Datasets:

pritamdeka

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dataset_aptner_test

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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: 'One certificate was generated locally on what appeared to be a HP-UX box , and another was generated on 8569985.securefastserver.com with an email address root@8569985.securefastserver.com , as seen here for their nethostnet.com domain .' [/INST] [One:O, certificate:O, was:O, generated:O, locally:O, on:O, what:O, appeared:O, to:O, be:O, a:O, HP-UX:S-OS, box:O, ,:O, and:O, another:O, was:O, generated:O, on:O, 8569985.securefastserver.com:S-DOM, with:O, an:O, email:S-TOOL, address:O, root@8569985.securefastserver.com:S-EMAIL, ,:O, as:O, seen:O, here:O, for:O, their:O, nethostnet.com:S-DOM, domain: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 certificate configuration is ignored by the malware .' [/INST] [This:O, certificate:O, configuration:O, is:O, ignored:O, by: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: 'Sofacy , one of the most active APT we monitor , continues to spearphish their way into targets , reportedly widely phishes for credentials , and infrequently participates in server side activity ( including host compromise with BeEF deployment , for example ) .' [/INST] [Sofacy:S-APT, ,:O, one:O, of:O, the:O, most:O, active:O, APT:O, we:O, monitor:O, ,:O, continues:O, to:O, spearphish:S-ACT, their:O, way:O, into:O, targets:O, ,:O, reportedly:O, widely:O, phishes:O, for:O, credentials:O, ,:O, and:O, infrequently:O, participates:O, in:O, server:O, side:O, activity:O, (:O, including:O, host:O, compromise:O, with:O, BeEF:S-TOOL, deployment:O, ,:O, for:O, example: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: 'KSN visibility and detections suggests a shift from their early 2017 high volume NATO spearphish targeting towards the middle east and Central Asia , and finally moving their focus further east into late 2017 .' [/INST] [KSN:S-SECTEAM, visibility:O, and:O, detections:O, suggests:O, a:O, shift:O, from:O, their:O, early:B-TIME, 2017:E-TIME, high:O, volume:O, NATO:S-IDTY, spearphish:S-ACT, targeting:O, towards:O, the:O, middle:B-LOC, east:E-LOC, and:O, Central:B-LOC, Asia:E-LOC, ,:O, and:O, finally:O, moving:O, their:O, focus:O, further:O, east:S-LOC, into:O, late:B-TIME, 2017:E-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: 'Their operational security is good .' [/INST] [Their:O, operational:O, security:O, is:O, good: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: 'Their campaigns appear to have broken out into subsets of activity and malware involving GAMEFISH , Zebrocy , and SPLM , to name a few .' [/INST] [Their:O, campaigns:O, appear:O, to:O, have:O, broken:O, out:O, into:O, subsets:O, of:O, activity:O, and:O, malware:O, involving:O, GAMEFISH:S-MAL, ,:O, Zebrocy:S-MAL, ,:O, and:O, SPLM:S-MAL, ,:O, to:O, name:O, a:O, few: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: 'Their evolving and modified SPLM / CHOPSTICK / XAgent code is a long-standing part of Sofacy activity , however much of it is changing .' [/INST] [Their:O, evolving:O, and:O, modified:O, SPLM:S-MAL, /:O, CHOPSTICK:S-MAL, /:O, XAgent:S-MAL, code:O, is:O, a:O, long-standing:O, part:O, of:O, Sofacy:S-APT, activity:O, ,:O, however:O, much:O, of:O, it:O, is:O, changing: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 ’ll cover more recent 2018 change in their targeting and the malware itself at SAS 2018 .' [/INST] [We:O, ’ll:O, cover:O, more:O, recent:O, 2018:S-TIME, change:O, in:O, their:O, targeting:O, and:O, the:O, malware:O, itself:O, at:O, SAS:S-IDTY, 2018:S-TIME, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'A journey to Zebrocy land .' [/INST] [A:O, journey:O, to:O, Zebrocy:S-MAL, land: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 Sednit group – also known as APT28 , Fancy Bear , Sofacy or STRONTIUM – has been operating since at least 2004 and has made headlines frequently in past years .' [/INST] [The:O, Sednit:S-APT, group:O, –:O, also:O, known:O, as:O, APT28:S-APT, ,:O, Fancy:B-APT, Bear:E-APT, ,:O, Sofacy:S-APT, or:O, STRONTIUM:S-APT, –:O, has:O, been:O, operating:O, since:O, at:O, least:O, 2004:S-TIME, and:O, has:O, made:O, headlines:O, frequently:O, in:O, past:O, years:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Recently , we unveiled the existence of a UEFI rootkit , called LoJax , which we attribute to the Sednit group .' [/INST] [Recently:O, ,:O, we:O, unveiled:O, the:O, existence:O, of:O, a:O, UEFI:S-TOOL, rootkit:O, ,:O, called:O, LoJax:S-MAL, ,:O, which:O, we:O, attribute:O, to:O, the:O, Sednit:S-APT, group:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This is a first for an APT group , and shows Sednit has access to very sophisticated tools to conduct its espionage operations .' [/INST] [This:O, is:O, a:O, first:O, for:O, an:O, APT:O, group:O, ,:O, and:O, shows:O, Sednit:S-APT, has:O, access:O, to:O, very:O, sophisticated:O, tools:O, to:O, conduct:O, its:O, espionage:O, 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: 'Three years ago , the Sednit group unleashed new components targeting victims in various countries in the Middle East and Central Asia .' [/INST] [Three:O, years:O, ago:O, ,:O, the:O, Sednit:S-APT, group:O, unleashed:O, new:O, components:O, targeting:O, victims:O, in:O, various:O, countries:O, in:O, the:O, Middle:B-LOC, East:E-LOC, and:O, Central:B-LOC, Asia:E-LOC, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 then , the number and diversity of components has increased drastically .' [/INST] [Since:O, then:O, ,:O, the:O, number:O, and:O, diversity:O, of:O, components:O, has:O, increased:O, drastically: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: 'ESET researchers and colleagues from other companies have documented these components ; however , in this article we will focus on what ’s beyond the compromise , what the operators do once a victim system is running a Zebrocy Delphi backdoor .' [/INST] [ESET:S-SECTEAM, researchers:O, and:O, colleagues:O, from:O, other:O, companies:O, have:O, documented:O, these:O, components:O, ;:O, however:O, ,:O, in:O, this:O, article:O, we:O, will:O, focus:O, on:O, what:O, ’s:O, beyond:O, the:O, compromise:O, ,:O, what:O, the:O, operators:O, do:O, once:O, a:O, victim:O, system:O, is:O, running:O, a:O, Zebrocy:S-MAL, Delphi:S-TOOL, backdoor:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'At the end of August 2018 , the Sednit group launched a spearphishing email campaign where it distributed shortened URLs that delivered the first stage of Zebrocy components .' [/INST] [At:O, the:O, end:O, of:O, August:B-TIME, 2018:E-TIME, ,:O, the:O, Sednit:S-APT, group:O, launched:O, a:O, spearphishing:S-ACT, email:S-TOOL, campaign:O, where:O, it:O, distributed:O, shortened:O, URLs:O, that:O, delivered:O, the:O, first:O, stage:O, of:O, Zebrocy:S-MAL, components: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 past , Sednit used a similar technique for credential phishing .' [/INST] [In:O, the:O, past:O, ,:O, Sednit:S-APT, used:O, a:O, similar:O, technique:O, for:O, credential:O, phishing:E-ACT, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , it is unusual for the group to use this technique to deliver one of its malware components directly .' [/INST] [However:O, ,:O, it:O, is:O, unusual:O, for:O, the:O, group:O, to:O, use:O, this:O, technique:O, to:O, deliver:O, one:O, of:O, its:O, malware:O, components:O, directly: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: 'Previously , it had used exploits to deliver and execute the first stage malware , while in this campaign the group relied entirely on social engineering to lure victims into running the first part of the chain .' [/INST] [Previously:O, ,:O, it:O, had:O, used:O, exploits:O, to:O, deliver:O, and:O, execute:O, the:O, first:O, stage:O, malware:O, ,:O, while:O, in:O, this:O, campaign:O, the:O, group:O, relied:O, entirely:O, on:O, social:O, engineering:O, to:O, lure:O, victims:O, into:O, running:O, the:O, first:O, part:O, of:O, the:O, chain: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 screenshot in Figure 1 shows Bitly statistics for the shortened URL used in this campaign .' [/INST] [The:O, screenshot:O, in:O, Figure:O, 1:O, shows:O, Bitly:S-TOOL, statistics:O, for:O, the:O, shortened:O, URL:O, used:O, in:O, this:O, campaign:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While ESET telemetry data indicates that this URL was delivered by spearphishing emails , we don’t have a sample of such an email .' [/INST] [While:O, ESET:S-SECTEAM, telemetry:O, data:O, indicates:O, that:O, this:O, URL:O, was:O, delivered:O, by:O, spearphishing:S-ACT, emails:S-TOOL, ,:O, we:O, don’t:O, have:O, a:O, sample:O, of:O, such:O, an:O, email:S-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 shortened URL leads the victim to an IP-address-based URL , where the archived payload is located .' [/INST] [The:O, shortened:O, URL:O, leads:O, the:O, victim:O, to:O, an:O, IP-address-based:O, URL:O, ,:O, where:O, the:O, archived:O, payload:O, is:O, located: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: 'Unfortunately , without the email message , we don’t know if there are any instructions for the user , if there is any further social engineering , or if it relies solely on the victim ’s curiosity .' [/INST] [Unfortunately:O, ,:O, without:O, the:O, email:S-TOOL, message:O, ,:O, we:O, don’t:O, know:O, if:O, there:O, are:O, any:O, instructions:O, for:O, the:O, user:O, ,:O, if:O, there:O, is:O, any:O, further:O, social:O, engineering:O, ,:O, or:O, if:O, it:O, relies:O, solely:O, on:O, the:O, victim:O, ’s:O, curiosity: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 archive contains two files ; the first is an executable file , while the second is a decoy PDF document .' [/INST] [The:O, archive:O, contains:O, two:O, files:O, ;:O, the:O, first:O, is:O, an:O, executable:O, file:O, ,:O, while:O, the:O, second:O, is:O, a:O, decoy:O, PDF:S-TOOL, 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: 'Note there is a typo in the executable ’s filename ; Once the binary is executed , a password prompt dialog box opens .' [/INST] [Note:O, there:O, is:O, a:O, typo:O, in:O, the:O, executable:O, ’s:O, filename:O, ;:O, Once:O, the:O, binary:O, is:O, executed:O, ,:O, a:O, password:O, prompt:O, dialog:O, box:O, opens: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 result of the password validation will always be wrong , but after the apparent validation attempt , the decoy PDF document is opened .' [/INST] [The:O, result:O, of:O, the:O, password:O, validation:O, will:O, always:O, be:O, wrong:O, ,:O, but:O, after:O, the:O, apparent:O, validation:O, attempt:O, ,:O, the:O, decoy:O, PDF:S-TOOL, document:O, is:O, opened: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: 'That document appears to be empty , but the downloader , which is written in Delphi , continues running in the background .' [/INST] [That:O, document:O, appears:O, to:O, be:O, empty:O, ,:O, but:O, the:O, downloader:O, ,:O, which:O, is:O, written:O, in:O, Delphi:S-TOOL, ,:O, continues:O, running:O, in:O, the:O, background: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 IP address is also used in the URL hardcoded into the first binary downloader .' [/INST] [The:O, IP:O, address:O, is:O, also:O, used:O, in:O, the:O, URL:O, hardcoded:O, into:O, the:O, first:O, binary:O, downloader: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 Stage-1 downloader will download and execute a new downloader , written in C++ , not so different from other Zebrocy downloaders .' [/INST] [The:O, Stage-1:O, downloader:O, will:O, download:O, and:O, execute:O, a:O, new:O, downloader:O, ,:O, written:O, in:O, C++:S-TOOL, ,:O, not:O, so:O, different:O, from:O, other:O, Zebrocy:S-MAL, downloaders: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: 'Once again this downloader is as straightforward as the Zebrocy gang ’s other downloaders .' [/INST] [Once:O, again:O, this:O, downloader:O, is:O, as:O, straightforward:O, as:O, the:O, Zebrocy:S-MAL, gang:O, ’s:O, other:O, downloaders: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 creates an ID and it downloads a new , interesting backdoor , ( this time ) written in Delphi .' [/INST] [It:O, creates:O, an:O, ID:O, and:O, it:O, downloads:O, a:O, new:O, ,:O, interesting:O, backdoor:O, ,:O, (:O, this:O, time:O, ):O, written:O, in:O, Delphi:S-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: 'As we explained in our most recent blogpost about Zebrocy , the configuration of the backdoor is stored in in the resource section and is split into four different hex-encoded , encrypted blobs .' [/INST] [As:O, we:O, explained:O, in:O, our:O, most:O, recent:O, blogpost:O, about:O, Zebrocy:S-MAL, ,:O, the:O, configuration:O, of:O, the:O, backdoor:O, is:O, stored:O, in:O, in:O, the:O, resource:O, section:O, and:O, is:O, split:O, into:O, four:O, different:O, hex-encoded:S-ENCR, ,:O, encrypted:O, blobs: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 blobs contain the different parts of the configuration .' [/INST] [These:O, blobs:O, contain:O, the:O, different:O, parts:O, of:O, the: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: 'Once the backdoor sends basic information about its newly compromised system , the operators take control of the backdoor and start to send commands right away .' [/INST] [Once:O, the:O, backdoor:O, sends:O, basic:O, information:O, about:O, its:O, newly:O, compromised:O, system:O, ,:O, the:O, operators:O, take:O, control:O, of:O, the:O, backdoor:O, and:O, start:O, to:O, send:O, commands:O, right:O, away: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: 'Hence , the time between the victim running the downloader and the operators ’ first commands is only a few minutes .' [/INST] [Hence:O, ,:O, the:O, time:O, between:O, the:O, victim:O, running:O, the:O, downloader:O, and:O, the:O, operators:O, ’:O, first:O, commands:O, is:O, only:O, a:O, few:O, minutes: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 section we describe in more detail the commands performed manually by the operators through their Delphi backdoor .' [/INST] [In:O, this:O, section:O, we:O, describe:O, in:O, more:O, detail:O, the:O, commands:O, performed:O, manually:O, by:O, the:O, operators:O, through:O, their:O, Delphi:S-TOOL, backdoor: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 commands available are located in one of the configuration blobs mentioned earlier .' [/INST] [The:O, commands:O, available:O, are:O, located:O, in:O, one:O, of:O, the:O, configuration:O, blobs:O, mentioned:O, earlier: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 number of supported commands has increased over time , with the latest version of the backdoor having more than thirty .' [/INST] [The:O, number:O, of:O, supported:O, commands:O, has:O, increased:O, over:O, time:O, ,:O, with:O, the:O, latest:O, version:O, of:O, the:O, backdoor:O, having:O, more:O, than:O, thirty:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'As we did not identify a pattern in the order which the commands are invoked , we believe the operators are executing them manually .' [/INST] [As:O, we:O, did:O, not:O, identify:O, a:O, pattern:O, in:O, the:O, order:O, which:O, the:O, commands:O, are:O, invoked:O, ,:O, we:O, believe:O, the:O, operators:O, are:O, executing:O, them:O, manually: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 set of commands gathers information about the victim ’s computer and environment :' [/INST] [The:O, first:O, set:O, of:O, commands:O, gathers:O, information:O, about:O, the:O, victim:O, ’s:O, computer:O, and:O, environment: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: 'Commands Arguments SCREENSHOT None SYS_INFO None GET_NETWORK None SCAN_ALL None .' [/INST] [Commands:O, Arguments:O, SCREENSHOT:O, None:O, SYS_INFO:O, None:O, GET_NETWORK:O, None:O, SCAN_ALL:O, None: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 commands above are commonly executed when the operators first connect to a newly activated backdoor .' [/INST] [The:O, commands:O, above:O, are:O, commonly:O, executed:O, when:O, the:O, operators:O, first:O, connect:O, to:O, a:O, newly:O, activated:O, backdoor:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'They don’t have any arguments , and they are quite self-explanatory .' [/INST] [They:O, don’t:O, have:O, any:O, arguments:O, ,:O, and:O, they:O, are:O, quite:O, self-explanatory:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Other commands commonly seen executed shortly after these backdoors are activated .' [/INST] [Other:O, commands:O, commonly:O, seen:O, executed:O, shortly:O, after:O, these:O, backdoors:O, are:O, activated: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: 'Those who already have read our previous articles about Zebrocy will notice that more or less the same kind of information is sent , over and over again by previous stages .' [/INST] [Those:O, who:O, already:O, have:O, read:O, our:O, previous:O, articles:O, about:O, Zebrocy:S-MAL, will:O, notice:O, that:O, more:O, or:O, less:O, the:O, same:O, kind:O, of:O, information:O, is:O, sent:O, ,:O, over:O, and:O, over:O, again:O, by:O, previous:O, stages: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 information is requested within a few minutes of initial compromise and the amount of data the operator will have to deal with is quite considerable .' [/INST] [This:O, information:O, is:O, requested:O, within:O, a:O, few:O, minutes:O, of:O, initial:O, compromise:O, and:O, the:O, amount:O, of:O, data:O, the:O, operator:O, will:O, have:O, to:O, deal:O, with:O, is:O, quite:O, considerable:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In order to collect even more information , from time to time the Zebrocy operators upload and use dumpers on victims ’ machines .' [/INST] [In:O, order:O, to:O, collect:O, even:O, more:O, information:O, ,:O, from:O, time:O, to:O, time:O, the:O, Zebrocy:S-MAL, operators:O, upload:O, and:O, use:O, dumpers:O, on:O, victims:O, ’:O, machines: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 current dumpers have some similarities with those previously used by the group .' [/INST] [The:O, current:O, dumpers:O, have:O, some:O, similarities:O, with:O, those:O, previously:O, used:O, by:O, the:O, group:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this case , Yandex Browser , Chromium , 7Star Browser ( a Chromium-based browser ) , and CentBrowser are targeted , as well as versions of Microsoft Outlook from 1997 through 2016 .' [/INST] [In:O, this:O, case:O, ,:O, Yandex:B-TOOL, Browser:E-TOOL, ,:O, Chromium:S-TOOL, ,:O, 7Star:B-TOOL, Browser:E-TOOL, (:O, a:O, Chromium-based:B-TOOL, browser:E-TOOL, ):O, ,:O, and:O, CentBrowser:S-TOOL, are:O, targeted:O, ,:O, as:O, well:O, as:O, versions:O, of:O, Microsoft:S-IDTY, Outlook:S-TOOL, from:O, 1997:S-TIME, through:O, 2016:S-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: 'These dumpers create log files indicating the presence or absence of potential databases to dump :' [/INST] [These:O, dumpers:O, create:O, log:O, files:O, indicating:O, the:O, presence:O, or:O, absence:O, of:O, potential:O, databases:O, to:O, dump: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: 'Command Arguments DOWNLOAD_LIST C:\ProgramData\Office\MS\out.txt , C:\ProgramData\Office\MS\text.txt .' [/INST] [Command:O, Arguments:O, DOWNLOAD_LIST:O, C:\ProgramData\Office\MS\out.txt:S-FILE, ,:O, C:\ProgramData\Office\MS\text.txt:S-FILE, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 dumpers are quickly removed once they have done their job .' [/INST] [These:O, dumpers:O, are:O, quickly:O, removed:O, once:O, they:O, have:O, done:O, their:O, job: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: 'Moreover , the backdoor contains a list of filenames related to credentials from software listed below ( database names ) :' [/INST] [Moreover:O, ,:O, the:O, backdoor:O, contains:O, a:O, list:O, of:O, filenames:O, related:O, to:O, credentials:O, from:O, software:O, listed:O, below:O, (:O, database:O, names: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: 'key3.db Firefox private keys ( now named key4.db ) cert8.db Firefox certificate database logins.json Firefox encrypted password database account.cfn The Bat ! ( email client ) account credentials wand.dat Opera password database .' [/INST] [key3.db:S-FILE, Firefox:S-TOOL, private:O, keys:O, (:O, now:O, named:O, key4.db:S-FILE, ):O, cert8.db:S-FILE, Firefox:S-TOOL, certificate:O, database:O, logins.json:S-FILE, Firefox:S-TOOL, encrypted:O, password:O, database:O, account.cfn:S-FILE, The:O, Bat:O, !:O, (:O, email:S-TOOL, client:O, ):O, account:O, credentials:O, wand.dat:S-FILE, Opera:S-TOOL, password:O, database: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 operators retrieve these files on the machine using the DOWNLOAD_LIST command .' [/INST] [The:O, operators:O, retrieve:O, these:O, files:O, on:O, the:O, machine:O, using:O, the:O, DOWNLOAD_LIST:O, command: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 command can be used when the operators are aware of the presence of interesting files on the computer .' [/INST] [This:O, command:O, can:O, be:O, used:O, when:O, the:O, operators:O, are:O, aware:O, of:O, the:O, presence:O, of:O, interesting:O, files:O, on:O, the:O, computer:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Finally , depending on how interesting the victim is , they malware operators may deploy another custom backdoor .' [/INST] [Finally:O, ,:O, depending:O, on:O, how:O, interesting:O, the:O, victim:O, is:O, ,:O, they:O, malware:O, operators:O, may:O, deploy:O, another:O, custom:O, backdoor: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 backdoor is executed using the CMD_EXECUTE command .' [/INST] [This:O, backdoor:O, is:O, executed:O, using:O, the:O, CMD_EXECUTE:O, command: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 are some interesting facts here .' [/INST] [There:O, are:O, some:O, interesting:O, facts:O, here: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: 'First , they use COM object hijacking to make the malware persistent on the system even though the custom backdoor is installed only for a few hours .' [/INST] [First:O, ,:O, they:O, use:O, COM:S-TOOL, object:O, hijacking:O, to:O, make:O, the:O, malware:O, persistent:O, on:O, the:O, system:O, even:O, though:O, the:O, custom:O, backdoor:O, is:O, installed:O, only:O, for:O, a:O, few:O, hours: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: 'Second , the hex-encoded string is the C&C used by the custom backdoor while in the Delphi backdoor the C&C is embedded in the configuration .' [/INST] [Second:O, ,:O, the:O, hex-encoded:S-ENCR, string:O, is:O, the:O, C&C:S-TOOL, used:O, by:O, the:O, custom:O, backdoor:O, while:O, in:O, the:O, Delphi:S-TOOL, backdoor:O, the:O, C&C:S-TOOL, is:O, embedded:O, in:O, the: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: 'Sofacy Group’s Parallel Attacks .' [/INST] [Sofacy:S-APT, Group’s:O, Parallel:O, Attacks:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Sofacy group remains a persistent global threat .' [/INST] [The:O, Sofacy:S-APT, group:O, remains:O, a:O, persistent:O, global:O, threat: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 and others have shown in the first half of 2018 how this threat actor group continues to target multiple organizations throughout the world with a strong emphasis on government , diplomatic and other strategic organizations primarily in North America and Europe .' [/INST] [Unit:B-SECTEAM, 42:E-SECTEAM, and:O, others:O, have:O, shown:O, in:O, the:O, first:B-TIME, half:I-TIME, of:I-TIME, 2018:E-TIME, how:O, this:O, threat:O, actor:O, group:O, continues:O, to:O, target:O, multiple:O, organizations:O, throughout:O, the:O, world:O, with:O, a:O, strong:O, emphasis:O, on:O, government:O, ,:O, diplomatic:O, and:O, other:O, strategic:O, organizations:O, primarily:O, in:O, North:B-LOC, America:E-LOC, and:O, Europe:S-LOC, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Following up our most recent Sofacy research in February and March of 2018 , we have found a new campaign that uses a lesser known tool widely attributed to the Sofacy group called Zebrocy .' [/INST] [Following:O, up:O, our:O, most:O, recent:O, Sofacy:S-APT, research:O, in:O, February:S-TIME, and:O, March:B-TIME, of:I-TIME, 2018:E-TIME, ,:O, we:O, have:O, found:O, a:O, new:O, campaign:O, that:O, uses:O, a:O, lesser:O, known:O, tool:O, widely:O, attributed:O, to:O, the:O, Sofacy:S-APT, group:O, called:O, Zebrocy:S-MAL, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Zebrocy is delivered primarily via phishing attacks that contain malicious Microsoft Office documents with macros as well as simple executable file attachments .' [/INST] [Zebrocy:S-MAL, is:O, delivered:O, primarily:O, via:O, phishing:S-ACT, attacks:O, that:O, contain:O, malicious:O, Microsoft:S-IDTY, Office:S-IDTY, documents:O, with:O, macros:O, as:O, well:O, as:O, simple:O, executable:O, file:O, attachments: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 third campaign is consistent with two previously reported attack campaigns in terms of targeting : the targets were government organizations dealing with foreign affairs .' [/INST] [This:O, third:O, campaign:O, is:O, consistent:O, with:O, two:O, previously:O, reported:O, attack:O, campaigns:O, in:O, terms:O, of:O, targeting:O, ::O, the:O, targets:O, were:O, government:O, organizations:O, dealing:O, with:O, foreign:O, affairs:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this case however the targets were in different geopolitical regions .' [/INST] [In:O, this:O, case:O, however:O, the:O, targets:O, were:O, in:O, different:O, geopolitical:O, regions:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'An interesting difference we found in this newest campaign was that the attacks using Zebrocy cast a far wider net within the target organization : the attackers sent phishing emails to a an exponentially larger number of individuals .' [/INST] [An:O, interesting:O, difference:O, we:O, found:O, in:O, this:O, newest:O, campaign:O, was:O, that:O, the:O, attacks:O, using:O, Zebrocy:S-MAL, cast:O, a:O, far:O, wider:O, net:O, within:O, the:O, target:O, organization:O, ::O, the:O, attackers:O, sent:O, phishing:S-ACT, emails:S-TOOL, to:O, a:O, an:O, exponentially:O, larger:O, number:O, of:O, individuals: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 targeted individuals did not follow any significant pattern , and the email addresses were found easily using web search engines .' [/INST] [The:O, targeted:O, individuals:O, did:O, not:O, follow:O, any:O, significant:O, pattern:O, ,:O, and:O, the:O, email:S-TOOL, addresses:O, were:O, found:O, easily:O, using:O, web:O, search:O, engines: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 is a stark contrast with other attacks commonly associated with the Sofacy group where generally no more than a handful of victims are targeted within a single organization in a focus-fire style of attack .' [/INST] [This:O, is:O, a:O, stark:O, contrast:O, with:O, other:O, attacks:O, commonly:O, associated:O, with:O, the:O, Sofacy:S-APT, group:O, where:O, generally:O, no:O, more:O, than:O, a:O, handful:O, of:O, victims:O, are:O, targeted:O, within:O, a:O, single:O, organization:O, in:O, a:O, focus-fire:O, style:O, of:O, attack:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition to the large number of Zebrocy attacks we discovered , we also observed instances of the Sofacy group leveraging the Dynamic Data Exchange ( DDE ) exploit technique previously documented by McAfee .' [/INST] [In:O, addition:O, to:O, the:O, large:O, number:O, of:O, Zebrocy:S-MAL, attacks:O, we:O, discovered:O, ,:O, we:O, also:O, observed:O, instances:O, of:O, the:O, Sofacy:S-APT, group:O, leveraging:O, the:O, Dynamic:B-PROT, Data:I-PROT, Exchange:E-PROT, (:O, DDE:S-PROT, ):O, exploit:O, technique:O, previously:O, documented:O, by:O, McAfee:S-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: 'The instances we observed , however , used the DDE exploit to deliver different payloads than what was observed previously .' [/INST] [The:O, instances:O, we:O, observed:O, ,:O, however:O, ,:O, used:O, the:O, DDE:O, exploit:O, to:O, deliver:O, different:O, payloads:O, than:O, what:O, was:O, observed:O, previously: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 one instance the DDE attack was used to deliver and install Zebrocy .' [/INST] [In:O, one:O, instance:O, the:O, DDE:S-PROT, attack:O, was:O, used:O, to:O, deliver:O, and:O, install:O, Zebrocy:S-MAL, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 instance , the DDE attack was used to deliver an open-source penetration testing toolkit called Koadic .' [/INST] [In:O, another:O, instance:O, ,:O, the:O, DDE:S-PROT, attack:O, was:O, used:O, to:O, deliver:O, an:O, open-source:O, penetration:O, testing:O, toolkit:O, called:O, Koadic:S-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 Sofacy group has leveraged open source or freely available tools and exploits in the past but this is the first time that Unit 42 has observed them leveraging the Koadic toolkit .' [/INST] [The:O, Sofacy:S-APT, group:O, has:O, leveraged:O, open:O, source:O, or:O, freely:O, available:O, tools:O, and:O, exploits:O, in:O, the:O, past:O, but:O, this:O, is:O, the:O, first:O, time:O, that:O, Unit:B-SECTEAM, 42:E-SECTEAM, has:O, observed:O, them:O, leveraging:O, the:O, Koadic:S-TOOL, toolkit: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 our February report , we discovered the Sofacy group using Microsoft Office documents with malicious macros to deliver the SofacyCarberp payload to multiple government entities .' [/INST] [In:O, our:O, February:S-TIME, report:O, ,:O, we:O, discovered:O, the:O, Sofacy:S-APT, group:O, using:O, Microsoft:S-IDTY, Office:S-IDTY, documents:O, with:O, malicious:O, macros:O, to:O, deliver:O, the:O, SofacyCarberp:S-MAL, payload:O, to:O, multiple:O, government:O, entities:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In that report , we documented our observation that the Sofacy group appeared to use conventional obfuscation techniques to mask their infrastructure attribution by using random registrant and service provider information for each of their attacks .' [/INST] [In:O, that:O, report:O, ,:O, we:O, documented:O, our:O, observation:O, that:O, the:O, Sofacy:S-APT, group:O, appeared:O, to:O, use:O, conventional:O, obfuscation:O, techniques:O, to:O, mask:O, their:O, infrastructure:O, attribution:O, by:O, using:O, random:O, registrant:O, and:O, service:O, provider:O, information:O, for:O, each:O, of:O, their:O, attacks:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In particular , we noted that the Sofacy group deployed a webpage on each of the domains .' [/INST] [In:O, particular:O, ,:O, we:O, noted:O, that:O, the:O, Sofacy:S-APT, group:O, deployed:O, a:O, webpage:O, on:O, each:O, of:O, the:O, domains:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This is odd because attackers almost never set up an actual webpage on adversary C2 infrastructure .' [/INST] [This:O, is:O, odd:O, because:O, attackers:O, almost:O, never:O, set:O, up:O, an:O, actual:O, webpage:O, on:O, adversary:O, C2:S-TOOL, infrastructure: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: 'Even stranger , each webpage contained the same content within the body .' [/INST] [Even:O, stranger:O, ,:O, each:O, webpage:O, contained:O, the:O, same:O, content:O, within:O, the:O, body: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 report , we continued our research into this oddity .' [/INST] [Since:O, that:O, report:O, ,:O, we:O, continued:O, our:O, research:O, into:O, this:O, oddity:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Using this artifact , we were able to pivot and discover another attack campaign using the DealersChoice exploit kit with similar victimology to what we saw in February .' [/INST] [Using:O, this:O, artifact:O, ,:O, we:O, were:O, able:O, to:O, pivot:O, and:O, discover:O, another:O, attack:O, campaign:O, using:O, the:O, DealersChoice:S-TOOL, exploit:O, kit:O, with:O, similar:O, victimology:O, to:O, what:O, we:O, saw:O, in:O, February:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Continuing to use this artifact , we discovered another domain with the same content body , supservermgr.com .' [/INST] [Continuing:O, to:O, use:O, this:O, artifact:O, ,:O, we:O, discovered:O, another:O, domain:O, with:O, the:O, same:O, content:O, body:O, ,:O, supservermgr.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: 'This domain was registered on December 20 , 2017 and within a few days was resolving to 92.222.136.105 , which belonged to a well-known VPS provider often used by the Sofacy group .' [/INST] [This:O, domain:O, was:O, registered:O, on:O, December:B-TIME, 20:I-TIME, ,:I-TIME, 2017:E-TIME, and:O, within:O, a:O, few:O, days:O, was:O, resolving:O, to:O, 92.222.136.105:S-IP, ,:O, which:O, belonged:O, to:O, a:O, well-known:O, VPS:S-TOOL, provider:O, often:O, used:O, by:O, the:O, Sofacy:S-APT, group:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Unfortunately , at the time of collection , the C2 domain had been sinkholed by a third party .' [/INST] [Unfortunately:O, ,:O, at:O, the:O, time:O, of:O, collection:O, ,:O, the:O, C2:S-TOOL, domain:O, had:O, been:O, sinkholed:O, by:O, a:O, third:O, party: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 dynamic and static analysis of the malware sample associated with the supservermgr.com domain however , we were able to determine several unique artifacts which allowed us to expand our dataset and discover additional findings .' [/INST] [Based:O, on:O, dynamic:O, and:O, static:O, analysis:O, of:O, the:O, malware:O, sample:O, associated:O, with:O, the:O, supservermgr.com:S-DOM, domain:O, however:O, ,:O, we:O, were:O, able:O, to:O, determine:O, several:O, unique:O, artifacts:O, which:O, allowed:O, us:O, to:O, expand:O, our:O, dataset:O, and:O, discover:O, additional:O, findings: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: 'First , we determined the sample we collected , d697160aecf152a81a89a6b5a7d9e1b8b5e121724038c676157ac72f20364edc was attempting to communicate to its C2 at http://supservermgr.com/sys/upd/pageupd.php to retrieve a Zebrocy AutoIT downloader .' [/INST] [First:O, ,:O, we:O, determined:O, the:O, sample:O, we:O, collected:O, ,:O, d697160aecf152a81a89a6b5a7d9e1b8b5e121724038c676157ac72f20364edc:S-SHA2, was:O, attempting:O, to:O, communicate:O, to:O, its:O, C2:S-TOOL, at:O, http://supservermgr.com/sys/upd/pageupd.php:S-URL, to:O, retrieve:O, a:O, Zebrocy:S-MAL, AutoIT:S-TOOL, downloader: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: 'Because the domain had been sinkholed , this activity could not be completed .' [/INST] [Because:O, the:O, domain:O, had:O, been:O, sinkholed:O, ,:O, this:O, activity:O, could:O, not:O, be:O, completed:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Using AutoFocus , we pivoted from the user agent string to expand our data set to three additional Zebrocy samples using the exact same user agent .' [/INST] [Using:O, AutoFocus:S-TOOL, ,:O, we:O, pivoted:O, from:O, the:O, user:O, agent:O, string:O, to:O, expand:O, our:O, data:O, set:O, to:O, three:O, additional:O, Zebrocy:S-MAL, samples:O, using:O, the:O, exact:O, same:O, user:O, agent: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 led us to additional infrastructure for Zebrocy at 185.25.51.198 and 185.25.50.93 .' [/INST] [This:O, led:O, us:O, to:O, additional:O, infrastructure:O, for:O, Zebrocy:S-MAL, at:O, 185.25.51.198:S-IP, and:O, 185.25.50.93:S-IP, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 this point we had collected nearly thirty samples of Zebrocy in relation to the original sample and its associated C2 domain .' [/INST] [At:O, this:O, point:O, we:O, had:O, collected:O, nearly:O, thirty:O, samples:O, of:O, Zebrocy:S-MAL, in:O, relation:O, to:O, the:O, original:O, sample:O, and:O, its:O, associated:O, C2:S-TOOL, domain: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: 'Additional pivoting based on artifacts unique to this malware family expanded our dataset to hundreds of samples used over the last several years .' [/INST] [Additional:O, pivoting:O, based:O, on:O, artifacts:O, unique:O, to:O, this:O, malware:O, family:O, expanded:O, our:O, dataset:O, to:O, hundreds:O, of:O, samples:O, used:O, over:O, the:O, last:O, several:O, years:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Most of the additional samples were the Delphi and AutoIT variants as reported by ESET .' [/INST] [Most:O, of:O, the:O, additional:O, samples:O, were:O, the:O, Delphi:S-TOOL, and:O, AutoIT:S-TOOL, variants:O, as:O, reported:O, by:O, ESET:S-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: 'However , several of the collected samples were a C++ variant of the Zebrocy downloader tool .' [/INST] [However:O, ,:O, several:O, of:O, the:O, collected:O, samples:O, were:O, a:O, C++:S-TOOL, variant:O, of:O, the:O, Zebrocy:S-MAL, downloader:O, 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: 'In addition , we discovered evidence of a completely different payload in Koadic being delivered as well .' [/INST] [In:O, addition:O, ,:O, we:O, discovered:O, evidence:O, of:O, a:O, completely:O, different:O, payload:O, in:O, Koadic:S-TOOL, being:O, delivered: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: 'Also , we found the IP address 185.25.50.93 hosting C2 services for a Delphi backdoor that ESET ’s report states is the final stage payload for these attacks .' [/INST] [Also:O, ,:O, we:O, found:O, the:O, IP:O, address:O, 185.25.50.93:S-IP, hosting:O, C2:S-TOOL, services:O, for:O, a:O, Delphi:S-TOOL, backdoor:O, that:O, ESET:S-SECTEAM, ’s:O, report:O, states:O, is:O, the:O, final:O, stage:O, payload:O, for:O, these:O, attacks:O, .:O] </s>

<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Please note this is not a comprehensive chart of all Zebrocy and Koadic samples we were able to collect .' [/INST] [Please:O, note:O, this:O, is:O, not:O, a:O, comprehensive:O, chart:O, of:O, all:O, Zebrocy:S-MAL, and:O, Koadic:O, samples:O, we:O, were:O, able:O, to:O, collect: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 samples mentioned or relevant to the relational analysis have been included .' [/INST] [Only:O, samples:O, mentioned:O, or:O, relevant:O, to:O, the:O, relational:O, analysis:O, have:O, been:O, included: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 185.25.50.93 C2 IP , we discovered another hard-coded user agent being used by Zebrocy :' [/INST] [From:O, the:O, 185.25.50.93:S-IP, C2:S-TOOL, IP:O, ,:O, we:O, discovered:O, another:O, hard-coded:O, user:O, agent:O, being:O, used:O, by:O, Zebrocy:S-MAL, ::O] </s>