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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: 'These VNC exectuables would either be included in the SFX file or downloaded by the batch script .' [/INST] [These:O, VNC:B-Tool, exectuables:O, would:O, either:O, be:O, included:O, in:O, the:O, SFX:B-Way, file:I-Way, or:O, downloaded:O, by:O, the:O, batch:B-Way, script:I-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The batch script would then attempt to have the VNC program connect to a command and control ( C2 ) server to enable the server to control the compromised system .' [/INST] [The:O, batch:O, script:O, would:O, then:O, attempt:O, to:O, have:O, the:O, VNC:B-Tool, program:O, connect:B-Features, to:I-Features, a:I-Features, command:I-Features, and:I-Features, control:I-Features, (:O, C2:O, ):O, server:O, to:O, enable:O, the:O, server:O, to:O, control:O, the:O, compromised:O, system:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While the most recent samples observed still use batch scripts and SFX files , the Gamaredon Group has moved away from applications like wget , Remote Manipulator Tool , VNC and ChkFlsh.exe .' [/INST] [While:O, the:O, most:O, recent:O, samples:O, observed:O, still:O, use:O, batch:B-Tool, scripts:I-Tool, and:O, SFX:B-Tool, files:I-Tool, ,:O, the:O, Gamaredon:B-HackOrg, Group:I-HackOrg, has:O, moved:O, away:O, from:O, applications:O, like:O, wget:B-Tool, ,:O, Remote:B-Tool, Manipulator:I-Tool, Tool:I-Tool, ,:O, VNC:B-Tool, and:O, ChkFlsh.exe: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: 'The threat group using these implants has been active since at least 2014 and has been seen targeting individuals likely involved in the Ukrainian government .' [/INST] [The:O, threat:B-HackOrg, group:I-HackOrg, using:O, these:O, implants:O, has:O, been:O, active:O, since:O, at:O, least:O, 2014:B-Time, and:O, has:O, been:O, seen:O, targeting:O, individuals:O, likely:O, involved:O, in:O, the:O, Ukrainian:B-Area, government:B-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Some of the samples share delivery mechanisms and infrastructure with samples which are detected by a few antivirus vendors as Gamaredon .' [/INST] [Some:O, of:O, the:O, samples:O, share:O, delivery:O, mechanisms:O, and:O, infrastructure:O, with:O, samples:O, which:O, are:O, detected:O, by:O, a:O, few:O, antivirus:O, vendors:O, as:O, Gamaredon: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: 'Periodically , researchers at Palo Alto Networks hunt through WildFire execution reports , using AutoFocus , to identify untagged samples ' artifacts in the hopes of identifying previously undiscovered malware families , behaviors , and campaigns .' [/INST] [Periodically:O, ,:O, researchers:O, at:O, Palo:B-SecTeam, Alto:I-SecTeam, Networks:I-SecTeam, hunt:O, through:O, WildFire:B-SecTeam, execution:O, reports:O, ,:O, using:O, AutoFocus:O, ,:O, to:O, identify:O, untagged:O, samples:O, ':O, artifacts:O, in:O, the:O, hopes:O, of:O, identifying:O, previously:O, undiscovered:O, malware:O, families:O, ,:O, behaviors:O, ,:O, and: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: 'Just a few months later , in February 2015 , we announced the discovery of Carbanak , a cyber-criminal gang that used custom malware and APT techniques to steal millions of dollars while infecting hundreds of financial institutions in at least 30 countries .' [/INST] [Just:O, a:O, few:O, months:O, later:O, ,:O, in:O, February:B-Time, 2015:I-Time, ,:O, we:O, announced:O, the:O, discovery:O, of:O, Carbanak:B-Exp, ,:O, a:O, cyber-criminal:B-HackOrg, gang:I-HackOrg, that:O, used:O, custom:O, malware:O, and:O, APT:B-Way, techniques:I-Way, to:O, steal:B-Purp, millions:I-Purp, of:I-Purp, dollars:I-Purp, while:O, infecting:O, hundreds:O, of:O, financial:B-Org, institutions:I-Org, in:O, at:O, least:O, 30: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: 'Today at the Security Analyst Summit ( SAS 2016 ) , Kaspersky Lab is announcing the discovery of two new gangs engaged in APT-style bank robberies – Metel and GCMAN – and the reemergence of the Carbanak group with new targets in its sights .' [/INST] [Today:O, at:O, the:O, Security:O, Analyst:O, Summit:O, (:O, SAS:O, 2016:O, ):O, ,:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, is:O, announcing:O, the:O, discovery:O, of:O, two:O, new:O, gangs:O, engaged:O, in:O, APT-style:O, bank:B-Idus, robberies:O, –:O, Metel:B-HackOrg, and:O, GCMAN:B-HackOrg, –:O, and:O, the:O, reemergence:O, of:O, the:O, Carbanak:B-HackOrg, group:I-HackOrg, with:O, new:O, targets:O, in:O, its:O, sights:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 2015 , Kaspersky Lab researchers conducted Incident Response for 29 organizations located in Russia and infected by these three groups .' [/INST] [In:O, 2015:B-Time, ,:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, researchers:O, conducted:O, Incident:O, Response:O, for:O, 29:O, organizations:O, located:O, in:O, Russia:B-Area, and:O, infected:O, by:O, these:O, three:O, groups: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: 'Kaspersky Lab is releasing crucial Indicators of Compromise ( IOCs ) and other data to help organizations search for traces of these attack groups in their corporate networks .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, is:O, releasing:O, crucial:O, Indicators:O, of:O, Compromise:O, (:O, IOCs:O, ):O, and:O, other:O, data:O, to:O, help:O, organizations:O, search:O, for:O, traces:O, of:O, these:O, attack:B-HackOrg, groups:I-HackOrg, in:O, their:O, corporate: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: 'In all , Kaspersky Lab discovered Metel in more than 30 financial institutions .' [/INST] [In:O, all:O, ,:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, discovered:O, Metel:B-HackOrg, in:O, more:O, than:O, 30: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: 'It is highly likely that this threat is far more widespread and we urge financial institutions around the world to scan their networks for signs of the Metel malware .' [/INST] [It:O, is:O, highly:O, likely:O, that:O, this:O, threat:O, is:O, far:O, more:O, widespread:O, and:O, we:O, urge:O, financial:B-Org, institutions:I-Org, around:O, the:O, world:O, to:O, scan:O, their:O, networks:O, for:O, signs:O, of:O, the:O, Metel:B-Tool, malware:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'A second group , which we call GCMAN because the malware is based on code compiled on the GCC compiler , emerged recently using similar techniques to the Metel Group to infect banking institutions and attempt to transfer money to e-currency services .' [/INST] [A:O, second:O, group:B-HackOrg, ,:O, which:O, we:O, call:O, GCMAN:B-HackOrg, because:O, the:O, malware:O, is:O, based:O, on:O, code:O, compiled:O, on:O, the:O, GCC:O, compiler:O, ,:O, emerged:O, recently:O, using:O, similar:O, techniques:O, to:O, the:O, Metel:B-HackOrg, Group:I-HackOrg, to:O, infect:O, banking:B-Org, institutions:I-Org, and:O, attempt:O, to:O, transfer:O, money:O, to:O, e-currency:O, services:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 investigations revealed that the attackers drove around several cities in Russia , stealing money from ATMs belonging to different banks .' [/INST] [Our:O, investigations:O, revealed:O, that:O, the:O, attackers:B-HackOrg, drove:O, around:O, several:O, cities:O, in:O, Russia:B-Area, ,:O, stealing:B-Purp, money:I-Purp, from:O, ATMs:O, belonging:O, to:O, different:O, banks:B-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once inside the network , the GCMAN group uses legitimate and penetration testing tools such as Putty , VNC , and Meterpreter for lateral movement .' [/INST] [Once:O, inside:O, the:O, network:O, ,:O, the:O, GCMAN:B-HackOrg, group:I-HackOrg, uses:O, legitimate:O, and:O, penetration:O, testing:O, tools:O, such:O, as:O, Putty:B-Tool, ,:O, VNC:B-Tool, ,:O, and:O, Meterpreter:B-Tool, for:O, lateral:O, movement:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 investigation revealed an attack where the GCMAN group then planted a cron script into bank 's server , sending financial transactions at the rate of $200 per minute .' [/INST] [Our:O, investigation:O, revealed:O, an:O, attack:B-OffAct, where:O, the:O, GCMAN:B-HackOrg, group:I-HackOrg, then:O, planted:O, a:O, cron:B-Way, script:I-Way, into:O, bank:B-Idus, 's:O, server:O, ,:O, sending:O, financial:O, transactions:O, at:O, the:O, rate:O, of:O, $200:O, per:O, minute:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 GCMAN group used an MS SQL injection in commercial software running on one of bank 's public web services , and about a year and a half later , they came back to cash out .' [/INST] [The:O, GCMAN:B-HackOrg, group:I-HackOrg, used:O, an:O, MS:B-Way, SQL:I-Way, injection:I-Way, in:O, commercial:O, software:O, running:O, on:O, one:O, of:O, bank:B-Idus, 's:O, public:O, web:O, services:O, ,:O, and:O, about:O, a:O, year:O, and:O, a:O, half:O, later:O, ,:O, they:O, came:O, back:O, to:O, cash:O, out:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 that time they poked 70 internal hosts , compromised 56 accounts , making their way from 139 attack sources ( TOR and compromised home routers ) .' [/INST] [During:O, that:O, time:O, they:O, poked:O, 70:O, internal:O, hosts:O, ,:O, compromised:O, 56:O, accounts:O, ,:O, making:O, their:O, way:O, from:O, 139:O, attack:O, sources:O, (:O, TOR:O, and:O, compromised:O, home:O, routers: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: 'However , in September last year , our friends at CSIS published a blog detailing a new Carbanak variant affecting one of its customers .' [/INST] [However:O, ,:O, in:O, September:B-Time, last:O, year:O, ,:O, our:O, friends:O, at:O, CSIS:B-SecTeam, published:O, a:O, blog:O, detailing:O, a:O, new:O, Carbanak:B-Exp, variant:O, affecting:O, one:O, of:O, its:O, customers: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: 'Kaspersky Lab 's research team responded to three financial institutions in Russia that were infected with the GCMAN malware .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, 's:O, research:O, team:O, responded:O, to:O, three:O, financial:B-Org, institutions:I-Org, in:O, Russia:B-Area, that:O, were:O, infected:O, with:O, the:O, GCMAN:B-Tool, malware:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In one remarkable case , the Carbanak 2.0 gang used its access to a financial institution that stores information about shareholders to change the ownership details of a large company .' [/INST] [In:O, one:O, remarkable:O, case:O, ,:O, the:O, Carbanak:B-Exp, 2.0:O, gang:O, used:O, its:O, access:O, to:O, a:O, financial:B-Org, institution:I-Org, that:O, stores:O, information:O, about:O, shareholders:O, to:O, change:O, the:O, ownership:O, details:O, of:O, a:O, large:O, company:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Recently Subaat drew our attention due to renewed targeted attack activity .' [/INST] [Recently:O, Subaat:B-HackOrg, drew:O, our:O, attention:O, due:O, to:O, renewed:O, targeted:B-OffAct, attack:I-OffAct, activity:I-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Technical analysis on some of the attacks as well as attribution links with Pakistan actors have been already depicted by 360 and Tuisec , in which they found interesting connections to a larger group of attackers Unit 42 researchers have been tracking , which we are calling Gorgon Group .' [/INST] [Technical:O, analysis:O, on:O, some:O, of:O, the:O, attacks:B-OffAct, as:O, well:O, as:O, attribution:O, links:O, with:O, Pakistan:B-Area, actors:B-HackOrg, have:O, been:O, already:O, depicted:O, by:O, 360:B-SecTeam, and:O, Tuisec:B-SecTeam, ,:O, in:O, which:O, they:O, found:O, interesting:O, connections:O, to:O, a:O, larger:O, group:B-HackOrg, of:O, attackers:B-HackOrg, Unit:B-SecTeam, 42:I-SecTeam, researchers:O, have:O, been:O, tracking:O, ,:O, which:O, we:O, are:O, calling:O, Gorgon: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: 'Starting in February 2018 , Palo Alto Networks identified a campaign of attacks performed by members of Gorgon Group targeting governmental organizations in the United Kingdom , Spain , Russia , and the United States .' [/INST] [Starting:O, in:O, February:B-Time, 2018:I-Time, ,:O, Palo:B-SecTeam, Alto:I-SecTeam, Networks:I-SecTeam, identified:O, a:O, campaign:B-OffAct, of:O, attacks:B-OffAct, performed:O, by:O, members:O, of:O, Gorgon:B-HackOrg, Group:I-HackOrg, targeting:O, governmental:B-Org, organizations:I-Org, in:O, the:O, United:B-Area, Kingdom:I-Area, ,:O, Spain:B-Area, ,:O, Russia:B-Area, ,:O, and:O, the:O, United:B-Area, States:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Starting in February 2018 , Palo Alto Networks Unit 42 identified a' [/INST] [Starting:O, in:O, February:B-Time, 2018:I-Time, ,:O, Palo:B-SecTeam, Alto:I-SecTeam, Networks:I-SecTeam, Unit:I-SecTeam, 42:I-SecTeam, identified:O, a:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'of attacks performed by members of Gorgon Group targeting governmental organizations in the United Kingdom , Spain , Russia , and the United States .' [/INST] [of:O, attacks:B-OffAct, performed:O, by:O, members:O, of:O, Gorgon:B-HackOrg, Group:I-HackOrg, targeting:O, governmental:B-Org, organizations:I-Org, in:O, the:O, United:B-Area, Kingdom:I-Area, ,:O, Spain:B-Area, ,:O, Russia:B-Area, ,:O, and:O, the:O, United:B-Area, States:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The GCMAN group has moved beyond banks and is now targeting the budgeting and accounting departments in any organization of interest to them , using the same APT-style tools and techniques .' [/INST] [The:O, GCMAN:B-HackOrg, group:I-HackOrg, has:O, moved:O, beyond:O, banks:B-Idus, and:O, is:O, now:O, targeting:O, the:O, budgeting:B-Org, and:O, accounting:B-Org, departments:I-Org, in:O, any:O, organization:O, of:O, interest:O, to:O, them:O, ,:O, using:O, the:O, same:O, APT-style: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: 'Starting in February 2018 , Unit 42 identified a campaign of attacks performed by members of Gorgon Group targeting governmental organizations in the United Kingdom , Spain , Russia , and the United States .' [/INST] [Starting:O, in:O, February:B-Time, 2018:I-Time, ,:O, Unit:B-SecTeam, 42:I-SecTeam, identified:O, a:O, campaign:B-OffAct, of:O, attacks:B-OffAct, performed:O, by:O, members:O, of:O, Gorgon:B-HackOrg, Group:I-HackOrg, targeting:O, governmental:B-Org, organizations:I-Org, in:O, the:O, United:B-Area, Kingdom:I-Area, ,:O, Spain:B-Area, ,:O, Russia:B-Area, ,:O, and:O, the:O, United:B-Area, States:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT38 's increasingly aggressive targeting against banks .' [/INST] [APT38:B-HackOrg, 's:O, increasingly:O, aggressive:O, targeting:O, against:O, banks:B-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Gorgon Group used common URL shortening services to download payloads .' [/INST] [Gorgon:B-HackOrg, Group:I-HackOrg, used:O, common:O, URL:B-Way, shortening:I-Way, services:I-Way, to:O, download:O, payloads:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The GCMAN group has moved beyond banks and is now targeting the budgeting and accounting departments in any organization of interest to them , using the same APT-style tools and techniques .' [/INST] [The:O, GCMAN:B-HackOrg, group:I-HackOrg, has:O, moved:O, beyond:O, banks:B-Idus, and:O, is:O, now:O, targeting:O, the:O, budgeting:B-Org, and:O, accounting:B-Org, departments:I-Org, in:O, any:O, organization:O, of:O, interest:O, to:O, them:O, ,:O, using:O, the:O, same:O, APT-style: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: 'APT38 has paralleled North Korea 's worsening financial condition .' [/INST] [APT38:B-HackOrg, has:O, paralleled:O, North:B-Area, Korea:I-Area, 's:O, worsening:O, financial:O, condition:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 much of the C2 infrastructure we identified several crimeware family samples .' [/INST] [On:O, much:O, of:O, the:O, C2:O, infrastructure:O, we:O, identified:O, several:O, crimeware:O, family:O, samples:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While investigating the domains and infrastructure used by the phishing components of Gorgon Group , Unit 42 researchers witnessed several common operational security flaws with Gorgon Group 's actors throughout their many campaigns .' [/INST] [While:O, investigating:O, the:O, domains:O, and:O, infrastructure:O, used:O, by:O, the:O, phishing:B-Way, components:I-Way, of:O, Gorgon:B-HackOrg, Group:I-HackOrg, ,:O, Unit:B-SecTeam, 42:I-SecTeam, researchers:O, witnessed:O, several:O, common:O, operational:O, security:O, flaws:O, with:O, Gorgon:B-HackOrg, Group:I-HackOrg, 's:I-HackOrg, actors:I-HackOrg, throughout:O, their:O, many: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: '360 and Tuisec already identified some Gorgon Group members .' [/INST] [360:B-SecTeam, and:O, Tuisec:B-SecTeam, already:O, identified:O, some:O, Gorgon:B-HackOrg, Group:I-HackOrg, members: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: 'RATs such as NjRat and infostealers like Lokibot were leveraging the same C2 infrastructure as that of the targeted attacks .' [/INST] [RATs:B-Tool, such:O, as:O, NjRat:B-Tool, and:O, infostealers:O, like:O, Lokibot:B-Tool, were:O, leveraging:O, the:O, same:O, C2:O, infrastructure:O, as:O, that:O, of:O, the:O, targeted:B-OffAct, attacks:I-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'it 's not known if the attackers physically reside in Pakistan .' [/INST] [it:O, 's:O, not:O, known:O, if:O, the:O, attackers:B-HackOrg, physically:O, reside:O, in:O, Pakistan: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: 'Gorgon used numerous decoy documents and phishing emails , both styles of attacks lacked overall sophistication .' [/INST] [Gorgon:B-HackOrg, used:O, numerous:O, decoy:B-Way, documents:I-Way, and:O, phishing:B-Way, emails:I-Way, ,:O, both:O, styles:O, of:O, attacks:B-OffAct, lacked:O, overall:O, sophistication:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 it 's not known if the attackers physically reside in Pakistan , all members of Gorgon Group purport to be in Pakistan based on their online personas .' [/INST] [While:O, it:O, 's:O, not:O, known:O, if:O, the:O, attackers:B-HackOrg, physically:O, reside:O, in:O, Pakistan:B-Area, ,:O, all:O, members:O, of:O, Gorgon:B-HackOrg, Group:I-HackOrg, purport:O, to:O, be:O, in:O, Pakistan:B-Area, based:O, on:O, their:O, online:O, personas:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Starting in mid-February , Unit 42 researchers have been tracking an active campaign sharing a significant portion of infrastructure leveraged by Gorgon Group for criminal and targeted attacks .' [/INST] [Starting:O, in:O, mid-February:B-Time, ,:O, Unit:B-SecTeam, 42:I-SecTeam, researchers:O, have:O, been:O, tracking:O, an:O, active:B-OffAct, campaign:I-OffAct, sharing:O, a:O, significant:O, portion:O, of:O, infrastructure:O, leveraged:O, by:O, Gorgon:B-HackOrg, Group:I-HackOrg, for:O, criminal:B-OffAct, and:I-OffAct, targeted:I-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: 'Unit 42 researchers have been tracking Gorgon Group for criminal and targeted attacks .' [/INST] [Unit:B-SecTeam, 42:I-SecTeam, researchers:O, have:O, been:O, tracking:O, Gorgon:B-HackOrg, Group:I-HackOrg, for:O, criminal:B-OffAct, and:I-OffAct, targeted:I-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: 'As part of the investigation , Unit 42 researchers were able to identify an interesting characteristic about how the Gorgon Group crew uses shared infrastructure between cybercrime and targeted attacks .' [/INST] [As:O, part:O, of:O, the:O, investigation:O, ,:O, Unit:B-SecTeam, 42:I-SecTeam, researchers:O, were:O, able:O, to:O, identify:O, an:O, interesting:O, characteristic:O, about:O, how:O, the:O, Gorgon:B-HackOrg, Group:I-HackOrg, crew:O, uses:O, shared:B-Tool, infrastructure:I-Tool, between:O, cybercrime:B-OffAct, and:I-OffAct, targeted:I-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: 'The crew combines both regular crime and targeted attack objectives using the same domain infrastructure over time , rarely changing their TTPs .' [/INST] [The:O, crew:O, combines:O, both:O, regular:O, crime:O, and:O, targeted:B-OffAct, attack:I-OffAct, objectives:O, using:O, the:O, same:O, domain:B-Tool, infrastructure:I-Tool, over:O, time:O, ,:O, rarely:O, changing:O, their:O, TTPs:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 interesting note about the criminal activity of Gorgon Group is their usage of Bitly .' [/INST] [One:O, interesting:O, note:O, about:O, the:O, criminal:B-OffAct, activity:I-OffAct, of:O, Gorgon:B-HackOrg, Group:I-HackOrg, is:O, their:O, usage:O, of:O, Bitly: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: 'Between April 1 , 2018 and May 30 , 2018 , we observed the domain stevemike-fireforce.info used in a Gorgon Group cybercrime campaign involving more than 2,300 emails and 19 documents in the initial attack .' [/INST] [Between:O, April:B-Time, 1:I-Time, ,:I-Time, 2018:I-Time, and:O, May:B-Time, 30:I-Time, ,:I-Time, 2018:I-Time, ,:O, we:O, observed:O, the:O, domain:O, stevemike-fireforce.info:O, used:O, in:O, a:O, Gorgon:B-OffAct, Group:I-OffAct, cybercrime:I-OffAct, campaign:I-OffAct, involving:O, more:O, than:O, 2,300:O, emails:B-Way, and:O, 19:O, documents:O, in:O, the:O, initial:O, attack:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 that of their targeted attacks , Gorgon Group leveraged Bitly for distribution and shortening of C2 domains .' [/INST] [Similar:O, to:O, that:O, of:O, their:O, targeted:B-OffAct, attacks:I-OffAct, ,:O, Gorgon:B-HackOrg, Group:I-HackOrg, leveraged:O, Bitly:B-Tool, for:O, distribution:O, and:O, shortening:O, of:O, C2:O, domains:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Beginning in early March 2018 , Unit 42 started observing targeted attacks against Russian , Spanish and United States government agencies operating in Pakistan .' [/INST] [Beginning:O, in:O, early:B-Time, March:I-Time, 2018:I-Time, ,:O, Unit:B-SecTeam, 42:I-SecTeam, started:O, observing:O, targeted:B-OffAct, attacks:I-OffAct, against:O, Russian:B-Area, ,:O, Spanish:B-Area, and:O, United:B-Area, States:I-Area, government:B-Org, agencies:I-Org, operating:O, in:O, Pakistan: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: 'Leveraging click counts for the campaign for Bitly , we were able to see Gorgon Group 's activity volume increase throughout April .' [/INST] [Leveraging:O, click:O, counts:O, for:O, the:O, campaign:B-OffAct, for:O, Bitly:B-Tool, ,:O, we:O, were:O, able:O, to:O, see:O, Gorgon:B-HackOrg, Group:I-HackOrg, 's:O, activity:B-OffAct, volume:O, increase:O, throughout: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: 'As we continued to investigate , it became apparent that Gorgon Group had been consistently targeting worldwide governmental organizations operating within Pakistan .' [/INST] [As:O, we:O, continued:O, to:O, investigate:O, ,:O, it:O, became:O, apparent:O, that:O, Gorgon:B-HackOrg, Group:I-HackOrg, had:O, been:O, consistently:O, targeting:O, worldwide:O, governmental:B-Org, organizations:I-Org, operating:O, within:O, Pakistan: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: 'Starting in mid-February .' [/INST] [Starting:O, in:O, mid-February: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: 'Additionally , during that time , members of Gorgon Group were also performing criminal operations against targets across the globe , often using shared infrastructure with their targeted attack operations .' [/INST] [Additionally:O, ,:O, during:O, that:O, time:O, ,:O, members:O, of:O, Gorgon:B-HackOrg, Group:I-HackOrg, were:O, also:O, performing:O, criminal:B-OffAct, operations:I-OffAct, against:O, targets:O, across:O, the:O, globe:O, ,:O, often:O, using:O, shared:B-Tool, infrastructure:I-Tool, with:O, their:O, targeted:B-OffAct, attack:I-OffAct, operations: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: 'Unit 42 researchers have been tracking an active campaign .' [/INST] [Unit:B-SecTeam, 42:I-SecTeam, researchers:O, have:O, been:O, tracking:O, an:O, active:B-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: 'This Gorgon Group campaign leveraged spear phishing emails with Microsoft Word documents exploiting CVE-2017-0199 .' [/INST] [This:O, Gorgon:B-OffAct, Group:I-OffAct, campaign:I-OffAct, leveraged:O, spear:B-Way, phishing:I-Way, emails:I-Way, with:O, Microsoft:B-SamFile, Word:I-SamFile, documents:I-SamFile, exploiting:O, CVE-2017-0199: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: 'Beginning in early March 2018 , Unit 42 started observing Gorgon group attacks against Russian , Spanish and United States government agencies operating in Pakistan .' [/INST] [Beginning:O, in:O, early:B-Time, March:I-Time, 2018:I-Time, ,:O, Unit:B-SecTeam, 42:I-SecTeam, started:O, observing:O, Gorgon:B-OffAct, group:I-OffAct, attacks:I-OffAct, against:O, Russian:B-Area, ,:O, Spanish:B-Area, and:O, United:B-Area, States:I-Area, government:B-Org, agencies:I-Org, operating:O, in:O, Pakistan: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: 'Like all of Gorgon Group 's members , Fudpage 's online profile , infrastructure utilization and standardization , connects them back to Gorgon Group .' [/INST] [Like:O, all:O, of:O, Gorgon:B-HackOrg, Group:I-HackOrg, 's:O, members:O, ,:O, Fudpage:O, 's:O, online:O, profile:O, ,:O, infrastructure:B-Tool, utilization:I-Tool, and:O, standardization:B-Tool, ,:O, connects:O, them:O, back:O, to:O, Gorgon: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: 'Ultimately , this lead us to the conclusion that several of Gorgon Group 's members have a nexus in Pakistan .' [/INST] [Ultimately:O, ,:O, this:O, lead:O, us:O, to:O, the:O, conclusion:O, that:O, several:O, of:O, Gorgon:B-HackOrg, Group:I-HackOrg, 's:O, members:O, have:O, a:O, nexus:O, in:O, Pakistan: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: 'Gorgon Group isn't the first actor group we've witnessed dabble in both nation state level and criminal attacks .' [/INST] [Gorgon:B-HackOrg, Group:I-HackOrg, isn't:O, the:O, first:O, actor:B-HackOrg, group:I-HackOrg, we've:O, witnessed:O, dabble:O, in:O, both:O, nation:O, state:O, level:O, and:O, criminal: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: 'Overall , in spite of the lack of sophistication in Gorgon Group 's activity , they were still relatively successful ; once again proving that simple attacks on individuals without proper protections , work .' [/INST] [Overall:O, ,:O, in:O, spite:O, of:O, the:O, lack:O, of:O, sophistication:O, in:O, Gorgon:B-HackOrg, Group:I-HackOrg, 's:O, activity:B-OffAct, ,:O, they:O, were:O, still:O, relatively:O, successful:O, ;:O, once:O, again:O, proving:O, that:O, simple:O, attacks:B-OffAct, on:O, individuals:O, without:O, proper:O, protections:O, ,:O, work:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 January 15 , Advanced Threat Research discovered an operation using a new variant of the SYSCON backdoor .' [/INST] [On:O, January:B-Time, 15:I-Time, ,:O, Advanced:B-SecTeam, Threat:I-SecTeam, Research:I-SecTeam, discovered:O, an:O, operation:O, using:O, a:O, new:O, variant:O, of:O, the:O, SYSCON:B-Tool, backdoor:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Korean-language Word document manual.doc appeared in Vietnam on January 17 , with the original author name of Honeybee .' [/INST] [The:O, Korean-language:O, Word:B-Tool, document:I-Tool, manual.doc:B-SamFile, appeared:O, in:O, Vietnam:B-Area, on:O, January:B-Time, 17:I-Time, ,:O, with:O, the:O, original:O, author:O, name:O, of:O, Honeybee: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: 'While Gorgon Group has been making minor changes in their methodologies , they are still actively involved in both targeted and criminal attacks .' [/INST] [While:O, Gorgon:B-HackOrg, Group:I-HackOrg, has:O, been:O, making:O, minor:O, changes:O, in:O, their:O, methodologies:O, ,:O, they:O, are:O, still:O, actively:O, involved:O, in:O, both:O, targeted:O, and:O, criminal: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: 'This malicious document contains a Visual Basic macro that dropped and executed an upgraded version of the implant known as SYSCON , which appeared in 2017 in malicious Word documents as part of several campaigns using North Korea–related topics .' [/INST] [This:O, malicious:O, document:O, contains:O, a:O, Visual:B-Way, Basic:I-Way, macro:I-Way, that:O, dropped:O, and:O, executed:O, an:O, upgraded:O, version:O, of:O, the:O, implant:O, known:O, as:O, SYSCON:B-Tool, ,:O, which:O, appeared:O, in:O, 2017:B-Time, in:O, malicious:B-SamFile, Word:I-SamFile, documents:I-SamFile, as:O, part:O, of:O, several:O, campaigns:B-OffAct, using:O, North:B-Area, Korea–related:O, topics:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 key was also used in the Honeybee campaign and appears to have been used since August 2017 .' [/INST] [This:O, key:O, was:O, also:O, used:O, in:O, the:O, Honeybee:B-OffAct, campaign:I-OffAct, and:O, appears:O, to:O, have:O, been:O, used:O, since:O, August: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: 'Several additional documents surfaced between January 17 and February 3 .' [/INST] [Several:O, additional:O, documents:O, surfaced:O, between:O, January:B-Time, 17:I-Time, and:O, February:B-Time, 3: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: 'All contain the same Visual Basic macro code and author name as Honeybee .' [/INST] [All:O, contain:O, the:O, same:O, Visual:B-Way, Basic:I-Way, macro:I-Way, code:I-Way, and:O, author:O, name:O, as:O, Honeybee: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: 'Some of the malicious documents were test files without the implant .' [/INST] [Some:O, of:O, the:O, malicious:O, documents:O, were:O, test:B-Tool, files:I-Tool, without:O, the:O, implant:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'From our analysis , Honeybee submitted most of these documents from South Korea , indicating that some of the targeting was in South Korea .' [/INST] [From:O, our:O, analysis:O, ,:O, Honeybee:B-HackOrg, submitted:O, most:O, of:O, these:O, documents:O, from:O, South:B-Area, Korea:I-Area, ,:O, indicating:O, that:O, some:O, of:O, the:O, targeting:O, was:O, in:O, South:B-Area, Korea: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: 'Honeybee attacked beyond the borders of South Korea to target Vietnam , Singapore , Argentina , Japan , Indonesia , and Canada .' [/INST] [Honeybee:B-HackOrg, attacked:O, beyond:O, the:O, borders:O, of:O, South:B-Area, Korea:I-Area, to:O, target:O, Vietnam:B-Area, ,:O, Singapore:B-Area, ,:O, Argentina:B-Area, ,:O, Japan:B-Area, ,:O, Indonesia:B-Area, ,:O, and:O, Canada: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: 'Honeybee appears to target humanitarian aid and inter-Korean affairs .' [/INST] [Honeybee:B-HackOrg, appears:O, to:O, target:O, humanitarian:O, aid:O, and:O, inter-Korean:B-Area, affairs:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'McAfee Advanced Threat Research team 's analysis , we find multiple components from this operation are unique from a code perspective , even though the code is loosely based on previous versions of the SYSCON backdoor .' [/INST] [McAfee:B-SecTeam, Advanced:I-SecTeam, Threat:I-SecTeam, Research:I-SecTeam, team:O, 's:O, analysis:O, ,:O, we:O, find:O, multiple:O, components:O, from:O, this:O, operation:O, are:O, unique:O, from:O, a:O, code:O, perspective:O, ,:O, even:O, though:O, the:O, code:O, is:O, loosely:O, based:O, on:O, previous:O, versions:O, of:O, the:O, SYSCON:B-Tool, backdoor:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Large-scale cyber espionage campaigns such as , GhostNet , .' [/INST] [Large-scale:O, cyber:B-OffAct, espionage:I-OffAct, campaigns:I-OffAct, such:O, as:O, ,:O, GhostNet:B-OffAct, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the crisis in Syria escalates , FireEye researchers have discovered a cyber espionage campaign , which we call , Ke3chang , , that falsely advertises information updates about the ongoing crisis to compromise MFA networks in Europe .' [/INST] [As:O, the:O, crisis:O, in:O, Syria:B-Area, escalates:O, ,:O, FireEye:B-SecTeam, researchers:O, have:O, discovered:O, a:O, cyber:B-OffAct, espionage:I-OffAct, campaign:I-OffAct, ,:O, which:O, we:O, call:O, ,:O, Ke3chang:B-HackOrg, ,:O, ,:O, that:O, falsely:O, advertises:O, information:O, updates:O, about:O, the:O, ongoing:O, crisis:O, to:O, compromise:O, MFA:O, networks:O, in:O, Europe:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'As the crisis in Syria escalates , FireEye researchers have discovered a threat group , which we call , Ke3chang , , that falsely advertises information updates about the ongoing crisis to compromise MFA networks in Europe .' [/INST] [As:O, the:O, crisis:O, in:O, Syria:B-Area, escalates:O, ,:O, FireEye:B-SecTeam, researchers:O, have:O, discovered:O, a:O, threat:B-HackOrg, group:I-HackOrg, ,:O, which:O, we:O, call:O, ,:O, Ke3chang:B-HackOrg, ,:O, ,:O, that:O, falsely:O, advertises:O, information:O, updates:O, about:O, the:O, ongoing:O, crisis:O, to:O, compromise:O, MFA:O, networks:O, in:O, Europe: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: 'We believe that the Ke3chang attackers are operating out of China and have been active since at least 2010 .' [/INST] [We:O, believe:O, that:O, the:O, Ke3chang:B-HackOrg, attackers:B-HackOrg, are:O, operating:O, out:O, of:O, China:B-Area, and:O, have:O, been:O, active:O, since:O, at:O, least:O, 2010: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: 'FireEye gained visibility into one of 23 known command-and-control ( CnC ) servers operated by the Ke3chang actor for about one week .' [/INST] [FireEye:B-SecTeam, gained:O, visibility:O, into:O, one:O, of:O, 23:O, known:O, command-and-control:B-Tool, (:O, CnC:B-Tool, ):O, servers:O, operated:O, by:O, the:O, Ke3chang:B-HackOrg, actor:I-HackOrg, for:O, about:O, one:O, week:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Each attack comprises a variety of phases , including reconnaissance , exploitation , command and control , lateral movement , and exfiltration .' [/INST] [Each:O, attack:B-OffAct, comprises:O, a:O, variety:O, of:O, phases:O, ,:O, including:O, reconnaissance:O, ,:O, exploitation:O, ,:O, command:O, and:O, control:O, ,:O, lateral:O, movement:O, ,:O, and:O, exfiltration:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Ke3chang attackers have been active since at least 2010 .' [/INST] [The:O, Ke3chang:B-HackOrg, attackers:B-HackOrg, have:O, been:O, active:O, since:O, at:O, least:O, 2010: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: 'traditionally targeted the aerospace , energy , government , high-tech , consulting services , and chemicals / manufacturing / mining sectors .' [/INST] [traditionally:O, targeted:O, the:O, aerospace:B-Idus, ,:O, energy:B-Idus, ,:O, government:B-Idus, ,:O, high-tech:B-Idus, ,:O, consulting:B-Idus, services:I-Idus, ,:O, and:O, chemicals:B-Idus, /:O, manufacturing:B-Idus, /:O, mining: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 Ke3chang have used three types of malware over the years and have traditionally targeted the aerospace , energy , government , high-tech , consulting services , chemicals , manufacturing , mining sectors .' [/INST] [The:O, Ke3chang:B-HackOrg, have:O, used:O, three:O, types:O, of:O, malware:O, over:O, the:O, years:O, and:O, have:O, traditionally:O, targeted:O, the:O, aerospace:B-Idus, ,:O, energy:B-Idus, ,:O, government:B-Idus, ,:O, high-tech:B-Idus, ,:O, consulting:B-Idus, services:I-Idus, ,:O, chemicals:B-Idus, ,:O, manufacturing:B-Idus, ,:O, mining: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: 'August 2013 , FireEye gained visibility on one of 22 CnC servers used at that time by the Ke3chang attackers .' [/INST] [August:B-Time, 2013:I-Time, ,:O, FireEye:B-SecTeam, gained:O, visibility:O, on:O, one:O, of:O, 22:O, CnC:O, servers:O, used:O, at:O, that:O, time:O, by:O, the:O, Ke3chang:B-HackOrg, 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: 'In this report , we present the historical intelligence we have gathered on the Ke3chang campaign , as well as an in-depth assessment of the ongoing Syrian-themed attacks against these MFAs .' [/INST] [In:O, this:O, report:O, ,:O, we:O, present:O, the:O, historical:O, intelligence:O, we:O, have:O, gathered:O, on:O, the:O, Ke3chang:B-OffAct, campaign:I-OffAct, ,:O, as:O, well:O, as:O, an:O, in-depth:O, assessment:O, of:O, the:O, ongoing:O, Syrian-themed:B-OffAct, attacks:I-OffAct, against:O, these:O, MFAs:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Ke3chang attackers have used spear-phishing emails .' [/INST] [Ke3chang:B-HackOrg, attackers:B-HackOrg, have:O, used:O, spear-phishing:B-Way, emails:I-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Ke3chang has also leveraged a Java zero-day vulnerability ( CVE-2012-4681 ) , as well as older , reliable exploits for Microsoft Word ( CVE-2010-3333 ) and Adobe PDF Reader ( CVE-2010-2883 ) .' [/INST] [Ke3chang:B-HackOrg, has:O, also:O, leveraged:O, a:O, Java:B-Exp, zero-day:I-Exp, vulnerability:I-Exp, (:O, CVE-2012-4681:B-Exp, ):O, ,:O, as:O, well:O, as:O, older:O, ,:O, reliable:O, exploits:O, for:O, Microsoft:B-SamFile, Word:I-SamFile, (:O, CVE-2010-3333:B-Exp, ):O, and:O, Adobe:B-Tool, PDF:I-Tool, Reader:I-Tool, (:O, CVE-2010-2883:B-Exp, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Traditionally , the Ke3chang attackers have used spear-phishing emails with either a malware attachment or a link to a malicious download .' [/INST] [Traditionally:O, ,:O, the:O, Ke3chang:B-HackOrg, attackers:B-HackOrg, have:O, used:O, spear-phishing:B-Way, emails:I-Way, with:O, either:O, a:O, malware:O, attachment:O, or:O, a:O, link:O, to:O, a:O, malicious:O, download:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Over the years , the Ke3chang attackers have used three types of malware that we call : , BS2005 , , , BMW , , and , MyWeb , .' [/INST] [Over:O, the:O, years:O, ,:O, the:O, Ke3chang:B-HackOrg, attackers:B-HackOrg, have:O, used:O, three:O, types:O, of:O, malware:O, that:O, we:O, call:O, ::O, ,:O, BS2005:B-Tool, ,:O, ,:O, ,:O, BMW:B-Tool, ,:O, ,:O, and:O, ,:O, MyWeb:B-Tool, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'it is a typical first stage backdoor commonly found in APT attacks .' [/INST] [it:O, is:O, a:O, typical:O, first:O, stage:O, backdoor:O, commonly:O, found:O, in:O, APT: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: 'The attackers have used three types of malware over the years and have traditionally targeted the aerospace , energy , government , high-tech , consulting services , and chemicals / manufacturing / mining sectors .' [/INST] [The:O, attackers:B-HackOrg, have:O, used:O, three:O, types:O, of:O, malware:O, over:O, the:O, years:O, and:O, have:O, traditionally:O, targeted:O, the:O, aerospace:B-Idus, ,:O, energy:B-Idus, ,:O, government:B-Idus, ,:O, high-tech:B-Idus, ,:O, consulting:B-Idus, services:I-Idus, ,:O, and:O, chemicals:B-Idus, /:O, manufacturing:B-Idus, /:O, mining: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: 'All of the CnC communications are performed over the HTTP protocol .' [/INST] [All:O, of:O, the:O, CnC:O, communications:O, are:O, performed:O, over:O, the:O, HTTP:B-Tool, protocol:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The current Ke3chang campaign leverages the BS2005 malware , while older activity from 2010 - 2011 leveraged BMW , followed by the MyWeb malware sporadically used in between .' [/INST] [The:O, current:O, Ke3chang:B-OffAct, campaign:I-OffAct, leverages:O, the:O, BS2005:B-Tool, malware:I-Tool, ,:O, while:O, older:O, activity:B-OffAct, from:O, 2010:B-Time, -:O, 2011:B-Time, leveraged:O, BMW:B-Tool, ,:O, followed:O, by:O, the:O, MyWeb:B-Tool, malware:I-Tool, sporadically:O, used:O, in:O, between:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 trait common to all three malware families we analyzed is that they use the IWebBrowser2 COM interface to perform their CnC communication .' [/INST] [A:O, trait:O, common:O, to:O, all:O, three:O, malware:O, families:O, we:O, analyzed:O, is:O, that:O, they:O, use:O, the:O, IWebBrowser2:B-Tool, COM:I-Tool, interface:O, to:O, perform:O, their:O, CnC:O, communication:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Three months after the Olympics-themed attacks , FireEye observed a new BS2005 campaign labeled , newtiger , , which is possibly a reference to an older 2010 campaign labeled , tiger , .' [/INST] [Three:O, months:O, after:O, the:O, Olympics-themed:B-OffAct, attacks:I-OffAct, ,:O, FireEye:B-SecTeam, observed:O, a:O, new:O, BS2005:B-OffAct, campaign:I-OffAct, labeled:O, ,:O, newtiger:B-OffAct, ,:O, ,:O, which:O, is:O, possibly:O, a:O, reference:O, to:O, an:O, older:O, 2010:B-OffAct, campaign:I-OffAct, labeled:O, ,:O, tiger: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: 'Using information from the FireEye DTI cloud , FireEye observed that Ke3chang targeted a single firm .' [/INST] [Using:O, information:O, from:O, the:O, FireEye:B-SecTeam, DTI:I-SecTeam, cloud:O, ,:O, FireEye:B-SecTeam, observed:O, that:O, Ke3chang:B-HackOrg, targeted:O, a:O, single:O, firm:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Ke3chang attackers used the older , MyWeb , malware family from 2010 to 2011 .' [/INST] [The:O, Ke3chang:B-HackOrg, attackers:B-HackOrg, used:O, the:O, older:O, ,:O, MyWeb:B-Tool, ,:O, malware:O, family:O, from:O, 2010:B-Time, to:O, 2011: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 Ke3chang attackers used the older MyWeb malware family from 2010 to 2011 .' [/INST] [The:O, Ke3chang:B-HackOrg, attackers:B-HackOrg, used:O, the:O, older:O, MyWeb:B-Tool, malware:I-Tool, family:O, from:O, 2010:B-Time, to:O, 2011: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: 'During our period of visibility into the BS2005 , moviestar , campaign against various ministries of foreign affairs in Europe , FireEye discovered that the Ke3chang had initially tested the malware in virtual machines , prior to compromising actual targets .' [/INST] [During:O, our:O, period:O, of:O, visibility:O, into:O, the:O, BS2005:B-OffAct, ,:O, moviestar:B-OffAct, ,:O, campaign:B-OffAct, against:O, various:O, ministries:B-Org, of:I-Org, foreign:I-Org, affairs:I-Org, in:O, Europe:B-Area, ,:O, FireEye:B-SecTeam, discovered:O, that:O, the:O, Ke3chang:B-HackOrg, had:O, initially:O, tested:O, the:O, malware:O, in:O, virtual:O, machines:O, ,:O, prior:O, to:O, compromising:O, actual:O, targets:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 MyWeb sample that FireEye analyzed has a compile date of 1/20/2011 .' [/INST] [The:O, MyWeb:B-Tool, sample:I-Tool, that:O, FireEye:B-SecTeam, analyzed:O, has:O, a:O, compile:O, date:O, of:O, 1/20/2011: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: 'At least one of the attacks in this campaign leveraged a European security and defense-themed lure , which aligns with the targeting preferences for this group .' [/INST] [At:O, least:O, one:O, of:O, the:O, attacks:B-OffAct, in:O, this:O, campaign:B-OffAct, leveraged:O, a:O, European:B-Area, security:O, and:O, defense-themed:O, lure:O, ,:O, which:O, aligns:O, with:O, the:O, targeting:O, preferences:O, for:O, this:O, group: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: 'MyWeb is the second-generation malware used by Ke3chang .' [/INST] [MyWeb:B-Tool, is:O, the:O, second-generation:O, malware:O, used:O, by:O, Ke3chang: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: 'ministries of foreign affairs in Europe have been targeted and compromised by a threat actor we call Ke3chang .' [/INST] [ministries:B-Org, of:I-Org, foreign:I-Org, affairs:I-Org, in:O, Europe:B-Area, have:O, been:O, targeted:O, and:O, compromised:O, by:O, a:O, threat:B-HackOrg, actor:I-HackOrg, we:O, call:O, Ke3chang: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: 'This attack used the crisis in Syria as a lure to deliver malware to its targets .' [/INST] [This:O, attack:B-OffAct, used:O, the:O, crisis:O, in:O, Syria:B-Area, as:O, a:O, lure:O, to:O, deliver:O, malware:O, to:O, its:O, targets:O, .:O] </s> |