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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: 'Adobe on Thursday patched a zero-day vulnerability in Flash Player that has been used in targeted attacks carried out by a new APT group operating primarily against high-profile victims in Russia and Asia .' [/INST] [Adobe:O, on:O, Thursday:O, patched:O, a:O, zero-day:B-Exp, vulnerability:I-Exp, in:O, Flash:O, Player:O, that:O, has:O, been:O, used:O, in:O, targeted:B-OffAct, attacks:I-OffAct, carried:O, out:O, by:O, a:O, new:O, APT:O, group:O, operating:O, primarily:O, against:O, high-profile:O, victims:O, in:O, Russia:B-Area, and:O, Asia:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Researchers at Kaspersky Lab privately disclosed the flaw to Adobe after exploits against the zero-day were used in March by the ScarCruft APT gang in what Kaspersky Lab is calling Operation Daybreak .' [/INST] [Researchers:O, at:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, privately:O, disclosed:O, the:O, flaw:O, to:O, Adobe:O, after:O, exploits:O, against:O, the:O, zero-day:B-Exp, were:O, used:O, in:O, March:B-Time, by:O, the:O, ScarCruft:O, APT:O, gang:O, in:O, what:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, is:O, calling:O, Operation:B-OffAct, Daybreak: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: 'Kaspersky speculates that ScarCruft could also be behind another zero-day , CVE-2016-0147 , a vulnerability in Microsoft XML Core Services that was patched in April .' [/INST] [Kaspersky:B-SecTeam, speculates:O, that:O, ScarCruft:B-HackOrg, could:O, also:O, be:O, behind:O, another:O, zero-day:B-Exp, ,:O, CVE-2016-0147:B-Exp, ,:O, a:O, vulnerability:O, in:O, Microsoft:O, XML:O, Core:O, Services:O, that:O, was:O, patched: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: 'Attacks start with spear-phishing emails that include a link to a website hosting an exploit kit associated with ScarCruft and used in other attacks .' [/INST] [Attacks:B-OffAct, start:O, with:O, spear-phishing:B-Way, emails:I-Way, that:O, include:O, a:O, link:O, to:O, a:O, website:O, hosting:O, an:O, exploit:O, kit:O, associated:O, with:O, ScarCruft:B-HackOrg, and:O, used:O, in:O, other:O, attacks: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: 'Another set of attacks called Operation Erebus leverages another Flash exploit , CVE-2016-4117 , and relies on watering hole attacks as a means of propagation .' [/INST] [Another:O, set:O, of:O, attacks:B-OffAct, called:O, Operation:B-OffAct, Erebus:I-OffAct, leverages:O, another:O, Flash:B-Exp, exploit:I-Exp, ,:O, CVE-2016-4117:B-Exp, ,:O, and:O, relies:O, on:O, watering:B-OffAct, hole:I-OffAct, attacks:I-OffAct, as:O, a:O, means:O, of:O, propagation:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Thursday 's Flash Player update patched 36 vulnerabilities in total including the zero day CVE-2016-4171 .' [/INST] [Thursday:O, 's:O, Flash:O, Player:O, update:O, patched:O, 36:O, vulnerabilities:O, in:O, total:O, including:O, the:O, zero:B-Exp, day:I-Exp, CVE-2016-4171:B-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The ongoing operation likely began as early as January 2017 and has continued through the first quarter of 2019 .' [/INST] [The:O, ongoing:O, operation:O, likely:O, began:O, as:O, early:O, as:O, January:B-Time, 2017:I-Time, and:O, has:O, continued:O, through:O, the:O, first:O, quarter:O, of:O, 2019: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: 'Cisco Talos assess with high confidence that these operations are distinctly different and independent from the operations performed by DNSpionage , which we reported on in November 2018 .' [/INST] [Cisco:B-SecTeam, Talos:I-SecTeam, assess:O, with:O, high:O, confidence:O, that:O, these:O, operations:O, are:O, distinctly:O, different:O, and:O, independent:O, from:O, the:O, operations:O, performed:O, by:O, DNSpionage:B-OffAct, ,:O, which:O, we:O, reported:O, on:O, in:O, November: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: 'We assess with high confidence that these operations are distinctly different and independent from the operations performed by DNSpionage , which we reported on in November 2018 .' [/INST] [We:O, assess:O, with:O, high:O, confidence:O, that:O, these:O, operations:O, are:O, distinctly:O, different:O, and:O, independent:O, from:O, the:O, operations:O, performed:O, by:O, DNSpionage:B-OffAct, ,:O, which:O, we:O, reported:O, on:O, in:O, November: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: 'The common use of the Enfal Trojan suggests that Shadow Network may be exchanging tools and techniques .' [/INST] [The:O, common:O, use:O, of:O, the:O, Enfal:B-Tool, Trojan:I-Tool, suggests:O, that:O, Shadow:O, Network:O, may:O, be:O, exchanging:O, tools:O, and:O, 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: 'While Silence had previously targeted Russian banks , Group-IB experts also have discovered evidence of the group 's activity in more than 25 countries worldwide .' [/INST] [While:B-HackOrg, Silence:I-HackOrg, had:O, previously:O, targeted:O, Russian:B-Area, banks:B-Idus, ,:O, Group-IB:B-SecTeam, experts:O, also:O, have:O, discovered:O, evidence:O, of:O, the:O, group:O, 's:O, activity:B-OffAct, in:O, more:O, than:O, 25:O, countries:O, worldwide:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 August 2017 , the National Bank of Ukraine warned state-owned and private banks across the country about a large-scale phishing attack .' [/INST] [In:O, August:B-Time, 2017:I-Time, ,:O, the:O, National:B-Org, Bank:I-Org, of:O, Ukraine:B-Area, warned:O, state-owned:O, and:O, private:B-Idus, banks:I-Idus, across:O, the:O, country:O, about:O, a:O, large-scale:O, phishing:B-OffAct, attack: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 threat actor used an exploit from the arsenal of the state-sponsored hacker group APT28 .' [/INST] [The:O, threat:O, actor:O, used:O, an:O, exploit:O, from:O, the:O, arsenal:O, of:O, the:O, state-sponsored:O, hacker:O, group:O, APT28:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The new threat actor group was eventually named Silence .' [/INST] [The:O, new:O, threat:O, actor:O, group:O, was:O, eventually:O, named:O, Silence:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Silence is a group of Russian-speaking hackers , based on their commands language , the location of infrastructure they used , and the geography of their targets ( Russia , Ukraine , Belarus , Azerbaijan , Poland , and Kazakhstan ) .' [/INST] [Silence:O, is:O, a:O, group:O, of:O, Russian-speaking:B-Area, hackers:O, ,:O, based:O, on:O, their:O, commands:O, language:O, ,:O, the:O, location:O, of:O, infrastructure:O, they:O, used:O, ,:O, and:O, the:O, geography:O, of:O, their:O, targets:O, (:O, Russia:B-Area, ,:O, Ukraine:B-Area, ,:O, Belarus:B-Area, ,:O, Azerbaijan:B-Area, ,:O, Poland:B-Area, ,:O, and:O, Kazakhstan:B-Area, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Although Silence 's phishing emails were also sent to bank employees in Central and Western Europe , Africa , and Asia ) .' [/INST] [Although:O, Silence:O, 's:O, phishing:B-Way, emails:I-Way, were:O, also:O, sent:O, to:O, bank:B-Org, employees:I-Org, in:O, Central:B-Area, and:I-Area, Western:I-Area, Europe:I-Area, ,:O, Africa:B-Area, ,:O, and:O, Asia:B-Area, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Silence also used Russian-language web hosting services .' [/INST] [Silence:O, also:O, used:O, Russian-language:B-Area, web:B-Tool, hosting:I-Tool, services:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Financially motivated APT groups which focus efforts on targeted attacks on the financial sector such as — Anunak , Corkow , Buhtrap — usually managed botnets using developed or modified banking Trojans .' [/INST] [Financially:B-Purp, motivated:I-Purp, APT:O, groups:O, which:O, focus:O, efforts:O, on:O, targeted:B-OffAct, attacks:I-OffAct, on:O, the:O, financial:B-Org, sector:I-Org, such:O, as:O, —:O, Anunak:O, ,:O, Corkow:B-Tool, ,:O, Buhtrap:O, —:O, usually:O, managed:O, botnets:O, using:O, developed:O, or:O, modified:O, banking:B-Idus, Trojans:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 tried new techniques to steal from banking systems , including AWS CBR ( the Russian Central Bank 's Automated Workstation Client ) , ATMs , and card processing .' [/INST] [They:O, tried:O, new:O, techniques:O, to:O, steal:O, from:O, banking:O, systems:O, ,:O, including:O, AWS:O, CBR:O, (:O, the:O, Russian:B-Area, Central:B-Org, Bank:I-Org, 's:I-Org, Automated:I-Org, Workstation:I-Org, Client:I-Org, ):O, ,:O, ATMs:B-Org, ,:O, and:O, card:O, processing:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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-IB researchers were tracking Silence throughout this period and conducting response following incidents in the financial sector .' [/INST] [Group-IB:B-SecTeam, researchers:O, were:O, tracking:O, Silence:O, throughout:O, this:O, period:O, and:O, conducting:O, response:O, following:O, incidents:O, in:O, the:O, financial:B-Org, sector: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: 'Group-IB detected the first incidents relating to Silence in June 2016 .' [/INST] [Group-IB:B-SecTeam, detected:O, the:O, first:O, incidents:O, relating:O, to:O, Silence:O, in:O, June:B-Time, 2016:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'One of Silence 's first targets was a Russian bank , when they tried to attack AWS CBR .' [/INST] [One:O, of:O, Silence:O, 's:O, first:O, targets:O, was:O, a:O, Russian:B-Area, bank:B-Idus, ,:O, when:O, they:O, tried:O, to:O, attack:O, AWS:O, CBR:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 are selective in their attacks and wait for about three months between incidents , which is approximately three times longer than other financially motivated APT groups , like MoneyTaker , Anunak ( Carbanak ) , Buhtrap or Cobalt .' [/INST] [They:O, are:O, selective:O, in:O, their:O, attacks:B-OffAct, and:O, wait:O, for:O, about:O, three:O, months:O, between:O, incidents:O, ,:O, which:O, is:O, approximately:O, three:O, times:O, longer:O, than:O, other:O, financially:B-Purp, motivated:I-Purp, APT:O, groups:O, ,:O, like:O, MoneyTaker:O, ,:O, Anunak:O, (:O, Carbanak:O, ):O, ,:O, Buhtrap:O, or:O, Cobalt:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Silence try to apply new techniques and ways of stealing from various banking systems , including AWS CBR , ATMs , and card processing .' [/INST] [Silence:O, try:O, to:O, apply:O, new:O, techniques:O, and:O, ways:O, of:O, stealing:O, from:O, various:O, banking:O, systems:O, ,:O, including:O, AWS:O, CBR:O, ,:O, ATMs:O, ,:O, and:O, card:O, processing:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Silence 's successful attacks currently have been limited to the CIS and Eastern European countries .' [/INST] [Silence:O, 's:O, successful:O, attacks:B-OffAct, currently:O, have:O, been:O, limited:O, to:O, the:O, CIS:O, and:O, Eastern:O, European:O, countries:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'He is responsible for developing tools for conducting attacks and is also able to modify complex exploits and third party software .' [/INST] [He:O, is:O, responsible:O, for:O, developing:B-Features, tools:I-Features, for:O, conducting:O, attacks:B-OffAct, and:O, is:O, also:O, able:O, to:O, modify:B-Features, complex:I-Features, exploits:I-Features, and:O, third:B-Features, party:I-Features, software: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: 'Silence 's main targets are located in Russia , Ukraine , Belarus , Azerbaijan , Poland , and Kazakhstan .' [/INST] [Silence:O, 's:O, main:O, targets:O, are:O, located:O, in:O, Russia:B-Area, ,:O, Ukraine:B-Area, ,:O, Belarus:B-Area, ,:O, Azerbaijan:B-Area, ,:O, Poland:B-Area, ,:O, and:O, Kazakhstan: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 , some phishing emails were sent to bank employees in more than 25 countries of Central and Western Europe , Africa and Asia including : Kyrgyzstan , Armenia , Georgia , Serbia , Germany , Latvia , Czech Republic , Romania , Kenya , Israel , Cyprus , Greece , Turkey , Taiwan , Malaysia , Switzerland , Vietnam , Austria , Uzbekistan , Great Britain , Hong Kong , and others .' [/INST] [However:O, ,:O, some:O, phishing:B-Way, emails:I-Way, were:O, sent:O, to:O, bank:B-Org, employees:I-Org, in:O, more:O, than:O, 25:O, countries:O, of:O, Central:B-Area, and:O, Western:B-Area, Europe:B-Area, ,:O, Africa:B-Area, and:O, Asia:B-Area, including:O, ::O, Kyrgyzstan:B-Area, ,:O, Armenia:B-Area, ,:O, Georgia:B-Area, ,:O, Serbia:B-Area, ,:O, Germany:B-Area, ,:O, Latvia:B-Area, ,:O, Czech:B-Area, Republic:I-Area, ,:O, Romania:B-Area, ,:O, Kenya:B-Area, ,:O, Israel:B-Area, ,:O, Cyprus:B-Area, ,:O, Greece:B-Area, ,:O, Turkey:B-Area, ,:O, Taiwan:B-Area, ,:O, Malaysia:B-Area, ,:O, Switzerland:B-Area, ,:O, Vietnam:B-Area, ,:O, Austria:B-Area, ,:O, Uzbekistan:B-Area, ,:O, Great:B-Area, Britain:I-Area, ,:O, Hong:B-Area, Kong:I-Area, ,:O, and:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In the same year , they conducted DDoS attacks using the Perl IRC bot and public IRC chats to control Trojans .' [/INST] [In:O, the:O, same:O, year:O, ,:O, they:O, conducted:O, DDoS:B-OffAct, attacks:I-OffAct, using:O, the:O, Perl:B-Tool, IRC:I-Tool, bot:I-Tool, and:O, public:B-Tool, IRC:I-Tool, chats:I-Tool, to:O, control:O, Trojans:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 same year , Silence conducted DDoS attacks using the Perl IRC bot and public IRC chats to control Trojans .' [/INST] [In:O, the:O, same:O, year:O, ,:O, Silence:O, conducted:O, DDoS:B-OffAct, attacks:I-OffAct, using:O, the:O, Perl:B-Tool, IRC:I-Tool, bot:I-Tool, and:O, public:B-Tool, IRC:I-Tool, chats:I-Tool, to:O, control:O, Trojans:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 two months , the group returned to their proven method and withdrew funds again through ATMs .' [/INST] [In:O, two:O, months:O, ,:O, the:O, group:O, returned:O, to:O, their:O, proven:O, method:O, and:O, withdrew:O, funds:O, again:O, through: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: 'In September 2017 , we discovered a new targeted attack on financial institutions .' [/INST] [In:O, September:B-Time, 2017:I-Time, ,:O, we:O, discovered:O, a:O, new:O, targeted:B-OffAct, attack:I-OffAct, on:O, financial:B-Org, institutions: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 September 2017 , we discovered Silence attack on financial institutions .' [/INST] [In:O, September:B-Time, 2017:I-Time, ,:O, we:O, discovered:O, Silence:B-OffAct, attack:I-OffAct, on:O, financial:B-Org, institutions:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The infection vector is a spear-phishing email with a malicious attachment .' [/INST] [The:O, infection:O, vector:O, is:O, a:O, spear-phishing:B-Way, email:I-Way, with:O, a:O, malicious:O, attachment:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'An interesting point in the Silence attack is that the cybercriminals had already compromised banking infrastructure in order to send their spear-phishing emails from the addresses of real bank employees and look as unsuspicious as possible to future victims .' [/INST] [An:O, interesting:O, point:O, in:O, the:O, Silence:B-OffAct, attack:I-OffAct, is:O, that:O, the:O, cybercriminals:O, had:O, already:O, compromised:O, banking:B-Idus, infrastructure:O, in:O, order:O, to:O, send:O, their:O, spear-phishing:B-Way, emails:I-Way, from:O, the:O, addresses:O, of:O, real:O, bank:B-Org, employees:I-Org, and:O, look:O, as:O, unsuspicious:O, as:O, possible:O, to:O, future: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 spear-phishing infection vector is still the most popular way to initiate targeted campaigns .' [/INST] [The:O, spear-phishing:B-Way, infection:O, vector:O, is:O, still:O, the:O, most:O, popular:O, way:O, to:O, initiate:O, targeted:O, campaigns:B-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We conclude that the actor behind the attack is Silence group , a relatively new threat actor that's been operating since mid-2016 .' [/INST] [We:O, conclude:O, that:O, the:O, actor:O, behind:O, the:O, attack:B-OffAct, is:O, Silence:O, group:O, ,:O, a:O, relatively:O, new:O, threat:O, actor:O, that's:O, been:O, operating:O, since:O, mid-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: 'A preliminary analysis caught the attention of our Threat Analysis and Intelligence team as it yielded interesting data that , among other things , shows that Silence was targeting employees from financial entities , specifically in the Russian Federation and the Republic of Belarus .' [/INST] [A:O, preliminary:O, analysis:O, caught:O, the:O, attention:O, of:O, our:O, Threat:O, Analysis:O, and:O, Intelligence:O, team:O, as:O, it:O, yielded:O, interesting:O, data:O, that:O, ,:O, among:O, other:O, things:O, ,:O, shows:O, that:O, Silence:O, was:O, targeting:O, employees:B-Org, from:O, financial:B-Org, entities:I-Org, ,:O, specifically:O, in:O, the:O, Russian:B-Area, Federation:I-Area, and:O, the:O, Republic:B-Area, of:I-Area, Belarus: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: 'As shown above , the threat runs several native binaries to collect useful information for its recon phase .' [/INST] [As:O, shown:O, above:O, ,:O, the:O, threat:O, runs:O, several:O, native:B-Tool, binaries:I-Tool, to:O, collect:O, useful:O, information:O, for:O, its:O, recon:O, phase:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 intelligence we have collected shows that Silence is part of a more extensive operation , still focused on financial institutions operating mainly on Russian territory .' [/INST] [The:O, intelligence:O, we:O, have:O, collected:O, shows:O, that:O, Silence:O, is:O, part:O, of:O, a:O, more:O, extensive:O, operation:O, ,:O, still:O, focused:O, on:O, financial:B-Org, institutions:I-Org, operating:O, mainly:O, on:O, Russian:O, territory:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 spearphishing attempts represent an evolution of Iranian actors based on their social engineering tactics and narrow targeting .' [/INST] [These:O, spearphishing:B-Way, attempts:O, represent:O, an:O, evolution:O, of:O, Iranian:O, actors:O, based:O, on:O, their:O, social:B-Way, engineering:I-Way, tactics:I-Way, and:O, narrow:O, targeting:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Based on file modification dates and timestamps of samples , it appears that the observed campaign was initiated in the middle of February 2016 , with the infrastructure taken offline at the start of March .' [/INST] [Based:O, on:O, file:O, modification:O, dates:O, and:O, timestamps:O, of:O, samples:O, ,:O, it:O, appears:O, that:O, the:O, observed:O, campaign:B-OffAct, was:O, initiated:O, in:O, the:O, middle:O, of:O, February:B-Time, 2016:I-Time, ,:O, with:O, the:O, infrastructure:O, taken:O, offline:O, at:O, the:O, start:O, of:O, March: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: 'While the Sima moniker could similarly originate from software labels , it is a common female Persian name and a Persian-language word for , visage , or , appearance , .' [/INST] [While:O, the:O, Sima:O, moniker:O, could:O, similarly:O, originate:O, from:O, software:O, labels:O, ,:O, it:O, is:O, a:O, common:O, female:O, Persian:O, name:O, and:O, a:O, Persian-language:O, word:O, for:O, ,:O, visage:O, ,:O, or:O, ,:O, appearance:O, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Given its use in more advanced social engineering campaigns against women 's rights activists , the label seem particularly apt .' [/INST] [Given:O, its:O, use:O, in:O, more:O, advanced:O, social:B-Org, engineering:I-Org, campaigns:I-Org, against:O, women:B-Org, 's:I-Org, rights:I-Org, activists:I-Org, ,:O, the:O, label:O, seem:O, particularly:O, apt:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Samples and resource names contained the family names of prominent Iranians , and several of these individuals received the malware located in their respective folder .' [/INST] [Samples:O, and:O, resource:O, names:O, contained:O, the:O, family:O, names:O, of:O, prominent:O, Iranians:B-Org, ,:O, and:O, several:O, of:O, these:O, individuals:O, received:O, the:O, malware:O, located:O, in:O, their:O, respective:O, folder:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Sima group also engaged in impersonation of Citizenship and Immigration Services at the Department of Homeland Security , posing as a notice about the expiration of the recipient 's Permanent Residence status .' [/INST] [The:O, Sima:B-HackOrg, group:O, also:O, engaged:O, in:O, impersonation:O, of:O, Citizenship:B-Idus, and:O, Immigration:B-Idus, Services:I-Idus, at:O, the:O, Department:B-SecTeam, of:I-SecTeam, Homeland:I-SecTeam, Security:I-SecTeam, ,:O, posing:O, as:O, a:O, notice:O, about:O, the:O, expiration:O, of:O, the:O, recipient:O, 's:O, Permanent:O, Residence:O, status:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 another case , Sima mirrored an announcement made about the broadcast of a television program on Iranian-American cultural affairs in order to impersonate the individual and engage in spearphishing within hours of the legitimate message .' [/INST] [In:O, another:O, case:O, ,:O, Sima:B-HackOrg, mirrored:O, an:O, announcement:O, made:O, about:O, the:O, broadcast:O, of:O, a:O, television:O, program:O, on:O, Iranian-American:O, cultural:O, affairs:O, in:O, order:O, to:O, impersonate:O, the:O, individual:O, and:O, engage:O, in:O, spearphishing:B-Way, within:O, hours:O, of:O, the:O, legitimate:O, message:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 server used to host these malware samples was located on the German provider Hetzner ( 148.251.55.114 ) , within a small block of IP addresses that are registered with the customer ID , HOS-156205 , .' [/INST] [The:O, server:O, used:O, to:O, host:O, these:O, malware:O, samples:O, was:O, located:O, on:O, the:O, German:B-Area, provider:B-Org, Hetzner:O, (:O, 148.251.55.114:O, ):O, ,:O, within:O, a:O, small:O, block:O, of:O, IP:O, addresses:O, that:O, are:O, registered:O, with:O, the:O, customer:O, ID:O, ,:O, HOS-156205:O, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'All the samples appear to be have been compiled between February 29 and March 1 2016 , shortly before our discovery , suggesting that , despite the known C&C servers having quickly gone offline shortly after , this spree of attacks might be fresh and currently undergoing .' [/INST] [All:O, the:O, samples:O, appear:O, to:O, be:O, have:O, been:O, compiled:O, between:O, February:B-Time, 29:I-Time, and:O, March:B-Time, 1:I-Time, 2016:I-Time, ,:O, shortly:O, before:O, our:O, discovery:O, ,:O, suggesting:O, that:O, ,:O, despite:O, the:O, known:O, C&C:O, servers:O, having:O, quickly:O, gone:O, offline:O, shortly:O, after:O, ,:O, this:O, spree:O, of:O, attacks:B-OffAct, might:O, be:O, fresh:O, and:O, currently:O, undergoing:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 archives provide further indication that those entities behind the campaigns are Persian-language speakers , due to the naming of files and folders in Persian .' [/INST] [These:O, archives:O, provide:O, further:O, indication:O, that:O, those:O, entities:O, behind:O, the:O, campaigns:B-OffAct, are:O, Persian-language:O, speakers:O, ,:O, due:O, to:O, the:O, naming:O, of:O, files:O, and:O, folders:O, in:O, Persian:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'For the sake of narrative we are going to focus exclusively to those samples we identified being used in attacks against Iranian civil society and diaspora .' [/INST] [For:O, the:O, sake:O, of:O, narrative:O, we:O, are:O, going:O, to:O, focus:O, exclusively:O, to:O, those:O, samples:O, we:O, identified:O, being:O, used:O, in:O, attacks:B-OffAct, against:O, Iranian:B-Area, civil:B-Idus, society:I-Idus, and:O, diaspora: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: 'Butterfly has attacked multi-billion dollar companies operating in the internet , IT software , pharmaceutical , and commodities sectors .' [/INST] [Butterfly:B-HackOrg, has:O, attacked:O, multi-billion:B-Org, dollar:I-Org, companies:I-Org, operating:O, in:O, the:O, internet:O, ,:O, IT:O, software:O, ,:O, pharmaceutical:B-Idus, ,:O, and:O, commodities:B-Org, sectors:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The first signs of Butterfly 's activities emerged in early 2013 when several major technology and internet firms were compromised .' [/INST] [The:O, first:O, signs:O, of:O, Butterfly:O, 's:O, activities:B-OffAct, emerged:O, in:O, early:B-Time, 2013:I-Time, when:O, several:O, major:O, technology:B-Idus, and:O, internet:B-Org, firms:I-Org, were:O, compromised:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , an investigation by Symantec has found that the group has been active since at least March 2012 and its attacks have not only continued to the present day , but have also increased in number .' [/INST] [However:O, ,:O, an:O, investigation:O, by:O, Symantec:B-SecTeam, has:O, found:O, that:O, the:O, group:O, has:O, been:O, active:O, since:O, at:O, least:O, March:B-Time, 2012:B-Time, and:O, its:O, attacks:B-OffAct, have:O, not:O, only:O, continued:O, to:O, the:O, present:O, day:O, ,:O, but:O, have:O, also:O, increased:O, in:O, number:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Symantec has to date discovered 49 different organizations in more than 20 countries that have been attacked by Butterfly .' [/INST] [Symantec:B-SecTeam, has:O, to:O, date:O, discovered:O, 49:O, different:O, organizations:O, in:O, more:O, than:O, 20:O, countries:O, that:O, have:O, been:O, attacked:O, by:O, Butterfly:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Aside from the four companies which have publicly acknowledged attacks , Symantec has identified five other large technology firms compromised by Butterfly , primarily headquartered in the US .' [/INST] [Aside:O, from:O, the:O, four:O, companies:O, which:O, have:O, publicly:O, acknowledged:O, attacks:B-OffAct, ,:O, Symantec:B-SecTeam, has:O, identified:O, five:O, other:O, large:O, technology:B-Org, firms:I-Org, compromised:O, by:O, Butterfly:O, ,:O, primarily:O, headquartered:O, in:O, the:O, US:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In the first attack , Butterfly gained a foothold by first attacking a small European office belonging to one firm and using this infection to then move on to its US office and European headquarters .' [/INST] [In:O, the:O, first:O, attack:B-OffAct, ,:O, Butterfly:O, gained:O, a:O, foothold:O, by:O, first:O, attacking:O, a:O, small:O, European:O, office:O, belonging:O, to:O, one:O, firm:O, and:O, using:O, this:O, infection:O, to:O, then:O, move:O, on:O, to:O, its:O, US:O, office:O, and:O, European:B-Area, headquarters:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , technology is not the only sector the group has focused on and Symantec has found evidence that Butterfly has attacked three major European pharmaceutical firms .' [/INST] [However:O, ,:O, technology:B-Idus, is:O, not:O, the:O, only:O, sector:O, the:O, group:O, has:O, focused:O, on:O, and:O, Symantec:B-SecTeam, has:O, found:O, evidence:O, that:O, Butterfly:O, has:O, attacked:O, three:O, major:O, European:O, pharmaceutical:B-Org, firms: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: 'Butterfly has also shown an interest in the commodities sector , attacking two major companies involved in gold and oil in late 2014 .' [/INST] [Butterfly:B-HackOrg, has:O, also:O, shown:O, an:O, interest:O, in:O, the:O, commodities:B-Org, sector:I-Org, ,:O, attacking:O, two:O, major:O, companies:O, involved:O, in:O, gold:B-Idus, and:O, oil:B-Idus, in:O, late:O, 2014:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The company specializes in finance and natural resources specific to that region .' [/INST] [The:O, company:O, specializes:O, in:O, finance:B-Idus, and:O, natural:B-Purp, resources:I-Purp, specific:O, to:O, that: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: 'The latter was one of at least three law firms Butterfly has targeted over the past three years .' [/INST] [The:O, latter:O, was:O, one:O, of:O, at:O, least:O, three:O, law:B-Org, firms:I-Org, Butterfly:B-HackOrg, has:O, targeted:O, over:O, the:O, past:O, three:O, years:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In many attacks , the group has succeeded in compromising Microsoft Exchange or Lotus Domino email servers in order to intercept company emails and possibly use them to send counterfeit emails .' [/INST] [In:O, many:O, attacks:B-OffAct, ,:O, the:O, group:O, has:O, succeeded:O, in:O, compromising:O, Microsoft:B-Tool, Exchange:I-Tool, or:O, Lotus:B-Tool, Domino:I-Tool, email:I-Tool, servers:I-Tool, in:O, order:O, to:O, intercept:O, company:O, emails:B-Way, and:O, possibly:O, use:O, them:O, to:O, send:O, counterfeit:O, emails: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: 'A powerful threat actor known as , Wild Neutron , ( also known as , Jripbot , and , Morpho , ) has been active since at least 2011 , infecting high profile companies for several years by using a combination of exploits , watering holes and multi-platform malware .' [/INST] [A:O, powerful:O, threat:O, actor:O, known:O, as:O, ,:O, Wild:O, Neutron:O, ,:O, (:O, also:O, known:O, as:O, ,:O, Jripbot:B-HackOrg, ,:O, and:O, ,:O, Morpho:B-HackOrg, ,:O, ):O, has:O, been:O, active:O, since:O, at:O, least:O, 2011:B-Time, ,:O, infecting:O, high:B-Org, profile:I-Org, companies:I-Org, for:O, several:O, years:O, by:O, using:O, a:O, combination:O, of:O, exploits:O, ,:O, watering:B-Way, holes:I-Way, and:O, multi-platform: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: 'Based on the profile of the victims and the type of information targeted by the attackers , Symantec believes that Butterfly is financially motivated , stealing information it can potentially profit from .' [/INST] [Based:O, on:O, the:O, profile:O, of:O, the:O, victims:O, and:O, the:O, type:O, of:O, information:O, targeted:O, by:O, the:O, attackers:O, ,:O, Symantec:B-SecTeam, believes:O, that:O, Butterfly:O, is:O, financially:B-Purp, motivated:I-Purp, ,:O, stealing:B-Purp, information:I-Purp, it:O, can:O, potentially:O, profit:O, from:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Wild Neutron hit the spotlight in 2013 , when it successfully infected companies such as Apple , Facebook , Twitter and Microsoft .' [/INST] [Wild:O, Neutron:O, hit:O, the:O, spotlight:O, in:O, 2013:B-Time, ,:O, when:O, it:O, successfully:O, infected:O, companies:O, such:O, as:O, Apple:B-Org, ,:O, Facebook:B-Org, ,:O, Twitter:B-Org, and:O, Microsoft: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: 'Wild Neutron 's attacks in 2015 uses a stolen code signing certificate belonging to Taiwanese electronics maker Acer and an unknown Flash Player exploit .' [/INST] [Wild:B-HackOrg, Neutron:I-HackOrg, 's:O, attacks:B-OffAct, in:O, 2015:B-Time, uses:O, a:O, stolen:B-Tool, code:I-Tool, signing:I-Tool, certificate:I-Tool, belonging:O, to:O, Taiwanese:B-Area, electronics:B-Idus, maker:O, Acer:O, and:O, an:O, unknown:O, Flash:B-Exp, Player:I-Exp, exploit:I-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'During the 2013 attacks , the Wild Neutron actor successfully compromised and leveraged the website www.iphonedevsdk.com , which is an iPhone developers forum .' [/INST] [During:O, the:O, 2013:B-OffAct, attacks:I-OffAct, ,:O, the:O, Wild:O, Neutron:O, actor:O, successfully:O, compromised:O, and:O, leveraged:O, the:O, website:O, www.iphonedevsdk.com:O, ,:O, which:O, is:O, an:O, iPhone:O, developers:O, forum:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Wild Neutron 's attack took advantage of a Java zero-day exploit and used hacked forums as watering holes .' [/INST] [Wild:B-HackOrg, Neutron:I-HackOrg, 's:O, attack:B-OffAct, took:O, advantage:O, of:O, a:O, Java:B-Exp, zero-day:I-Exp, exploit:I-Exp, and:O, used:O, hacked:O, forums:O, as:O, watering:B-Way, holes: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: 'While the group used watering hole attacks in 2013 , it's still unclear how victims get redirected to the exploitation kits in the new 2014-2015 attacks .' [/INST] [While:O, the:O, group:O, used:O, watering:B-OffAct, hole:I-OffAct, attacks:I-OffAct, in:O, 2013:B-Time, ,:O, it's:O, still:O, unclear:O, how:O, victims:O, get:O, redirected:O, to:O, the:O, exploitation:O, kits:O, in:O, the:O, new:O, 2014-2015:B-OffAct, attacks:I-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Wild Neutron 's tools include a password harvesting trojan , a reverse-shell backdoor and customized implementations of OpenSSH , WMIC and SMB .' [/INST] [Wild:B-HackOrg, Neutron:I-HackOrg, 's:O, tools:O, include:O, a:O, password:B-Tool, harvesting:I-Tool, trojan:I-Tool, ,:O, a:O, reverse-shell:B-Tool, backdoor:I-Tool, and:O, customized:B-Tool, implementations:I-Tool, of:I-Tool, OpenSSH:I-Tool, ,:O, WMIC:B-Tool, and:O, SMB: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: 'Instead of Flash exploits , older Wild Neutron exploitation and watering holes used what was a Java zero-day at the end of 2012 and the beginning of 2013 , detected by Kaspersky Lab products as Exploit.Java.CVE-2012-3213.b .' [/INST] [Instead:O, of:O, Flash:B-Exp, exploits:I-Exp, ,:O, older:O, Wild:O, Neutron:O, exploitation:O, and:O, watering:B-Way, holes:I-Way, used:O, what:O, was:O, a:O, Java:B-Exp, zero-day:I-Exp, at:O, the:O, end:B-Time, of:I-Time, 2012:I-Time, and:O, the:O, beginning:B-Time, of:I-Time, 2013:I-Time, ,:O, detected:O, by:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, products:O, as:O, Exploit.Java.CVE-2012-3213.b:B-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The victims for the 2014-2015 versions are generally IT and real estate/investment companies and in both cases , a small number of computers have been infected throughout Wild Neutron .' [/INST] [The:O, victims:O, for:O, the:O, 2014-2015:B-Time, versions:O, are:O, generally:O, IT:B-Org, and:O, real:B-Org, estate/investment:I-Org, companies:I-Org, and:O, in:O, both:O, cases:O, ,:O, a:O, small:O, number:O, of:O, computers:O, have:O, been:O, infected:O, throughout:O, Wild:B-HackOrg, Neutron: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: 'Wild Neutron 's targeting of major IT companies , spyware developers ( FlexiSPY ) , jihadist forums ( the , Ansar Al-Mujahideen English Forum , ) and Bitcoin companies indicate a flexible yet unusual mindset and interests .' [/INST] [Wild:B-HackOrg, Neutron:I-HackOrg, 's:O, targeting:O, of:O, major:O, IT:B-Org, companies:I-Org, ,:O, spyware:B-Org, developers:I-Org, (:O, FlexiSPY:B-Org, ):O, ,:O, jihadist:B-Org, forums:I-Org, (:O, the:O, ,:O, Ansar:B-Org, Al-Mujahideen:I-Org, English:I-Org, Forum:I-Org, ,:O, ):O, and:O, Bitcoin:B-Org, companies:I-Org, indicate:O, a:O, flexible:O, yet:O, unusual:O, mindset:O, and:O, interests:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 continue to track the Wild Neutron group , which is still active as of June 2015 .' [/INST] [We:O, continue:O, to:O, track:O, the:O, Wild:B-HackOrg, Neutron:I-HackOrg, group:I-HackOrg, ,:O, which:O, is:O, still:O, active:O, as:O, of:O, June:B-Time, 2015:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'A ransomware variant dubbed PyLocky was observed in September 2018 being distributed by a phishing campaign using an invoicing theme .' [/INST] [A:O, ransomware:O, variant:O, dubbed:O, PyLocky:B-Tool, was:O, observed:O, in:O, September:B-Time, 2018:I-Time, being:O, distributed:O, by:O, a:O, phishing:B-OffAct, campaign:I-OffAct, using:O, an:O, invoicing:O, theme:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'PyLocky was found to be targeting entities in France and Germany .' [/INST] [PyLocky:B-Tool, was:O, found:O, to:O, be:O, targeting:O, entities:O, in:O, France:B-Area, and:O, Germany: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: 'Fxmsp specialize in breaching highly secure protected networks to access private corporate and government information .' [/INST] [Fxmsp:B-HackOrg, specialize:O, in:O, breaching:O, highly:O, secure:O, protected:O, networks:O, to:O, access:O, private:O, corporate:O, and:O, government:B-Purp, information:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Fxmsp is a hacking collective that has operated in various top-tier Russian- and English-speaking underground communities since 2017 .' [/INST] [Fxmsp:B-HackOrg, is:O, a:O, hacking:O, collective:O, that:O, has:O, operated:O, in:O, various:O, top-tier:O, Russian-:O, and:O, English-speaking:O, underground:O, communities:O, since: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: 'Throughout 2017 and 2018 , Fxmsp established a network of trusted proxy resellers to promote their breaches on the criminal underground .' [/INST] [Throughout:O, 2017:B-Time, and:O, 2018:B-Time, ,:O, Fxmsp:B-HackOrg, established:O, a:O, network:O, of:O, trusted:O, proxy:O, resellers:O, to:O, promote:O, their:O, breaches:O, on:O, the:O, criminal:O, underground:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'On April 24 , 2019 , Fxmsp claimed to have secured access to three leading antivirus companies .' [/INST] [On:O, April:B-Time, 24:I-Time, ,:O, 2019:B-Time, ,:O, Fxmsp:B-HackOrg, claimed:O, to:O, have:O, secured:O, access:O, to:O, three:O, leading:O, antivirus:B-Org, companies: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: 'According to the Fxmsp , they worked tirelessly for the first quarter of 2019 to breach these companies and finally succeeded and obtained access to the companies' internal networks .' [/INST] [According:O, to:O, the:O, Fxmsp:O, ,:O, they:O, worked:O, tirelessly:O, for:O, the:O, first:O, quarter:O, of:O, 2019:B-Time, to:O, breach:O, these:O, companies:O, and:O, finally:O, succeeded:O, and:O, obtained:O, access:O, to:O, the:O, companies':O, internal:O, networks:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Booz Allen Hamilton in 2014 and AhnLab in 2015 reported on Bisonal using a simple XOR cipher to hide the C2 address strings in the body . For example , Bisonal malware in 2012 used send() and recv() APIs to communicate with its C2 This Bisonal variant used in the latest attack communicates with one of the following hard-coded C2 addresses by using the HTTP POST method on TCP port 443 .' [/INST] [Booz:B-SecTeam, Allen:I-SecTeam, Hamilton:I-SecTeam, in:O, 2014:B-Time, and:O, AhnLab:B-SecTeam, in:O, 2015:B-Time, reported:O, on:O, Bisonal:O, using:O, a:O, simple:O, XOR:O, cipher:O, to:O, hide:O, the:O, C2:O, address:O, strings:O, in:O, the:O, body:O, .:O, For:O, example:O, ,:O, Bisonal:B-HackOrg, malware:I-HackOrg, in:O, 2012:B-Time, used:O, send():O, and:O, recv():O, APIs:O, to:O, communicate:O, with:O, its:O, C2:O, This:O, Bisonal:B-SamFile, variant:O, used:O, in:O, the:O, latest:O, attack:O, communicates:O, with:O, one:O, of:O, the:O, following:O, hard-coded:O, C2:O, addresses:O, by:O, using:O, the:O, HTTP:B-Way, POST:I-Way, method:O, on:O, TCP:O, port:O, 443:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Previous reports have discussed Bisonal malware used in attacks against Japan , South Korea and Russia .' [/INST] [Previous:O, reports:O, have:O, discussed:O, Bisonal:B-SamFile, malware:I-SamFile, used:O, in:O, attacks:O, against:O, Japan:B-Area, ,:O, South:B-Area, Korea:I-Area, and: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: 'This particular sample we found targeted an organization in Russia and there is a specific system language check for Cyrillic and no others .' [/INST] [This:O, particular:O, sample:B-SamFile, we:O, found:O, targeted:O, an:O, organization:O, in:O, Russia:B-Area, and:O, there:O, is:O, a:O, specific:O, system:O, language:O, check:O, for:O, Cyrillic:O, and:O, no:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'If it's Cyrillic and the command to the shell is not ‘ipconfig’ , the threat converts the command result text encoding from Cyrillic to UTF-16 .' [/INST] [If:O, it's:B-SamFile, Cyrillic:B-Tool, and:O, the:O, command:O, to:O, the:O, shell:O, is:O, not:O, ‘ipconfig’:O, ,:O, the:O, threat:O, converts:O, the:O, command:O, result:O, text:O, encoding:O, from:O, Cyrillic:O, to:O, UTF-16: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: 'Similar to the Bisonal variant targeting the Russian organization , this sample was also disguised as PDF document .' [/INST] [Similar:O, to:O, the:O, Bisonal:B-SamFile, variant:O, targeting:O, the:O, Russian:B-Area, organization:I-Area, ,:O, this:O, sample:O, was:O, also:O, disguised:O, as:O, PDF:O, document:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 contents of the decoy PDF is a job descriptions with the South Korean Coast Guard .' [/INST] [The:O, contents:O, of:O, the:B-SamFile, decoy:I-SamFile, PDF:I-SamFile, is:O, a:O, job:O, descriptions:O, with:O, the:O, South:B-Area, Korean:I-Area, Coast:B-Idus, Guard: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: 'The installed EXE file is almost exactly the same as the DLL version of Bisonal variant used against the Russian organization .' [/INST] [The:O, installed:B-SamFile, EXE:I-SamFile, file:I-SamFile, is:O, almost:O, exactly:O, the:O, same:O, as:O, the:O, DLL:O, version:O, of:O, Bisonal:B-SamFile, variant:I-SamFile, used:O, against:O, the:O, Russian:B-Area, 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: 'The targets are military or defense industry in particular countries , it used DDNS for C2 servers , and tracked connections from their victims by using target or campaign codes , as well as disguising the malware as document file , and using a dropper to install the malware and decoy file .' [/INST] [The:O, targets:O, are:O, military:O, or:O, defense:O, industry:O, in:O, particular:B-Area, countries:I-Area, ,:O, it:O, used:O, DDNS:O, for:O, C2:O, servers:O, ,:O, and:O, tracked:O, connections:O, from:O, their:O, victims:O, by:O, using:O, target:O, or:O, campaign:O, codes:O, ,:O, as:O, well:O, as:O, disguising:O, the:O, malware:B-Way, as:O, document:O, file:O, ,:O, and:O, using:O, a:O, dropper:B-Tool, to:O, install:O, the:O, malware:O, and:O, decoy: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: 'A previous campaign of this APT group was uncovered by Talos in June 2017 , and since then very little of this operation was seen in the wild .' [/INST] [A:O, previous:O, campaign:O, of:O, this:O, APT:O, group:O, was:O, uncovered:O, by:O, Talos:B-SecTeam, in:O, June:B-Time, 2017:I-Time, ,:O, and:O, since:O, then:O, very:O, little:O, of:O, this:O, operation:O, was:O, seen:O, in:O, the:O, wild:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'ined in the archive is called DriverInstallerU.exe” but its metadata shows that its original name is Interenet Assistant.exe” .' [/INST] [ined:O, in:O, the:O, archive:O, is:O, called:O, DriverInstallerU.exe”:B-SamFile, but:O, its:O, metadata:O, shows:O, that:O, its:O, original:O, name:O, is:O, Interenet:B-SamFile, Assistant.exe”: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: 'After reviewing all the malware functionalities , we are confident in saying that the attackers look for victims who answer well-defined characteristics and believe that further stages of the attack are delivered only to those who fit the specific victim profile .' [/INST] [After:O, reviewing:O, all:O, the:O, malware:O, functionalities:O, ,:O, we:O, are:O, confident:O, in:O, saying:O, that:O, the:O, attackers:B-HackOrg, look:O, for:O, victims:B-Org, who:I-Org, answer:I-Org, well-defined:O, characteristics:O, and:O, believe:O, that:O, further:O, stages:O, of:O, the:O, attack:O, are:O, delivered:O, only:O, to:O, those:O, who:O, fit:O, the:O, specific:O, victim:O, profile:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 sample , however , the module names were changed from actors and characters’ names to car models , namely BMW_x1” , BMW_x2” and up to BMW_x8” .' [/INST] [In:O, this:O, sample:O, ,:O, however:O, ,:O, the:O, module:O, names:O, were:O, changed:O, from:O, actors:O, and:O, characters’:O, names:O, to:O, car:O, models:O, ,:O, namely:O, BMW_x1”:B-SamFile, ,:O, BMW_x2”:B-SamFile, and:O, up:O, to:O, BMW_x8”: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: 'But , thanks to the attackers known affection for decoy documents that pose as news summaries , we were able to date the campaign back to March 2018 .' [/INST] [But:O, ,:O, thanks:O, to:O, the:O, attackers:B-HackOrg, known:O, affection:O, for:O, decoy:B-Purp, documents:I-Purp, that:O, pose:O, as:O, news:O, summaries:O, ,:O, we:O, were:O, able:O, to:O, date:O, the:O, campaign:O, back:O, to:O, March: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: 'With the experience gained from the APT attack that began in March 2017 , it seems this campaign has evolved into an attack with new capabilities , and an even more specific target , over a year later .' [/INST] [With:O, the:O, experience:O, gained:O, from:O, the:O, APT:B-OffAct, attack:I-OffAct, that:O, began:O, in:O, March:B-Time, 2017:I-Time, ,:O, it:O, seems:O, this:O, campaign:O, has:O, evolved:O, into:O, an:O, attack:O, with:O, new:O, capabilities:O, ,:O, and:O, an:O, even:O, more:O, specific:O, target:O, ,:O, over:O, a:O, year: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: 'These unknown actors continued launching DDoS attacks over the next few years .' [/INST] [These:O, unknown:B-HackOrg, actors:I-HackOrg, continued:O, launching:O, DDoS:B-OffAct, attacks:O, over:O, the:O, next:O, few:O, years:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'For simplicity , Kaspersky is calling them the BlackEnergy APT group .' [/INST] [For:O, simplicity:O, ,:O, Kaspersky:B-SecTeam, is:O, calling:O, them:O, the:O, BlackEnergy:I-HackOrg, 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: 'Since the middle of 2015 , one of the preferred attack vectors for BlackEnergy in Ukraine has been Excel documents with macros that drop the Trojan to disk if the user chooses to run the script in the document .' [/INST] [Since:O, the:O, middle:B-Time, of:I-Time, 2015:I-Time, ,:O, one:O, of:O, the:O, preferred:O, attack:O, vectors:O, for:O, BlackEnergy:B-HackOrg, in:O, Ukraine:B-Area, has:O, been:O, Excel:O, documents:O, with:O, macros:O, that:O, drop:O, the:O, Trojan:O, to:O, disk:O, if:O, the:O, user:O, chooses:O, to:O, run:O, the:O, script:O, in:O, the:O, document:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 very good analysis and overview of the BlackEnergy attacks in Ukraine throughout 2014 and 2015 was published by the Ukrainian security firm Cys Centrum the text is only available in Russian for now , but can be read via Google Translate .' [/INST] [A:O, very:O, good:O, analysis:O, and:O, overview:O, of:O, the:O, BlackEnergy:O, attacks:O, in:O, Ukraine:O, throughout:O, 2014:B-Time, and:O, 2015:B-Time, was:O, published:O, by:O, the:O, Ukrainian:O, security:O, firm:O, Cys:B-SecTeam, Centrum:I-SecTeam, the:O, text:O, is:O, only:O, available:O, in:O, Russian:O, for:O, now:O, ,:O, but:O, can:O, be:O, read:O, via:O, Google:O, Translate:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 signs of destructive payloads with BlackEnergy go back as far as June 2014 .' [/INST] [The:O, earliest:O, signs:O, of:O, destructive:B-OffAct, payloads:I-OffAct, with:O, BlackEnergy:B-HackOrg, go:O, back:O, as:O, far:O, as:O, June:B-Time, 2014:I-Time, .:O] </s> |
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