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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this case , the first sample I looked at stood out for another reason entirely .' [/INST] [In:O, this:O, case:O, ,:O, the:O, first:O, sample:O, I:O, looked:O, at:O, stood:O, out:O, for:O, another:O, reason:O, entirely:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 you take a look at the below PowerShell , you ’ll quickly understand why .' [/INST] [If:O, you:O, take:O, a:O, look:O, at:O, the:O, below:O, PowerShell:S-TOOL, ,:O, you:O, ’ll:O, quickly:O, understand:O, why:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 commonly , PowerShell is launched from a Microsoft Office document that uses a VBA macro to launch PowerShell to perform something malicious – typically downloading the β€œ real ” malware to run .' [/INST] [Most:O, commonly:O, ,:O, PowerShell:S-TOOL, is:O, launched:O, from:O, a:O, Microsoft:B-TOOL, Office:I-TOOL, document:E-TOOL, that:O, uses:O, a:O, VBA:B-TOOL, macro:E-TOOL, to:O, launch:O, PowerShell:S-TOOL, to:O, perform:O, something:O, malicious:O, –:O, typically:O, downloading:O, the:O, β€œ:O, real:O, ”:O, malware:O, to:O, run:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'I focused my hunting on the PowerShell activity with Palo Alto Networks AutoFocus to determine whether it ’s worth digging into further based on β€œ uniqueness ” and functionality .' [/INST] [I:O, focused:O, my:O, hunting:O, on:O, the:O, PowerShell:S-TOOL, activity:O, with:O, Palo:O, Alto:O, Networks:O, AutoFocus:O, to:O, determine:O, whether:O, it:O, ’s:O, worth:O, digging:O, into:O, further:O, based:O, on:O, β€œ:O, uniqueness:O, ”:O, and:O, functionality:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'My initial thought was the worst-case scenario – they ’ve been compromised and are distributing malware ! I immediately downloaded the file from the website , but everything looked normal .' [/INST] [My:O, initial:O, thought:O, was:O, the:O, worst-case:O, scenario:O, –:O, they:O, ’ve:O, been:O, compromised:O, and:O, are:O, distributing:B-ACT, malware:E-ACT, !:O, I:O, immediately:O, downloaded:O, the:O, file:O, from:O, the:O, website:O, ,:O, but:O, everything:O, looked:O, normal:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Of course , I had to investigate further .' [/INST] [Of:O, course:O, ,:O, I:O, had:O, to:O, investigate:O, further:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Looking under the hood we see the VBA code that builds the command and launches it but something seemed off .' [/INST] [Looking:O, under:O, the:O, hood:O, we:O, see:O, the:O, VBA:S-TOOL, code:O, that:O, builds:O, the:O, command:E-FILE, and:O, launches:O, it:O, but:O, something:O, seemed:O, off:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 a ton of functions that are clearly decoding information from arrays after which it executes an already decoded PowerShell command .' [/INST] [There:O, are:O, a:O, ton:O, of:O, functions:O, that:O, are:O, clearly:O, decoding:O, information:O, from:O, arrays:O, after:O, which:O, it:O, executes:O, an:O, already:O, decoded:O, PowerShell:S-TOOL, 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: 'I decided to debug the macro and see exactly what it ’s doing before I made any decisions .' [/INST] [I:O, decided:O, to:O, debug:O, the:O, macro:O, and:O, see:O, exactly:O, what:O, it:O, ’s:O, doing:O, before:O, I:O, made:O, any:O, decisions:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 most likely conclusion that can be drawn here is that an analyst or researcher obtained this file , modified it to see the content ( misspelling the variable name along the way ) post-decoding , and uploaded it to see what it did in a sandbox .' [/INST] [The:O, most:O, likely:O, conclusion:O, that:O, can:O, be:O, drawn:O, here:O, is:O, that:O, an:O, analyst:O, or:O, researcher:O, obtained:O, this:O, file:O, ,:O, modified:O, it:O, to:O, see:O, the:O, content:O, (:O, misspelling:O, the:O, variable:O, name:O, along:O, the:O, way:O, ):O, post-decoding:O, ,:O, and:O, uploaded:O, it:O, to:O, see:O, what:O, it:O, did:O, in:O, a:O, sandbox:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 be sure though , I needed to find other samples and see how they stacked up against this one .' [/INST] [To:O, be:O, sure:O, though:O, ,:O, I:O, needed:O, to:O, find:O, other:O, samples:O, and:O, see:O, how:O, they:O, stacked:O, up:O, against:O, this:O, one:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Going back to the PowerShell command , the initial reason I stopped to look at it was due to the way they concatenated variables to form the download command and output .' [/INST] [Going:O, back:O, to:O, the:O, PowerShell:S-TOOL, command:O, ,:O, the:O, initial:O, reason:O, I:O, stopped:O, to:O, look:O, at:O, it:O, was:O, due:O, to:O, the:O, way:O, they:O, concatenated:O, variables:O, to:O, form:O, the:O, download:O, command:O, and:O, output:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 also provides a perfect pivot point to hunt for samples .' [/INST] [This:O, also:O, provides:O, a:O, perfect:O, pivot:B-TOOL, point:E-TOOL, to:O, hunt:O, for: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: 'The dates were all fairly recent , having been received in the past few days since the beginning of August .' [/INST] [The:O, dates:O, were:O, all:O, fairly:O, recent:O, ,:O, having:O, been:O, received:O, in:O, the:O, past:O, few:O, days:O, since:O, the:O, beginning:B-TIME, of:I-TIME, August: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: 'The documents shared the same themes for lures but the VBA macro and resulting PowerShell were more along the lines of what I expected .' [/INST] [The:O, documents:O, shared:O, the:O, same:O, themes:O, for:O, lures:O, but:O, the:O, VBA:B-TOOL, macro:E-TOOL, and:O, resulting:O, PowerShell:S-TOOL, were:O, more:O, along:O, the:O, lines:O, of:O, what:O, I:O, expected:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 sample β€œ 538ff577a80748d87b5e738e95c8edd2bd54ea406fe3a75bf452714b17528a87 ” the following is an excerpt from the VBA macro building the PowerShell command .' [/INST] [For:O, sample:O, β€œ:O, 538ff577a80748d87b5e738e95c8edd2bd54ea406fe3a75bf452714b17528a87:S-SHA2, ”:O, the:O, following:O, is:O, an:O, excerpt:O, from:O, the:O, VBA:B-TOOL, macro:E-TOOL, building:O, the:O, PowerShell:S-TOOL, 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: 'Along with the subsequent Process Activity using the newly built PowerShell command , which aligns with what was commented out of the first sample analyzed .' [/INST] [Along:O, with:O, the:O, subsequent:O, Process:O, Activity:O, using:O, the:O, newly:O, built:O, PowerShell:S-TOOL, command:O, ,:O, which:O, aligns:O, with:O, what:O, was:O, commented:O, out:O, of:O, the:O, first:O, sample:O, analyzed:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 this , I iterated over all 171 samples and extracted the following URL ’s where PowerShell is downloading a payload :' [/INST] [Given:O, this:O, ,:O, I:O, iterated:O, over:O, all:O, 171:O, samples:O, and:O, extracted:O, the:O, following:O, URL:O, ’s:O, where:O, PowerShell:S-TOOL, is:O, downloading:O, a:O, payload:O, ::O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: '.' [/INST] [.:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 iterating over the 171 samples , we ’re left with this list of hashes for the downloaded files .' [/INST] [After:O, iterating:O, over:O, the:O, 171:O, samples:O, ,:O, we:O, ’re:O, left:O, with:O, this:O, list:O, of:O, hashes:O, for:O, the:O, downloaded: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: 'Note that there are fewer payloads than there are samples , indicating many of the documents download the same payload .' [/INST] [Note:O, that:O, there:O, are:O, fewer:O, payloads:O, than:O, there:O, are:O, samples:O, ,:O, indicating:O, many:O, of:O, the:O, documents:O, download:O, the:O, same:O, payload:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Below is a table with the compile date and some PDB strings found within a few of the binaries .' [/INST] [Below:O, is:O, a:O, table:O, with:O, the:O, compile:O, date:O, and:O, some:O, PDB:O, strings:O, found:O, within:O, a:O, few:O, of:O, the:O, binaries:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 compile times are within the past two months , with 6 in August and a couple from as recently as two days ago at the time of this writing . 29c7740f487a461a96fad1c8db3921ccca8cc3e7548d44016da64cf402a475ad 2016-12-10 01 . d5e56b9b5f52293b209a60c2ccd0ade6c883f9d3ec09571a336a3a4d4c79134b 2016-12-10 03 C:\RAMDrive\Charles\heaven\reams\Teac.pdb . dd5f237153856d19cf20e80ff8238ca42047113c44fae27b5c3ad00be2755eea 2016-12-10 16 C:\Cleaner\amuse\rang\AutoPopulate\la.pdb . a5001e9b29078f532b1a094c8c16226d20c03922e37a4fca2e9172350bc160a0 2016-12-20 18 . 8284ec768a06b606044defe2c2da708ca6b3b51f8e58cb66f61bfca56157bc88 2017-07-05 10 . f0ce51eb0e6c33fdb8e1ccb36b9f42139c1dfc58d243195aedc869c7551a5f89 2017-07-09 20 C:\TableAdapter\encyclopedia\Parik.pdb . 145d47f4c79206c6c9f74b0ab76c33ad0fd40ac6724b4fac6f06afec47b307c6 2017-07-10 08 C:\ayakhnin\reprductive\distortedc.pdb . dc8f34829d5fede991b478cf9117fb18c32d639573a827227b2fc50f0b475085 2017-07-11 01 C:\positioning\scrapping\Szets\thi.pdb . 7fe1069c118611113b4e34685e7ee58cb469bda4aa66a22db10842c95f332c77 2017-07-11 02 C:\NeXT\volatile\legacyExchangeDNs.pdb . 5edf117e7f8cd176b1efd0b5fd40c6cd530699e7a280c5c7113d06e9c21d6976 2017-07-12 23 . 2a80fdda87127bdc56fd35c3e04eb64a01a159b7b574177e2e346439c97b770a 2017-07-13 00. a9021e253ae52122cbcc2284b88270ceda8ad9647515d6cca96db264a76583f5 2017-07-18 00 . dd639d76ff6f33bbfaf3bd398056cf4e95e27822bd9476340c7703f5b38e0183 2017-07-18 00 . e5a00b49d4ab3e5a3a8f60278b9295f3d252e3e04dadec2624bb4dcb2eb0fada 2017-07-24 17 . 6263730ef54fbed0c2d3a7c6106b6e8b12a6b2855a03e7caa8fb184ed1eabeb2 2017-07-24 22 C:\Snapshot\Diskette\hiding\ROCKMA.pdb . 43bfaf9a2a4d46695bb313a32d88586c510d040844f29852c755845a5a09d9df 2017-07-25 06 . b41660db6dcb0d3c7b17f98eae3141924c8c0ee980501ce541b42dc766f85628 2017-07-25 06 C:\mdb\Changed\Container\praise.pdb . 9acdad02ca8ded6043ab52b4a7fb2baac3a08c9f978ce9da2eb51c816a9e7a2e 2017-07-25 07 . 2ddaa30ba3c3e625e21eb7ce7b93671ad53326ef8b6e2bc20bc0d2de72a3929d 2017-07-25 20 C:\helpers\better\Expr\Eight\DS.pdb . b836576877b2fcb3cacec370e5e6a029431f59d5070da89d94200619641ca0c4 2017-07-26 12 C:\V\regard\violates\update\AMBW\a.pdb . 0972fc9602b00595e1022d9cfe7e9c9530d4e9adb5786fea830324b3f7ff4448 2017-07-26 20 . 2c258ac862d5e31d8921b64cfa7e5a9cd95cca5643c9d51db4c2fcbe75fa957a 2017-07-27 01 C:\executablery\constructed\IIc.pdb . dd9c558ba58ac81a2142ecb308ac8d0f044c7059a039d2e367024d953cd14a00 2017-07-27 02 . cb3173a820ac392005de650bbd1dd24543a91e72d4d56300a7795e887a8323b2 2017-07-31 14 C:\letterbxing\EVP\Chices\legit.pdb . a636f49814ea6603534f780b83a5d0388f5a5d0eb848901e1e1bf2d19dd84f05 2017-07-31 18 C:\Biomuse\moment\705\cnvincing.pdb . 677dd11912a0f13311d025f88caabeeeb1bda27c7c1b5c78cffca36de46e8560 2017-07-31 21 . fdedf0f90d42d3779b07951d1e8826c7015b3f3e724ab89e350c9608e1f23852 2017-08-01 21 . 142bf7f47bfbd592583fbcfa22a25462df13da46451b17bb984d50ade68a5b17 2017-08-02 09 . 6f4b2c95b1a0f320da1b1eaa918c338c0bab5cddabe169f12ee734243ed8bba8 2017-08-02 12 C:\cataloging\Dr\VarianceShadows11.pdb . fd5fd7058cf157ea249d4dcba71331f0041b7cf8fd635f37ad13aed1b06bebf2 2017-08-04 02 C:\dumplings\That\BIT\Warez\loc.pdb . 5785c2d68d6f669b96c3f31065f0d9804d2ab1f333a90d225bd993e66656b7d9 2017-08-07 12 C:\Lgisys\hypothesized\donatedc.pdb . 675719a9366386034c285e99bf33a1a8bafc7644874b758f307d9a288e95bdbd 2017-08-07 17 C:\work\cr\nata\cpp\seven\seven\release\seven.pdb .' [/INST] [Most:O, of:O, the:O, compile:O, times:O, are:O, within:O, the:B-TIME, past:I-TIME, two:I-TIME, months:E-TIME, ,:O, with:O, 6:O, in:O, August:S-TIME, and:O, a:O, couple:O, from:O, as:O, recently:B-TIME, as:I-TIME, two:I-TIME, days:I-TIME, ago:E-TIME, at:O, the:O, time:O, of:O, this:O, writing:O, .:O, 29c7740f487a461a96fad1c8db3921ccca8cc3e7548d44016da64cf402a475ad:S-SHA2, 2016-12-10:B-TIME, 01:E-TIME, .:O, d5e56b9b5f52293b209a60c2ccd0ade6c883f9d3ec09571a336a3a4d4c79134b:S-SHA2, 2016-12-10:B-TIME, 03:E-TIME, C:\RAMDrive\Charles\heaven\reams\Teac.pdb:O, .:O, dd5f237153856d19cf20e80ff8238ca42047113c44fae27b5c3ad00be2755eea:S-SHA2, 2016-12-10:B-TIME, 16:E-TIME, C:\Cleaner\amuse\rang\AutoPopulate\la.pdb:O, .:O, a5001e9b29078f532b1a094c8c16226d20c03922e37a4fca2e9172350bc160a0:S-SHA2, 2016-12-20:B-TIME, 18:E-TIME, .:O, 8284ec768a06b606044defe2c2da708ca6b3b51f8e58cb66f61bfca56157bc88:S-SHA2, 2017-07-05:B-TIME, 10:E-TIME, .:O, f0ce51eb0e6c33fdb8e1ccb36b9f42139c1dfc58d243195aedc869c7551a5f89:S-SHA2, 2017-07-09:B-TIME, 20:E-TIME, C:\TableAdapter\encyclopedia\Parik.pdb:O, .:O, 145d47f4c79206c6c9f74b0ab76c33ad0fd40ac6724b4fac6f06afec47b307c6:S-SHA2, 2017-07-10:B-TIME, 08:E-TIME, C:\ayakhnin\reprductive\distortedc.pdb:O, .:O, dc8f34829d5fede991b478cf9117fb18c32d639573a827227b2fc50f0b475085:S-SHA2, 2017-07-11:B-TIME, 01:E-TIME, C:\positioning\scrapping\Szets\thi.pdb:O, .:O, 7fe1069c118611113b4e34685e7ee58cb469bda4aa66a22db10842c95f332c77:S-SHA2, 2017-07-11:B-TIME, 02:E-TIME, C:\NeXT\volatile\legacyExchangeDNs.pdb:O, .:O, 5edf117e7f8cd176b1efd0b5fd40c6cd530699e7a280c5c7113d06e9c21d6976:S-SHA2, 2017-07-12:B-TIME, 23:E-TIME, .:O, 2a80fdda87127bdc56fd35c3e04eb64a01a159b7b574177e2e346439c97b770a:S-SHA2, 2017-07-13:B-TIME, 00.:E-TIME, a9021e253ae52122cbcc2284b88270ceda8ad9647515d6cca96db264a76583f5:S-SHA2, 2017-07-18:B-TIME, 00:E-TIME, .:O, dd639d76ff6f33bbfaf3bd398056cf4e95e27822bd9476340c7703f5b38e0183:S-SHA2, 2017-07-18:B-TIME, 00:E-TIME, .:O, e5a00b49d4ab3e5a3a8f60278b9295f3d252e3e04dadec2624bb4dcb2eb0fada:S-SHA2, 2017-07-24:B-TIME, 17:E-TIME, .:O, 6263730ef54fbed0c2d3a7c6106b6e8b12a6b2855a03e7caa8fb184ed1eabeb2:S-SHA2, 2017-07-24:B-TIME, 22:E-TIME, C:\Snapshot\Diskette\hiding\ROCKMA.pdb:O, .:O, 43bfaf9a2a4d46695bb313a32d88586c510d040844f29852c755845a5a09d9df:S-SHA2, 2017-07-25:B-TIME, 06:E-TIME, .:O, b41660db6dcb0d3c7b17f98eae3141924c8c0ee980501ce541b42dc766f85628:S-SHA2, 2017-07-25:B-TIME, 06:E-TIME, C:\mdb\Changed\Container\praise.pdb:O, .:O, 9acdad02ca8ded6043ab52b4a7fb2baac3a08c9f978ce9da2eb51c816a9e7a2e:S-SHA2, 2017-07-25:B-TIME, 07:E-TIME, .:O, 2ddaa30ba3c3e625e21eb7ce7b93671ad53326ef8b6e2bc20bc0d2de72a3929d:S-SHA2, 2017-07-25:B-TIME, 20:E-TIME, C:\helpers\better\Expr\Eight\DS.pdb:O, .:O, b836576877b2fcb3cacec370e5e6a029431f59d5070da89d94200619641ca0c4:S-SHA2, 2017-07-26:B-TIME, 12:E-TIME, C:\V\regard\violates\update\AMBW\a.pdb:O, .:O, 0972fc9602b00595e1022d9cfe7e9c9530d4e9adb5786fea830324b3f7ff4448:S-SHA2, 2017-07-26:B-TIME, 20:E-TIME, .:O, 2c258ac862d5e31d8921b64cfa7e5a9cd95cca5643c9d51db4c2fcbe75fa957a:S-SHA2, 2017-07-27:B-TIME, 01:E-TIME, C:\executablery\constructed\IIc.pdb:O, .:O, dd9c558ba58ac81a2142ecb308ac8d0f044c7059a039d2e367024d953cd14a00:S-SHA2, 2017-07-27:B-TIME, 02:E-TIME, .:O, cb3173a820ac392005de650bbd1dd24543a91e72d4d56300a7795e887a8323b2:S-SHA2, 2017-07-31:B-TIME, 14:E-TIME, C:\letterbxing\EVP\Chices\legit.pdb:O, .:O, a636f49814ea6603534f780b83a5d0388f5a5d0eb848901e1e1bf2d19dd84f05:S-SHA2, 2017-07-31:B-TIME, 18:E-TIME, C:\Biomuse\moment\705\cnvincing.pdb:O, .:O, 677dd11912a0f13311d025f88caabeeeb1bda27c7c1b5c78cffca36de46e8560:S-SHA2, 2017-07-31:B-TIME, 21:E-TIME, .:O, fdedf0f90d42d3779b07951d1e8826c7015b3f3e724ab89e350c9608e1f23852:S-SHA2, 2017-08-01:B-TIME, 21:E-TIME, .:O, 142bf7f47bfbd592583fbcfa22a25462df13da46451b17bb984d50ade68a5b17:S-SHA2, 2017-08-02:B-TIME, 09:E-TIME, .:O, 6f4b2c95b1a0f320da1b1eaa918c338c0bab5cddabe169f12ee734243ed8bba8:S-SHA2, 2017-08-02:B-TIME, 12:E-TIME, C:\cataloging\Dr\VarianceShadows11.pdb:O, .:O, fd5fd7058cf157ea249d4dcba71331f0041b7cf8fd635f37ad13aed1b06bebf2:S-SHA2, 2017-08-04:B-TIME, 02:E-TIME, C:\dumplings\That\BIT\Warez\loc.pdb:O, .:O, 5785c2d68d6f669b96c3f31065f0d9804d2ab1f333a90d225bd993e66656b7d9:S-SHA2, 2017-08-07:B-TIME, 12:E-TIME, C:\Lgisys\hypothesized\donatedc.pdb:O, .:O, 675719a9366386034c285e99bf33a1a8bafc7644874b758f307d9a288e95bdbd:S-SHA2, 2017-08-07:B-TIME, 17:E-TIME, C:\work\cr\nata\cpp\seven\seven\release\seven.pdb:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'At least one of the binaries compiled in August had a PDB string I was able to locate online in a collection of other PDB files , so they may be introducing their malicious code into these files before compiling someone else ’s project .' [/INST] [At:O, least:O, one:O, of:O, the:O, binaries:O, compiled:O, in:O, August:S-TIME, had:O, a:O, PDB:O, string:O, I:O, was:O, able:O, to:O, locate:O, online:O, in:O, a:O, collection:O, of:O, other:O, PDB:O, files:O, ,:O, so:O, they:O, may:O, be:O, introducing:O, their:O, malicious:O, code:O, into:O, these:O, files:O, before:O, compiling:O, someone:O, else:O, ’s:O, project:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 file has been downloaded and executed , the new process will launch a legitimate executable , such as β€œ msiexec.exe ” , and inject code into it .' [/INST] [Once:O, the:O, file:O, has:O, been:O, downloaded:O, and:O, executed:O, ,:O, the:O, new:O, process:O, will:O, launch:O, a:O, legitimate:O, executable:O, ,:O, such:O, as:O, β€œ:O, msiexec.exe:S-FILE, ”:O, ,:O, and:O, inject:O, code:O, into:O, it:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 code will then download further payloads through a POST request to various websites .' [/INST] [This:O, code:O, will:O, then:O, download:O, further:O, payloads:O, through:O, a:O, POST:S-PROT, request:O, to:O, various:O, websites:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 pattern is shared across the original samples .' [/INST] [This:O, pattern:O, is:O, shared:O, across:O, the:O, original: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: 'These HTTP requests match known patterns for a banking Trojan named Chthonic , which is a variant of Zeus .' [/INST] [These:O, HTTP:S-PROT, requests:O, match:O, known:O, patterns:O, for:O, a:O, banking:B-MAL, Trojan:E-MAL, named:O, Chthonic:S-MAL, ,:O, which:O, is:O, a:O, variant:O, of:O, Zeus:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 good write-up from 2014 on the malware can be found in this writeup from Yury Namestnikov , Vladimir Kuskov , Oleg Kupreev at Kaspersky Lab here and indicates that the returned data is an RC4 encrypted loader that sets-up the main Chthonic module which can download additional modules or malware .' [/INST] [A:O, good:O, write-up:O, from:O, 2014:S-TIME, on:O, the:O, malware:O, can:O, be:O, found:O, in:O, this:O, writeup:O, from:O, Yury:O, Namestnikov:O, ,:O, Vladimir:O, Kuskov:O, ,:O, Oleg:O, Kupreev:O, at:O, Kaspersky:B-LOC, Lab:E-LOC, here:O, and:O, indicates:O, that:O, the:O, returned:O, data:O, is:O, an:O, RC4:S-ENCR, encrypted:O, loader:O, that:O, sets-up:O, the:O, main:O, Chthonic:S-MAL, module:O, which:O, can:O, download:O, additional:O, modules:O, or: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: 'Iterating once again over the 171 samples and scraping out the HTTP POST requests , I ended up with the below set of domains :' [/INST] [Iterating:O, once:O, again:O, over:O, the:O, 171:O, samples:O, and:O, scraping:O, out:O, the:O, HTTP:S-PROT, POST:S-PROT, requests:O, ,:O, I:O, ended:O, up:O, with:O, the:O, below:O, set:O, of: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: 'amellet.bit danrnysvp.com ejtmjealr.com firop.com gefinsioje.com gesofgamd.com ponedobla.bit unoset.com .' [/INST] [amellet.bit:S-DOM, danrnysvp.com:S-DOM, ejtmjealr.com:S-DOM, firop.com:S-DOM, gefinsioje.com:S-DOM, gesofgamd.com:S-DOM, ponedobla.bit:S-DOM, unoset.com:S-DOM, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 as the next pivot , we have 6,034 unique samples that get returned in AutoFocus having made POST requests to these sites .' [/INST] [Using:O, this:O, as:O, the:O, next:O, pivot:O, ,:O, we:O, have:O, 6,034:O, unique:O, samples:O, that:O, get:O, returned:O, in:O, AutoFocus:O, having:O, made:O, POST:S-PROT, requests:O, to:O, these:O, sites:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Additionally , we can see there were at least 3 very large campaigns where Palo Alto Networks saw activity to these sites in July .' [/INST] [Additionally:O, ,:O, we:O, can:O, see:O, there:O, were:O, at:O, least:O, 3:O, very:O, large:O, campaigns:O, where:O, Palo:O, Alto:O, Networks:O, saw:O, activity:O, to:O, these:O, sites:O, in:O, July: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: 'From these distribution sites , we can see that 5,520 samples are making HTTP requests to them and these samples have been identified as another downloader Trojan named Nymaim .' [/INST] [From:O, these:O, distribution:O, sites:O, ,:O, we:O, can:O, see:O, that:O, 5,520:O, samples:O, are:O, making:O, HTTP:S-PROT, requests:O, to:O, them:O, and:O, these:O, samples:O, have:O, been:O, identified:O, as:O, another:O, downloader:O, Trojan:S-MAL, named:O, Nymaim: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: 'The majority of the overall samples came from the following four sites :' [/INST] [The:O, majority:O, of:O, the:O, overall:O, samples:O, came:O, from:O, the:O, following:O, four:O, sites:O, ::O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'ejtmjealr.com gefinsioje.com gesofgamd.com ponedobla.bit .' [/INST] [ejtmjealr.com:S-DOM, gefinsioje.com:S-DOM, gesofgamd.com:S-DOM, ponedobla.bit:S-DOM, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 β€˜ ejtmjealr.com ’ domain is particularly interesting due to a similar domain , β€˜ ejdqzkd.com ’ being discussed by JarosΕ‚aw Jedynak of CERT.PL in this analysis of Nymaim from earlier in the year .' [/INST] [The:O, β€˜:O, ejtmjealr.com:S-DOM, ’:O, domain:O, is:O, particularly:O, interesting:O, due:O, to:O, a:O, similar:O, domain:O, ,:O, β€˜:O, ejdqzkd.com:S-DOM, ’:O, being:O, discussed:O, by:O, JarosΕ‚aw:O, Jedynak:O, of:O, CERT.PL:S-IDTY, in:O, this:O, analysis:O, of:O, Nymaim:S-MAL, from:O, earlier:B-TIME, in:I-TIME, the:I-TIME, year: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: 'They go on to discuss how Nymaim uses a static configuration to contact that domain , which will return IP ’s that go into a DGA and output the actual IP addresses needed for C2 communication .' [/INST] [They:O, go:O, on:O, to:O, discuss:O, how:O, Nymaim:S-MAL, uses:O, a:O, static:O, configuration:O, to:O, contact:O, that:O, domain:O, ,:O, which:O, will:O, return:O, IP:O, ’s:O, that:O, go:O, into:O, a:O, DGA:O, and:O, output:O, the:O, actual:O, IP:O, addresses:O, needed:O, for:O, C2:S-TOOL, communication:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Ben Baker , Edmund Brumaghin and Jonah Samost of Talos have a fantastic write-up of this process here .' [/INST] [Ben:O, Baker:O, ,:O, Edmund:O, Brumaghin:O, and:O, Jonah:O, Samost:O, of:O, Talos:S-IDTY, have:O, a:O, fantastic:O, write-up:O, of:O, this:O, process: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: 'To continue my analysis , I shifted focus to Maltego so as to visually graph the infrastructure .' [/INST] [To:O, continue:O, my:O, analysis:O, ,:O, I:O, shifted:O, focus:O, to:O, Maltego:S-TOOL, so:O, as:O, to:O, visually:O, graph:O, the:O, 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: 'For this task , I used PassiveTotal ’s Passive DNS and AutoFocus Maltego transforms .' [/INST] [For:O, this:O, task:O, ,:O, I:O, used:O, PassiveTotal:B-TOOL, ’s:I-TOOL, Passive:I-TOOL, DNS:E-TOOL, and:O, AutoFocus:B-TOOL, Maltego:I-TOOL, transforms:E-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: 'Pivoting off the five highlighted IP ’s above with a shared infrastructure , I pulled the reverse DNS to see what other sites may be present .' [/INST] [Pivoting:O, off:O, the:O, five:O, highlighted:O, IP:O, ’s:O, above:O, with:O, a:O, shared:O, infrastructure:O, ,:O, I:O, pulled:O, the:O, reverse:O, DNS:S-PROT, to:O, see:O, what:O, other:O, sites:O, may:O, be:O, present:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 β€œ idXXXXX.top ” pattern immediately stands out and may suggest a pattern in the static configuration for the initial domains used by the DGA for Nymaim since the previous two started with β€œ ejX.com .' [/INST] [The:O, β€œ:O, idXXXXX.top:O, ”:O, pattern:O, immediately:O, stands:O, out:O, and:O, may:O, suggest:O, a:O, pattern:O, in:O, the:O, static:O, configuration:O, for:O, the:O, initial:O, domains:O, used:O, by:O, the:O, DGA:O, for:O, Nymaim:S-MAL, since:O, the:O, previous:O, two:O, started:O, with:O, β€œ:O, ejX.com:S-DOM, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 level of overlap already , I proceeded to grab all of the passive DNS available for each of the 707 IP addresses .' [/INST] [Given:O, the:O, level:O, of:O, overlap:O, already:O, ,:O, I:O, proceeded:O, to:O, grab:O, all:O, of:O, the:O, passive:O, DNS:S-PROT, available:O, for:O, each:O, of:O, the:O, 707:O, IP:O, addresses:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 full list of the domains can be seen here .' [/INST] [A:O, full:O, list:O, of:O, the:O, domains:O, can:O, be:O, seen: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: 'From the first cluster on the left , if we sort by incoming links per node a pattern stands out in the domain names looking similar to the previously mentioned Nymaim ones .' [/INST] [From:O, the:O, first:O, cluster:O, on:O, the:O, left:O, ,:O, if:O, we:O, sort:O, by:O, incoming:O, links:O, per:O, node:O, a:O, pattern:O, stands:O, out:O, in:O, the:O, domain:O, names:O, looking:O, similar:O, to:O, the:O, previously:O, mentioned:O, Nymaim:S-MAL, ones:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 quick search with the AutoFocus transform to pull tag information shows these are specifically related to Nymaim , most likely for the DGA seed ; however , looking at domains with less links , other malware families begin to emerge .' [/INST] [A:O, quick:O, search:O, with:O, the:O, AutoFocus:O, transform:O, to:O, pull:O, tag:O, information:O, shows:O, these:O, are:O, specifically:O, related:O, to:O, Nymaim:S-MAL, ,:O, most:O, likely:O, for:O, the:O, DGA:O, seed:O, ;:O, however:O, ,:O, looking:O, at:O, domains:O, with:O, less:O, links:O, ,:O, other:B-MAL, malware:I-MAL, families:E-MAL, begin:O, to:O, emerge:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 cluster on the right is actually collapsing one collection of entities due to the sheer size of it .' [/INST] [The:O, cluster:O, on:O, the:O, right:O, is:O, actually:O, collapsing:O, one:O, collection:O, of:O, entities:O, due:O, to:O, the:O, sheer:O, size:O, of:O, it:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'All of these connected domains follow a pattern similar to phishing attacks masquerading as legitimate services – in this case β€œ online.verify.paypal ” ( 588 ) and β€œ hmrc.secure.refund ” ( 1021 ) .' [/INST] [All:O, of:O, these:O, connected:O, domains:O, follow:O, a:O, pattern:O, similar:O, to:O, phishing:B-ACT, attacks:E-ACT, masquerading:O, as:O, legitimate:O, services:O, –:O, in:O, this:O, case:O, β€œ:O, online.verify.paypal:O, ”:O, (:O, 588:O, ):O, and:O, β€œ:O, hmrc.secure.refund:O, ”:O, (:O, 1021:O, ):O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition to domains of that type , there is evidence of other malware distribution being carried out on this infrastructure .' [/INST] [In:O, addition:O, to:O, domains:O, of:O, that:O, type:O, ,:O, there:O, is:O, evidence:O, of:O, other:O, malware:O, distribution:O, being:O, carried:O, out:O, on:O, this:O, 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: 'Collapsing the collection back down , note the two domains β€œ brontorittoozzo.com ” and β€œ randomessstioprottoy.net ” that fall outside of the collection due to more infrastructure connections .' [/INST] [Collapsing:O, the:O, collection:O, back:O, down:O, ,:O, note:O, the:O, two:O, domains:O, β€œ:O, brontorittoozzo.com:S-DOM, ”:O, and:O, β€œ:O, randomessstioprottoy.net:S-DOM, ”:O, that:O, fall:O, outside:O, of:O, the:O, collection:O, due:O, to:O, more:O, infrastructure:O, connections:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 pivoting off of one sample we were able to zoom out and identify a sizable infrastructure of what appears to be 707 IP ’s and 2,611 domains being utilized for malicious activity .' [/INST] [By:O, pivoting:O, off:O, of:O, one:O, sample:O, we:O, were:O, able:O, to:O, zoom:O, out:O, and:O, identify:O, a:O, sizable:O, infrastructure:O, of:O, what:O, appears:O, to:O, be:O, 707:O, IP:O, ’s:O, and:O, 2,611:O, domains:O, being:O, utilized:O, for:O, malicious:O, activity:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 such , these findings represent a collection of compromised websites , compromised registrar accounts used to spin up subdomains , domains used by malware DGA ’s , phishing kits , carding forums , malware C2 sites , and a slew of other domains that revolve around criminal activity .' [/INST] [As:O, such:O, ,:O, these:O, findings:O, represent:O, a:O, collection:O, of:O, compromised:O, websites:O, ,:O, compromised:O, registrar:O, accounts:O, used:O, to:O, spin:O, up:O, subdomains:O, ,:O, domains:O, used:O, by:O, malware:O, DGA:S-MAL, ’s:O, ,:O, phishing:E-ACT, kits:O, ,:O, carding:O, forums:O, ,:O, malware:O, C2:S-TOOL, sites:O, ,:O, and:O, a:O, slew:O, of:O, other:O, domains:O, that:O, revolve:O, around:O, criminal:O, activity:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Hopefully this analysis has been helpful in understanding how truly connected some of these infrastructures can be and how with a little digging , you can uncover a substantial amount of operationally useful indicators to protect you and yours .' [/INST] [Hopefully:O, this:O, analysis:O, has:O, been:O, helpful:O, in:O, understanding:O, how:O, truly:O, connected:O, some:O, of:O, these:O, infrastructures:O, can:O, be:O, and:O, how:O, with:O, a:O, little:O, digging:O, ,:O, you:O, can:O, uncover:O, a:O, substantial:O, amount:O, of:O, operationally:O, useful:O, indicators:O, to:O, protect:O, you:O, and:O, yours:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Full Shamoon : How the Devastating Malware Was Inserted Into Networks' [/INST] [The:O, Full:O, Shamoon:S-MAL, ::O, How:O, the:O, Devastating:O, Malware:O, Was:O, Inserted:O, Into:O, Networks:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: '.' [/INST] [.:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Researchers from the IBM X-Force Incident Response and Intelligence Services ( IRIS ) team identified a missing link in the operations of a threat actor involved in recent Shamoon malware attacks against Gulf state organizations .' [/INST] [Researchers:O, from:O, the:O, IBM:B-SECTEAM, X-Force:I-SECTEAM, Incident:I-SECTEAM, Response:I-SECTEAM, and:I-SECTEAM, Intelligence:I-SECTEAM, Services:I-SECTEAM, (:I-SECTEAM, IRIS:I-SECTEAM, ):I-SECTEAM, team:E-SECTEAM, identified:O, a:O, missing:O, link:O, in:O, the:O, operations:O, of:O, a:O, threat:O, actor:O, involved:O, in:O, recent:O, Shamoon:O, malware:O, attacks:O, against:O, Gulf:B-LOC, state:E-LOC, organizations:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 attacks , which occurred in November 2016 and January 2017 , reportedly affected thousands of computers across multiple government and civil organizations in Saudi Arabia and elsewhere in Gulf states .' [/INST] [These:O, attacks:O, ,:O, which:O, occurred:O, in:O, November:B-TIME, 2016:E-TIME, and:O, January:B-TIME, 2017:E-TIME, ,:O, reportedly:O, affected:O, thousands:O, of:O, computers:O, across:O, multiple:O, government:O, and:O, civil:O, organizations:O, in:O, Saudi:B-LOC, Arabia:E-LOC, and:O, elsewhere:O, in:O, Gulf:B-LOC, states: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: 'Shamoon is designed to destroy computer hard drives by wiping the master boot record ( MBR ) and data irretrievably , unlike ransomware , which holds the data hostage for a fee .' [/INST] [Shamoon:S-MAL, is:O, designed:O, to:O, destroy:O, computer:O, hard:O, drives:O, by:O, wiping:O, the:O, master:O, boot:O, record:O, (:O, MBR:O, ):O, and:O, data:O, irretrievably:O, ,:O, unlike:O, ransomware:O, ,:O, which:O, holds:O, the:O, data:O, hostage:O, for:O, a:O, fee:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Through their recent investigations , our forensics analysts pinpointed the initial compromise vector and post-compromise operations that led to the deployment of the destructive Shamoon malware on targeted infrastructures .' [/INST] [Through:O, their:O, recent:O, investigations:O, ,:O, our:O, forensics:O, analysts:O, pinpointed:O, the:O, initial:O, compromise:O, vector:O, and:O, post-compromise:O, operations:O, that:O, led:O, to:O, the:O, deployment:O, of:O, the:O, destructive:O, Shamoon:S-MAL, malware:O, on:O, targeted:O, infrastructures:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'It ’s worth mentioning that , according to X-Force IRIS , the initial compromise took place weeks before the actual Shamoon deployment and activation were launched .' [/INST] [It:O, ’s:O, worth:O, mentioning:O, that:O, ,:O, according:O, to:O, X-Force:B-SECTEAM, IRIS:E-SECTEAM, ,:O, the:O, initial:O, compromise:O, took:O, place:O, weeks:O, before:O, the:O, actual:O, Shamoon:S-MAL, deployment:O, and:O, activation:O, were: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: 'Since Shamoon incidents feature the infiltration and escalation stages of targeted attacks , X-Force IRIS responders sought out the attackers ’ entry point .' [/INST] [Since:O, Shamoon:O, incidents:O, feature:O, the:O, infiltration:O, and:O, escalation:O, stages:O, of:O, targeted:O, attacks:O, ,:O, X-Force:B-TOOL, IRIS:I-TOOL, responders:E-TOOL, sought:O, out:O, the:O, attackers:O, ’:O, entry:O, point:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 findings pointed to what appears to be the initial point of compromise the attackers used : a document containing a malicious macro that , when approved to execute , enabled C2 communications to the attacker ’s server and remote shell via PowerShell .' [/INST] [Their:O, findings:O, pointed:O, to:O, what:O, appears:O, to:O, be:O, the:O, initial:O, point:O, of:O, compromise:O, the:O, attackers:O, used:O, ::O, a:O, document:O, containing:O, a:O, malicious:O, macro:O, that:O, ,:O, when:O, approved:O, to:O, execute:O, ,:O, enabled:O, C2:S-PROT, communications:O, to:O, the:O, attacker:O, ’s:O, server:O, and:O, remote:O, shell:O, via:O, PowerShell: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 document was not the only one discovered in the recent attack waves .' [/INST] [The:O, document:O, was:O, not:O, the:O, only:O, one:O, discovered:O, in:O, the:O, recent:O, attack:O, waves:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'X-Force IRIS researchers had been tracking earlier activity associated with similar malicious , PowerShell-laden documents themed as resumes and human resources documents , some of which related to organizations in Saudi Arabia .' [/INST] [X-Force:B-SECTEAM, IRIS:E-SECTEAM, researchers:O, had:O, been:O, tracking:O, earlier:O, activity:O, associated:O, with:O, similar:O, malicious:O, ,:O, PowerShell-laden:O, documents:O, themed:O, as:O, resumes:O, and:O, human:O, resources:O, documents:O, ,:O, some:O, of:O, which:O, related:O, to:O, organizations:O, in:O, Saudi:B-LOC, Arabia: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: 'This research identified several bouts of offensive activity that occurred in the past few months , which revealed similar operational methods in which the attackers served malicious documents and other malware executables from web servers to their targets to establish an initial foothold in the network .' [/INST] [This:O, research:O, identified:O, several:O, bouts:O, of:O, offensive:O, activity:O, that:O, occurred:O, in:O, the:O, past:O, few:O, months:O, ,:O, which:O, revealed:O, similar:O, operational:O, methods:O, in:O, which:O, the:O, attackers:O, served:O, malicious:O, documents:O, and:O, other:O, malware:O, executables:O, from:O, web:O, servers:O, to:O, their:O, targets:O, to:O, establish:O, an:O, initial:O, foothold:O, in:O, the:O, network:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Although Shamoon was previously documented in research blogs , the specific network compromise methods leading to the attacks have remained unclear in the reported cases .' [/INST] [Although:O, Shamoon:S-MAL, was:O, previously:O, documented:O, in:O, research:O, blogs:O, ,:O, the:O, specific:O, network:O, compromise:O, methods:O, leading:O, to:O, the:O, attacks:O, have:O, remained:O, unclear:O, in:O, the:O, reported:O, cases:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'X-Force IRIS researchers studied Shamoon ’s attack life cycle and observed its tactics at Saudi-based organizations and private sector companies .' [/INST] [X-Force:B-SECTEAM, IRIS:E-SECTEAM, researchers:O, studied:O, Shamoon:S-MAL, ’s:O, attack:O, life:O, cycle:O, and:O, observed:O, its:O, tactics:O, at:O, Saudi-based:O, organizations:O, and:O, private:O, sector:O, companies:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 research led them to believe that the actor using Shamoon in recent attacks relied heavily on weaponized documents built to leverage PowerShell to establish their initial network foothold and subsequent operations :' [/INST] [This:O, research:O, led:O, them:O, to:O, believe:O, that:O, the:O, actor:O, using:O, Shamoon:S-MAL, in:O, recent:O, attacks:O, relied:O, heavily:O, on:O, weaponized:O, documents:O, built:O, to:O, leverage:O, PowerShell:S-TOOL, to:O, establish:O, their:O, initial:O, network:O, foothold:O, and:O, subsequent: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: 'Attackers send a spear phishing email to employees at the target organization .' [/INST] [Attackers:O, send:O, a:O, spear:B-ACT, phishing:E-ACT, email:S-TOOL, to:O, employees:O, at:O, the:O, target:O, organization:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The email contains a Microsoft Office document as an attachment .' [/INST] [The:O, email:S-TOOL, contains:O, a:O, Microsoft:B-TOOL, Office:E-TOOL, document:O, as:O, an:O, attachment:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Opening the attachment from the email invokes PowerShell and enables command line access to the compromised machine .' [/INST] [Opening:O, the:O, attachment:O, from:O, the:O, email:S-TOOL, invokes:O, PowerShell:S-TOOL, and:O, enables:O, command:O, line:O, access:O, to:O, the:O, compromised: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: 'Attackers can now communicate with the compromised machine and remotely execute commands on it .' [/INST] [Attackers:O, can:O, now:O, communicate:O, with:O, the:O, compromised:O, machine:O, and:O, remotely:O, execute:O, commands:O, on:O, it:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The attackers use their access to deploy additional tools and malware to other endpoints or escalate privileges in the network .' [/INST] [The:O, attackers:O, use:O, their:O, access:O, to:O, deploy:O, additional:O, tools:O, and:O, malware:O, to:O, other:O, endpoints:O, or:O, escalate:O, privileges:O, in:O, the:O, network:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Attackers study the network by connecting to additional systems and locating critical servers .' [/INST] [Attackers:O, study:O, the:O, network:O, by:O, connecting:O, to:O, additional:O, systems:O, and:O, locating:O, critical:O, servers:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The attackers deploy the Shamoon malware .' [/INST] [The:O, attackers:O, deploy:O, the:O, Shamoon:S-MAL, 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: 'A coordinated Shamoon outbreak begins and computer hard drives across the organization are permanently wiped .' [/INST] [A:O, coordinated:O, Shamoon:S-MAL, outbreak:O, begins:O, and:O, computer:O, hard:O, drives:O, across:O, the:O, organization:O, are:O, permanently:O, wiped:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'X-Force IRIS identified the below malicious document .' [/INST] [X-Force:B-SECTEAM, IRIS:E-SECTEAM, identified:O, the:O, below:O, malicious:O, document:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'X-Force IRIS File name : cv_itworx.doc .' [/INST] [X-Force:O, IRIS:O, File:O, name:O, ::O, cv_itworx.doc: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: 'X-Force IRIS MD5 : 45b0e5a457222455384713905f886bd4 .' [/INST] [X-Force:O, IRIS:O, MD5:S-ENCR, ::O, 45b0e5a457222455384713905f886bd4:S-MD5, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'X-Force IRIS SHA256 : 528714aaaa4a083e72599c32c18aa146db503eee80da236b20aea11aa43bdf62 .' [/INST] [X-Force:O, IRIS:O, SHA256:S-ENCR, ::O, 528714aaaa4a083e72599c32c18aa146db503eee80da236b20aea11aa43bdf62:S-SHA1, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'X-Force IRIS Hosting URL : http://mol.com-ho.me/cv_itworx.doc .' [/INST] [X-Force:O, IRIS:O, Hosting:O, URL:O, ::O, http://mol.com-ho.me/cv_itworx.doc:S-URL, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 researchers examined the domain that hosted the first malicious file , mol.com-ho.me .' [/INST] [Our:O, researchers:O, examined:O, the:O, domain:O, that:O, hosted:O, the:O, first:O, malicious:O, file:O, ,:O, mol.com-ho.me:S-DOM, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Per the domain ’s WHOIS record , an anonymized registrant registered com-ho.me in October 2016 and used it to serve malicious documents with similar macro activation features .' [/INST] [Per:O, the:O, domain:O, ’s:O, WHOIS:S-PROT, record:O, ,:O, an:O, anonymized:O, registrant:O, registered:O, com-ho.me:S-DOM, in:O, October:B-TIME, 2016:E-TIME, and:O, used:O, it:O, to:O, serve:O, malicious:O, documents:O, with:O, similar:O, macro:O, activation:O, features:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 following list of documents included :' [/INST] [The:O, following:O, list:O, of:O, documents: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: 'cv.doc : f4d18316e367a80e1005f38445421b1f . cv_itworx.doc : 45b0e5a457222455384713905f886bd4 . cv_mci.doc : f4d18316e367a80e1005f38445421b1f . discount_voucher_codes.xlsm : 19cea065aa033f5bcfa94a583ae59c08 .' [/INST] [cv.doc:S-FILE, ::O, f4d18316e367a80e1005f38445421b1f:S-MD5, .:O, cv_itworx.doc:S-FILE, ::O, 45b0e5a457222455384713905f886bd4:S-MD5, .:O, cv_mci.doc:S-FILE, ::O, f4d18316e367a80e1005f38445421b1f:S-MD5, .:O, discount_voucher_codes.xlsm:S-FILE, ::O, 19cea065aa033f5bcfa94a583ae59c08:S-MD5, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Health_insurance_plan.doc : ecfc0275c7a73a9c7775130ebca45b74 .' [/INST] [Health_insurance_plan.doc:S-FILE, ::O, ecfc0275c7a73a9c7775130ebca45b74:S-MD5, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Health_insurance_registration.doc : 1b5e33e5a244d2d67d7a09c4ccf16e56 . job_titles.doc : fa72c068361c05da65bf2117db76aaa8 . job_titles_itworx.doc : 43fad2d62bc23ffdc6d301571135222c . job_titles_mci.doc : ce25f1597836c28cf415394fb350ae93 .' [/INST] [Health_insurance_registration.doc:S-FILE, ::O, 1b5e33e5a244d2d67d7a09c4ccf16e56:S-MD5, .:O, job_titles.doc:S-FILE, ::O, fa72c068361c05da65bf2117db76aaa8:S-MD5, .:O, job_titles_itworx.doc:S-FILE, ::O, 43fad2d62bc23ffdc6d301571135222c:S-MD5, .:O, job_titles_mci.doc:S-FILE, ::O, ce25f1597836c28cf415394fb350ae93:S-MD5, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Password_Policy.xlsm : 03ea9457bf71d51d8109e737158be888 .' [/INST] [Password_Policy.xlsm:S-FILE, ::O, 03ea9457bf71d51d8109e737158be888:S-MD5, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 files were most likely delivered via spear phishing emails to lure employees into unwittingly launching the malicious payload .' [/INST] [These:O, files:O, were:O, most:O, likely:O, delivered:O, via:O, spear:B-ACT, phishing:E-ACT, emails:S-TOOL, to:O, lure:O, employees:O, into:O, unwittingly:O, launching:O, the:O, malicious:O, payload:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'A closer review of the file names revealed β€œ IT Worx ” and β€œ MCI ” .' [/INST] [A:O, closer:O, review:O, of:O, the:O, file:O, names:O, revealed:O, β€œ:O, IT:B-SECTEAM, Worx:E-SECTEAM, ”:O, and:O, β€œ:O, MCI:S-IDTY, ”:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 search of the name IT Worx brings up a global software professional services organization headquartered in Egypt .' [/INST] [A:O, search:O, of:O, the:O, name:O, IT:B-SECTEAM, Worx:E-SECTEAM, brings:O, up:O, a:O, global:B-SECTEAM, software:I-SECTEAM, professional:I-SECTEAM, services:I-SECTEAM, organization:E-SECTEAM, headquartered:O, in:O, Egypt: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: 'MCI is Saudi Arabia ’s Ministry of Commerce and Investment .' [/INST] [MCI:S-IDTY, is:O, Saudi:B-IDTY, Arabia:I-IDTY, ’s:I-IDTY, Ministry:I-IDTY, of:I-IDTY, Commerce:I-IDTY, and:I-IDTY, Investment:E-IDTY, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 possible these names were used in spear phishing emails because they would seem benign to Saudi-based employees and lure them to open the attachment .' [/INST] [It:O, is:O, possible:O, these:O, names:O, were:O, used:O, in:O, spear:B-ACT, phishing:E-ACT, emails:S-TOOL, because:O, they:O, would:O, seem:O, benign:O, to:O, Saudi-based:O, employees:O, and:O, lure:O, them:O, to:O, open:O, the:O, attachment:O, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'X-Force IRIS researchers further identified that the threat actor behind the malicious documents served many of them using a URL-shortening scheme in the following pattern : briefl.ink/{a-z0-9}[5] .' [/INST] [X-Force:B-SECTEAM, IRIS:E-SECTEAM, researchers:O, further:O, identified:O, that:O, the:O, threat:O, actor:O, behind:O, the:O, malicious:O, documents:O, served:O, many:O, of:O, them:O, using:O, a:O, URL-shortening:O, scheme:O, in:O, the:O, following:O, pattern:O, ::O, briefl.ink/{a-z0-9}[5]:S-URL, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'File Detail : Info File name : job_titles_itworx.doc .' [/INST] [File:O, Detail:O, ::O, Info:O, File:O, name:O, ::O, job_titles_itworx.doc: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: 'MD5 : 43fad2d62bc23ffdc6d301571135222c .' [/INST] [MD5:S-ENCR, ::O, 43fad2d62bc23ffdc6d301571135222c:S-MD5, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'SHA256 : e5b643cb6ec30d0d0b458e3f2800609f260a5f15c4ac66faf4ebf384f7976df6 .' [/INST] [SHA256:S-ENCR, ::O, e5b643cb6ec30d0d0b458e3f2800609f260a5f15c4ac66faf4ebf384f7976df6:S-SHA1, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Hosting URL : http://briefl.ink/qhtma .' [/INST] [Hosting:O, URL:O, ::O, http://briefl.ink/qhtma:S-URL, .:O] </s>
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Passive DNS results on a communications domain associated with the Shamoon attack revealed related network infrastructure , identifying additional domains used by the threat actors .' [/INST] [Passive:O, DNS:S-PROT, results:O, on:O, a:O, communications:O, domain:O, associated:O, with:O, the:O, Shamoon:S-MAL, attack:O, revealed:O, related:O, network:O, infrastructure:O, ,:O, identifying:O, additional:O, domains:O, used:O, by:O, the:O, threat:O, actors:O, .:O] </s>