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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: 'In addition , the attackers employed hacking tools of Chinese origin and that are prevalent on Chinese underground hacking forums .' [/INST] [In:O, addition:O, ,:O, the:O, attackers:B-HackOrg, employed:O, hacking:O, tools:O, of:O, Chinese:B-Area, origin:O, and:O, that:O, are:O, prevalent:O, on:O, Chinese:B-Area, underground:O, hacking:O, forums:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 have been presented with a rare opportunity to see some development activities from the actors associated with the OilRig attack campaign , a campaign Unit 42 has been following since May 2016 .' [/INST] [We:O, have:O, been:O, presented:O, with:O, a:O, rare:O, opportunity:O, to:O, see:O, some:O, development:B-OffAct, activities:I-OffAct, from:O, the:O, actors:B-HackOrg, associated:O, with:O, the:O, OilRig:B-OffAct, attack:I-OffAct, campaign:I-OffAct, ,:O, a:O, campaign:B-OffAct, Unit:B-SecTeam, 42:I-SecTeam, has:O, been:O, following:O, since:O, May: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: 'Recently we were able to observe these actors making modifications to their Clayslide delivery documents in an attempt to evade antivirus detection .' [/INST] [Recently:O, we:O, were:O, able:O, to:O, observe:O, these:O, actors:B-HackOrg, making:O, modifications:O, to:O, their:O, Clayslide:B-Tool, delivery:I-Tool, documents:I-Tool, in:O, an:O, attempt:O, to:O, evade:O, antivirus:O, detection:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 collected two sets of Clayslide samples that appear to be created during the OilRig actor 's development phase of their attack lifecycle .' [/INST] [We:O, collected:O, two:O, sets:O, of:O, Clayslide:B-Tool, samples:I-Tool, that:O, appear:O, to:O, be:O, created:O, during:O, the:O, OilRig:B-HackOrg, actor:I-HackOrg, 's:O, development:O, phase:O, of:O, their:O, attack:B-OffAct, lifecycle:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 November 15 , 2016 , an actor related to the OilRig campaign began testing the Clayslide delivery documents .' [/INST] [On:O, November:B-Time, 15:I-Time, ,:I-Time, 2016:I-Time, ,:O, an:O, actor:B-HackOrg, related:O, to:O, the:O, OilRig:B-OffAct, campaign:I-OffAct, began:O, testing:O, the:O, Clayslide:B-Tool, delivery:I-Tool, documents: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 actor then made subtle modifications to the file and uploaded the newly created file to the same popular antivirus testing website in order to determine how to evade detection .' [/INST] [The:O, actor:B-HackOrg, then:O, made:O, subtle:O, modifications:O, to:O, the:O, file:O, and:O, uploaded:O, the:O, newly:O, created:O, file:O, to:O, the:O, same:O, popular:O, antivirus:O, testing:O, website:O, in:O, order:O, to:O, determine:O, how:O, to:O, evade:O, detection:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 addition to making changes to the Excel worksheets that contain the decoy content , the actor also made changes to the worksheet that is initially displayed to the user .' [/INST] [In:O, addition:O, to:O, making:O, changes:O, to:O, the:O, Excel:B-Way, worksheets:I-Way, that:O, contain:O, the:O, decoy:O, content:O, ,:O, the:O, actor:B-HackOrg, also:O, made:O, changes:O, to:O, the:O, worksheet:O, that:O, is:O, initially:O, displayed:O, to:O, the:O, user:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Taking a step back , as discussed in the Appendix in our initial OilRig blog , Clayslide delivery documents initially open with a worksheet named , Incompatible , that displays content that instructs the user to , Enable Content , to see the contents of the document , which in fact runs the malicious macro and compromises the system .' [/INST] [Taking:O, a:O, step:O, back:O, ,:O, as:O, discussed:O, in:O, the:O, Appendix:O, in:O, our:O, initial:O, OilRig:B-HackOrg, blog:O, ,:O, Clayslide:B-SamFile, delivery:I-SamFile, documents:I-SamFile, initially:O, open:O, with:O, a:O, worksheet:O, named:O, ,:O, Incompatible:O, ,:O, that:O, displays:O, content:O, that:O, instructs:O, the:O, user:O, to:O, ,:O, Enable:O, Content:O, ,:O, to:O, see:O, the:O, contents:O, of:O, the:O, document:O, ,:O, which:O, in:O, fact:O, runs:B-Features, the:I-Features, malicious:I-Features, macro:I-Features, and:O, compromises:B-Features, the:I-Features, system: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: 'This realization suggests that the OilRig threat group will continue to use their delivery documents for extended periods with subtle modifications to remain effective .' [/INST] [This:O, realization:O, suggests:O, that:O, the:O, OilRig:B-HackOrg, threat:B-HackOrg, group:I-HackOrg, will:O, continue:O, to:O, use:O, their:O, delivery:B-Tool, documents:I-Tool, for:O, extended:O, periods:O, with:O, subtle:O, modifications:O, to:O, remain:O, effective:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Iranian threat agent OilRig has been targeting multiple organisations in Israel and other countries in the Middle East since the end of 2015 .' [/INST] [Iranian:B-Area, threat:O, agent:O, OilRig:B-HackOrg, has:O, been:O, targeting:O, multiple:O, organisations:O, in:O, Israel:B-Area, and:O, other:O, countries:O, in:O, the:O, Middle:B-Area, East:I-Area, since:O, the:O, end:B-Time, of:I-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: 'In recent attacks they set up a fake VPN Web Portal and targeted at least five Israeli IT vendors , several financial institutes , and the Israeli Post Office .' [/INST] [In:O, recent:O, attacks:B-OffAct, they:O, set:O, up:O, a:O, fake:O, VPN:B-Tool, Web:I-Tool, Portal:I-Tool, and:O, targeted:O, at:O, least:O, five:O, Israeli:B-Area, IT:B-Org, vendors:I-Org, ,:O, several:O, financial:B-Org, institutes:I-Org, ,:O, and:O, the:O, Israeli:B-Org, Post:I-Org, Office: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 these websites they hosted malware that was digitally signed with a valid , likely stolen code signing certificate .' [/INST] [In:O, these:O, websites:O, they:O, hosted:O, malware:O, that:O, was:O, digitally:O, signed:O, with:O, a:O, valid:O, ,:O, likely:O, stolen:B-Tool, code:I-Tool, signing:I-Tool, certificate: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 December 2015 , Symantec published a post about , two Iran-based attack groups that appear to be connected , Cadelle and Chafer , that , have been using Backdoor.Cadelspy and Backdoor.Remexi to spy on Iranian individuals and Middle Eastern organizations , .' [/INST] [In:O, December:B-Time, 2015:I-Time, ,:O, Symantec:B-SecTeam, published:O, a:O, post:O, about:O, ,:O, two:O, Iran-based:B-Area, attack:B-HackOrg, groups:I-HackOrg, that:O, appear:O, to:O, be:O, connected:O, ,:O, Cadelle:B-HackOrg, and:O, Chafer:B-HackOrg, ,:O, that:O, ,:O, have:O, been:O, using:O, Backdoor.Cadelspy:B-Tool, and:O, Backdoor.Remexi:B-Tool, to:O, spy:O, on:O, Iranian:B-Area, individuals:O, and:O, Middle:B-Area, Eastern:I-Area, organizations: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: 'In May 2016 , Unit 42 observed attacks of OilRig primarily focused on financial institutions and technology organizations within Saudi Arabia .' [/INST] [In:O, May:B-Time, 2016:I-Time, ,:O, Unit:B-SecTeam, 42:I-SecTeam, observed:O, attacks:B-OffAct, of:O, OilRig:B-HackOrg, primarily:O, focused:O, on:O, financial:B-Org, institutions:I-Org, and:O, technology:B-Org, organizations:I-Org, within:O, Saudi:B-Area, Arabia:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In recent OilRig attacks , the threat actors purport to be legitimate service providers offering service and technical troubleshooting as a social engineering theme in their spear-phishing attacks .' [/INST] [In:O, recent:O, OilRig:B-OffAct, attacks:I-OffAct, ,:O, the:O, threat:B-HackOrg, actors:I-HackOrg, purport:O, to:O, be:O, legitimate:B-Org, service:I-Org, providers:I-Org, offering:O, service:O, and:O, technical:O, troubleshooting:O, as:O, a:O, social:B-Idus, engineering:I-Idus, theme:O, in:O, their:O, spear-phishing: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 campaign appears highly targeted and delivers a backdoor we have called ' Helminth ' .' [/INST] [The:O, campaign:B-OffAct, appears:O, highly:O, targeted:O, and:O, delivers:O, a:O, backdoor:O, we:O, have:O, called:O, ':O, Helminth: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: 'Artifacts identified within the malware samples related to these attacks also suggest the targeting of the defense industry in Saudi Arabia , which appears to be related to an earlier wave of attacks carried out in the fall of 2015 .' [/INST] [Artifacts:O, identified:O, within:O, the:O, malware:O, samples:O, related:O, to:O, these:O, attacks:B-OffAct, also:O, suggest:O, the:O, targeting:O, of:O, the:O, defense:B-Idus, industry:I-Idus, in:O, Saudi:B-Area, Arabia:I-Area, ,:O, which:O, appears:O, to:O, be:O, related:O, to:O, an:O, earlier:O, wave:O, of:O, attacks:B-OffAct, carried:O, out:O, in:O, the:O, fall:B-Time, of:I-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: 'In May 2016 , Unit 42 began researching attacks that used spear-phishing emails with attachments , specifically malicious Excel spreadsheets sent to financial organizations within Saudi Arabia .' [/INST] [In:O, May:B-Time, 2016:I-Time, ,:O, Unit:B-SecTeam, 42:I-SecTeam, began:O, researching:O, attacks:B-OffAct, that:O, used:O, spear-phishing:B-Way, emails:I-Way, with:I-Way, attachments:I-Way, ,:O, specifically:O, malicious:O, Excel:B-Way, spreadsheets:I-Way, sent:O, to:O, financial:B-Org, organizations:I-Org, within:O, Saudi:B-Area, Arabia: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: 'Over the course of the attack campaign , we have observed two different variations of the Helminth backdoor , one written in VBScript and PowerShell that was delivered via a macro within Excel spreadsheets and the other a standalone Windows executable .' [/INST] [Over:O, the:O, course:O, of:O, the:O, attack:B-OffAct, campaign:I-OffAct, ,:O, we:O, have:O, observed:O, two:O, different:O, variations:O, of:O, the:O, Helminth:B-Tool, backdoor:I-Tool, ,:O, one:O, written:O, in:O, VBScript:O, and:O, PowerShell:O, that:O, was:O, delivered:O, via:O, a:O, macro:O, within:O, Excel:B-Way, spreadsheets:I-Way, and:O, the:O, other:O, a:O, standalone:O, Windows:B-Way, executable: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: 'FireEye also reported on these attacks in a May 22 blog post .' [/INST] [FireEye:B-SecTeam, also:O, reported:O, on:O, these:O, attacks:B-OffAct, in:O, a:O, May:B-Time, 22:I-Time, blog:O, post:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The executable variant of Helminth is installed with a dropper Trojan that we are tracking as the HerHer Trojan .' [/INST] [The:O, executable:O, variant:O, of:O, Helminth:B-Tool, is:O, installed:O, with:O, a:O, dropper:B-Tool, Trojan:I-Tool, that:O, we:O, are:O, tracking:O, as:O, the:O, HerHer:B-Tool, Trojan: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 Helminth executable variant is very similar in functionality to its script-based counterpart , as it also communicates with its C2 server using both HTTP and DNS queries .' [/INST] [The:O, Helminth:B-Tool, executable:O, variant:O, is:O, very:O, similar:O, in:O, functionality:O, to:O, its:O, script-based:O, counterpart:O, ,:O, as:O, it:O, also:O, communicates:O, with:O, its:O, C2:O, server:O, using:O, both:O, HTTP:B-Tool, and:O, DNS:B-Tool, queries:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Helminth executable samples send artifacts within network beacons to its C2 server that the Trojan refers to as a ' Group ' and ' Name ' .' [/INST] [Helminth:B-Tool, executable:O, samples:O, send:O, artifacts:O, within:O, network:B-Way, beacons:I-Way, to:O, its:O, C2:O, server:O, that:O, the:O, Trojan:O, refers:O, to:O, as:O, a:O, ':O, Group:O, ':O, and:O, ':O, Name: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: 'It appears that the group values hardcoded into the malware is associated with the targeted organization , as several are Saudi Arabian organizations within the telecommunications and defense industries .' [/INST] [It:O, appears:O, that:O, the:O, group:B-HackOrg, values:O, hardcoded:O, into:O, the:O, malware:O, is:O, associated:O, with:O, the:O, targeted:O, organization:O, ,:O, as:O, several:O, are:O, Saudi:B-Area, Arabian:I-Area, organizations:O, within:O, the:O, telecommunications:B-Idus, and:O, defense:B-Idus, industries:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'It appears that the group values hardcoded into the malware is associated with the targeted organization , as several are Saudi Arabian organizations within the telecommunications and defense industries .' [/INST] [It:O, appears:O, that:O, the:O, group:B-HackOrg, values:O, hardcoded:O, into:O, the:O, malware:O, is:O, associated:O, with:O, the:O, targeted:O, organization:O, ,:O, as:O, several:O, are:O, Saudi:B-Area, Arabian:I-Area, organizations:O, within:O, the:O, telecommunications:B-Idus, and:O, defense:B-Idus, industries:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This suggests that the threat actors are not only focused on financial organizations , as their target set could include other industries as well .' [/INST] [This:O, suggests:O, that:O, the:O, threat:B-HackOrg, actors:I-HackOrg, are:O, not:O, only:O, focused:O, on:O, financial:B-Org, organizations:I-Org, ,:O, as:O, their:O, target:O, set:O, could:O, include:O, other:O, industries:O, as:O, well:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The email address edmundj@chmail.ir and the geolocation of Tehran , Iran , being of note .' [/INST] [The:O, email:O, address:O, edmundj@chmail.ir:O, and:O, the:O, geolocation:O, of:O, Tehran:B-Area, ,:O, Iran:B-Area, ,:O, being:O, of:O, note:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 registrant information for kernel.ws also provided a geolocation of Tehran , IR and the email provider for the address used in checkgoogle.org was the same used for mydomain1607.com , chmail.ir .' [/INST] [The:O, registrant:O, information:O, for:O, kernel.ws:O, also:O, provided:O, a:O, geolocation:O, of:O, Tehran:B-Area, ,:O, IR:B-Area, and:O, the:O, email:B-Org, provider:I-Org, for:O, the:O, address:O, used:O, in:O, checkgoogle.org:O, was:O, the:O, same:O, used:O, for:O, mydomain1607.com:O, ,:O, chmail.ir:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 mydomain1110.com domain did not appear to reuse any of the previously observed WHOIS data artifacts , but did still give a geolocation of Tehran in addition to the use of an email address linked to other domains thematically similar to the know command and control domains and are potentially related .' [/INST] [The:O, mydomain1110.com:O, domain:O, did:O, not:O, appear:O, to:O, reuse:O, any:O, of:O, the:O, previously:O, observed:O, WHOIS:O, data:O, artifacts:O, ,:O, but:O, did:O, still:O, give:O, a:O, geolocation:O, of:O, Tehran:B-Area, in:O, addition:O, to:O, the:O, use:O, of:O, an:O, email:O, address:O, linked:O, to:O, other:O, domains:O, thematically:O, similar:O, to:O, the:O, know:O, command:O, and:O, control:O, domains:O, and:O, are:O, potentially:O, related:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 researching the OilRig campaign , we have seen two waves of targeted attacks on Saudi Arabian organizations in which a group of threat actors delivered the Helminth Trojan as a payload .' [/INST] [While:O, researching:O, the:O, OilRig:B-OffAct, campaign:I-OffAct, ,:O, we:O, have:O, seen:O, two:O, waves:O, of:O, targeted:B-OffAct, attacks:I-OffAct, on:O, Saudi:B-Area, Arabian:I-Area, organizations:O, in:O, which:O, a:O, group:B-HackOrg, of:O, threat:B-HackOrg, actors:I-HackOrg, delivered:O, the:O, Helminth:B-Way, Trojan:I-Way, as:O, a:O, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 two variants of Helminth do require different delivery methods , with the script variant relying on an Excel spreadsheet for delivery , while the executable variant is more traditional in the fact that it can be installed without a delivery document .' [/INST] [The:O, two:O, variants:O, of:O, Helminth:B-Tool, do:O, require:O, different:O, delivery:O, methods:O, ,:O, with:O, the:O, script:O, variant:O, relying:O, on:O, an:O, Excel:B-Way, spreadsheet:I-Way, for:O, delivery:O, ,:O, while:O, the:O, executable:B-Way, variant:I-Way, is:O, more:O, traditional:O, in:O, the:O, fact:O, that:O, it:O, can:O, be:O, installed:O, without:O, a:O, delivery: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: 'Since our first published analysis of the OilRig campaign in May 2016 , we have continued to monitor this group for new activity .' [/INST] [Since:O, our:O, first:O, published:O, analysis:O, of:O, the:O, OilRig:B-OffAct, campaign:I-OffAct, in:O, May:B-Time, 2016:I-Time, ,:O, we:O, have:O, continued:O, to:O, monitor:O, this:O, group:B-HackOrg, for:O, new:O, activity: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: 'Additionally , the scope of organizations targeted by this group has expanded to not only include organizations within Saudi Arabia , but also a company in Qatar and government organizations in Turkey , Israel and the United States .' [/INST] [Additionally:O, ,:O, the:O, scope:O, of:O, organizations:O, targeted:O, by:O, this:O, group:B-HackOrg, has:O, expanded:O, to:O, not:O, only:O, include:O, organizations:O, within:O, Saudi:B-Area, Arabia:I-Area, ,:O, but:O, also:O, a:O, company:O, in:O, Qatar:B-Area, and:O, government:B-Org, organizations:I-Org, in:O, Turkey:B-Area, ,:O, Israel:B-Area, 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 group behind the OilRig campaign continues to leverage spear-phishing emails with malicious Microsoft Excel documents to compromise victims .' [/INST] [The:O, group:B-HackOrg, behind:O, the:O, OilRig:B-OffAct, campaign:I-OffAct, continues:O, to:O, leverage:O, spear-phishing:B-Way, emails:I-Way, with:O, malicious:O, Microsoft:B-Way, Excel:I-Way, documents:I-Way, to:O, compromise:O, victims:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition to these instances , multiple Qatari organizations were the subject to spear phishing attacks carrying Helminth samples earlier this year .' [/INST] [In:O, addition:O, to:O, these:O, instances:O, ,:O, multiple:O, Qatari:B-Org, organizations:I-Org, were:O, the:O, subject:O, to:O, spear:B-OffAct, phishing:I-OffAct, attacks:I-OffAct, carrying:O, Helminth:B-Tool, samples:I-Tool, earlier:O, this:O, year:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While the malware deployed is not terribly sophisticated , it uses techniques such as DNS command and control ( C2 ) that allows it to stay under the radar at many establishments .' [/INST] [While:O, the:O, malware:O, deployed:O, is:O, not:O, terribly:O, sophisticated:O, ,:O, it:O, uses:O, techniques:O, such:O, as:O, DNS:B-Way, command:I-Way, and:I-Way, control:I-Way, (:O, C2:O, ):O, that:O, allows:O, it:O, to:O, stay:O, under:O, the:O, radar:O, at:O, many:O, establishments:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Less than a week after Microsoft issued a patch for CVE-2017-11882 on Nov. 14 , 2017 , FireEye observed an attacker using an exploit for the Microsoft Office vulnerability to target a government organization in the Middle East .' [/INST] [Less:O, than:O, a:O, week:O, after:O, Microsoft:B-Org, issued:O, a:O, patch:O, for:O, CVE-2017-11882:B-Exp, on:O, Nov.:B-Time, 14:I-Time, ,:I-Time, 2017:I-Time, ,:O, FireEye:B-SecTeam, observed:O, an:O, attacker:B-HackOrg, using:O, an:O, exploit:O, for:O, the:O, Microsoft:B-Exp, Office:I-Exp, vulnerability:I-Exp, to:O, target:O, a:O, government:B-Org, organization:I-Org, in:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We assess this activity was carried out by a suspected Iranian cyber espionage threat group , whom we refer to as APT34 , using a custom PowerShell backdoor to achieve its objectives .' [/INST] [We:O, assess:O, this:O, activity:B-OffAct, was:O, carried:O, out:O, by:O, a:O, suspected:O, Iranian:B-Area, cyber:B-HackOrg, espionage:I-HackOrg, threat:I-HackOrg, group:I-HackOrg, ,:O, whom:O, we:O, refer:O, to:O, as:O, APT34:B-HackOrg, ,:O, using:O, a:O, custom:B-Tool, PowerShell:I-Tool, backdoor:I-Tool, to:O, achieve:O, its:O, objectives:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 threat group has conducted broad targeting across a variety of industries , including financial , government , energy , chemical , and telecommunications , and has largely focused its operations within the Middle East .' [/INST] [This:O, threat:B-HackOrg, group:I-HackOrg, has:O, conducted:O, broad:O, targeting:O, across:O, a:O, variety:O, of:O, industries:O, ,:O, including:O, financial:B-Idus, ,:O, government:B-Idus, ,:O, energy:B-Idus, ,:O, chemical:B-Idus, ,:O, and:O, telecommunications:B-Idus, ,:O, and:O, has:O, largely:O, focused:O, its:O, operations:O, within:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We assess that APT34 works on behalf of the Iranian government based on infrastructure details that contain references to Iran , use of Iranian infrastructure , and targeting that aligns with nation-state interests .' [/INST] [We:O, assess:O, that:O, APT34:B-HackOrg, works:O, on:O, behalf:O, of:O, the:O, Iranian:B-Area, government:O, based:O, on:O, infrastructure:O, details:O, that:O, contain:O, references:O, to:O, Iran:B-Area, ,:O, use:O, of:O, Iranian:B-Area, infrastructure:O, ,:O, and:O, targeting:O, that:O, aligns:O, with:O, nation-state: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: 'APT34 uses a mix of public and non-public tools , often conducting spear phishing operations using compromised accounts , sometimes coupled with social engineering tactics .' [/INST] [APT34:B-HackOrg, uses:O, a:O, mix:O, of:O, public:B-Tool, and:I-Tool, non-public:I-Tool, tools:I-Tool, ,:O, often:O, conducting:O, spear:B-Way, phishing:I-Way, operations:I-Way, using:O, compromised:B-Tool, accounts:I-Tool, ,:O, sometimes:O, coupled:O, with:O, social:B-Way, engineering:I-Way, tactics: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: 'We believe APT34 is involved in a long-term cyber espionage operation largely focused on reconnaissance efforts to benefit Iranian nation-state interests and has been operational since at least 2014 .' [/INST] [We:O, believe:O, APT34:B-HackOrg, is:O, involved:O, in:O, a:O, long-term:O, cyber:O, espionage:O, operation:O, largely:O, focused:O, on:O, reconnaissance:O, efforts:O, to:O, benefit:O, Iranian:B-Area, nation-state:O, interests:O, and:O, has:O, been:O, operational:O, since:O, at:O, least: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: 'In May 2016 , we published a blog detailing a spear phishing campaign targeting banks in the Middle East region that used macro-enabled attachments to distribute POWBAT malware .' [/INST] [In:O, May:B-Time, 2016:I-Time, ,:O, we:O, published:O, a:O, blog:O, detailing:O, a:O, spear:B-OffAct, phishing:I-OffAct, campaign:I-OffAct, targeting:O, banks:B-Idus, in:O, the:O, Middle:B-Area, East:I-Area, region:O, that:O, used:O, macro-enabled:O, attachments:O, to:O, distribute:O, POWBAT: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 July 2017 , we observed APT34 targeting a Middle East organization using a PowerShell-based backdoor that we call POWRUNER and a downloader with domain generation algorithm functionality that we call BONDUPDATER , based on strings within the malware .' [/INST] [In:O, July:B-Time, 2017:I-Time, ,:O, we:O, observed:O, APT34:B-HackOrg, targeting:O, a:O, Middle:B-Area, East:I-Area, organization:O, using:O, a:O, PowerShell-based:B-Tool, backdoor:I-Tool, that:O, we:O, call:O, POWRUNER:B-Tool, and:O, a:O, downloader:O, with:O, domain:O, generation:O, algorithm:O, functionality:O, that:O, we:O, call:O, BONDUPDATER:B-Tool, ,:O, based:O, on:O, strings:O, within:O, the: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: 'APT34 loosely aligns with public reporting related to the group , OilRig , .' [/INST] [APT34:B-HackOrg, loosely:O, aligns:O, with:O, public:O, reporting:O, related:O, to:O, the:O, group:B-HackOrg, ,:O, OilRig:B-HackOrg, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 backdoor was delivered via a malicious .rtf file that exploited CVE-2017-0199 .' [/INST] [The:O, backdoor:O, was:O, delivered:O, via:O, a:O, malicious:O, .rtf:B-SamFile, file:I-SamFile, that:O, exploited: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: 'In this latest campaign , APT34 leveraged the recent Microsoft Office vulnerability CVE-2017-11882 to deploy POWRUNER and BONDUPDATER .' [/INST] [In:O, this:O, latest:O, campaign:B-OffAct, ,:O, APT34:B-HackOrg, leveraged:O, the:O, recent:O, Microsoft:B-Exp, Office:I-Exp, vulnerability:I-Exp, CVE-2017-11882:B-Exp, to:O, deploy:O, POWRUNER:B-Tool, and:O, BONDUPDATER: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 vulnerability was patched by Microsoft on Nov 14 , 2017 .' [/INST] [The:O, vulnerability:O, was:O, patched:O, by:O, Microsoft:B-Org, on:O, Nov:B-Time, 14:I-Time, ,:I-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: 'The vulnerability exists in the old Equation Editor ( EQNEDT32.EXE ) , a component of Microsoft Office that is used to insert and evaluate mathematical formulas .' [/INST] [The:O, vulnerability:O, exists:O, in:O, the:O, old:O, Equation:B-Tool, Editor:I-Tool, (:O, EQNEDT32.EXE:B-SamFile, ):O, ,:O, a:O, component:O, of:O, Microsoft:O, Office:O, that:O, is:O, used:O, to:O, insert:B-Features, and:I-Features, evaluate:I-Features, mathematical:I-Features, formulas: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: 'During the past few months , APT34 has been able to quickly incorporate exploits for at least two publicly vulnerabilities ( CVE-2017-0199 and CVE-2017-11882 ) to target organizations in the Middle East .' [/INST] [During:O, the:O, past:O, few:O, months:O, ,:O, APT34:B-HackOrg, has:O, been:O, able:O, to:O, quickly:O, incorporate:O, exploits:O, for:O, at:O, least:O, two:O, publicly:O, vulnerabilities:O, (:O, CVE-2017-0199:B-Exp, and:O, CVE-2017-11882:B-Exp, ):O, to:O, target:O, organizations:O, in:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The OilRig group ( AKA APT34 , Helix Kitten ) is an adversary motivated by espionage primarily operating in the Middle East region .' [/INST] [The:O, OilRig:B-HackOrg, group:I-HackOrg, (:O, AKA:O, APT34:B-HackOrg, ,:O, Helix:B-HackOrg, Kitten:I-HackOrg, ):O, is:O, an:O, adversary:O, motivated:O, by:O, espionage:B-HackOrg, primarily:O, operating:O, in:O, the:O, Middle:B-Area, East:I-Area, region:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We expect APT34 will continue to evolve their malware and tactics as they continue to pursue access to entities in the Middle East region .' [/INST] [We:O, expect:O, APT34:B-HackOrg, will:O, continue:O, to:O, evolve:O, their:O, malware:O, and:O, tactics:O, as:O, they:O, continue:O, to:O, pursue:O, access:O, to:O, entities:O, in:O, the:O, Middle:B-Area, East:I-Area, region:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The OilRig group ( AKA APT34 , Helix Kitten ) is an adversary motivated by espionage primarily operating in the Middle East region .' [/INST] [The:O, OilRig:B-HackOrg, group:I-HackOrg, (:O, AKA:O, APT34:B-HackOrg, ,:O, Helix:B-HackOrg, Kitten:I-HackOrg, ):O, is:O, an:O, adversary:O, motivated:O, by:O, espionage:B-HackOrg, primarily:O, operating:O, in:O, the:O, Middle:B-Area, East:I-Area, region:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We first discovered this group in mid-2016 , although it is possible their operations extends earlier than that time frame .' [/INST] [We:O, first:O, discovered:O, this:O, group:B-HackOrg, in:O, mid-2016:B-Time, ,:O, although:O, it:O, is:O, possible:O, their:O, operations:O, extends:O, earlier:O, than:O, that:O, time:O, frame:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 May and June 2018 , Unit 42 observed multiple attacks by the OilRig group appearing to originate from a government agency in the Middle East .' [/INST] [Between:O, May:B-Time, and:O, June:B-Time, 2018:I-Time, ,:O, Unit:B-SecTeam, 42:I-SecTeam, observed:O, multiple:O, attacks:B-OffAct, by:O, the:O, OilRig:B-HackOrg, group:I-HackOrg, appearing:O, to:O, originate:O, from:O, a:O, government:B-Org, agency:I-Org, in:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The use of script-based backdoors is a common technique used by the OilRig group as we have previously documented .' [/INST] [The:O, use:O, of:O, script-based:B-Tool, backdoors:I-Tool, is:O, a:O, common:O, technique:O, used:O, by:O, the:O, OilRig:B-HackOrg, group:I-HackOrg, as:O, we:O, have:O, previously:O, documented:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 attacks delivered a PowerShell backdoor called QUADAGENT , a tool attributed to the OilRig group by both ClearSky Cyber Security and FireEye .' [/INST] [The:O, attacks:B-OffAct, delivered:O, a:O, PowerShell:B-Tool, backdoor:I-Tool, called:O, QUADAGENT:B-Tool, ,:O, a:O, tool:O, attributed:O, to:O, the:O, OilRig:B-HackOrg, group:I-HackOrg, by:O, both:O, ClearSky:B-SecTeam, Cyber:I-SecTeam, Security:I-SecTeam, and:O, FireEye:B-SecTeam, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'A closer examination revealed the obfuscation used by the OilRig group in these QUADAGENT samples were likely the result of using an open-source toolkit called Invoke-Obfuscation .' [/INST] [A:O, closer:O, examination:O, revealed:O, the:O, obfuscation:O, used:O, by:O, the:O, OilRig:B-HackOrg, group:I-HackOrg, in:O, these:O, QUADAGENT:B-Tool, samples:I-Tool, were:O, likely:O, the:O, result:O, of:O, using:O, an:O, open-source:O, toolkit:O, called:O, Invoke-Obfuscation: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: 'All three waves involved a single spear phishing email that appeared to originate from a government agency based in the Middle East .' [/INST] [All:O, three:O, waves:O, involved:O, a:O, single:O, spear:B-Way, phishing:I-Way, email:I-Way, that:O, appeared:O, to:O, originate:O, from:O, a:O, government:B-Org, agency:I-Org, based:O, in:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This latest attack consisted of three waves between May and June 2018 .' [/INST] [This:O, latest:O, attack:B-OffAct, consisted:O, of:O, three:O, waves:O, between:O, May:B-Time, and:O, June: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 OilRig group continues to be a persistent adversary group in the Middle East region .' [/INST] [The:O, OilRig:B-HackOrg, group:I-HackOrg, continues:O, to:O, be:O, a:O, persistent:O, adversary:O, group:B-HackOrg, in:O, the:O, Middle:B-Area, East:I-Area, region:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT34 are involved in long-term cyber espionage operations largely focused on the Middle East .' [/INST] [APT34:B-HackOrg, are:O, involved:O, in:O, long-term:O, cyber:B-OffAct, espionage:I-OffAct, operations:I-OffAct, largely:O, focused:O, on:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This threat group has conducted broad targeting across a variety of industries , including financial , government , energy , chemical , and telecommunications .' [/INST] [This:O, threat:B-HackOrg, group:I-HackOrg, has:O, conducted:O, broad:O, targeting:O, across:O, a:O, variety:O, of:O, industries:O, ,:O, including:O, financial:B-Idus, ,:O, government:B-Idus, ,:O, energy:B-Idus, ,:O, chemical:B-Idus, ,:O, and:O, telecommunications: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: 'Recent investigations by FireEye 's Mandiant incident response consultants combined with FireEye iSIGHT Threat Intelligence analysis have given us a more complete picture of a suspected Iranian threat group , that we believe has been operating since at least 2014 .' [/INST] [Recent:O, investigations:O, by:O, FireEye:B-SecTeam, 's:I-SecTeam, Mandiant:I-SecTeam, incident:O, response:O, consultants:O, combined:O, with:O, FireEye:B-SecTeam, iSIGHT:I-SecTeam, Threat:I-SecTeam, Intelligence:I-SecTeam, analysis:O, have:O, given:O, us:O, a:O, more:O, complete:O, picture:O, of:O, a:O, suspected:O, Iranian:B-Area, threat:B-HackOrg, group:I-HackOrg, ,:O, that:O, we:O, believe:O, has:O, been:O, operating:O, since:O, at:O, least: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: 'Join us in a live webinar as we discuss this threat group whom we assess to be working on behalf of the Iranian Government , with a mission that would benefit nation-state geopolitical and economic needs .' [/INST] [Join:O, us:O, in:O, a:O, live:O, webinar:O, as:O, we:O, discuss:O, this:O, threat:B-HackOrg, group:I-HackOrg, whom:O, we:O, assess:O, to:O, be:O, working:O, on:O, behalf:O, of:O, the:O, Iranian:B-Org, Government:I-Org, ,:O, with:O, a:O, mission:O, that:O, would:O, benefit:O, nation-state:B-Idus, geopolitical:I-Idus, and:O, economic:B-Idus, needs:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 8 , 2018 , Unit 42 observed the OilRig threat group carry out an attack on an insurance agency based in the Middle East .' [/INST] [On:O, January:B-Time, 8:I-Time, ,:I-Time, 2018:I-Time, ,:O, Unit:B-SecTeam, 42:I-SecTeam, observed:O, the:O, OilRig:B-HackOrg, threat:B-HackOrg, group:I-HackOrg, carry:O, out:O, an:O, attack:B-OffAct, on:O, an:O, insurance:B-Org, agency:I-Org, based:O, in:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT34 uses a mix of public and non-public tools , often conducting spear phishing operations using compromised accounts from trusted third parties , sometimes coupled with social engineering tactics .' [/INST] [APT34:B-HackOrg, uses:O, a:O, mix:O, of:O, public:B-Tool, and:I-Tool, non-public:I-Tool, tools:I-Tool, ,:O, often:O, conducting:O, spear:B-Way, phishing:I-Way, operations:I-Way, using:O, compromised:B-Tool, accounts:I-Tool, from:O, trusted:O, third:O, parties:O, ,:O, sometimes:O, coupled:O, with:O, social:B-Way, engineering:I-Way, tactics: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: 'Just over a week later , on January 16 , 2018 , we observed an attack on a Middle Eastern financial institution .' [/INST] [Just:O, over:O, a:O, week:O, later:O, ,:O, on:O, January:B-Time, 16:I-Time, ,:I-Time, 2018:I-Time, ,:O, we:O, observed:O, an:O, attack:B-OffAct, on:O, a:O, Middle:B-Area, Eastern:I-Area, financial:B-Org, institution: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 January 8 attack used a variant of the ThreeDollars delivery document , which we identified as part of the OilRig toolset based on attacks that occurred in August 2017 .' [/INST] [The:O, January:B-OffAct, 8:I-OffAct, attack:I-OffAct, used:O, a:O, variant:O, of:O, the:O, ThreeDollars:B-SamFile, delivery:I-SamFile, document:I-SamFile, ,:O, which:O, we:O, identified:O, as:O, part:O, of:O, the:O, OilRig:B-HackOrg, toolset:O, based:O, on:O, attacks:B-OffAct, that:O, occurred:O, in: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: 'However , the attack on January 16 did not involve ThreeDollars at all .' [/INST] [However:O, ,:O, the:O, attack:B-OffAct, on:O, January:B-Time, 16:I-Time, did:O, not:O, involve:O, ThreeDollars:B-Tool, at:O, all:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Interestingly , the targeted organization in the January 16 attack had already been targeted by the OilRig group a year ago on January 2017 .' [/INST] [Interestingly:O, ,:O, the:O, targeted:O, organization:O, in:O, the:O, January:B-OffAct, 16:I-OffAct, attack:I-OffAct, had:O, already:O, been:O, targeted:O, by:O, the:O, OilRig:B-HackOrg, group:I-HackOrg, a:O, year:O, ago:O, on:O, January: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: 'Instead , OilRig 's attack involved delivering the OopsIE Trojan directly to the victim , most likely using a link in a spear phishing email .' [/INST] [Instead:O, ,:O, OilRig:B-HackOrg, 's:O, attack:B-OffAct, involved:O, delivering:O, the:O, OopsIE:B-Tool, Trojan:I-Tool, directly:O, to:O, the:O, victim:O, ,:O, most:O, likely:O, using:O, a:O, link:O, in:O, a:O, spear:B-Way, phishing:I-Way, email: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: 'In the January 16 , 2018 attack , we observed OilRig attacking an organization it previously targeted in January 2017 .' [/INST] [In:O, the:O, January:B-Time, 16:I-Time, ,:O, 2018:B-OffAct, attack:I-OffAct, ,:O, we:O, observed:O, OilRig:O, attacking:O, an:O, organization:O, it:O, previously:O, targeted:O, in:O, January: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: 'On January 8 , 2018 , the OilRig threat group sent an email with the subject Beirut Insurance Seminar Invitation to an insurance agency in the Middle East .' [/INST] [On:O, January:B-Time, 8:I-Time, ,:I-Time, 2018:I-Time, ,:O, the:O, OilRig:B-HackOrg, threat:B-HackOrg, group:I-HackOrg, sent:O, an:O, email:B-Way, with:O, the:O, subject:O, Beirut:O, Insurance:O, Seminar:O, Invitation:O, to:O, an:O, insurance:B-Org, agency:I-Org, in:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The email contained an attachment named Seminar-Invitation.doc , which is a malicious Microsoft Word document we track as ThreeDollars .' [/INST] [The:O, email:B-Way, contained:O, an:O, attachment:O, named:O, Seminar-Invitation.doc:B-SamFile, ,:O, which:O, is:O, a:O, malicious:O, Microsoft:B-Tool, Word:I-Tool, document:O, we:O, track:O, as:O, ThreeDollars: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: 'This suggests that due to the January 2017 attack , the targeted organization may have taken actions to counter known OilRig TTPs , in this case delivering malicious macro documents , causing the OilRig operators to adopt a different delivery tactic .' [/INST] [This:O, suggests:O, that:O, due:O, to:O, the:O, January:B-OffAct, 2017:I-OffAct, attack:I-OffAct, ,:O, the:O, targeted:O, organization:O, may:O, have:O, taken:O, actions:O, to:O, counter:O, known:O, OilRig:B-HackOrg, TTPs:O, ,:O, in:O, this:O, case:O, delivering:O, malicious:O, macro:O, documents:O, ,:O, causing:O, the:O, OilRig:B-HackOrg, operators:B-HackOrg, to:O, adopt:O, a:O, different:O, delivery:O, tactic:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 also identified another sample of ThreeDollars , created on January 15 , 2017 with the file name strategy preparation.dot .' [/INST] [We:O, also:O, identified:O, another:O, sample:O, of:O, ThreeDollars:B-Tool, ,:O, created:O, on:O, January:B-Time, 15:I-Time, ,:O, 2017:B-Time, with:O, the:O, file:O, name:O, strategy:O, preparation.dot:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The samples of ThreeDollars we collected in these attacks are structurally very similar to the first sample we analyzed in October 2017 , down to the lure image used to trick the recipient into clicking the , Enable Content , button to execute the malicious macro .' [/INST] [The:O, samples:O, of:O, ThreeDollars:B-Tool, we:O, collected:O, in:O, these:O, attacks:B-OffAct, are:O, structurally:O, very:O, similar:O, to:O, the:O, first:O, sample:O, we:O, analyzed:O, in:O, October:B-Time, 2017:I-Time, ,:O, down:O, to:O, the:O, lure:O, image:O, used:O, to:O, trick:O, the:O, recipient:O, into:O, clicking:O, the:O, ,:O, Enable:O, Content:O, ,:O, button:O, to:O, execute:O, the:O, malicious:O, macro:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 May 2016 , we have continued to monitor and uncover various attacks and tools associated with the OilRig group .' [/INST] [Since:O, May:B-Time, 2016:I-Time, ,:O, we:O, have:O, continued:O, to:O, monitor:O, and:O, uncover:O, various:O, attacks:B-OffAct, and:O, tools:O, associated:O, with:O, the:O, OilRig: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: '] com , which we previously identified in October 2017 to be an OilRig C2 .' [/INST] []:O, com:O, ,:O, which:O, we:O, previously:O, identified:O, in:O, October:B-Time, 2017:I-Time, to:O, be:O, an:O, OilRig:B-HackOrg, C2:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Based on previously observed tactics , it is highly likely the OilRig group leveraged credential harvesting and compromised accounts to use the government agency as a launching platform for their true attacks .' [/INST] [Based:O, on:O, previously:O, observed:O, tactics:O, ,:O, it:O, is:O, highly:O, likely:O, the:O, OilRig:B-HackOrg, group:I-HackOrg, leveraged:O, credential:B-Tool, harvesting:I-Tool, and:O, compromised:B-Tool, accounts:I-Tool, to:O, use:O, the:O, government:B-Org, agency:I-Org, as:O, a:O, launching:O, platform:O, for:O, their:O, true: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: 'Inspecting the class C network for 185.162.235.0/24 shows us that another IP on the same network resolves to an OilRig domain , msoffice-cdn.com which we identified in August 2017 .' [/INST] [Inspecting:O, the:O, class:O, C:O, network:O, for:O, 185.162.235.0/24:O, shows:O, us:O, that:O, another:O, IP:O, on:O, the:O, same:O, network:O, resolves:O, to:O, an:O, OilRig:B-HackOrg, domain:O, ,:O, msoffice-cdn.com:O, which:O, we:O, identified:O, in: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: 'We had previously observed this author name in use once before , in the very first ThreeDollars document we collected that we had reported on in August 2017 .' [/INST] [We:O, had:O, previously:O, observed:O, this:O, author:O, name:O, in:O, use:O, once:O, before:O, ,:O, in:O, the:O, very:O, first:O, ThreeDollars:B-SamFile, document:I-SamFile, we:O, collected:O, that:O, we:O, had:O, reported:O, on:O, in: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: 'The OilRig group continues to remain a highly active adversary in the Middle East region .' [/INST] [The:O, OilRig:B-HackOrg, group:I-HackOrg, continues:O, to:O, remain:O, a:O, highly:O, active:O, adversary:O, in:O, the:O, Middle:B-Area, East:I-Area, region:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Organizations detected a compromise themselves in 62% of the cases that Mandiant worked in 2017 .' [/INST] [Organizations:O, detected:O, a:O, compromise:O, themselves:O, in:O, 62%:O, of:O, the:O, cases:O, that:O, Mandiant:B-SecTeam, worked:O, in: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: 'The group conducts operations primarily in the Middle East , targeting financial , government , energy , chemical , telecommunications and other industries .' [/INST] [The:O, group:B-HackOrg, conducts:O, operations:O, primarily:O, in:O, the:O, Middle:B-Area, East:I-Area, ,:O, targeting:O, financial:B-Idus, ,:O, government:B-Idus, ,:O, energy:B-Idus, ,:O, chemical:B-Idus, ,:O, telecommunications:B-Idus, and:O, other:O, industries:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Repeated targeting of Middle Eastern financial , energy and government organizations leads FireEye to assess that those sectors are a primary concern of APT34 .' [/INST] [Repeated:O, targeting:O, of:O, Middle:B-Area, Eastern:I-Area, financial:B-Org, ,:O, energy:B-Org, and:O, government:B-Org, organizations:I-Org, leads:O, FireEye:B-SecTeam, to:O, assess:O, that:O, those:O, sectors:O, are:O, a:O, primary:O, concern:O, of:O, APT34: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 use of infrastructure tied to Iranian operations , timing and alignment with the national interests of Iran also lead FireEye to assess that APT34 acts on behalf of the Iranian government .' [/INST] [The:O, use:O, of:O, infrastructure:O, tied:O, to:O, Iranian:B-Area, operations:O, ,:O, timing:O, and:O, alignment:O, with:O, the:O, national:O, interests:O, of:O, Iran:B-Area, also:O, lead:O, FireEye:B-SecTeam, to:O, assess:O, that:O, APT34:B-HackOrg, acts:O, on:O, behalf:O, of:O, the:O, Iranian:B-Area, government:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT34 uses a mix of public and non-public tools ( Fig.2 ) and often uses compromised accounts to conduct spear-phishing operations .' [/INST] [APT34:B-HackOrg, uses:O, a:O, mix:O, of:O, public:B-Tool, and:I-Tool, non-public:I-Tool, tools:I-Tool, (:O, Fig.2:O, ):O, and:O, often:O, uses:O, compromised:B-Tool, accounts:I-Tool, to:O, conduct:O, spear-phishing:B-Way, operations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 November 2017 , APT34 leveraged the Microsoft Office vulnerability CVE-2017-11882 to deploy POWRUNER and BONDUPDATER less than a week after Microsoft issued a patch .' [/INST] [In:O, November:B-Time, 2017:I-Time, ,:O, APT34:B-HackOrg, leveraged:O, the:O, Microsoft:B-Exp, Office:I-Exp, vulnerability:I-Exp, CVE-2017-11882:B-Exp, to:O, deploy:O, POWRUNER:B-Tool, and:O, BONDUPDATER:B-Tool, less:O, than:O, a:O, week:O, after:O, Microsoft:B-Org, issued:O, a:O, patch:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 's ongoing research into the OilRig campaign shows that the threat actors involved in the original attack campaign continue to add new Trojans to their toolset and continue their persistent attacks in the Middle East .' [/INST] [Unit:B-SecTeam, 42:I-SecTeam, 's:O, ongoing:O, research:O, into:O, the:O, OilRig:B-OffAct, campaign:I-OffAct, shows:O, that:O, the:O, threat:B-HackOrg, actors:I-HackOrg, involved:O, in:O, the:O, original:O, attack:B-OffAct, campaign:I-OffAct, continue:O, to:O, add:O, new:O, Trojans:O, to:O, their:O, toolset:O, and:O, continue:O, their:O, persistent:O, attacks:B-OffAct, in:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'When we first discovered the OilRig attack campaign in May 2016 , we believed at the time it was a unique attack campaign likely operated by a known , existing threat group .' [/INST] [When:O, we:O, first:O, discovered:O, the:O, OilRig:B-OffAct, attack:I-OffAct, campaign:I-OffAct, in:O, May:B-Time, 2016:I-Time, ,:O, we:O, believed:O, at:O, the:O, time:O, it:O, was:O, a:O, unique:O, attack:B-OffAct, campaign:I-OffAct, likely:O, operated:O, by:O, a:O, known:O, ,:O, existing:O, threat: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: 'The email address is associated with the Lebanese domain of a major global financial institution .' [/INST] [The:O, email:O, address:O, is:O, associated:O, with:O, the:O, Lebanese:O, domain:O, of:O, a:O, major:O, global:O, financial:B-Org, institution: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: 'POWRUNER was delivered using a malicious RTF file that exploited CVE-2017-0199 .' [/INST] [POWRUNER:B-Tool, was:O, delivered:O, using:O, a:O, malicious:B-Tool, RTF:I-Tool, file:O, that:O, exploited: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: 'In July 2017 , we observed the OilRig group using a tool they developed called ISMAgent in a new set of targeted attacks .' [/INST] [In:O, July:B-Time, 2017:I-Time, ,:O, we:O, observed:O, the:O, OilRig:B-HackOrg, group:I-HackOrg, using:O, a:O, tool:O, they:O, developed:O, called:O, ISMAgent:B-Tool, in:O, a:O, new:O, set:O, of: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: 'In August 2017 , we found this threat group has developed yet another Trojan that they call ' Agent Injector ' with the specific purpose of installing the ISMAgent backdoor .' [/INST] [In:O, August:B-Time, 2017:I-Time, ,:O, we:O, found:O, this:O, threat:B-HackOrg, group:I-HackOrg, has:O, developed:O, yet:O, another:O, Trojan:O, that:O, they:O, call:O, ':O, Agent:O, Injector:O, ':O, with:O, the:O, specific:O, purpose:O, of:O, installing:O, the:O, ISMAgent: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: 'On August 23 , 2017 , we observed OilRig targeting an organization within the United Arab Emirates government .' [/INST] [On:O, August:B-Time, 23:I-Time, ,:I-Time, 2017:I-Time, ,:O, we:O, observed:O, OilRig:B-HackOrg, targeting:O, an:O, organization:O, within:O, the:O, United:B-Area, Arab:I-Area, Emirates:I-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: 'Based on that research and this observation , we postulate that the OilRig group gathered credentials to a legitimate user 's OWA account and logged into the user 's account to send phishing attacks to other individuals within the same , targeted organization .' [/INST] [Based:O, on:O, that:O, research:O, and:O, this:O, observation:O, ,:O, we:O, postulate:O, that:O, the:O, OilRig:B-HackOrg, group:I-HackOrg, gathered:O, credentials:O, to:O, a:O, legitimate:O, user:O, 's:O, OWA:O, account:O, and:O, logged:O, into:O, the:O, user:O, 's:O, account:O, to:O, send:O, phishing:B-OffAct, attacks:I-OffAct, to:O, other:O, individuals:O, within:O, the:O, same:O, ,:O, targeted:O, organization:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The OilRig group continues to target organizations in the Middle East , in this instance targeting the government of the United Arab Emirates .' [/INST] [The:O, OilRig:B-HackOrg, group:I-HackOrg, continues:O, to:O, target:O, organizations:O, in:O, the:O, Middle:B-Area, East:I-Area, ,:O, in:O, this:O, instance:O, targeting:O, the:O, government:B-Idus, of:O, the:O, United:B-Area, Arab:I-Area, Emirates: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 payload embedded within the ISMInjector sample delivered in this attack is a variant of the ISMAgent backdoor that we had discussed in detail in our blog discussing a targeted attack on a Saudi Arabian technology company .' [/INST] [The:O, payload:O, embedded:O, within:O, the:O, ISMInjector:B-Tool, sample:I-Tool, delivered:O, in:O, this:O, attack:B-OffAct, is:O, a:O, variant:O, of:O, the:O, ISMAgent:B-Tool, backdoor:I-Tool, that:O, we:O, had:O, discussed:O, in:O, detail:O, in:O, our:O, blog:O, discussing:O, a:O, targeted:B-OffAct, attack:I-OffAct, on:O, a:O, Saudi:B-Area, Arabian:I-Area, technology:B-Org, company:I-Org, .:O] </s> |
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