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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: 'Report_URL : https://unit42.paloaltonetworks.com/unit42-sofacy-attacks-multiple-government-entities/' [/INST] [Report_URL:O, ::O, https://unit42.paloaltonetworks.com/unit42-sofacy-attacks-multiple-government-entities/:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 ( AKA APT28 , Fancy Bear , STRONTIUM , Sednit , Tsar Team , Pawn Storm ) is a well-known adversary that remains highly active in the new calendar year of 2018 .' [/INST] [The:O, Sofacy:S-APT, group:O, (:O, AKA:O, APT28:S-APT, ,:O, Fancy:B-APT, Bear:E-APT, ,:O, STRONTIUM:S-APT, ,:O, Sednit:S-APT, ,:O, Tsar:B-APT, Team:E-APT, ,:O, Pawn:B-APT, Storm:E-APT, ):O, is:O, a:O, well-known:O, adversary:O, that:O, remains:O, highly:O, active:O, in:O, the:O, new:O, calendar:O, year:O, of:O, 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: 'Unit 42 actively monitors this group due to their persistent nature globally across all industry verticals .' [/INST] [Unit:B-SECTEAM, 42:E-SECTEAM, actively:O, monitors:O, this:O, group:O, due:O, to:O, their:O, persistent:O, nature:O, globally:O, across:O, all:O, industry:O, verticals:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 discovered a campaign launched at various Ministries of Foreign Affairs around the world .' [/INST] [Recently:O, ,:O, we:O, discovered:O, a:O, campaign:O, launched:O, at:O, various:O, Ministries:B-IDTY, of:I-IDTY, Foreign:I-IDTY, Affairs:E-IDTY, around:O, the:O, world:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Interestingly , there appear to be two parallel efforts within the campaign , with each effort using a completely different toolset for the attacks .' [/INST] [Interestingly:O, ,:O, there:O, appear:O, to:O, be:O, two:O, parallel:O, efforts:O, within:O, the:O, campaign:O, ,:O, with:O, each:O, effort:O, using:O, a:O, completely:O, different:O, toolset:O, for:O, the: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 this blog , we will discuss one of the efforts which leveraged tools that have been known to be associated with the Sofacy group .' [/INST] [In:O, this:O, blog:O, ,:O, we:O, will:O, discuss:O, one:O, of:O, the:O, efforts:O, which:O, leveraged:O, tools:O, that:O, have:O, been:O, known:O, to:O, be:O, associated:O, with: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: 'At the beginning of February 2018 , we discovered an attack targeting two government institutions related to foreign affairs .' [/INST] [At:O, the:O, beginning:O, of:O, February:B-TIME, 2018:E-TIME, ,:O, we:O, discovered:O, an:O, attack:O, targeting:O, two:O, government:O, institutions:O, related:O, to: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: 'These entities are not regionally congruent , and the only shared victimology involves their organizational functions .' [/INST] [These:O, entities:O, are:O, not:O, regionally:O, congruent:O, ,:O, and:O, the:O, only:O, shared:O, victimology:O, involves:O, their:O, organizational:O, functions:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Specifically , one organization is geographically located in Europe and the other in North America .' [/INST] [Specifically:O, ,:O, one:O, organization:O, is:O, geographically:O, located:O, in:O, Europe:S-LOC, and:O, the:O, other:O, in:O, North:B-LOC, America: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: 'The initial attack vector leveraged a phishing email , using the subject line of Upcoming Defense events February 2018 and a sender address claiming to be from Jane ’s 360 defense events events@ihsmarkit.com .' [/INST] [The:O, initial:O, attack:O, vector:O, leveraged:O, a:O, phishing:B-ACT, email:E-ACT, ,:O, using:O, the:O, subject:O, line:O, of:O, Upcoming:B-SECTEAM, Defense:E-SECTEAM, events:O, February:B-TIME, 2018:E-TIME, and:O, a:O, sender:O, address:O, claiming:O, to:O, be:O, from:O, Jane:O, ’s:O, 360:S-SECTEAM, defense:O, events:O, events@ihsmarkit.com:S-EMAIL, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Jane ’s by IHSMarkit is a well-known supplier of information and analysis often times associated with the defense and government sector .' [/INST] [Jane:O, ’s:O, by:O, IHSMarkit:S-IDTY, is:O, a:O, well-known:O, supplier:O, of:O, information:O, and:O, analysis:O, often:O, times:O, associated:O, with:O, the:O, defense:O, and:O, government:O, sector:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Analysis of the email header data showed that the sender address was spoofed and did not originate from IHSMarkit at all .' [/INST] [Analysis:O, of:O, the:O, email:S-TOOL, header:O, data:O, showed:O, that:O, the:O, sender:O, address:O, was:O, spoofed:O, and:O, did:O, not:O, originate:O, from:O, IHSMarkit:S-IDTY, at:O, all:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The lure text in the phishing email claims the attachment is a calendar of events relevant to the targeted organizations and contained specific instructions regarding the actions the victim would have to take if they had “ trouble viewing the document ” .' [/INST] [The:O, lure:O, text:O, in:O, the:O, phishing:B-ACT, email:E-ACT, claims:O, the:O, attachment:O, is:O, a:O, calendar:O, of:O, events:O, relevant:O, to:O, the:O, targeted:O, organizations:O, and:O, contained:O, specific:O, instructions:O, regarding:O, the:O, actions:O, the:O, victim:O, would:O, have:O, to:O, take:O, if:O, they:O, had:O, “:O, trouble:O, viewing:O, the:O, document: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: 'The attachment itself is an Microsoft Excel XLS document that contains malicious macro script .' [/INST] [The:O, attachment:O, itself:O, is:O, an:O, Microsoft:S-IDTY, Excel:S-TOOL, XLS:S-TOOL, document:O, that:O, contains:O, malicious:O, macro:S-TOOL, script:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 presents itself as a standard macro document but has all of its text hidden until the victim enables macros .' [/INST] [The:O, document:O, presents:O, itself:O, as:O, a:O, standard:O, macro:S-TOOL, document:O, but:O, has:O, all:O, of:O, its:O, text:O, hidden:O, until:O, the:O, victim:O, enables:O, macros: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: 'Notably , all of the content text is accessible to the victim even before macros are enabled .' [/INST] [Notably:O, ,:O, all:O, of:O, the:O, content:O, text:O, is:O, accessible:O, to:O, the:O, victim:O, even:O, before:O, macros:S-TOOL, are:O, enabled:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , a white font color is applied to the text to make it appear that the victim must enable macros to access the content .' [/INST] [However:O, ,:O, a:O, white:O, font:O, color:O, is:O, applied:O, to:O, the:O, text:O, to:O, make:O, it:O, appear:O, that:O, the:O, victim:O, must:O, enable:O, macros:O, to:O, access:O, the:O, content:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 code above changes the font color to black within the specified cell range and presents the content to the user .' [/INST] [The:O, code:O, above:O, changes:O, the:O, font:O, color:O, to:O, black:O, within:O, the:O, specified:O, cell:O, range:O, and:O, presents:O, the:O, content:O, to:O, the:O, user:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'On initial inspection , the content appears to be the expected legitimate content , however , closer examination of the document shows several abnormal artifacts that would not exist in a legitimate document .' [/INST] [On:O, initial:O, inspection:O, ,:O, the:O, content:O, appears:O, to:O, be:O, the:O, expected:O, legitimate:O, content:O, ,:O, however:O, ,:O, closer:O, examination:O, of:O, the:O, document:O, shows:O, several:O, abnormal:O, artifacts:O, that:O, would:O, not:O, exist:O, in:O, a:O, legitimate: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: 'Figure 2 below shows how the delivery document initially looks and the transformation the content undergoes as the macro runs .' [/INST] [Figure:O, 2:O, below:O, shows:O, how:O, the:O, delivery:O, document:O, initially:O, looks:O, and:O, the:O, transformation:O, the:O, content:O, undergoes:O, as:O, the:O, macro:S-TOOL, runs:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 mentioned in a recent ISC diary entry , the macro gets the contents of cells in column 170 in rows 2227 to 2248 to obtain the base64 encoded payload .' [/INST] [As:O, mentioned:O, in:O, a:O, recent:O, ISC:S-TOOL, diary:O, entry:O, ,:O, the:O, macro:S-TOOL, gets:O, the:O, contents:O, of:O, cells:O, in:O, column:O, 170:O, in:O, rows:O, 2227:O, to:O, 2248:O, to:O, obtain:O, the:O, base64:S-ENCR, encoded:O, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The macro prepends the string —–BEGIN CERTIFICATE—– to the beginning of the base64 encoded payload and appends —–END CERTIFICATE—– to the end of the data .' [/INST] [The:O, macro:S-TOOL, prepends:O, the:O, string:O, —–BEGIN:O, CERTIFICATE—–:O, to:O, the:O, beginning:O, of:O, the:O, base64:S-ENCR, encoded:O, payload:O, and:O, appends:O, —–END:O, CERTIFICATE—–:O, to:O, the:O, end:O, of:O, the:O, data:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 macro then writes this data to a text file in the C:\Programdata folder using a random filename with the .txt extension .' [/INST] [The:O, macro:S-TOOL, then:O, writes:O, this:O, data:O, to:O, a:O, text:O, file:O, in:O, the:O, C:\Programdata:O, folder:O, using:O, a:O, random:O, filename:O, with:O, the:O, .txt:S-FILE, extension:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 macro then uses the command certutil -decode to decode the contents of this text file and outputs the decoded content to a randomly named file with a .exe extension in the C:\Programdata folder .' [/INST] [The:O, macro:S-TOOL, then:O, uses:O, the:O, command:O, certutil:O, -decode:O, to:O, decode:O, the:O, contents:O, of:O, this:O, text:O, file:O, and:O, outputs:O, the:O, decoded:O, content:O, to:O, a:O, randomly:O, named:O, file:O, with:O, a:O, .exe:S-FILE, extension:O, in:O, the:O, C:\Programdata:O, folder:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 macro sleeps for two seconds and then executes the newly dropped executable .' [/INST] [The:O, macro:S-TOOL, sleeps:O, for:O, two:O, seconds:O, and:O, then:O, executes:O, the:O, newly:O, dropped:O, executable:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 newly dropped executable is a loader Trojan responsible for installing and running the payload of this attack .' [/INST] [The:O, newly:O, dropped:O, executable:O, is:O, a:O, loader:O, Trojan:S-VULNAME, responsible:O, for:O, installing:O, and:O, running:O, the:O, payload:O, of:O, this: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: 'We performed a more detailed analysis on this loader Trojan , which readers can view in this report ’s appendix .' [/INST] [We:O, performed:O, a:O, more:O, detailed:O, analysis:O, on:O, this:O, loader:O, Trojan:S-VULNAME, ,:O, which:O, readers:O, can:O, view:O, in:O, this:O, report:O, ’s:O, appendix:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Upon execution , the loader will decrypt the embedded payload ( DLL ) using a custom algorithm , decompress it and save it to the following file : %LOCALAPPDATA%\cdnver.dll .' [/INST] [Upon:O, execution:O, ,:O, the:O, loader:O, will:O, decrypt:O, the:O, embedded:O, payload:O, (:O, DLL:S-TOOL, ):O, using:O, a:O, custom:O, algorithm:O, ,:O, decompress:O, it:O, and:O, save:O, it:O, to:O, the:O, following:O, file:O, ::O, %LOCALAPPDATA%\cdnver.dll: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: 'The loader will then create the batch file %LOCALAPPDATA%\cdnver.bat , which it will write the following :' [/INST] [The:O, loader:O, will:O, then:O, create:O, the:O, batch:O, file:O, %LOCALAPPDATA%\cdnver.bat:S-FILE, ,:O, which:O, it:O, will:O, write:O, the:O, following:O, ::O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'start rundll32.exe “ C:\Users\user\AppData\Local\cdnver.dll ” .' [/INST] [start:O, rundll32.exe:S-FILE, “:O, C:\Users\user\AppData\Local\cdnver.dll:S-FILE, ”:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 loader Trojan uses this batch file to run the embedded DLL payload .' [/INST] [The:O, loader:O, Trojan:S-VULNAME, uses:O, this:O, batch:O, file:O, to:O, run:O, the:O, embedded:O, DLL:S-TOOL, 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: 'For persistence , the loader will write the path to this batch file to the following registry key .' [/INST] [For:O, persistence:O, ,:O, the:O, loader:O, will:O, write:O, the:O, path:O, to:O, this:O, batch:O, file:O, to:O, the:O, following:O, registry:O, key:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 cdnver.dll payload installed by the loader executable is a variant of the SofacyCarberp payload , which is used extensively by the Sofacy threat group .' [/INST] [The:O, cdnver.dll:S-FILE, payload:O, installed:O, by:O, the:O, loader:O, executable:O, is:O, a:O, variant:O, of:O, the:O, SofacyCarberp:S-MAL, payload:O, ,:O, which:O, is:O, used:O, extensively:O, by:O, the:O, Sofacy:S-APT, threat: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: 'Overall , SofacyCarberp does initial reconnaissance by gathering system information and sending it to the C2 server prior to downloading additional tools to the system .' [/INST] [Overall:O, ,:O, SofacyCarberp:S-MAL, does:O, initial:O, reconnaissance:O, by:O, gathering:O, system:O, information:O, and:O, sending:O, it:O, to:O, the:O, C2:S-TOOL, server:O, prior:O, to:O, downloading:O, additional:O, tools:O, to:O, the:O, system:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This variant of SofacyCarberp was configured to use the following domain as its C2 server : cdnverify.net .' [/INST] [This:O, variant:O, of:O, SofacyCarberp:S-MAL, was:O, configured:O, to:O, use:O, the:O, following:O, domain:O, as:O, its:O, C2:S-TOOL, server:O, ::O, cdnverify.net: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 loader and the SofacyCarberp sample delivered in this attack is similar to samples we have analyzed in the past but contains marked differences .' [/INST] [The:O, loader:O, and:O, the:O, SofacyCarberp:S-MAL, sample:O, delivered:O, in:O, this:O, attack:O, is:O, similar:O, to:O, samples:O, we:O, have:O, analyzed:O, in:O, the:O, past:O, but:O, contains:O, marked:O, differences:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 differences include a new hashing algorithm to resolve API functions and to find running browser processes for injection , as well as changes to the C2 communication mechanisms .' [/INST] [These:O, differences:O, include:O, a:O, new:O, hashing:O, algorithm:O, to:O, resolve:O, API:S-TOOL, functions:O, and:O, to:O, find:O, running:O, browser:O, processes:O, for:O, injection:O, ,:O, as:O, well:O, as:O, changes:O, to:O, the:O, C2:S-TOOL, communication:O, mechanisms:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'It appears that Sofacy may have used an open-source tool called Luckystrike to generate the delivery document and/or the macro used in this attack .' [/INST] [It:O, appears:O, that:O, Sofacy:S-APT, may:O, have:O, used:O, an:O, open-source:O, tool:O, called:O, Luckystrike:S-TOOL, to:O, generate:O, the:O, delivery:O, document:O, and/or:O, the:O, macro:S-TOOL, used:O, in:O, this: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: 'Luckystrike , which was presented at DerbyCon 6 in September 2016 , is a Microsoft PowerShell based tool that generates malicious delivery documents by allowing a user to add a macro to an Excel or Word document to execute an embedded payload .' [/INST] [Luckystrike:S-TOOL, ,:O, which:O, was:O, presented:O, at:O, DerbyCon:S-SECTEAM, 6:O, in:O, September:B-TIME, 2016:E-TIME, ,:O, is:O, a:O, Microsoft:S-IDTY, PowerShell:S-TOOL, based:O, tool:O, that:O, generates:O, malicious:O, delivery:O, documents:O, by:O, allowing:O, a:O, user:O, to:O, add:O, a:O, macro:S-TOOL, to:O, an:O, Excel:S-TOOL, or:O, Word:S-TOOL, document:O, to:O, execute:O, an:O, embedded: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: 'We believe Sofacy used this tool , as the macro within their delivery document closely resembles the macros found within Luckystrike .' [/INST] [We:O, believe:O, Sofacy:S-APT, used:O, this:O, tool:O, ,:O, as:O, the:O, macro:S-TOOL, within:O, their:O, delivery:O, document:O, closely:O, resembles:O, the:O, macros:O, found:O, within:O, Luckystrike: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: 'To confirm our suspicions , we generated a malicious Excel file with Luckystrike and compared its macro to the macro found within Sofacy ’s delivery document .' [/INST] [To:O, confirm:O, our:O, suspicions:O, ,:O, we:O, generated:O, a:O, malicious:O, Excel:S-TOOL, file:O, with:O, Luckystrike:S-TOOL, and:O, compared:O, its:O, macro:S-TOOL, to:O, the:O, macro:S-TOOL, found:O, within:O, Sofacy:S-APT, ’s:O, delivery:O, document:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We found that there was only one difference between the macros besides the random function name and random cell values that the Luckystrike tool generates for each created payload .' [/INST] [We:O, found:O, that:O, there:O, was:O, only:O, one:O, difference:O, between:O, the:O, macros:O, besides:O, the:O, random:O, function:O, name:O, and:O, random:O, cell:O, values:O, that:O, the:O, Luckystrike:S-TOOL, tool:O, generates:O, for:O, each:O, created:O, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The one non-random string difference was the path to the “ .txt ” and “ .exe ” files within the command “ certutil -decode ” , as the Sofacy document used “ C:\Programdata\ ” for the path whereas the Luckystrike document used the path stored in the Application.UserLibraryPath environment variable .' [/INST] [The:O, one:O, non-random:O, string:O, difference:O, was:O, the:O, path:O, to:O, the:O, “:O, .txt:S-FILE, ”:O, and:O, “:O, .exe:S-FILE, ”:O, files:O, within:O, the:O, command:O, “:O, certutil:O, -decode:O, ”:O, ,:O, as:O, the:O, Sofacy:S-APT, document:O, used:O, “:O, C:\Programdata\:O, ”:O, for:O, the:O, path:O, whereas:O, the:O, Luckystrike:S-TOOL, document:O, used:O, the:O, path:O, stored:O, in:O, the:O, Application.UserLibraryPath:S-FILE, environment:O, variable:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Figure 3 below shows a diff with the LuckyStrike macro on the left and Sofacy macro on the right , where everything except the file path and randomly generated values in the macro are exactly the same , including the obfuscation attempts that use concatenation to build strings .' [/INST] [Figure:O, 3:O, below:O, shows:O, a:O, diff:O, with:O, the:O, LuckyStrike:S-TOOL, macro:S-TOOL, on:O, the:O, left:O, and:O, Sofacy:S-APT, macro:S-TOOL, on:O, the:O, right:O, ,:O, where:O, everything:O, except:O, the:O, file:O, path:O, and:O, randomly:O, generated:O, values:O, in:O, the:O, macro:S-TOOL, are:O, exactly:O, the:O, same:O, ,:O, including:O, the:O, obfuscation:O, attempts:O, that:O, use:O, concatenation:O, to:O, build:O, strings:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'With much of our research , our initial direction and discovery of emerging threats is generally some combination of previously observed behavioral rulesets or relationships .' [/INST] [With:O, much:O, of:O, our:O, research:O, ,:O, our:O, initial:O, direction:O, and:O, discovery:O, of:O, emerging:O, threats:O, is:O, generally:O, some:O, combination:O, of:O, previously:O, observed:O, behavioral:O, rulesets:O, or:O, relationships:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , we had observed a strange pattern emerging from the Sofacy group over the past year within their command and control infrastructure .' [/INST] [In:O, this:O, case:O, ,:O, we:O, had:O, observed:O, a:O, strange:O, pattern:O, emerging:O, from:O, the:O, Sofacy:S-APT, group:O, over:O, the:O, past:O, year:O, within:O, their:O, command:B-TOOL, and:I-TOOL, control:E-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: 'Patterning such as reuse of WHOIS artifacts , IP reuse , or even domain name themes are common and regularly used to group attacks to specific campaigns .' [/INST] [Patterning:O, such:O, as:O, reuse:O, of:O, WHOIS:S-TOOL, artifacts:O, ,:O, IP:O, reuse:O, ,:O, or:O, even:O, domain:O, name:O, themes:O, are:O, common:O, and:O, regularly:O, used:O, to:O, group:O, attacks:O, to:O, specific:O, campaigns:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , we had observed the Sofacy group registering new domains , then placing a default landing page which they then used repeatedly over the course of the year .' [/INST] [In:O, this:O, case:O, ,:O, we:O, had:O, observed:O, the:O, Sofacy:S-APT, group:O, registering:O, new:O, domains:O, ,:O, then:O, placing:O, a:O, default:O, landing:O, page:O, which:O, they:O, then:O, used:O, repeatedly:O, over:O, the:O, course:O, of:O, the:O, year:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'No other parts of the C2 infrastructure amongst these domains contained any overlapping artifacts .' [/INST] [No:O, other:O, parts:O, of:O, the:O, C2:S-TOOL, infrastructure:O, amongst:O, these:O, domains:O, contained:O, any:O, overlapping:O, artifacts:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Instead , the actual content within the body of the websites was an exact match in each instance .' [/INST] [Instead:O, ,:O, the:O, actual:O, content:O, within:O, the:O, body:O, of:O, the:O, websites:O, was:O, an:O, exact:O, match:O, in:O, each:O, instance:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Specifically , the strings 866-593-54352 ( notice it is one digit too long ) , 403-965-2341 , or the address 522 Clematis .' [/INST] [Specifically:O, ,:O, the:O, strings:O, 866-593-54352:O, (:O, notice:O, it:O, is:O, one:O, digit:O, too:O, long:O, ):O, ,:O, 403-965-2341:O, ,:O, or:O, the:O, address:O, 522:O, Clematis:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Suite 3000 was repeatedly found in each instance .' [/INST] [Suite:O, 3000:O, was:O, repeatedly:O, found:O, in:O, each:O, instance:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'ThreatConnect had made the same observation regarding this patterning in September 2017 .' [/INST] [ThreatConnect:S-TOOL, had:O, made:O, the:O, same:O, observation:O, regarding:O, this:O, patterning:O, in:O, September: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: 'Hotfixmsupload.com is particularly interesting as it has been identified as a Sofacy C2 domain repeatedly , and was also brought forth by Microsoft in a legal complaint against STRONTIUM ( Sofacy ) as documented here .' [/INST] [Hotfixmsupload.com:S-DOM, is:O, particularly:O, interesting:O, as:O, it:O, has:O, been:O, identified:O, as:O, a:O, Sofacy:S-APT, C2:S-TOOL, domain:O, repeatedly:O, ,:O, and:O, was:O, also:O, brought:O, forth:O, by:O, Microsoft:S-IDTY, in:O, a:O, legal:O, complaint:O, against:O, STRONTIUM:S-APT, (:O, Sofacy:S-APT, ):O, as:O, documented: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: 'Leveraging this intelligence allowed us to begin predicting potential C2 domains that would eventually be used by the Sofacy group .' [/INST] [Leveraging:O, this:O, intelligence:O, allowed:O, us:O, to:O, begin:O, predicting:O, potential:O, C2:S-TOOL, domains:O, that:O, would:O, eventually:O, be: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: 'In this scenario , the domain cdnverify.net was registered on January 30 , 2018 and just two days later , an attack was launched using this domain as a C2 .' [/INST] [In:O, this:O, scenario:O, ,:O, the:O, domain:O, cdnverify.net:O, was:O, registered:O, on:O, January:B-TIME, 30:I-TIME, ,:I-TIME, 2018:E-TIME, and:O, just:O, two:O, days:O, later:O, ,:O, an:O, attack:O, was:O, launched:O, using:O, this:O, domain:O, as:O, a:O, C2: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 should no longer be an unfamiliar threat at this stage .' [/INST] [The:O, Sofacy:S-APT, group:O, should:O, no:O, longer:O, be:O, an:O, unfamiliar:O, threat:O, at:O, this:O, stage:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 have been well documented and well researched with much of their attack methodologies exposed .' [/INST] [They:O, have:O, been:O, well:O, documented:O, and:O, well:O, researched:O, with:O, much:O, of:O, their:O, attack:O, methodologies:O, exposed:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 continue to be persistent in their attack campaigns and continue to use similar tooling as in the past .' [/INST] [They:O, continue:O, to:O, be:O, persistent:O, in:O, their:O, attack:O, campaigns:O, and:O, continue:O, to:O, use:O, similar:O, tooling:O, as:O, in:O, the:O, past:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 leads us to believe that their attack attempts are likely still succeeding , even with the wealth of threat intelligence available in the public domain .' [/INST] [This:O, leads:O, us:O, to:O, believe:O, that:O, their:O, attack:O, attempts:O, are:O, likely:O, still:O, succeeding:O, ,:O, even:O, with:O, the:O, wealth:O, of:O, threat:O, intelligence:O, available:O, in:O, the:O, public:O, 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: 'Application of the data remains challenging , and so to continue our initiative of establishing playbooks for adversary groups , we have added this attack campaign as the next playbook in our dataset .' [/INST] [Application:O, of:O, the:O, data:O, remains:O, challenging:O, ,:O, and:O, so:O, to:O, continue:O, our:O, initiative:O, of:O, establishing:O, playbooks:O, for:O, adversary:O, groups:O, ,:O, we:O, have:O, added:O, this:O, attack:O, campaign:O, as:O, the:O, next:O, playbook:O, in:O, our:O, dataset:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Palo Alto Networks customers are protected from this threat by :' [/INST] [Palo:B-SECTEAM, Alto:I-SECTEAM, Networks:E-SECTEAM, customers:O, are:O, protected:O, from:O, this:O, threat:O, by:O, ::O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'WildFire detects all SofacyCarberp payloads with malicious verdicts .' [/INST] [WildFire:S-SECTEAM, detects:O, all:O, SofacyCarberp:S-MAL, payloads:O, with:O, malicious:O, verdicts:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'AutoFocus customers can track these tools with the Sofacy , SofacyMacro and SofacyCarberp .' [/INST] [AutoFocus:S-SECTEAM, customers:O, can:O, track:O, these:O, tools:O, with:O, the:O, Sofacy:S-APT, ,:O, SofacyMacro:S-MAL, and:O, SofacyCarberp: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: 'Traps blocks the Sofacy delivery documents and the SofacyCarberp payload .' [/INST] [Traps:O, blocks:O, the:O, Sofacy:S-APT, delivery:O, documents:O, and:O, the:O, SofacyCarberp:S-MAL, 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: 'SHA256 : ff808d0a12676bfac88fd26f955154f8884f2bb7c534b9936510fd6296c543e8 SHA256 : 12e6642cf6413bdf5388bee663080fa299591b2ba023d069286f3be9647547c8 SHA256 : cb85072e6ca66a29cb0b73659a0fe5ba2456d9ba0b52e3a4c89e86549bc6e2c7 SHA256 : 23411bb30042c9357ac4928dc6fca6955390361e660fec7ac238bbdcc8b83701 Sofacy : Cdnverify.net Sofacy Filename : Upcoming_Events_February_2018.xls .' [/INST] [SHA256:S-ENCR, ::O, ff808d0a12676bfac88fd26f955154f8884f2bb7c534b9936510fd6296c543e8:S-SHA2, SHA256:S-ENCR, ::O, 12e6642cf6413bdf5388bee663080fa299591b2ba023d069286f3be9647547c8:S-SHA2, SHA256:S-ENCR, ::O, cb85072e6ca66a29cb0b73659a0fe5ba2456d9ba0b52e3a4c89e86549bc6e2c7:S-SHA2, SHA256:S-ENCR, ::O, 23411bb30042c9357ac4928dc6fca6955390361e660fec7ac238bbdcc8b83701:S-SHA2, Sofacy:S-APT, ::O, Cdnverify.net:S-DOM, Sofacy:S-APT, Filename:O, ::O, Upcoming_Events_February_2018.xls: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: 'APT28 Targets Hospitality Sector , Presents Threat to Travelers .' [/INST] [APT28:S-APT, Targets:O, Hospitality:O, Sector:O, ,:O, Presents:O, Threat:O, to:O, Travelers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Release_Time : 2017-08-11 Report_URL : https://www.fireeye.com/blog/threat-research/2017/08/apt28-targets-hospitality-sector.html' [/INST] [Release_Time:O, ::O, 2017-08-11:O, Report_URL:O, ::O, https://www.fireeye.com/blog/threat-research/2017/08/apt28-targets-hospitality-sector.html:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye has moderate confidence that a campaign targeting the hospitality sector is attributed to Russian actor APT28 .' [/INST] [FireEye:S-SECTEAM, has:O, moderate:O, confidence:O, that:O, a:O, campaign:S-ACT, targeting:O, the:O, hospitality:O, sector:O, is:O, attributed:O, to:O, Russian:O, actor:O, APT28:S-APT, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We believe this activity , which dates back to at least July 2017 , was intended to target travelers to hotels throughout Europe and the Middle East .' [/INST] [We:O, believe:O, this:O, activity:O, ,:O, which:O, dates:O, back:O, to:O, at:O, least:O, July:B-TIME, 2017:E-TIME, ,:O, was:O, intended:O, to:O, target:O, travelers:O, to:O, hotels:O, throughout:O, Europe:S-LOC, and:O, the:O, Middle:B-LOC, East: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: 'The actor has used several notable techniques in these incidents such as sniffing passwords from Wi-Fi traffic , poisoning the NetBIOS Name Service , and spreading laterally via the EternalBlue exploit .' [/INST] [The:O, actor:O, has:O, used:O, several:O, notable:O, techniques:O, in:O, these:O, incidents:O, such:O, as:O, sniffing:B-TOOL, passwords:E-TOOL, from:O, Wi-Fi:B-TOOL, traffic:E-TOOL, ,:O, poisoning:O, the:O, NetBIOS:B-TOOL, Name:I-TOOL, Service:E-TOOL, ,:O, and:O, spreading:O, laterally:O, via:O, the:O, EternalBlue:S-VULNAME, exploit:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye has uncovered a malicious document sent in spear phishing emails to multiple companies in the hospitality industry , including hotels in at least seven European countries and one Middle Eastern country in early July .' [/INST] [FireEye:S-SECTEAM, has:O, uncovered:O, a:O, malicious:O, document:O, sent:O, in:O, spear:B-ACT, phishing:I-ACT, emails:E-ACT, to:O, multiple:O, companies:O, in:O, the:O, hospitality:O, industry:O, ,:O, including:O, hotels:O, in:O, at:O, least:O, seven:O, European:O, countries:O, and:O, one:O, Middle:O, Eastern:O, country:O, in:O, early: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: 'Successful execution of the macro within the malicious document results in the installation of APT28 ’s signature GAMEFISH malware .' [/INST] [Successful:O, execution:O, of:O, the:O, macro:S-TOOL, within:O, the:O, malicious:O, document:O, results:O, in:O, the:O, installation:O, of:O, APT28:S-APT, ’s:O, signature:O, GAMEFISH: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: 'The malicious document – Hotel_Reservation_Form.doc ( MD5 : 9b10685b774a783eabfecdb6119a8aa3 ) , contains a macro that base64 decodes a dropper that then deploys APT28 ’s signature GAMEFISH malware ( MD5 : 1421419d1be31f1f9ea60e8ed87277db ) , which uses mvband.net and mvtband.net as command and control ( C2 ) domains .' [/INST] [The:O, malicious:O, document:O, –:O, Hotel_Reservation_Form.doc:S-FILE, (:O, MD5:S-ENCR, ::O, 9b10685b774a783eabfecdb6119a8aa3:S-MD5, ):O, ,:O, contains:O, a:O, macro:S-TOOL, that:O, base64:S-ENCR, decodes:O, a:O, dropper:O, that:O, then:O, deploys:O, APT28:S-APT, ’s:O, signature:O, GAMEFISH:S-MAL, malware:O, (:O, MD5:S-ENCR, ::O, 1421419d1be31f1f9ea60e8ed87277db:S-MD5, ):O, ,:O, which:O, uses:O, mvband.net:S-DOM, and:O, mvtband.net:S-DOM, as:O, command:B-TOOL, and:I-TOOL, control:E-TOOL, (:O, C2:S-TOOL, ):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: 'APT28 is using novel techniques involving the EternalBlue exploit and the open source tool Responder to spread laterally through networks and likely target travelers .' [/INST] [APT28:S-APT, is:O, using:O, novel:O, techniques:O, involving:O, the:O, EternalBlue:S-VULNAME, exploit:O, and:O, the:O, open:O, source:O, tool:O, Responder:S-TOOL, to:O, spread:O, laterally:O, through:O, networks:O, and:O, likely:O, target:O, travelers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once inside the network of a hospitality company , APT28 sought out machines that controlled both guest and internal Wi-Fi networks .' [/INST] [Once:O, inside:O, the:O, network:O, of:O, a:O, hospitality:O, company:O, ,:O, APT28:S-APT, sought:O, out:O, machines:O, that:O, controlled:O, both:O, guest:O, and:O, internal:O, Wi-Fi:B-TOOL, networks: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: 'No guest credentials were observed being stolen at the compromised hotels ; however , in a separate incident that occurred in Fall 2016 , APT28 gained initial access to a victim ’s network via credentials likely stolen from a hotel Wi-Fi network .' [/INST] [No:O, guest:O, credentials:O, were:O, observed:O, being:O, stolen:O, at:O, the:O, compromised:O, hotels:O, ;:O, however:O, ,:O, in:O, a:O, separate:O, incident:O, that:O, occurred:O, in:O, Fall:B-TIME, 2016:E-TIME, ,:O, APT28:S-APT, gained:O, initial:O, access:O, to:O, a:O, victim:O, ’s:O, network:O, via:O, credentials:O, likely:O, stolen:O, from:O, a:O, hotel:O, Wi-Fi:B-TOOL, network: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: 'Upon gaining access to the machines connected to corporate and guest Wi-Fi networks , APT28 deployed Responder .' [/INST] [Upon:O, gaining:O, access:O, to:O, the:O, machines:O, connected:O, to:O, corporate:O, and:O, guest:O, Wi-Fi:B-TOOL, networks:E-TOOL, ,:O, APT28:S-APT, deployed:O, Responder: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: 'Responder facilitates NetBIOS Name Service ( NBT-NS ) poisoning .' [/INST] [Responder:S-TOOL, facilitates:O, NetBIOS:B-TOOL, Name:I-TOOL, Service:E-TOOL, (:O, NBT-NS:S-TOOL, ):O, poisoning:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This technique listens for NBT-NS ( UDP ) broadcasts from victim computers attempting to connect to network resources .' [/INST] [This:O, technique:O, listens:O, for:O, NBT-NS:S-TOOL, (:O, UDP:S-PROT, ):O, broadcasts:O, from:O, victim:O, computers:O, attempting:O, to:O, connect:O, to:O, network:O, resources:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 received , Responder masquerades as the sought-out resource and causes the victim computer to send the username and hashed password to the attacker-controlled machine .' [/INST] [Once:O, received:O, ,:O, Responder:S-TOOL, masquerades:O, as:O, the:O, sought-out:O, resource:O, and:O, causes:O, the:O, victim:O, computer:O, to:O, send:O, the:O, username:O, and:O, hashed:O, password:O, to:O, the:O, attacker-controlled: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: 'APT28 used this technique to steal usernames and hashed passwords that allowed escalation of privileges in the victim network .' [/INST] [APT28:S-APT, used:O, this:O, technique:O, to:O, steal:O, usernames:O, and:O, hashed:O, passwords:O, that:O, allowed:O, escalation:O, of:O, privileges:O, in:O, the:O, victim: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: 'To spread through the hospitality company ’s network , APT28 used a version of the EternalBlue SMB exploit .' [/INST] [To:O, spread:O, through:O, the:O, hospitality:O, company:O, ’s:O, network:O, ,:O, APT28:S-APT, used:O, a:O, version:O, of:O, the:O, EternalBlue:S-VULNAME, SMB:S-PROT, exploit:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 was combined with the heavy use of py2exe to compile Python scripts .' [/INST] [This:O, was:O, combined:O, with:O, the:O, heavy:O, use:O, of:O, py2exe:S-TOOL, to:O, compile:O, Python:S-TOOL, scripts:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the first time we have seen APT28 incorporate this exploit into their intrusions .' [/INST] [This:O, is:O, the:O, first:O, time:O, we:O, have:O, seen:O, APT28:S-APT, incorporate:O, this:O, exploit:O, into:O, their:O, intrusions:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 2016 incident , the victim was compromised after connecting to a hotel Wi-Fi network .' [/INST] [In:O, the:O, 2016:S-TIME, incident:O, ,:O, the:O, victim:O, was:O, compromised:O, after:O, connecting:O, to:O, a:O, hotel:O, Wi-Fi:B-TOOL, network: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: 'Twelve hours after the victim initially connected to the publicly available Wi-Fi network , APT28 logged into the machine with stolen credentials .' [/INST] [Twelve:O, hours:O, after:O, the:O, victim:O, initially:O, connected:O, to:O, the:O, publicly:O, available:O, Wi-Fi:B-TOOL, network:E-TOOL, ,:O, APT28:S-APT, logged:O, into:O, the:O, machine:O, with:O, stolen:O, credentials:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 12 hours could have been used to crack a hashed password offline .' [/INST] [These:O, 12:O, hours:O, could:O, have:O, been:O, used:O, to:O, crack:O, a:O, hashed:O, password:O, offline:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'After successfully accessing the machine , the attacker deployed tools on the machine , spread laterally through the victim's network , and accessed the victim's OWA account .' [/INST] [After:O, successfully:O, accessing:O, the:O, machine:O, ,:O, the:O, attacker:O, deployed:O, tools:O, on:O, the:O, machine:O, ,:O, spread:O, laterally:O, through:O, the:O, victim's:O, network:O, ,:O, and:O, accessed:O, the:O, victim's:O, OWA:S-TOOL, account:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 login originated from a computer on the same subnet , indicating that the attacker machine was physically close to the victim and on the same Wi-Fi network .' [/INST] [The:O, login:O, originated:O, from:O, a:O, computer:O, on:O, the:O, same:O, subnet:O, ,:O, indicating:O, that:O, the:O, attacker:O, machine:O, was:O, physically:O, close:O, to:O, the:O, victim:O, and:O, on:O, the:O, same:O, Wi-Fi:B-TOOL, network: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: 'We cannot confirm how the initial credentials were stolen in the 2016 incident ; however , later in the intrusion , Responder was deployed .' [/INST] [We:O, cannot:O, confirm:O, how:O, the:O, initial:O, credentials:O, were:O, stolen:O, in:O, the:O, 2016:S-TIME, incident:O, ;:O, however:O, ,:O, later:O, in:O, the:O, intrusion:O, ,:O, Responder:S-TOOL, was:O, deployed:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 this tool allows an attacker to sniff passwords from network traffic , it could have been used on the hotel Wi-Fi network to obtain a user ’s credentials .' [/INST] [Since:O, this:O, tool:O, allows:O, an:O, attacker:O, to:O, sniff:O, passwords:O, from:O, network:B-TOOL, traffic:E-TOOL, ,:O, it:O, could:O, have:O, been:O, used:O, on:O, the:O, hotel:O, Wi-Fi:B-TOOL, network:E-TOOL, to:O, obtain:O, a:O, user:O, ’s:O, credentials:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Cyber espionage activity against the hospitality industry is typically focused on collecting information on or from hotel guests of interest rather than on the hotel industry itself , though actors may also collect information on the hotel as a means of facilitating operations .' [/INST] [Cyber:B-ACT, espionage:I-ACT, activity:E-ACT, against:O, the:O, hospitality:O, industry:O, is:O, typically:O, focused:O, on:O, collecting:O, information:O, on:O, or:O, from:O, hotel:O, guests:O, of:O, interest:O, rather:O, than:O, on:O, the:O, hotel:O, industry:O, itself:O, ,:O, though:O, actors:O, may:O, also:O, collect:O, information:O, on:O, the:O, hotel:O, as:O, a:O, means:O, of:O, facilitating: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: 'Business and government personnel who are traveling , especially in a foreign country , often rely on systems to conduct business other than those at their home office , and may be unfamiliar with threats posed while abroad .' [/INST] [Business:O, and:O, government:O, personnel:O, who:O, are:O, traveling:O, ,:O, especially:O, in:O, a:O, foreign:O, country:O, ,:O, often:O, rely:O, on:O, systems:O, to:O, conduct:O, business:O, other:O, than:O, those:O, at:O, their:O, home:O, office:O, ,:O, and:O, may:O, be:O, unfamiliar:O, with:O, threats:O, posed:O, while:O, abroad:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT28 isn’t the only group targeting travelers .' [/INST] [APT28:S-APT, isn’t:O, the:O, only:O, group:O, targeting:O, travelers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'South Korea nexus Fallout Team ( aka Darkhotel ) has used spoofed software updates on infected Wi-Fi networks in Asian hotels , and Duqu 2.0 malware has been found on the networks of European hotels used by participants in the Iranian nuclear negotiations .' [/INST] [South:B-LOC, Korea:E-LOC, nexus:O, Fallout:B-APT, Team:E-APT, (:O, aka:O, Darkhotel:S-APT, ):O, has:O, used:O, spoofed:O, software:O, updates:O, on:O, infected:O, Wi-Fi:B-TOOL, networks:E-TOOL, in:O, Asian:O, hotels:O, ,:O, and:O, Duqu:B-MAL, 2.0:E-MAL, malware:O, has:O, been:O, found:O, on:O, the:O, networks:O, of:O, European:O, hotels:O, used:O, by:O, participants:O, in:O, the:O, Iranian:O, nuclear:O, negotiations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , open sources have reported for several years that in Russia and China , high-profile hotel guests may expect their hotel rooms to be accessed and their laptops and other electronic devices accessed .' [/INST] [Additionally:O, ,:O, open:O, sources:O, have:O, reported:O, for:O, several:O, years:O, that:O, in:O, Russia:S-LOC, and:O, China:S-LOC, ,:O, high-profile:O, hotel:O, guests:O, may:O, expect:O, their:O, hotel:O, rooms:O, to:O, be:O, accessed:O, and:O, their:O, laptops:O, and:O, other:O, electronic:O, devices:O, accessed:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 incidents show a novel infection vector being used by APT28 .' [/INST] [These:O, incidents:O, show:O, a:O, novel:O, infection:O, vector:O, being:O, used:O, by:O, APT28:S-APT, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The group is leveraging less secure hotel Wi-Fi networks to steal credentials and a NetBIOS Name Service poisoning utility to escalate privileges .' [/INST] [The:O, group:O, is:O, leveraging:O, less:O, secure:O, hotel:O, Wi-Fi:B-TOOL, networks:E-TOOL, to:O, steal:O, credentials:O, and:O, a:O, NetBIOS:B-APT, Name:I-APT, Service:E-APT, poisoning:O, utility:O, to:O, escalate:O, privileges:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT28 ’s already wide-ranging capabilities and tactics are continuing to grow and refine as the group expands its infection vectors .' [/INST] [APT28:S-APT, ’s:O, already:O, wide-ranging:O, capabilities:O, and:O, tactics:O, are:O, continuing:O, to:O, grow:O, and:O, refine:O, as:O, the:O, group:O, expands:O, its:O, infection:O, vectors:O, .:O] </s> |