O, control:O, of:O, the:O, infected:O, computer:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 described in the infection flow , one of the first uses of the AutoHotKey scripts is to upload a screenshot from the compromised PC .' [/INST] [As:O, described:O, in:O, the:O, infection:O, flow:O, ,:O, one:O, of:O, the:O, first:O, uses:O, of:O, the:O, AutoHotKey:B-SamFile, scripts:I-SamFile, is:O, to:O, upload:B-Features, a:I-Features, screenshot:I-Features, from:O, the:O, compromised:O, PC:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 hard to tell if there are geopolitical motives behind this campaign by looking solely at the list of countries it was targeting , since it was not after a specific region and the victims came from different places in the world .' [/INST] [It:O, is:O, hard:O, to:O, tell:O, if:O, there:O, are:O, geopolitical:O, motives:O, behind:O, this:O, campaign:B-OffAct, by:O, looking:O, solely:O, at:O, the:O, list:O, of:O, countries:O, it:O, was:O, targeting:O, ,:O, since:O, it:O, was:O, not:O, after:O, a:O, specific:O, region:O, and:O, the:O, victims:O, came:O, from:O, different:B-Area, places:I-Area, in: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: 'The initial infection vector used by the threat actor also changed over time , during 2018 we have seen multiple uses of self-extracting archives instead of malicious documents with AutoHotKey , which displayed a decoy image to the user .' [/INST] [The:O, initial:O, infection:O, vector:O, used:O, by:O, the:O, threat:O, actor:O, also:O, changed:O, over:O, time:O, ,:O, during:O, 2018:B-Time, we:O, have:O, seen:O, multiple:O, uses:O, of:O, self-extracting:O, archives:B-Tool, instead:O, of:O, malicious:O, documents:O, with:O, AutoHotKey:B-HackOrg, ,:O, which:O, displayed:O, a:O, decoy:B-Tool, image:I-Tool, to:O, the:O, user:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 recent wave of FASTCash attacks demonstrates that financially motivated attacks are not simply a passing interest for the Lazarus group and can now be considered one of its core activities .' [/INST] [The:O, recent:O, wave:O, of:O, FASTCash:B-OffAct, attacks:I-OffAct, demonstrates:O, that:O, financially:B-Time, motivated:I-Time, attacks:O, are:O, not:O, simply:O, a:O, passing:O, interest:O, for:O, the:O, Lazarus:B-HackOrg, group:I-HackOrg, and:O, can:O, now:O, be:O, considered:O, one:O, of:O, its:O, core:O, activities:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 both examples of the different delivery methods described above show an exclusive targeting of Russian speakers , the recurring financial and political themes that they use highlight the attacker's interest in the financial world once more .' [/INST] [Although:O, both:O, examples:O, of:O, the:O, different:O, delivery:O, methods:O, described:O, above:O, show:O, an:O, exclusive:O, targeting:O, of:O, Russian:B-Area, speakers:O, ,:O, the:O, recurring:O, financial:O, and:O, political:O, themes:O, that:O, they:O, use:O, highlight:O, the:O, attacker's:B-HackOrg, interest:O, in:O, the:O, financial:B-Idus, world:O, once: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: 'Throughout our investigation , we have found evidence that shows operational similarities between this implant and Gamaredon Group .' [/INST] [Throughout:O, our:O, investigation:O, ,:O, we:O, have:O, found:O, evidence:O, that:O, shows:O, operational:O, similarities:O, between:O, this:O, implant:B-SamFile, and:O, Gamaredon:B-HackOrg, Group:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Gamaredon Group is an alleged Russian threat group .' [/INST] [Gamaredon:B-HackOrg, Group:I-HackOrg, is:O, an:O, alleged:O, Russian:B-Area, threat:O, group:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Gamaredon Group has been active since at least 2013 , and has targeted individuals likely involved with the Ukrainian government .' [/INST] [Gamaredon:B-HackOrg, Group:I-HackOrg, has:O, been:O, active:O, since:O, at:O, least:O, 2013:O, ,:O, and:O, has:O, targeted:O, individuals:O, likely:O, involved:O, with:O, the:O, Ukrainian:B-Idus, government: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: 'EvilGnome's functionalities include desktop screenshots , file stealing , allowing capturing audio recording from the user’s microphone and the ability to download and execute further modules .' [/INST] [EvilGnome's:B-HackOrg, functionalities:O, include:O, desktop:B-Tool, screenshots:I-Tool, ,:O, file:B-Tool, stealing:I-Tool, ,:O, allowing:O, capturing:B-Tool, audio:I-Tool, recording:I-Tool, from:O, the:O, user’s:O, microphone:O, and:O, the:O, ability:O, to:O, download:O, and:O, execute:O, further:O, modules:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Gamaredon Group primarily makes use of Russian hosting providers in order to distribute its malware .' [/INST] [Gamaredon:B-HackOrg, Group:I-HackOrg, primarily:O, makes:O, use:O, of:O, Russian:O, hosting:O, providers:O, in:O, order:O, to:O, distribute:O, its:O, malware: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: 'Gamaredon Group's implants are characterized by the employment of information stealing tools — among them being screenshot and document stealers delivered via a SFX , and made to achieve persistence through a scheduled task .' [/INST] [Gamaredon:B-HackOrg, Group's:I-HackOrg, implants:O, are:O, characterized:O, by:O, the:O, employment:O, of:O, information:B-Tool, stealing:I-Tool, tools:I-Tool, —:O, among:O, them:O, being:O, screenshot:O, and:O, document:O, stealers:O, delivered:O, via:O, a:O, SFX:O, ,:O, and:O, made:O, to:O, achieve:O, persistence:O, through:O, a:O, scheduled:O, task:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Gamaredon Group infects victims using malicious attachments , delivered via spear phishing techniques .' [/INST] [Gamaredon:B-HackOrg, Group:I-HackOrg, infects:O, victims:O, using:O, malicious:B-Tool, attachments:I-Tool, ,:O, delivered:O, via:O, spear:B-Way, phishing:I-Way, techniques:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 techniques and modules employed by EvilGnome — that is the use of SFX , persistence with task scheduler and the deployment of information stealing tools—remind us of Gamaredon Group’s Windows tools .' [/INST] [The:O, techniques:O, and:O, modules:O, employed:O, by:O, EvilGnome:B-HackOrg, —:O, that:O, is:O, the:O, use:O, of:O, SFX:B-Tool, ,:O, persistence:O, with:O, task:O, scheduler:O, and:O, the:O, deployment:O, of:O, information:O, stealing:O, tools—remind:O, us:O, of:O, Gamaredon:O, Group’s:O, Windows:B-SamFile, tools:I-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We can observe that the sample is very recent , created on Thursday , July 4 .' [/INST] [We:O, can:O, observe:O, that:O, the:O, sample:B-SamFile, is:O, very:O, recent:O, ,:O, created:O, on:O, Thursday:O, ,:O, July:B-Time, 4: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: 'As can be observed in the illustration above , the makeself script is instructed to run ./setup.sh after unpacking .' [/INST] [As:O, can:O, be:O, observed:O, in:O, the:O, illustration:O, above:O, ,:O, the:O, makeself:B-SamFile, script:I-SamFile, is:O, instructed:O, to:O, run:O, ./setup.sh:B-SamFile, after:O, unpacking:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 ShooterAudio module uses PulseAudio to capture audio from the user's microphone .' [/INST] [The:O, ShooterAudio:B-SamFile, module:I-SamFile, uses:O, PulseAudio:B-Tool, to:O, capture:O, audio:O, from:O, the:O, user's:O, microphone:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'makeself.sh is a small shell script that generates a self-extractable compressed tar archive from a directory .' [/INST] [makeself.sh:B-SamFile, is:O, a:O, small:O, shell:B-SamFile, script:I-SamFile, that:O, generates:O, a:O, self-extractable:O, compressed:O, tar:O, archive:O, from:O, a:O, directory:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'During our 2018 monitoring of this group , we were able to identify different techniques utilized by very similar attackers in the MENA region , sometimes on the same target .' [/INST] [During:O, our:O, 2018:O, monitoring:O, of:O, this:O, group:B-HackOrg, ,:O, we:O, were:O, able:O, to:O, identify:O, different:O, techniques:O, utilized:O, by:O, very:O, similar:O, attackers:O, in:O, the:O, MENA:B-Area, region:I-Area, ,:O, sometimes:O, on:O, the:O, same:O, target:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Gaza Cybergang Group3 (highest sophistication) whose activities previously went by the name Operation Parliament .' [/INST] [Gaza:B-HackOrg, Cybergang:I-HackOrg, Group3:I-HackOrg, (highest:O, sophistication):O, whose:O, activities:O, previously:O, went:O, by:O, the:O, name:O, Operation:B-OffAct, Parliament: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: 'Gaza Cybergang has been seen employing phishing , with several chained stages to evade detection and extend command and control server lifetimes .' [/INST] [Gaza:B-HackOrg, Cybergang:I-HackOrg, has:O, been:O, seen:O, employing:B-Way, phishing:I-Way, ,:O, with:O, several:O, chained:O, stages:O, to:O, evade:O, detection:O, and:O, extend:O, command:O, and:O, control:O, server:O, lifetimes:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 most popular targets of SneakyPastes are embassies , government entities , education , media outlets , journalists , activists , political parties or personnel , healthcare and banking .' [/INST] [The:O, most:O, popular:O, targets:O, of:O, SneakyPastes:B-HackOrg, are:O, embassies:B-Org, ,:O, government:B-Idus, entities:I-Idus, ,:O, education:B-Idus, ,:O, media:B-Idus, outlets:I-Idus, ,:O, journalists:O, ,:O, activists:B-Org, ,:O, political:O, parties:O, or:O, personnel:B-Org, ,:O, healthcare:B-Idus, and:O, banking: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: 'Through our continuous monitoring of threats during 2018 , we observed a new wave of attacks by Gaza Cybergang Group1 targeting embassies and political personnel .' [/INST] [Through:O, our:O, continuous:O, monitoring:O, of:O, threats:O, during:O, 2018:O, ,:O, we:O, observed:O, a:O, new:O, wave:O, of:O, attacks:O, by:O, Gaza:B-HackOrg, Cybergang:I-HackOrg, Group1:I-HackOrg, targeting:O, embassies:B-Idus, and:O, political:B-Org, personnel: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: 'Gaza Cybergang Group1 is an attack group with limited infrastructure and an open-source type of toolset , which conducts widespread attacks , but is nevertheless focused on Palestinian political problems .' [/INST] [Gaza:B-HackOrg, Cybergang:I-HackOrg, Group1:I-HackOrg, is:O, an:O, attack:O, group:O, with:O, limited:O, infrastructure:O, and:O, an:O, open-source:O, type:O, of:O, toolset:O, ,:O, which:O, conducts:O, widespread:O, attacks:O, ,:O, but:O, is:O, nevertheless:O, focused:O, on:O, Palestinian:B-Idus, political:O, problems:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this campaign , Gaza Cybergang used disposable emails and domains as the phishing platform to target the victims .' [/INST] [In:O, this:O, campaign:O, ,:O, Gaza:B-HackOrg, Cybergang:I-HackOrg, used:O, disposable:B-Way, emails:I-Way, and:O, domains:O, as:O, the:O, phishing:B-Way, platform:O, to:O, target:O, the:O, victims:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The RAT , however , had a multitude of functionalities (as listed in the table below) such as to download and execute , compress , encrypt , upload , search directories , etc .' [/INST] [The:O, RAT:B-SamFile, ,:O, however:O, ,:O, had:O, a:O, multitude:O, of:O, functionalities:O, (as:O, listed:O, in:O, the:O, table:O, below):O, such:O, as:O, to:O, download:B-Features, and:O, execute:B-Features, ,:O, compress:B-Features, ,:O, encrypt:B-Features, ,:O, upload:B-Features, ,:O, search:B-Features, directories:I-Features, ,:O, etc:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 expect the damage caused by these groups to intensify and the attacks to extend into other regions that are also linked to the complicated Palestinian situation .' [/INST] [We:O, expect:O, the:O, damage:O, caused:O, by:O, these:O, groups:O, to:O, intensify:O, and:O, the:O, attacks:B-HackOrg, to:O, extend:O, into:O, other:O, regions:O, that:O, are:O, also:O, linked:O, to:O, the:O, complicated:B-Idus, Palestinian:I-Idus, situation: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: 'Cylance determined that the ‘Ghost Dragon’ group utilized specifically tailored variants of Gh0st RAT , which the group modified from the 3.6 version of the source code released in 2008 .' [/INST] [Cylance:B-SecTeam, determined:O, that:O, the:O, ‘Ghost:B-HackOrg, Dragon’:I-HackOrg, group:O, utilized:O, specifically:O, tailored:O, variants:O, of:O, Gh0st:B-Tool, RAT:I-Tool, ,:O, which:O, the:O, group:O, modified:O, from:O, the:O, 3.6:O, version:O, of:O, the:O, source:O, code:O, released:O, in:O, 2008:B-Time, .:O] </s> |
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