text stringlengths 306 1.51k |
|---|
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 blog post we'll analyze two specific incidents apparently targeting victims in Vietnam and in India and we'll describe the capabilities of the custom backdoor being used that for convenience ( and to our knowledge , for a lack of an existing name ) we call KeyBoy , due to a string present in one of the samples .' [/INST] [In:O, this:O, blog:O, post:O, we'll:O, analyze:O, two:O, specific:O, incidents:O, apparently:O, targeting:O, victims:O, in:O, Vietnam:B-Area, and:O, in:O, India:B-Area, and:O, we'll:O, describe:O, the:O, capabilities:O, of:O, the:O, custom:O, backdoor:B-Tool, being:O, used:O, that:O, for:O, convenience:O, (:O, and:O, to:O, our:O, knowledge:O, ,:O, for:O, a:O, lack:O, of:O, an:O, existing:O, name:O, ):O, we:O, call:O, KeyBoy:B-Tool, ,:O, due:O, to:O, a:O, string:O, present:O, in:O, one:O, of:O, the: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: 'We encountered the first document exploit called , THAM luan - GD - NCKH2.doc , a few days ago , which appears to be leveraging some vulnerabilities patched with MS12-060 .' [/INST] [We:O, encountered:O, the:O, first:O, document:O, exploit:O, called:O, ,:O, THAM:B-SamFile, luan:I-SamFile, -:I-SamFile, GD:I-SamFile, -:I-SamFile, NCKH2.doc:B-SamFile, ,:O, a:O, few:O, days:O, ago:O, ,:O, which:O, appears:O, to:O, be:O, leveraging:O, some:O, vulnerabilities:O, patched:O, with:O, MS12-060: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 document , written in Vietnamese , appears to be reviewing and discussing best practices for teaching and researching scientific topics .' [/INST] [This:O, document:B-SamFile, ,:O, written:O, in:O, Vietnamese:O, ,:O, appears:O, to:O, be:O, reviewing:B-Features, and:I-Features, discussing:I-Features, best:I-Features, practices:I-Features, for:O, teaching:O, and:O, researching:O, scientific: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: 'For the sake of this analysis we'll take the Vietnamese backdoor as an example ; the one found in the Indian attack operates in the exact same way .' [/INST] [For:O, the:O, sake:O, of:O, this:O, analysis:O, we'll:O, take:O, the:O, Vietnamese:B-Tool, backdoor:I-Tool, as:O, an:O, example:O, ;:O, the:O, one:O, found:O, in:O, the:O, Indian:B-OffAct, attack:I-OffAct, operates:O, in:O, the:O, exact:O, same:O, way:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 second set they are making use of a dynamic DNS service by ChangeIP.com .' [/INST] [In:O, the:O, second:O, set:O, they:O, are:O, making:O, use:O, of:O, a:O, dynamic:B-Tool, DNS:I-Tool, service:I-Tool, by:O, ChangeIP.com:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Tibetan community has been targeted for over a decade by espionage operations that use malware to infiltrate communications and gather information .' [/INST] [The:O, Tibetan:B-Org, community:I-Org, has:O, been:O, targeted:O, for:O, over:O, a:O, decade:O, by:O, espionage:B-OffAct, operations:I-OffAct, that:O, use:O, malware:B-Tool, to:O, infiltrate:B-Purp, communications:I-Purp, and:O, gather:B-Purp, information:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'he Tibetan community has been targeted for over a decade by espionage operations that use malware to infiltrate communications and gather information .' [/INST] [he:O, Tibetan:B-Org, community:I-Org, has:O, been:O, targeted:O, for:O, over:O, a:O, decade:O, by:O, espionage:B-OffAct, operations:I-OffAct, that:O, use:O, malware:B-Tool, to:O, infiltrate:B-Purp, communications:I-Purp, and:O, gather:B-Purp, information:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'They are often targeted simultaneously with other ethnic minorities and religious groups in China .' [/INST] [They:O, are:O, often:O, targeted:O, simultaneously:O, with:O, other:O, ethnic:B-Org, minorities:I-Org, and:O, religious:B-Org, groups:I-Org, in:O, China:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Examples as early as 2008 document malware operations against Tibetan non-governmental organizations ( NGOs ) that also targeted Falun Gong and Uyghur groups .' [/INST] [Examples:O, as:O, early:O, as:O, 2008:B-Time, document:B-SamFile, malware:I-SamFile, operations:O, against:O, Tibetan:B-Org, non-governmental:I-Org, organizations:I-Org, (:O, NGOs:O, ):O, that:O, also:O, targeted:O, Falun:B-Org, Gong:I-Org, and:O, Uyghur:B-Org, groups: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: 'More recently in 2016 , Arbor Networks reported on connected malware operations continuing to target these same groups , which the Communist Party of China perceives as a threat to its power .' [/INST] [More:O, recently:O, in:O, 2016:B-Time, ,:O, Arbor:B-SecTeam, Networks:I-SecTeam, reported:O, on:O, connected:O, malware:O, operations:O, continuing:O, to:O, target:O, these:O, same:O, groups:O, ,:O, which:O, the:O, Communist:O, Party:O, of:O, China:O, perceives:O, as:O, a:O, threat:O, to:O, its:O, power:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'There is the exploit code and malware used to gain access to systems , the infrastructure that provides command and control to the malware operator , and the human elements – developers who create the malware , operators who deploy it , and analysts who extract value from the stolen information .' [/INST] [There:O, is:O, the:O, exploit:B-SamFile, code:I-SamFile, and:O, malware:O, used:O, to:O, gain:B-Features, access:I-Features, to:I-Features, systems:I-Features, ,:O, the:O, infrastructure:O, that:O, provides:B-Features, command:I-Features, and:I-Features, control:I-Features, to:O, the:O, malware:O, operator:O, ,:O, and:O, the:O, human:O, elements:O, –:O, developers:O, who:O, create:O, the:O, malware:O, ,:O, operators:O, who:O, deploy:O, it:O, ,:O, and:O, analysts:O, who:O, extract:O, value:O, from:O, the:O, stolen:O, information:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'For example , we have observed frequent reuse of older ( patched ) exploits in malware operations against the Tibetan community .' [/INST] [For:O, example:O, ,:O, we:O, have:O, observed:O, frequent:O, reuse:O, of:O, older:O, (:O, patched:O, ):O, exploits:O, in:O, malware:O, operations:O, against:O, the:O, Tibetan:B-Org, community: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: 'These operations involved highly targeted email lures with repurposed content and attachments that contained an updated version of KeyBoy .' [/INST] [These:O, operations:O, involved:O, highly:O, targeted:O, email:B-Tool, lures:I-Tool, with:O, repurposed:O, content:O, and:O, attachments:O, that:O, contained:O, an:O, updated:O, version:O, of:O, KeyBoy: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: 'In August and October 2016 we observed a malware operation targeting members of the Tibetan Parliament ( the highest legislative organ of the Tibetan government in exile , formally known as Central Tibetan Administration ) .' [/INST] [In:O, August:O, and:O, October:B-Time, 2016:I-Time, we:O, observed:O, a:O, malware:B-OffAct, operation:I-OffAct, targeting:O, members:O, of:O, the:O, Tibetan:B-Org, Parliament:I-Org, (:O, the:O, highest:O, legislative:O, organ:O, of:O, the:O, Tibetan:B-Org, government:I-Idus, in:O, exile:O, ,:O, formally:O, known:O, as:O, Central:B-Org, Tibetan:I-Org, Administration:I-Org, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Arbor report describes the ongoing use of these four vulnerabilities in a series of espionage campaigns against not only Tibetan groups , but also others related to Hong Kong , Taiwan , and Uyghur interests .' [/INST] [The:O, Arbor:B-SecTeam, report:O, describes:O, the:O, ongoing:O, use:O, of:O, these:O, four:O, vulnerabilities:O, in:O, a:O, series:O, of:O, espionage:B-OffAct, campaigns:I-OffAct, against:O, not:O, only:O, Tibetan:B-Org, groups:I-Org, ,:O, but:O, also:O, others:O, related:O, to:O, Hong:B-Area, Kong:I-Area, ,:O, Taiwan:B-Area, ,:O, and:O, Uyghur:B-Area, 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: 'The malware samples deployed in both of these operations are updated versions of the KeyBoy backdoor first discussed in 2013 by Rapid7 .' [/INST] [The:O, malware:O, samples:O, deployed:O, in:O, both:O, of:O, these:O, operations:O, are:O, updated:O, versions:O, of:O, the:O, KeyBoy:B-Tool, backdoor:I-Tool, first:O, discussed:O, in:O, 2013:B-Time, by:O, Rapid7: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: 'This behavioural tactic was previously mentioned in relation to KeyBoy in a 2013 blog post by Cisco .' [/INST] [This:O, behavioural:O, tactic:O, was:O, previously:O, mentioned:O, in:O, relation:O, to:O, KeyBoy:B-Tool, in:O, a:O, 2013:B-Time, blog:O, post:O, by:O, Cisco: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: 'These versions of KeyBoy differed from the one first described by Rapid7 in several ways , many of which will be described in the sections to follow .' [/INST] [These:O, versions:O, of:O, KeyBoy:B-Tool, differed:O, from:O, the:O, one:O, first:O, described:O, by:O, Rapid7:B-SecTeam, in:O, several:O, ways:O, ,:O, many:O, of:O, which:O, will:O, be:O, described:O, in:O, the:O, sections:O, to:O, follow:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 samples were contained in exploit documents containing distinct lure content , one having a Tibetan nexus , the other an Indian nexus .' [/INST] [These:O, samples:O, were:O, contained:O, in:O, exploit:O, documents:O, containing:O, distinct:O, lure:O, content:O, ,:O, one:O, having:O, a:O, Tibetan:O, nexus:O, ,:O, the:O, other:O, an:O, Indian:B-Area, nexus:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We believe the 2013 , 2015 , and 2016 KeyBoy samples provide evidence of a development effort focused on changing components that would be used by researchers to develop detection signatures .' [/INST] [We:O, believe:O, the:O, 2013:B-Time, ,:O, 2015:B-Time, ,:O, and:O, 2016:B-Time, KeyBoy:B-Tool, samples:I-Tool, provide:O, evidence:O, of:O, a:O, development:O, effort:O, focused:O, on:O, changing:O, components:O, that:O, would:O, be:O, used:O, by:O, researchers:O, to:O, develop:B-Features, detection:I-Features, signatures: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: 'In another modification , first observed in the most recent October 11 Parliamentarian operation ( version agewkassif ) , the developer (s ) of KeyBoy began using a string obfuscation routine in order to hide many of the critical values referenced within the malware .' [/INST] [In:O, another:O, modification:O, ,:O, first:O, observed:O, in:O, the:O, most:O, recent:O, October:B-Time, 11:O, Parliamentarian:O, operation:O, (:O, version:O, agewkassif:O, ):O, ,:O, the:O, developer:O, (s:O, ):O, of:O, KeyBoy:B-Tool, began:O, using:O, a:O, string:B-Tool, obfuscation:I-Tool, routine:I-Tool, in:O, order:O, to:O, hide:B-Purp, many:I-Purp, of:I-Purp, the:I-Purp, critical:I-Purp, values:I-Purp, referenced: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: 'Trend Micro specifically noted that the 2013 versions of KeyBoy used the same algorithm for encoding their configuration files as was observed in the Operation Tropic Trooper malware .' [/INST] [Trend:B-SecTeam, Micro:I-SecTeam, specifically:O, noted:O, that:O, the:O, 2013:B-Time, versions:O, of:O, KeyBoy:B-Tool, used:O, the:O, same:O, algorithm:O, for:O, encoding:O, their:O, configuration:O, files:O, as:O, was:O, observed:O, in:O, the:O, Operation:B-OffAct, Tropic:I-OffAct, Trooper:I-OffAct, malware:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This sample was also found to be deployed using the CVE-2012-0158 vulnerability .' [/INST] [This:O, sample:O, was:O, also:O, found:O, to:O, be:O, deployed:O, using:O, the:O, CVE-2012-0158:B-Exp, vulnerability:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The operation against the Tibetan Parliamentarians illustrates the continued use of malicious attachments in the form of documents bearing exploits .' [/INST] [The:O, operation:O, against:O, the:O, Tibetan:B-Org, Parliamentarians:I-Org, illustrates:O, the:O, continued:O, use:O, of:O, malicious:B-SamFile, attachments:I-SamFile, in:O, the:O, form:O, of:O, documents:B-Tool, bearing:I-Tool, exploits: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: 'Chances are about even , though , that Mofang is a relevant threat actor to any organization that invests in Myanmar or is otherwise politically involved .' [/INST] [Chances:O, are:O, about:O, even:O, ,:O, though:O, ,:O, that:O, Mofang:B-HackOrg, is:O, a:O, relevant:O, threat:O, actor:O, to:O, any:O, organization:O, that:O, invests:O, in:O, Myanmar:B-Area, or:O, is:O, otherwise:O, politically:B-Idus, involved:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the campaign in Myanmar , Mofang has been observed to attack targets across multiple sectors ( government , military , critical infrastructure and the automotive and weapon industries ) in multiple countries .' [/INST] [In:O, addition:O, to:O, the:O, campaign:B-OffAct, in:O, Myanmar:B-Area, ,:O, Mofang:B-HackOrg, has:O, been:O, observed:O, to:O, attack:O, targets:O, across:O, multiple:O, sectors:O, (:O, government:B-Idus, ,:O, military:B-Idus, ,:O, critical:B-Idus, infrastructure:I-Idus, and:O, the:O, automotive:B-Idus, and:O, weapon:B-Idus, industries:I-Idus, ):O, in:O, multiple: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: 'This threat report gives insight into some of the information that Fox-IT has about a threat actor that it follows , called Mofang .' [/INST] [This:O, threat:O, report:O, gives:O, insight:O, into:O, some:O, of:O, the:O, information:O, that:O, Fox-IT:B-SecTeam, has:O, about:O, a:O, threat:O, actor:O, that:O, it:O, follows:O, ,:O, called:O, Mofang: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 name Mofang is based on the Mandarin verb , which means to imitate .' [/INST] [The:O, name:O, Mofang:B-HackOrg, is:O, based:O, on:O, the:O, Mandarin:O, verb:O, ,:O, which:O, means:O, to:O, imitate:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the Mofang group is a group that operates out of China and is probably government-affiliated .' [/INST] [It:O, is:O, highly:O, likely:O, that:O, the:O, Mofang:B-HackOrg, group:I-HackOrg, is:O, a:O, group:O, that:O, operates:O, out:O, of:O, China:B-Area, and:O, is:O, probably:O, government-affiliated:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Chapter 7 explains the working of Mofang 's preferred tools : ShimRat and SimRatReporter .' [/INST] [Chapter:O, 7:O, explains:O, the:O, working:O, of:O, Mofang:O, 's:O, preferred:O, tools:O, ::O, ShimRat:B-Tool, and:O, SimRatReporter: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 Mofang group has been active in relation to the Kyaukphyu sez .' [/INST] [The:O, Mofang:B-HackOrg, group:I-HackOrg, has:O, been:O, active:O, in:O, relation:O, to:O, the:O, Kyaukphyu:O, sez:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'KeyBoy provides basic backdoor functionality , allowing the operators to select from various capabilities used to surveil and steal information from the victim machine .' [/INST] [KeyBoy:B-Tool, provides:O, basic:O, backdoor:O, functionality:O, ,:O, allowing:O, the:O, operators:O, to:O, select:B-Features, from:I-Features, various:I-Features, capabilities:I-Features, used:O, to:O, surveil:O, and:O, steal:B-Features, information:I-Features, from:O, the:O, victim:O, machine:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The first attack started in early July with a ShimRatReporter payload .' [/INST] [The:O, first:O, attack:B-OffAct, started:O, in:O, early:O, July:B-Time, with:O, a:O, ShimRatReporter:B-SamFile, 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: 'Myanmar has been the target of Mofang 's attacks for years before the campaign related to the sez .' [/INST] [Myanmar:B-Area, has:O, been:O, the:O, target:O, of:O, Mofang:B-HackOrg, 's:O, attacks:B-OffAct, for:O, years:O, before:O, the:O, campaign:B-OffAct, related:O, to:O, the:O, sez:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In late September 2015 Mofang used the website of Myanmar 's national airline hosted at www.flymna.com for an attack against an organization in Myanmar .' [/INST] [In:O, late:O, September:B-Time, 2015:I-Time, Mofang:B-HackOrg, used:O, the:O, website:O, of:O, Myanmar:B-Area, 's:O, national:O, airline:O, hosted:O, at:O, www.flymna.com:O, for:O, an:O, attack:B-OffAct, against:O, an:O, organization:O, in:O, Myanmar:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In December 2012 Mofang started a campaign against a new target , called ' seg ' for the purpose of this report .' [/INST] [In:O, December:B-Time, 2012:I-Time, Mofang:O, started:O, a:O, campaign:B-OffAct, against:O, a:O, new:O, target:O, ,:O, called:O, ':O, seg:O, ':O, for:O, the:O, purpose:O, of:O, this:O, report:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'From the configuration it can be determined that the company was running F-Secure Antivirus and Mofang registered the domain to not appear suspicious .' [/INST] [From:O, the:O, configuration:O, it:O, can:O, be:O, determined:O, that:O, the:O, company:O, was:O, running:O, F-Secure:B-Tool, Antivirus:I-Tool, and:O, Mofang:B-Tool, registered:O, the:O, domain:O, to:O, not:O, appear:O, suspicious:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In September 2015 Mofang launched another attack .' [/INST] [In:O, September:B-Time, 2015:I-Time, Mofang:B-HackOrg, launched:O, another:O, attack: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: 'A new version of ShimRat was built on the 7th of September , uploaded to the server and only days later used in a new campaign .' [/INST] [A:O, new:O, version:O, of:O, ShimRat:B-Tool, was:O, built:O, on:O, the:O, 7th:O, of:O, September:O, ,:O, uploaded:O, to:O, the:O, server:O, and:O, only:O, days:O, later:O, used:O, in:O, a:O, new:O, campaign: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: 'MoneyTaker has primarily been targeting card processing systems , including the AWS CBR ( Russian Interbank System ) and purportedly SWIFT ( US ) .' [/INST] [MoneyTaker:O, has:O, primarily:O, been:O, targeting:O, card:O, processing:O, systems:O, ,:O, including:O, the:O, AWS:O, CBR:O, (:O, Russian:O, Interbank:O, System:O, ):O, and:O, purportedly:O, SWIFT:O, (:O, US:O, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Given the wide usage of STAR in LATAM , financial institutions in LATAM could have particular exposure to a potential interest from the MoneyTaker group .' [/INST] [Given:O, the:O, wide:O, usage:O, of:O, STAR:O, in:O, LATAM:O, ,:O, financial:B-Org, institutions:I-Org, in:O, LATAM:O, could:O, have:O, particular:O, exposure:O, to:O, a:O, potential:O, interest:O, from:O, the:O, MoneyTaker: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: 'In addition to banks , the MoneyTaker group has attacked law firms and also financial software vendors .' [/INST] [In:O, addition:O, to:O, banks:B-Idus, ,:O, the:O, MoneyTaker:B-HackOrg, group:I-HackOrg, has:O, attacked:O, law:B-Org, firms:I-Org, and:O, also:O, financial:O, software:O, vendors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 that time , the group attacked companies in California , Utah , Oklahoma , Colorado , Illinois , Missouri , South Carolina , North Carolina , Virginia and Florida .' [/INST] [Since:O, that:O, time:O, ,:O, the:O, group:O, attacked:O, companies:O, in:O, California:B-Area, ,:O, Utah:B-Area, ,:O, Oklahoma:B-Area, ,:O, Colorado:B-Area, ,:O, Illinois:B-Area, ,:O, Missouri:B-Area, ,:O, South:B-Area, Carolina:I-Area, ,:O, North:B-Area, Carolina:I-Area, ,:O, Virginia:B-Area, and:O, Florida:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The first attack in the US that Group-IB attributes to MoneyTaker was conducted in the spring of 2016 : money was stolen from the bank by gaining access to First Data 's , STAR , network operator portal .' [/INST] [The:O, first:O, attack:B-OffAct, in:O, the:O, US:O, that:O, Group-IB:B-SecTeam, attributes:O, to:O, MoneyTaker:O, was:O, conducted:O, in:O, the:O, spring:O, of:O, 2016:B-Time, ::O, money:O, was:O, stolen:O, from:O, the:O, bank:B-Idus, by:O, gaining:O, access:O, to:O, First:O, Data:O, 's:O, ,:O, STAR:O, ,:O, network:O, operator:O, portal:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The first attack in the US that Group-IB attributes to this group was conducted in the spring of 2016 : money was stolen from the bank by gaining access to First Data 's , STAR , network operator portal .' [/INST] [The:O, first:O, attack:B-OffAct, in:O, the:O, US:B-Area, that:O, Group-IB:B-SecTeam, attributes:O, to:O, this:O, group:O, was:O, conducted:O, in:O, the:O, spring:O, of:O, 2016:B-Time, ::O, money:O, was:O, stolen:O, from:O, the:O, bank:B-Idus, by:O, gaining:O, access:O, to:O, First:O, Data:O, 's:O, ,:O, STAR:O, ,:O, network:O, operator:O, portal:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 2017 , the number of MoneyTaker 's attacks has remained the same with 8 US banks , 1 law firm and 1 bank in Russia being targeted .' [/INST] [In:O, 2017:O, ,:O, the:O, number:O, of:O, MoneyTaker:B-HackOrg, 's:O, attacks:B-OffAct, has:O, remained:O, the:O, same:O, with:O, 8:O, US:B-Area, banks:B-Idus, ,:O, 1:O, law:B-Org, firm:I-Org, and:O, 1:O, bank:B-Idus, in:O, Russia:O, being:O, targeted:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 2017 , the number of attacks has remained the same with 8 US banks , 1 law firm and 1 bank in Russia being targeted .' [/INST] [In:O, 2017:B-Time, ,:O, the:O, number:O, of:O, attacks:B-OffAct, has:O, remained:O, the:O, same:O, with:O, 8:O, US:O, banks:B-Idus, ,:O, 1:O, law:B-Org, firm:I-Org, and:O, 1:O, bank:B-Idus, in:O, Russia:B-Area, being:O, targeted:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'By analyzing the attack infrastructure , Group-IB identified that MoneyTaker group continuously exfiltrates internal banking documentation to learn about bank operations in preparation for future attacks .' [/INST] [By:O, analyzing:O, the:O, attack:B-OffAct, infrastructure:O, ,:O, Group-IB:B-SecTeam, identified:O, that:O, MoneyTaker:B-HackOrg, group:I-HackOrg, continuously:O, exfiltrates:O, internal:O, banking:O, documentation:O, to:O, learn:O, about:O, bank:B-Idus, operations:O, in:O, preparation:O, for:O, future: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: 'Group-IB reports that MoneyTaker uses both borrowed and their own self-written tools .' [/INST] [Group-IB:B-SecTeam, reports:O, that:O, MoneyTaker:O, uses:O, both:O, borrowed:O, and:O, their:O, own:O, self-written:O, tools:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Group-IB has provided Europol and Interpol with detailed information about the MoneyTaker group for further investigative activities as part of our cooperation in fighting cybercrime .' [/INST] [Group-IB:B-SecTeam, has:O, provided:O, Europol:O, and:O, Interpol:O, with:O, detailed:O, information:O, about:O, the:O, MoneyTaker:O, group:O, for:O, further:O, investigative:O, activities:B-OffAct, as:O, part:O, of:O, our:O, cooperation:O, in:O, fighting:O, cybercrime:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In late September 2015 Mofang used the website of Myanmara 's national airline hosted at www.flymna.com for an attack against an organization in Myanmar .' [/INST] [In:O, late:O, September:B-Time, 2015:I-Time, Mofang:O, used:O, the:O, website:O, of:O, Myanmara:O, 's:O, national:O, airline:O, hosted:O, at:O, www.flymna.com:O, for:O, an:O, attack:B-OffAct, against:O, an:O, organization:O, in:O, Myanmar: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: 'To control the full operation , MoneyTaker uses a Pentest framework Server .' [/INST] [To:O, control:B-Purp, the:I-Purp, full:I-Purp, operation:I-Purp, ,:O, MoneyTaker:B-HackOrg, uses:O, a:O, Pentest:B-Tool, framework:I-Tool, Server: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 it , MoneyTaker install a legitimate tool for penetration testing – Metasploit .' [/INST] [On:O, it:O, ,:O, MoneyTaker:B-HackOrg, install:O, a:O, legitimate:O, tool:O, for:O, penetration:O, testing:O, –:O, Metasploit: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: 'At the end of June 2015 Mofang started its campaign to gather information of a specific target in relation to the sezs : the cpg Corporation .' [/INST] [At:O, the:O, end:O, of:O, June:B-Time, 2015:I-Time, Mofang:O, started:O, its:O, campaign:B-OffAct, to:O, gather:B-Purp, information:I-Purp, of:O, a:O, specific:O, target:O, in:O, relation:O, to:O, the:O, sezs:O, ::O, the:O, cpg:B-Org, Corporation: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: 'MoneyTaker uses ' fileless ' malware only existing in RAM and is destroyed after reboot .' [/INST] [MoneyTaker:B-HackOrg, uses:O, ':O, fileless:B-Tool, ':O, malware:O, only:O, existing:O, in:O, RAM:O, and:O, is:O, destroyed:O, after:O, reboot:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To ensure persistence in the system MoneyTaker relies on PowerShell and VBS scripts - they are both difficult to detect by antivirus and easy to modify .' [/INST] [To:O, ensure:O, persistence:O, in:O, the:O, system:O, MoneyTaker:B-HackOrg, relies:O, on:O, PowerShell:B-Tool, and:O, VBS:B-Tool, scripts:I-Tool, -:O, they:O, are:O, both:O, difficult:O, to:O, detect:O, by:O, antivirus:O, and:O, easy:O, to:O, modify:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'After successfully infecting one of the computers and gaining initial access to the system , the attackers perform reconnaissance of the local network in order to gain domain administrator privileges and eventually consolidate control over the network .' [/INST] [After:O, successfully:O, infecting:O, one:O, of:O, the:O, computers:O, and:O, gaining:B-Purp, initial:I-Purp, access:I-Purp, to:I-Purp, the:I-Purp, system:I-Purp, ,:O, the:O, attackers:O, perform:O, reconnaissance:O, of:O, the:O, local:O, network:O, in:O, order:O, to:O, gain:B-Purp, domain:I-Purp, administrator:I-Purp, privileges:I-Purp, and:O, eventually:O, consolidate:B-Purp, control:I-Purp, over:I-Purp, the:I-Purp, network:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'MUSTANG PANDA has previously used the observed microblogging site to host malicious PowerShell scripts and Microsoft Office documents in targeted attacks on Mongolia-focused NGOs .' [/INST] [MUSTANG:B-HackOrg, PANDA:I-HackOrg, has:O, previously:O, used:O, the:O, observed:O, microblogging:O, site:O, to:O, host:O, malicious:O, PowerShell:B-Tool, scripts:I-Tool, and:O, Microsoft:B-Tool, Office:I-Tool, documents:I-Tool, in:O, targeted:B-OffAct, attacks:I-OffAct, on:O, Mongolia-focused:O, NGOs:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 newly observed activity uses a series of redirections and fileless , malicious implementations of legitimate tools to gain access to the targeted systems .' [/INST] [This:O, newly:O, observed:O, activity:B-OffAct, uses:O, a:O, series:O, of:O, redirections:O, and:O, fileless:O, ,:O, malicious:O, implementations:O, of:O, legitimate:O, tools:O, to:O, gain:B-Purp, access:I-Purp, to:O, the:O, targeted:O, systems:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Unit 42 recently identified a targeted attack against an individual working for the Foreign Ministry of Uzbekistan in China .' [/INST] [Unit:B-SecTeam, 42:I-SecTeam, recently:O, identified:O, a:O, targeted:B-OffAct, attack:I-OffAct, against:O, an:O, individual:O, working:O, for:O, the:O, Foreign:B-Org, Ministry:I-Org, of:O, Uzbekistan:B-Area, in:I-Area, China: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: 'Since that time , MoneyTaker attacked companies in California , Utah , Oklahoma , Colorado , Illinois , Missouri , South Carolina , North Carolina , Virginia and Florida .' [/INST] [Since:O, that:O, time:O, ,:O, MoneyTaker:B-HackOrg, attacked:O, companies:O, in:O, California:B-Area, ,:O, Utah:B-Area, ,:O, Oklahoma:B-Area, ,:O, Colorado:B-Area, ,:O, Illinois:B-Area, ,:O, Missouri:B-Area, ,:O, South:B-Area, Carolina:I-Area, ,:O, North:B-Area, Carolina:I-Area, ,:O, Virginia:B-Area, and:O, Florida:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In their Operation Tropic Trooper report , Trend Micro documented the behaviour and functionality of an espionage toolkit with several design similarities to those observed in the various components of KeyBoy .' [/INST] [In:O, their:O, Operation:B-OffAct, Tropic:I-OffAct, Trooper:I-OffAct, report:O, ,:O, Trend:B-SecTeam, Micro:I-SecTeam, documented:O, the:O, behaviour:O, and:O, functionality:O, of:O, an:O, espionage:B-SamFile, toolkit:I-SamFile, with:O, several:O, design:O, similarities:O, to:O, those:O, observed:O, in:O, the:O, various:O, components:O, of:O, KeyBoy: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: 'Our analysis shows that actors attempted to exploit CVE-2012-0158 to install NetTraveler Trojan .' [/INST] [Our:O, analysis:O, shows:O, that:O, actors:O, attempted:O, to:O, exploit:O, CVE-2012-0158:B-Exp, to:O, install:O, NetTraveler: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: 'Unit 42 's analysis shows that NetTraveler attempted to exploit CVE-2012-0158 to install NetTraveler Trojan .' [/INST] [Unit:B-SecTeam, 42:I-SecTeam, 's:O, analysis:O, shows:O, that:O, NetTraveler:B-Tool, attempted:O, to:O, exploit:O, CVE-2012-0158:B-Exp, to:O, install:O, NetTraveler: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: 'Our analysis shows that NetTraveler attempted to exploit CVE-2012-0158 to install NetTraveler Trojan .' [/INST] [Our:O, analysis:O, shows:O, that:O, NetTraveler:B-Tool, attempted:O, to:O, exploit:O, CVE-2012-0158:B-Exp, to:O, install:O, NetTraveler: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: 'In 2016 , Group-IB identified 10 attacks conducted by MoneyTaker , 6 attacks on banks in the US , 1 attack on a US service provider , 1 attack on a bank in the UK and 2 attacks on Russian banks .' [/INST] [In:O, 2016:B-Time, ,:O, Group-IB:B-SecTeam, identified:O, 10:O, attacks:B-OffAct, conducted:O, by:O, MoneyTaker:O, ,:O, 6:O, attacks:B-OffAct, on:O, banks:B-Idus, in:O, the:O, US:B-Area, ,:O, 1:O, attack:B-OffAct, on:O, a:O, US:B-Area, service:B-Org, provider:I-Org, ,:O, 1:O, attack:B-OffAct, on:O, a:O, bank:B-Idus, in:O, the:O, UK:B-Area, and:O, 2:O, attacks:B-OffAct, on:O, Russian:B-Area, 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: 'If KeyBoy is a single component of a larger espionage toolkit , the developers may have realized that this older , static-key based , configuration encoding algorithm was inadvertently providing a link between disparate components of their malware suite .' [/INST] [If:O, KeyBoy:B-Tool, is:O, a:O, single:O, component:O, of:O, a:O, larger:O, espionage:O, toolkit:O, ,:O, the:O, developers:O, may:O, have:O, realized:O, that:O, this:O, older:O, ,:O, static-key:O, based:O, ,:O, configuration:B-Tool, encoding:I-Tool, algorithm:I-Tool, was:O, inadvertently:O, providing:B-Features, a:I-Features, link:I-Features, between:O, disparate:O, components:O, of:O, their:O, malware:O, suite:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 2016 , Group-IB identified 10 attacks conducted by MoneyTaker ; 6 attacks on banks in the US , 1 attack on a US service provider , 1 attack on a bank in the UK and 2 attacks on Russian banks .' [/INST] [In:O, 2016:B-Time, ,:O, Group-IB:B-SecTeam, identified:O, 10:O, attacks:B-OffAct, conducted:O, by:O, MoneyTaker:O, ;:O, 6:O, attacks:B-OffAct, on:O, banks:B-Idus, in:O, the:O, US:B-Area, ,:O, 1:O, attack:B-OffAct, on:O, a:O, US:B-Area, service:B-Org, provider:I-Org, ,:O, 1:O, attack:B-OffAct, on:O, a:O, bank:B-Idus, in:O, the:O, UK:B-Area, and:O, 2:O, attacks:B-OffAct, on:O, Russian:B-Area, 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: 'The NetTraveler trojan has been known to be used in targeted cyber espionage attacks for more than a decade by nation state threat actors and continues to be used to target its victims and exfiltrate data .' [/INST] [The:O, NetTraveler:B-Tool, trojan:I-Tool, has:O, been:O, known:O, to:O, be:O, used:O, in:O, targeted:O, cyber:B-OffAct, espionage:I-OffAct, attacks:I-OffAct, for:O, more:O, than:O, a:O, decade:O, by:O, nation:O, state:O, threat:O, actors:O, and:O, continues:O, to:O, be:O, used:O, to:O, target:B-Features, its:I-Features, victims:I-Features, and:O, exfiltrate:B-Features, data:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The exploit document carrying this alternate KeyBoy configuration also used a decoy document which was displayed to the user after the exploit launched .' [/INST] [The:O, exploit:B-SamFile, document:I-SamFile, carrying:O, this:O, alternate:O, KeyBoy:B-Tool, configuration:O, also:O, used:O, a:O, decoy:B-SamFile, document:I-SamFile, which:O, was:O, displayed:O, to:O, the:O, user:O, after:O, the:O, exploit:O, launched:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Only one incident involving a Russian bank was promptly identified and prevented that is known to Group-IB .' [/INST] [Only:O, one:O, incident:O, involving:O, a:O, Russian:O, bank:B-Idus, was:O, promptly:O, identified:O, and:O, prevented:O, that:O, is:O, known:O, to:O, Group-IB: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: 'This program is designed to capture keystrokes , take screenshots of the user 's desktop and get contents from the clipboard .' [/INST] [This:O, program:O, is:O, designed:O, to:O, capture:B-Features, keystrokes:I-Features, ,:O, take:B-Features, screenshots:I-Features, of:O, the:O, user:O, 's:O, desktop:O, and:O, get:B-Features, contents:I-Features, from:O, the:O, clipboard:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To conduct targeted attacks , MoneyTaker use a distributed infrastructure that is difficult to track .' [/INST] [To:O, conduct:O, targeted:B-OffAct, attacks:I-OffAct, ,:O, MoneyTaker:B-HackOrg, use:O, a:O, distributed:B-Tool, infrastructure:I-Tool, that:O, is:O, difficult:O, to:O, track:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This technique hides the true C2 server from researchers that do not have access to both the rastls.dll and Sycmentec.config files .' [/INST] [This:O, technique:O, hides:O, the:O, true:O, C2:O, server:O, from:O, researchers:O, that:O, do:O, not:O, have:O, access:O, to:O, both:O, the:O, rastls.dll:B-SamFile, and:O, Sycmentec.config:B-SamFile, files:I-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Hackers use Metasploit to conduct all these activities : network reconnaissance , search for vulnerable applications , exploit vulnerabilities , escalate systems privileges , and collect information .' [/INST] [Hackers:O, use:O, Metasploit:B-Tool, to:O, conduct:O, all:O, these:O, activities:B-OffAct, ::O, network:B-Way, reconnaissance:I-Way, ,:O, search:O, for:O, vulnerable:B-Way, applications:I-Way, ,:O, exploit:O, vulnerabilities:O, ,:O, escalate:O, systems:O, privileges:O, ,:O, and:O, collect:O, information:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 they've used application components from Norman , McAfee and Norton .' [/INST] [Over:O, the:O, years:O, they've:O, used:O, application:O, components:O, from:O, Norman:B-SecTeam, ,:O, McAfee:B-SecTeam, and:O, Norton: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: 'Recently , Falcon Intelligence observed new activity from MUSTANG PANDA , using a unique infection chain to target likely Mongolia-based victims .' [/INST] [Recently:O, ,:O, Falcon:B-SecTeam, Intelligence:I-SecTeam, observed:O, new:O, activity:B-OffAct, from:O, MUSTANG:O, PANDA:O, ,:O, using:O, a:O, unique:O, infection:B-Tool, chain:I-Tool, to:O, target:O, likely:O, Mongolia-based: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: 'Throughout the years , the Mofang group has compromised countless servers belonging to government or other Myanmar related organizations , in order to stage attacks .' [/INST] [Throughout:O, the:O, years:O, ,:O, the:O, Mofang:O, group:O, has:O, compromised:O, countless:O, servers:O, belonging:O, to:O, government:B-Idus, or:O, other:O, Myanmar:O, related:O, organizations:O, ,:O, in:O, order:O, to:O, stage: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: 'This file requires the target to attempt to open the .lnk file , which redirects the user to a Windows Scripting Component ( .wsc ) file , hosted on an adversary-controlled microblogging page .' [/INST] [This:O, file:O, requires:O, the:O, target:O, to:O, attempt:O, to:O, open:O, the:O, .lnk:B-SamFile, file:I-SamFile, ,:O, which:O, redirects:B-Features, the:I-Features, user:I-Features, to:O, a:O, Windows:O, Scripting:O, Component:O, (:O, .wsc:O, ):O, file:O, ,:O, hosted:O, on:O, an:O, adversary-controlled:O, microblogging:O, page:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 report published by Kaspersky Labs in 2011 on NetTraveler also mentions the C2 servers were being hosted by Krypt Technolgies .' [/INST] [A:O, report:O, published:O, by:O, Kaspersky:B-SecTeam, Labs:I-SecTeam, in:O, 2011:B-Time, on:O, NetTraveler:B-Tool, also:O, mentions:O, the:O, C2:O, servers:O, were:O, being:O, hosted:O, by:O, Krypt:O, Technolgies:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Obviously , the developers behind NetTraveler have taken steps to try to hide the malware 's configuration .' [/INST] [Obviously:O, ,:O, the:O, developers:O, behind:O, NetTraveler:B-Tool, have:O, taken:O, steps:O, to:O, try:O, to:O, hide:O, the:O, malware:O, 's:O, configuration:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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'll review how the actors attempted to exploit CVE-2012-0158 to install the NetTraveler Trojan .' [/INST] [In:O, this:O, report:O, ,:O, we'll:O, review:O, how:O, the:O, actors:O, attempted:O, to:O, exploit:O, CVE-2012-0158:B-Exp, to:O, install:O, the:O, NetTraveler: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: 'In this report , we'll review how NetTraveler attempted to exploit CVE-2012-0158 to install the NetTraveler Trojan .' [/INST] [In:O, this:O, report:O, ,:O, we'll:O, review:O, how:O, NetTraveler:B-Tool, attempted:O, to:O, exploit:O, CVE-2012-0158:B-Exp, to:O, install:O, the:O, NetTraveler: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: 'In this report , we'll review how the NetTraveler attempted to exploit CVE-2012-0158 to install the NetTraveler Trojan .' [/INST] [In:O, this:O, report:O, ,:O, we'll:O, review:O, how:O, the:O, NetTraveler:B-Tool, attempted:O, to:O, exploit:O, CVE-2012-0158:B-Exp, to:O, install:O, the:O, NetTraveler: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: 'Upon successful exploitation , the attachment will install the trojan known as NetTraveler using a DLL side-loading attack technique .' [/INST] [Upon:O, successful:O, exploitation:O, ,:O, the:O, attachment:B-SamFile, will:O, install:B-Features, the:I-Features, trojan:I-Features, known:O, as:O, NetTraveler:B-Tool, using:O, a:O, DLL:B-SamFile, side-loading:I-SamFile, attack:O, technique:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'NetTraveler has been used to target diplomats , embassies and government institutions for over a decade , and remains the tool of choice by the adversaries behind these cyber espionage campaigns .' [/INST] [NetTraveler:B-Tool, has:O, been:O, used:O, to:O, target:O, diplomats:B-Org, ,:O, embassies:B-Org, and:O, government:B-Org, institutions:I-Org, for:O, over:O, a:O, decade:O, ,:O, and:O, remains:O, the:O, tool:O, of:O, choice:O, by:O, the:O, adversaries:O, behind:O, these:O, cyber:B-OffAct, espionage:I-OffAct, campaigns: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: 'WildFire correctly classifies NetTraveler as malicious .' [/INST] [WildFire:B-SecTeam, correctly:O, classifies:O, NetTraveler:B-Tool, as:O, malicious:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 NetTraveler group has infected victims across multiple establishments in both the public and private sector including government institutions , embassies , the oil and gas industry , research centers , military contractors and activists .' [/INST] [The:O, NetTraveler:O, group:O, has:O, infected:O, victims:O, across:O, multiple:O, establishments:O, in:O, both:O, the:O, public:O, and:O, private:O, sector:O, including:O, government:B-Org, institutions:I-Org, ,:O, embassies:B-Org, ,:O, the:O, oil:B-Idus, and:I-Idus, gas:I-Idus, industry:I-Idus, ,:O, research:O, centers:O, ,:O, military:B-Org, contractors:I-Org, and:O, activists: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: 'Today Kaspersky Lab 's team of experts published a new research report about NetTraveler , which is a family of malicious programs used by APT actors to successfully compromise more than 350 high-profile victims in 40 countries .' [/INST] [Today:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, 's:O, team:O, of:O, experts:O, published:O, a:O, new:O, research:O, report:O, about:O, NetTraveler:B-Tool, ,:O, which:O, is:O, a:O, family:O, of:O, malicious:O, programs:O, used:O, by:O, APT:O, actors:O, to:O, successfully:O, compromise:O, more:O, than:O, 350:O, high-profile:O, victims:O, in:O, 40: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: 'According to Kaspersky Lab 's report , this threat actor has been active since as early as 2004 ; however , the highest volume of activity occurred from 2010 – 2013 .' [/INST] [According:O, to:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, 's:O, report:O, ,:O, this:O, threat:O, actor:O, has:O, been:O, active:O, since:O, as:O, early:O, as:O, 2004:O, ;:O, however:O, ,:O, the:O, highest:O, volume:O, of:O, activity:B-OffAct, occurred:O, from:O, 2010:B-Time, –:I-Time, 2013: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: 'Most recently , the NetTraveler group 's main domains of interest for cyberespionage activities include space exploration , nanotechnology , energy production , nuclear power , lasers , medicine and communications .' [/INST] [Most:O, recently:O, ,:O, the:O, NetTraveler:O, group:O, 's:O, main:O, domains:O, of:O, interest:O, for:O, cyberespionage:B-OffAct, activities:I-OffAct, include:O, space:B-Idus, exploration:I-Idus, ,:O, nanotechnology:B-Idus, ,:O, energy:B-Idus, production:I-Idus, ,:O, nuclear:B-Idus, power:I-Idus, ,:O, lasers:B-Idus, ,:O, medicine:B-Idus, and:O, communications: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: 'In addition , the NetTraveler toolkit was able to install additional info-stealing malware as a backdoor , and it could be customized to steal other types of sensitive information such as configuration details for an application or computer-aided design files .' [/INST] [In:O, addition:O, ,:O, the:O, NetTraveler:B-Tool, toolkit:I-Tool, was:O, able:O, to:O, install:B-Features, additional:I-Features, info-stealing:I-Features, malware:I-Features, as:O, a:O, backdoor:O, ,:O, and:O, it:O, could:O, be:O, customized:O, to:O, steal:B-Features, other:I-Features, types:I-Features, of:I-Features, sensitive:I-Features, information:I-Features, such:O, as:O, configuration:O, details:O, for:O, an:O, application:O, or:O, computer-aided:O, design:O, files:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Kaspersky Lab 's analysis of NetTraveler , the company 's experts identified six victims that had been infected by both NetTraveler and Red October , which was another cyberespionage operation analyzed by Kaspersky Lab in January 2013 .' [/INST] [During:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, 's:O, analysis:O, of:O, NetTraveler:B-Tool, ,:O, the:O, company:O, 's:O, experts:O, identified:O, six:O, victims:O, that:O, had:O, been:O, infected:O, by:O, both:O, NetTraveler:O, and:O, Red:O, October:O, ,:O, which:O, was:O, another:O, cyberespionage:O, operation:O, analyzed:O, by:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, in:O, January:B-Time, 2013: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: 'Kaspersky Lab 's products detect and neutralize the malicious programs and its variants used by the NetTraveler Toolkit , including Trojan-Spy.Win32.TravNet and Downloader.Win32.NetTraveler .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, 's:O, products:O, detect:O, and:O, neutralize:O, the:O, malicious:O, programs:O, and:O, its:O, variants:O, used:O, by:O, the:O, NetTraveler:B-Tool, Toolkit:I-Tool, ,:O, including:O, Trojan-Spy.Win32.TravNet:B-Tool, and:O, Downloader.Win32.NetTraveler: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: 'Based on Kaspersky Lab 's analysis of NetTraveler 's C&C data , there were a total of 350 victims in 40 countries across including the United States , Canada , United Kingdom , Russia , Chile , Morocco , Greece , Belgium , Austria , Ukraine , Lithuania , Belarus , Australia , Hong Kong , Japan , China , Mongolia , Iran , Turkey , India , Pakistan , South Korea , Thailand , Qatar , Kazakhstan , and Jordan .' [/INST] [Based:O, on:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, 's:O, analysis:O, of:O, NetTraveler:O, 's:O, C&C:O, data:O, ,:O, there:O, were:O, a:O, total:O, of:O, 350:O, victims:O, in:O, 40:O, countries:O, across:O, including:O, the:O, United:B-Area, States:I-Area, ,:O, Canada:B-Area, ,:O, United:B-Area, Kingdom:I-Area, ,:O, Russia:B-Area, ,:O, Chile:B-Area, ,:O, Morocco:B-Area, ,:O, Greece:B-Area, ,:O, Belgium:B-Area, ,:O, Austria:B-Area, ,:O, Ukraine:B-Area, ,:O, Lithuania:B-Area, ,:O, Belarus:B-Area, ,:O, Australia:B-Area, ,:O, Hong:B-Area, Kong:I-Area, ,:O, Japan:B-Area, ,:O, China:B-Area, ,:O, Mongolia:B-Area, ,:O, Iran:B-Area, ,:O, Turkey:B-Area, ,:O, India:B-Area, ,:O, Pakistan:B-Area, ,:O, South:B-Area, Korea:I-Area, ,:O, Thailand:B-Area, ,:O, Qatar:B-Area, ,:O, Kazakhstan:B-Area, ,:O, and:O, Jordan: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: 'Kaspersky Lab 's products detect the Microsoft Office exploits used in the spear-phishing attacks , including Exploit.MSWord.CVE-2010-333 , Exploit.Win32.CVE-2012-0158 .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, 's:O, products:O, detect:O, the:O, Microsoft:B-Exp, Office:I-Exp, exploits:I-Exp, used:O, in:O, the:O, spear-phishing:B-OffAct, attacks:I-OffAct, ,:O, including:O, Exploit.MSWord.CVE-2010-333:B-SamFile, ,:O, Exploit.Win32.CVE-2012-0158: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: 'In this case , it was a group commonly referred to as , Nitro , , which was coined by Symantec in its 2011 whitepaper .' [/INST] [In:O, this:O, case:O, ,:O, it:O, was:O, a:O, group:O, commonly:O, referred:O, to:O, as:O, ,:O, Nitro:O, ,:O, ,:O, which:O, was:O, coined:O, by:O, Symantec:B-SecTeam, in:O, its:O, 2011:B-Time, whitepaper:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Historically , Nitro is known for targeted spear phishing campaigns and using Poison Ivy malware , which was not seen in these attacks .' [/INST] [Historically:O, ,:O, Nitro:O, is:O, known:O, for:O, targeted:O, spear:B-OffAct, phishing:I-OffAct, campaigns:I-OffAct, and:O, using:O, Poison:B-Tool, Ivy:I-Tool, malware:I-Tool, ,:O, which:O, was:O, not:O, seen:O, in:O, these: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: 'Since at least 2013 , Nitro appears to have somewhat modified their malware and delivery methods to include Spindest and legitimate compromised websites , as reported by Cyber Squared 's TCIRT .' [/INST] [Since:O, at:O, least:O, 2013:B-Time, ,:O, Nitro:O, appears:O, to:O, have:O, somewhat:O, modified:O, their:O, malware:O, and:O, delivery:O, methods:O, to:O, include:O, Spindest:B-Tool, and:O, legitimate:B-Tool, compromised:I-Tool, websites:I-Tool, ,:O, as:O, reported:O, by:O, Cyber:B-SecTeam, Squared:I-SecTeam, 's:I-SecTeam, TCIRT:I-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: 'In July , Nitro compromised a South Korean clothing and accessories manufacturer 's website to serve malware commonly referred to as , Spindest , .' [/INST] [In:O, July:O, ,:O, Nitro:O, compromised:O, a:O, South:B-Area, Korean:I-Area, clothing:O, and:O, accessories:O, manufacturer:O, 's:O, website:O, to:O, serve:O, malware:O, commonly:O, referred:O, to:O, as:O, ,:O, Spindest:B-Tool, ,:O, .:O] </s> |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.