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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: 'The CONFUCIUS_B executable is disguised as a PowerPoint presentation , using a Right-To-Left-Override ( RTLO ) trick and a false icon .' [/INST] [The:O, CONFUCIUS_B:B-SamFile, executable:O, is:O, disguised:B-Features, as:I-Features, a:I-Features, PowerPoint:I-Features, presentation:I-Features, ,:O, using:B-Features, a:I-Features, Right-To-Left-Override:I-Features, (:O, RTLO:B-Tool, ):O, trick:O, and:O, a:O, false:B-Features, icon:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We also believe that both clusters of activity have links to attacks with likely Indian origins , the CONFUCIUS_A attacks are linked to the use of SNEEPY/BYEBYESHELL and the CONFUCIUS_B have a loose link to Hangover .' [/INST] [We:O, also:O, believe:O, that:O, both:O, clusters:O, of:O, activity:B-OffAct, have:O, links:O, to:O, attacks:B-OffAct, with:O, likely:O, Indian:O, origins:O, ,:O, the:O, CONFUCIUS_A:B-OffAct, attacks:I-OffAct, are:O, linked:O, to:O, the:O, use:O, of:O, SNEEPY/BYEBYESHELL:B-Tool, and:O, the:O, CONFUCIUS_B:B-SamFile, have:O, a:O, loose:O, link:O, to:O, Hangover:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The two malware families themselves are also very similar , and therefore we think that the shared technique is an indication of a single developer , or development company , behind both CONFUCIUS_A and CONFUCIUS_B .' [/INST] [The:O, two:O, malware:O, families:O, themselves:O, are:O, also:O, very:O, similar:O, ,:O, and:O, therefore:O, we:O, think:O, that:O, the:O, shared:O, technique:O, is:O, an:O, indication:O, of:O, a:O, single:O, developer:O, ,:O, or:O, development:B-Org, company:I-Org, ,:O, behind:O, both:O, CONFUCIUS_A:B-SamFile, and:O, CONFUCIUS_B:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Android version , for instance , can steal SMS messages , accounts , contacts , and files , as well as record audio .' [/INST] [The:O, Android:B-SamFile, version:I-SamFile, ,:O, for:O, instance:O, ,:O, can:O, steal:B-Features, SMS:I-Features, messages:I-Features, ,:O, accounts:B-Features, ,:O, contacts:B-Features, ,:O, and:O, files:B-Features, ,:O, as:O, well:O, as:O, record:B-Features, audio:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The documents that exploit CVE2017-11882 download another payload — an HTML Application ( HTA ) file toting a malicious Visual Basic ( VBS ) script — from the server , which is executed accordingly by the command-line tool mshta.exe .' [/INST] [The:O, documents:O, that:O, exploit:O, CVE2017-11882:B-Exp, download:O, another:O, payload:O, —:O, an:O, HTML:B-Tool, Application:I-Tool, (:O, HTA:B-SamFile, ):O, file:O, toting:O, a:O, malicious:O, Visual:O, Basic:O, (:O, VBS:O, ):O, script:O, —:O, from:O, the:O, server:O, ,:O, which:O, is:O, executed:O, accordingly:O, by:O, the:O, command-line:O, tool:O, mshta.exe:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'According to our statistics , as of the beginning of 2015 this botnet encompassed over 250 000 infected devices worldwide including infecting more than 100 financial institutions with 80% of them from the top 20 list .' [/INST] [According:O, to:O, our:O, statistics:O, ,:O, as:O, of:O, the:O, beginning:O, of:O, 2015:B-Time, this:O, botnet:B-SamFile, encompassed:I-SamFile, over:O, 250:O, 000:O, infected:O, devices:O, worldwide:O, including:O, infecting:O, more:O, than:O, 100:O, financial:B-Org, institutions:I-Org, with:O, 80%:O, of:O, them:O, from:O, the:O, top:O, 20:O, list:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 a bot was installed on a network that was of interest to the hacking group , this bot was then used to upload one of the remote access programs .' [/INST] [If:O, a:O, bot:B-SamFile, was:O, installed:O, on:O, a:O, network:O, that:O, was:O, of:O, interest:O, to:O, the:O, hacking:O, group:O, ,:O, this:O, bot:O, was:O, then:O, used:O, to:O, upload:B-Features, one:I-Features, of:I-Features, the:I-Features, remote:I-Features, access:I-Features, programs:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'At first look , it pretends to be a Java related application but after a quick analysis , it was obvious this was something more than just a simple Java file .' [/INST] [At:O, first:O, look:O, ,:O, it:O, pretends:O, to:O, be:O, a:O, Java:B-Tool, related:I-Tool, application:I-Tool, but:O, after:O, a:O, quick:O, analysis:O, ,:O, it:O, was:O, obvious:O, this:O, was:O, something:O, more:O, than:O, just:O, a:O, simple:O, Java:B-SamFile, file:I-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Contextually relevant emails are sent to specific targets with attached documents that are packed with exploit code and Trojan horse programmes designed to take advantage of vulnerabilities in software installed on the target 's computer .' [/INST] [Contextually:O, relevant:O, emails:B-Way, are:O, sent:O, to:O, specific:O, targets:O, with:O, attached:O, documents:B-SamFile, that:O, are:O, packed:O, with:O, exploit:O, code:O, and:O, Trojan:O, horse:O, programmes:O, designed:O, to:O, take:O, advantage:O, of:O, vulnerabilities:O, in:O, software:O, installed:O, on:O, the:O, target:O, 's:O, computer:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The authors of that report identify three primary tools used in the campaigns attributed to Hidden Lynx : Trojan.Naid , Backdoor.Moudoor , and Backdoor.Hikit .' [/INST] [The:O, authors:O, of:O, that:O, report:O, identify:O, three:O, primary:O, tools:O, used:O, in:O, the:O, campaigns:B-OffAct, attributed:O, to:O, Hidden:O, Lynx:O, ::O, Trojan.Naid:B-Tool, ,:O, Backdoor.Moudoor:B-SamFile, ,:O, and:O, Backdoor.Hikit:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The above network shows relationships between three tools used by Hidden Lynx during its VOHO campaign : Trojan.Naid , Backdoor.Moudoor , and Backdoor.Hikit .' [/INST] [The:O, above:O, network:O, shows:O, relationships:O, between:O, three:O, tools:O, used:O, by:O, Hidden:O, Lynx:O, during:O, its:O, VOHO:B-OffAct, campaign:I-OffAct, ::O, Trojan.Naid:B-Tool, ,:O, Backdoor.Moudoor:B-SamFile, ,:O, and:O, Backdoor.Hikit:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Symantec during 2012 linked the Elderwood Project to Operation Aurora ; Trojan.Naid and Backdoor.Moudoor were also used in Aurora , by the Elderwood Gang , and by Hidden Lynx .' [/INST] [Symantec:B-SecTeam, during:O, 2012:B-Time, linked:O, the:O, Elderwood:B-OffAct, Project:I-OffAct, to:O, Operation:B-OffAct, Aurora:I-OffAct, ;:O, Trojan.Naid:B-Tool, and:O, Backdoor.Moudoor:B-SamFile, were:O, also:O, used:O, in:O, Aurora:B-Tool, ,:O, by:O, the:O, Elderwood:B-HackOrg, Gang:I-HackOrg, ,:O, and:O, by:O, Hidden:B-HackOrg, Lynx:I-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'One e-mail carried a Microsoft PowerPoint file named , thanks.pps , ( VirusTotal ) , the other a Microsoft Word document named , request.docx , .' [/INST] [One:O, e-mail:B-Way, carried:O, a:O, Microsoft:B-SamFile, PowerPoint:I-SamFile, file:I-SamFile, named:O, ,:O, thanks.pps:B-SamFile, ,:O, (:O, VirusTotal:O, ):O, ,:O, the:O, other:O, a:O, Microsoft:B-SamFile, Word:I-SamFile, document:I-SamFile, named:O, ,:O, request.docx:B-SamFile, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Around the same time , WildFire also captured an e-mail containing a Word document ( , hello.docx , ) with an identical hash as the earlier Word document , this time sent to a U.S. Government recipient .' [/INST] [Around:O, the:O, same:O, time:O, ,:O, WildFire:B-SecTeam, also:O, captured:O, an:O, e-mail:B-Way, containing:O, a:O, Word:B-SamFile, document:I-SamFile, (:O, ,:O, hello.docx:B-SamFile, ,:O, ):O, with:O, an:O, identical:O, hash:O, as:O, the:O, earlier:O, Word:B-SamFile, document:I-SamFile, ,:O, this:O, time:O, sent:O, to:O, a:O, U.S.:B-Area, Government:I-Area, recipient:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 initially-observed , thanks.pps , example tricks the user into running the embedded file named ins8376.exe which loads a payload DLL named mpro324.dll .' [/INST] [The:O, initially-observed:O, ,:O, thanks.pps:B-SamFile, ,:O, example:O, tricks:O, the:O, user:O, into:O, running:O, the:O, embedded:O, file:O, named:O, ins8376.exe:B-SamFile, which:O, loads:O, a:O, payload:O, DLL:O, named:O, mpro324.dll:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this case , the file used the software name , Cyberlink , , and a description of , CLMediaLibrary Dynamic Link Library , and listing version 4.19.9.98 .' [/INST] [In:O, this:O, case:O, ,:O, the:O, file:O, used:O, the:O, software:O, name:O, ,:O, Cyberlink:B-SamFile, ,:O, ,:O, and:O, a:O, description:O, of:O, ,:O, CLMediaLibrary:O, Dynamic:O, Link:O, Library:O, ,:O, and:O, listing:O, version:O, 4.19.9.98:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 next stage library copies itself into the System32 directory of the Windows folder after the hardcoded file name — either KBDLV2.DLL or AUTO.DLL , depending on the malware sample .' [/INST] [This:O, next:O, stage:O, library:O, copies:O, itself:O, into:O, the:O, System32:O, directory:O, of:O, the:O, Windows:O, folder:O, after:O, the:O, hardcoded:O, file:O, name:O, —:O, either:O, KBDLV2.DLL:B-SamFile, or:O, AUTO.DLL:B-SamFile, ,:O, depending:O, on:O, the:O, malware:O, sample:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 BARIUM has established rapport , they spear-phish the victim using a variety of unsophisticated malware installation vectors , including malicious shortcut ( .lnk ) files with hidden payloads , compiled HTML help ( .chm ) files , or Microsoft Office documents containing macros or exploits .' [/INST] [Once:O, BARIUM:B-OffAct, has:O, established:O, rapport:O, ,:O, they:O, spear-phish:O, the:O, victim:O, using:O, a:O, variety:O, of:O, unsophisticated:B-Tool, malware:I-Tool, installation:O, vectors:O, ,:O, including:O, malicious:B-Tool, shortcut:I-Tool, (:O, .lnk:B-SamFile, ):O, files:O, with:O, hidden:O, payloads:O, ,:O, compiled:O, HTML:B-Tool, help:I-Tool, (:I-Tool, .chm:I-Tool, ):I-Tool, files:I-Tool, ,:O, or:O, Microsoft:B-Tool, Office:I-Tool, documents:I-Tool, containing:O, macros:O, or:O, exploits:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the case in two known intrusions in 2015 , where attackers named the implant DLL , ASPNET_FILTER.DLL , to disguise it as the DLL for the ASP.NET ISAPI Filter .' [/INST] [This:O, was:O, the:O, case:O, in:O, two:O, known:O, intrusions:O, in:O, 2015:B-Time, ,:O, where:O, attackers:O, named:O, the:O, implant:O, DLL:O, ,:O, ASPNET_FILTER.DLL:B-SamFile, ,:O, to:O, disguise:O, it:O, as:O, the:O, DLL:O, for:O, the:O, ASP.NET:B-SamFile, ISAPI:I-SamFile, Filter:I-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In early 2016 the Callisto Group began sending highly targeted spear phishing emails with malicious attachments that contained , as their final payload , the , Scout , malware tool from the HackingTeam RCS Galileo platform .' [/INST] [In:O, early:O, 2016:B-Time, the:O, Callisto:O, Group:O, began:O, sending:O, highly:O, targeted:O, spear:B-Way, phishing:I-Way, emails:I-Way, with:O, malicious:B-SamFile, attachments:I-SamFile, that:O, contained:O, ,:O, as:O, their:O, final:O, payload:O, ,:O, the:O, ,:O, Scout:B-Tool, ,:O, malware:O, tool:O, from:O, the:O, HackingTeam:O, RCS:O, Galileo:O, platform:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 attachments purported to be invitations or drafts of the agenda for the conference .' [/INST] [The:O, malicious:B-SamFile, attachments:I-SamFile, purported:O, to:O, be:O, invitations:B-Tool, or:O, drafts:B-Tool, of:I-Tool, the:I-Tool, agenda:I-Tool, for:O, the:O, conference:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We encountered the first document exploit called , THAM luan - GD - NCKH2.doc , a few days ago , which appears to be leveraging some vulnerabilities patched with MS12-060 .' [/INST] [We:O, encountered:O, the:O, first:O, document:O, exploit:O, called:O, ,:O, THAM:B-SamFile, luan:I-SamFile, -:I-SamFile, GD:I-SamFile, -:I-SamFile, NCKH2.doc:B-SamFile, ,:O, a:O, few:O, days:O, ago:O, ,:O, which:O, appears:O, to:O, be:O, leveraging:O, some:O, vulnerabilities:O, patched:O, with:O, MS12-060:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This document , written in Vietnamese , appears to be reviewing and discussing best practices for teaching and researching scientific topics .' [/INST] [This:O, document:B-SamFile, ,:O, written:O, in:O, Vietnamese:O, ,:O, appears:O, to:O, be:O, reviewing:B-Features, and:I-Features, discussing:I-Features, best:I-Features, practices:I-Features, for:O, teaching:O, and:O, researching:O, scientific:O, topics:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Examples as early as 2008 document malware operations against Tibetan non-governmental organizations ( NGOs ) that also targeted Falun Gong and Uyghur groups .' [/INST] [Examples:O, as:O, early:O, as:O, 2008:B-Time, document:B-SamFile, malware:I-SamFile, operations:O, against:O, Tibetan:B-Org, non-governmental:I-Org, organizations:I-Org, (:O, NGOs:O, ):O, that:O, also:O, targeted:O, Falun:B-Org, Gong:I-Org, and:O, Uyghur:B-Org, groups:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'There is the exploit code and malware used to gain access to systems , the infrastructure that provides command and control to the malware operator , and the human elements – developers who create the malware , operators who deploy it , and analysts who extract value from the stolen information .' [/INST] [There:O, is:O, the:O, exploit:B-SamFile, code:I-SamFile, and:O, malware:O, used:O, to:O, gain:B-Features, access:I-Features, to:I-Features, systems:I-Features, ,:O, the:O, infrastructure:O, that:O, provides:B-Features, command:I-Features, and:I-Features, control:I-Features, to:O, the:O, malware:O, operator:O, ,:O, and:O, the:O, human:O, elements:O, –:O, developers:O, who:O, create:O, the:O, malware:O, ,:O, operators:O, who:O, deploy:O, it:O, ,:O, and:O, analysts:O, who:O, extract:O, value:O, from:O, the:O, stolen:O, information:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The operation against the Tibetan Parliamentarians illustrates the continued use of malicious attachments in the form of documents bearing exploits .' [/INST] [The:O, operation:O, against:O, the:O, Tibetan:B-Org, Parliamentarians:I-Org, illustrates:O, the:O, continued:O, use:O, of:O, malicious:B-SamFile, attachments:I-SamFile, in:O, the:O, form:O, of:O, documents:B-Tool, bearing:I-Tool, exploits:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The first attack started in early July with a ShimRatReporter payload .' [/INST] [The:O, first:O, attack:B-OffAct, started:O, in:O, early:O, July:B-Time, with:O, a:O, ShimRatReporter:B-SamFile, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In their Operation Tropic Trooper report , Trend Micro documented the behaviour and functionality of an espionage toolkit with several design similarities to those observed in the various components of KeyBoy .' [/INST] [In:O, their:O, Operation:B-OffAct, Tropic:I-OffAct, Trooper:I-OffAct, report:O, ,:O, Trend:B-SecTeam, Micro:I-SecTeam, documented:O, the:O, behaviour:O, and:O, functionality:O, of:O, an:O, espionage:B-SamFile, toolkit:I-SamFile, with:O, several:O, design:O, similarities:O, to:O, those:O, observed:O, in:O, the:O, various:O, components:O, of:O, KeyBoy:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The exploit document carrying this alternate KeyBoy configuration also used a decoy document which was displayed to the user after the exploit launched .' [/INST] [The:O, exploit:B-SamFile, document:I-SamFile, carrying:O, this:O, alternate:O, KeyBoy:B-Tool, configuration:O, also:O, used:O, a:O, decoy:B-SamFile, document:I-SamFile, which:O, was:O, displayed:O, to:O, the:O, user:O, after:O, the:O, exploit:O, launched:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This technique hides the true C2 server from researchers that do not have access to both the rastls.dll and Sycmentec.config files .' [/INST] [This:O, technique:O, hides:O, the:O, true:O, C2:O, server:O, from:O, researchers:O, that:O, do:O, not:O, have:O, access:O, to:O, both:O, the:O, rastls.dll:B-SamFile, and:O, Sycmentec.config:B-SamFile, files:I-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This file requires the target to attempt to open the .lnk file , which redirects the user to a Windows Scripting Component ( .wsc ) file , hosted on an adversary-controlled microblogging page .' [/INST] [This:O, file:O, requires:O, the:O, target:O, to:O, attempt:O, to:O, open:O, the:O, .lnk:B-SamFile, file:I-SamFile, ,:O, which:O, redirects:B-Features, the:I-Features, user:I-Features, to:O, a:O, Windows:O, Scripting:O, Component:O, (:O, .wsc:O, ):O, file:O, ,:O, hosted:O, on:O, an:O, adversary-controlled:O, microblogging:O, page:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Upon successful exploitation , the attachment will install the trojan known as NetTraveler using a DLL side-loading attack technique .' [/INST] [Upon:O, successful:O, exploitation:O, ,:O, the:O, attachment:B-SamFile, will:O, install:B-Features, the:I-Features, trojan:I-Features, known:O, as:O, NetTraveler:B-Tool, using:O, a:O, DLL:B-SamFile, side-loading:I-SamFile, attack:O, technique:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Kaspersky Lab 's products detect the Microsoft Office exploits used in the spear-phishing attacks , including Exploit.MSWord.CVE-2010-333 , Exploit.Win32.CVE-2012-0158 .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, 's:O, products:O, detect:O, the:O, Microsoft:B-Exp, Office:I-Exp, exploits:I-Exp, used:O, in:O, the:O, spear-phishing:B-OffAct, attacks:I-OffAct, ,:O, including:O, Exploit.MSWord.CVE-2010-333:B-SamFile, ,:O, Exploit.Win32.CVE-2012-0158:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The files exploit the well-known Microsoft Office vulnerability , CVE-2012-0158 , to execute malicious code in order to take control of the targeted systems .' [/INST] [The:O, files:B-SamFile, exploit:O, the:O, well-known:O, Microsoft:B-Exp, Office:I-Exp, vulnerability:I-Exp, ,:O, CVE-2012-0158:B-Exp, ,:O, to:O, execute:O, malicious:O, code:O, in:O, order:O, to:O, take:B-Features, control:I-Features, of:O, the:O, targeted:O, systems:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We also discovered an interesting piece of rare malware created by this threat actor – a Bluetooth device harvester .' [/INST] [We:O, also:O, discovered:O, an:O, interesting:O, piece:O, of:O, rare:O, malware:B-Tool, created:O, by:O, this:O, threat:O, actor:O, –:O, a:O, Bluetooth:B-SamFile, device:I-SamFile, harvester:I-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'For example , Bisonal malware in 2012 used send() and recv() APIs to communicate with its C2 This Bisonal variant used in the latest attack communicates with one of the following hard-coded C2 addresses by using the HTTP POST method on TCP port 443 .' [/INST] [For:O, example:O, ,:O, Bisonal:B-HackOrg, malware:I-HackOrg, in:O, 2012:B-Time, used:O, send():O, and:O, recv():O, APIs:O, to:O, communicate:O, with:O, its:O, C2:O, This:O, Bisonal:B-SamFile, variant:O, used:O, in:O, the:O, latest:O, attack:O, communicates:O, with:O, one:O, of:O, the:O, following:O, hard-coded:O, C2:O, addresses:O, by:O, using:O, the:O, HTTP:B-Way, POST:I-Way, method:O, on:O, TCP:O, port:O, 443:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Previous reports have discussed Bisonal malware used in attacks against Japan , South Korea and Russia .' [/INST] [Previous:O, reports:O, have:O, discussed:O, Bisonal:B-SamFile, malware:I-SamFile, used:O, in:O, attacks:O, against:O, Japan:B-Area, ,:O, South:B-Area, Korea:I-Area, and:O, Russia:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This particular sample we found targeted an organization in Russia and there is a specific system language check for Cyrillic and no others .' [/INST] [This:O, particular:O, sample:B-SamFile, we:O, found:O, targeted:O, an:O, organization:O, in:O, Russia:B-Area, and:O, there:O, is:O, a:O, specific:O, system:O, language:O, check:O, for:O, Cyrillic:O, and:O, no:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 it's Cyrillic and the command to the shell is not ‘ipconfig’ , the threat converts the command result text encoding from Cyrillic to UTF-16 .' [/INST] [If:O, it's:B-SamFile, Cyrillic:B-Tool, and:O, the:O, command:O, to:O, the:O, shell:O, is:O, not:O, ‘ipconfig’:O, ,:O, the:O, threat:O, converts:O, the:O, command:O, result:O, text:O, encoding:O, from:O, Cyrillic:O, to:O, UTF-16:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Similar to the Bisonal variant targeting the Russian organization , this sample was also disguised as PDF document .' [/INST] [Similar:O, to:O, the:O, Bisonal:B-SamFile, variant:O, targeting:O, the:O, Russian:B-Area, organization:I-Area, ,:O, this:O, sample:O, was:O, also:O, disguised:O, as:O, PDF: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: 'The contents of the decoy PDF is a job descriptions with the South Korean Coast Guard .' [/INST] [The:O, contents:O, of:O, the:B-SamFile, decoy:I-SamFile, PDF:I-SamFile, is:O, a:O, job:O, descriptions:O, with:O, the:O, South:B-Area, Korean:I-Area, Coast:B-Idus, Guard:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The installed EXE file is almost exactly the same as the DLL version of Bisonal variant used against the Russian organization .' [/INST] [The:O, installed:B-SamFile, EXE:I-SamFile, file:I-SamFile, is:O, almost:O, exactly:O, the:O, same:O, as:O, the:O, DLL:O, version:O, of:O, Bisonal:B-SamFile, variant:I-SamFile, used:O, against:O, the:O, Russian:B-Area, 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: 'ined in the archive is called DriverInstallerU.exe” but its metadata shows that its original name is Interenet Assistant.exe” .' [/INST] [ined:O, in:O, the:O, archive:O, is:O, called:O, DriverInstallerU.exe”:B-SamFile, but:O, its:O, metadata:O, shows:O, that:O, its:O, original:O, name:O, is:O, Interenet:B-SamFile, Assistant.exe”:I-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this sample , however , the module names were changed from actors and characters’ names to car models , namely BMW_x1” , BMW_x2” and up to BMW_x8” .' [/INST] [In:O, this:O, sample:O, ,:O, however:O, ,:O, the:O, module:O, names:O, were:O, changed:O, from:O, actors:O, and:O, characters’:O, names:O, to:O, car:O, models:O, ,:O, namely:O, BMW_x1”:B-SamFile, ,:O, BMW_x2”:B-SamFile, and:O, up:O, to:O, BMW_x8”:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'wuaupdt.exe is a CMD backdoor , which can receive and execute CMD commands sent from C2 .' [/INST] [wuaupdt.exe:B-SamFile, is:O, a:O, CMD:B-Tool, backdoor:O, ,:O, which:O, can:O, receive:B-Features, and:O, execute:B-Features, CMD:I-Features, commands:I-Features, sent:O, from:O, C2:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Furthermore , it has similar code logic as previous ones wuaupdt.exe in this attack appears in previous Donot attack , and C2 addresses are same to previous ones .' [/INST] [Furthermore:O, ,:O, it:O, has:O, similar:O, code:O, logic:O, as:O, previous:O, ones:O, wuaupdt.exe:B-SamFile, in:O, this:O, attack:O, appears:O, in:O, previous:O, Donot:O, attack:O, ,:O, and:O, C2:O, addresses:O, are:O, same:O, to:O, previous:O, 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: 'Other open source and semi-legitimate pen-testing tools like nbtscan and powercat are being used for mapping available resources and lateral movement as well .' [/INST] [Other:O, open:O, source:O, and:O, semi-legitimate:O, pen-testing:O, tools:O, like:O, nbtscan:B-SamFile, and:O, powercat:B-SamFile, are:O, being:O, used:O, for:O, mapping:O, available:O, resources:O, and:O, lateral:O, movement:O, as:O, well:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'As described in the infection flow , one of the first uses of the AutoHotKey scripts is to upload a screenshot from the compromised PC .' [/INST] [As:O, described:O, in:O, the:O, infection:O, flow:O, ,:O, one:O, of:O, the:O, first:O, uses:O, of:O, the:O, AutoHotKey:B-SamFile, scripts:I-SamFile, is:O, to:O, upload:B-Features, a:I-Features, screenshot:I-Features, from:O, the:O, compromised:O, PC:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Throughout our investigation , we have found evidence that shows operational similarities between this implant and Gamaredon Group .' [/INST] [Throughout:O, our:O, investigation:O, ,:O, we:O, have:O, found:O, evidence:O, that:O, shows:O, operational:O, similarities:O, between:O, this:O, implant:B-SamFile, and:O, Gamaredon:B-HackOrg, 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: 'The techniques and modules employed by EvilGnome — that is the use of SFX , persistence with task scheduler and the deployment of information stealing tools—remind us of Gamaredon Group’s Windows tools .' [/INST] [The:O, techniques:O, and:O, modules:O, employed:O, by:O, EvilGnome:B-HackOrg, —:O, that:O, is:O, the:O, use:O, of:O, SFX:B-Tool, ,:O, persistence:O, with:O, task:O, scheduler:O, and:O, the:O, deployment:O, of:O, information:O, stealing:O, tools—remind:O, us:O, of:O, Gamaredon:O, Group’s:O, Windows:B-SamFile, tools:I-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We can observe that the sample is very recent , created on Thursday , July 4' [/INST] [We:O, can:O, observe:O, that:O, the:O, sample:B-SamFile, is:O, very:O, recent:O, ,:O, created:O, on:O, Thursday:O, ,:O, July:B-Time, 4:I-Time] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 can be observed in the illustration above , the makeself script is instructed to run ./setup.sh after unpacking .' [/INST] [As:O, can:O, be:O, observed:O, in:O, the:O, illustration:O, above:O, ,:O, the:O, makeself:B-SamFile, script:I-SamFile, is:O, instructed:O, to:O, run:O, ./setup.sh:B-SamFile, after:O, unpacking:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 ShooterAudio module uses PulseAudio to capture audio from the user's microphone .' [/INST] [The:O, ShooterAudio:B-SamFile, module:I-SamFile, uses:O, PulseAudio:B-Tool, to:O, capture:O, audio:O, from:O, the:O, user's:O, microphone:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'makeself.sh is a small shell script that generates a self-extractable compressed tar archive from a directory .' [/INST] [makeself.sh:B-SamFile, is:O, a:O, small:O, shell:B-SamFile, script:I-SamFile, that:O, generates:O, a:O, self-extractable:O, compressed:O, tar:O, archive:O, from:O, a:O, directory:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 RAT , however , had a multitude of functionalities (as listed in the table below) such as to download and execute , compress , encrypt , upload , search directories , etc .' [/INST] [The:O, RAT:B-SamFile, ,:O, however:O, ,:O, had:O, a:O, multitude:O, of:O, functionalities:O, (as:O, listed:O, in:O, the:O, table:O, below):O, such:O, as:O, to:O, download:B-Features, and:O, execute:B-Features, ,:O, compress:B-Features, ,:O, encrypt:B-Features, ,:O, upload:B-Features, ,:O, search:B-Features, directories:I-Features, ,:O, etc:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 a more recent version of the modified Gh0st RAT malware , Ghost Dragon implemented dynamic packet flags which change the first five bytes of the header in every login request with the controller .' [/INST] [In:O, a:O, more:O, recent:O, version:O, of:O, the:O, modified:O, Gh0st:B-SamFile, RAT:I-SamFile, malware:O, ,:O, Ghost:B-HackOrg, Dragon:I-HackOrg, implemented:O, dynamic:O, packet:O, flags:O, which:O, change:O, the:O, first:O, five:O, bytes:O, of:O, the:O, header:O, in:O, every:O, login:O, request:O, with:O, the:O, controller:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'One hour later , Bemstour was used against an educational institution in Belgium .' [/INST] [One:O, hour:O, later:O, ,:O, Bemstour:B-SamFile, was:O, used:O, against:O, an:O, educational:O, institution:O, in:O, Belgium:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Bemstour is specifically designed to deliver a variant of the DoublePulsar backdoor .' [/INST] [Bemstour:B-SamFile, is:O, specifically:O, designed:O, to:O, deliver:B-Features, a:O, variant:O, of:O, the:O, DoublePulsar:B-Tool, backdoor:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'DoublePulsar is then used to inject a secondary payload , which runs in memory only .' [/INST] [DoublePulsar:B-SamFile, is:O, then:O, used:O, to:O, inject:B-Features, a:O, secondary:O, payload:O, ,:O, which:O, runs:O, in:O, memory:O, only:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 significantly improved variant of the Bemstour exploit tool was rolled out in September 2016 , when it was used in an attack against an educational institution in Hong Kong .' [/INST] [A:O, significantly:O, improved:O, variant:O, of:O, the:O, Bemstour:B-SamFile, exploit:O, tool:O, was:O, rolled:O, out:O, in:O, September:B-Time, 2016:I-Time, ,:O, when:O, it:O, was:O, used:O, in:O, an:O, attack:O, against:O, an:O, educational:O, institution:O, in:O, Hong:B-Area, Kong:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Bemstour was used again in June 2017 in an attack against an organization in Luxembourg .' [/INST] [Bemstour:B-SamFile, was:O, used:O, again:O, in:O, June:O, 2017:O, in:O, an:O, attack:O, against:O, an:O, organization:O, in:O, Luxembourg:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Between June and September 2017 , Bemstour was also used against targets in the Philippines and Vietnam .' [/INST] [Between:O, June:O, and:O, September:O, 2017:O, ,:O, Bemstour:B-SamFile, was:O, also:O, used:O, against:O, targets:O, in:O, the:O, Philippines:B-Area, and:O, Vietnam:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Development of Bemstour has continued into 2019 .' [/INST] [Development:O, of:O, Bemstour:B-SamFile, has:O, continued:O, into:O, 2019:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Unlike earlier attacks when Bemstour was delivered using Buckeye's Pirpi backdoor , in this attack Bemstour was delivered to the victim by a different backdoor Trojan (Backdoor.Filensfer) .' [/INST] [Unlike:O, earlier:O, attacks:O, when:O, Bemstour:B-SamFile, was:O, delivered:O, using:O, Buckeye's:O, Pirpi:B-SamFile, backdoor:B-SamFile, ,:O, in:O, this:O, attack:O, Bemstour:O, was:O, delivered:O, to:O, the:O, victim:O, by:O, a:O, different:B-Tool, backdoor:B-Tool, Trojan:O, (Backdoor.Filensfer):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 recent sample of Bemstour seen by Symantec appears to have been compiled on March 23 , 2019 , eleven days after the zero-day vulnerability was patched by Microsoft .' [/INST] [The:O, most:O, recent:O, sample:O, of:O, Bemstour:B-SamFile, seen:O, by:O, Symantec:B-SecTeam, appears:O, to:O, have:O, been:O, compiled:O, on:O, March:B-Time, 23:I-Time, ,:O, 2019:O, ,:O, eleven:O, days:O, after:O, the:O, zero-day:O, vulnerability:O, was:O, patched:O, by:O, Microsoft:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Filensfer is a family of malware that has been used in targeted attacks since at least 2013 .' [/INST] [Filensfer:B-SamFile, is:O, a:O, family:O, of:O, malware:O, that:O, has:O, been:O, used:O, in:O, targeted:O, attacks:O, since:O, at:O, least:O, 2013:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While Symantec has never observed the use of Filensfer alongside any known Buckeye tools , information shared privately by another vendor included evidence of Filensfer being used in conjunction with known Buckeye malware (Backdoor.Pirpi) .' [/INST] [While:O, Symantec:B-SecTeam, has:O, never:O, observed:O, the:O, use:O, of:O, Filensfer:B-SamFile, alongside:O, any:O, known:O, Buckeye:O, tools:O, ,:O, information:O, shared:O, privately:O, by:O, another:O, vendor:O, included:O, evidence:O, of:O, Filensfer:O, being:O, used:O, in:O, conjunction:O, with:O, known:O, Buckeye:B-SamFile, malware:I-SamFile, (Backdoor.Pirpi):B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CVE-2017-0143 was also used by two other exploit tools—EternalRomance and EternalSynergy—that were released as part of the Shadow Brokers leak in April 2017 .' [/INST] [CVE-2017-0143:B-Exp, was:O, also:O, used:O, by:O, two:O, other:O, exploit:O, tools—EternalRomance:B-SamFile, and:O, EternalSynergy—that:B-SamFile, were:O, released:O, as:O, part:O, of:O, the:O, Shadow:O, Brokers:O, leak:O, in:O, April:B-Time, 2017:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Buckeye's exploit tool , EternalRomance , as well as EternalSynergy , can exploit the CVE-2017-0143 message type confusion vulnerability to perform memory corruption on unpatched victim computers .' [/INST] [Buckeye's:O, exploit:O, tool:O, ,:O, EternalRomance:B-SamFile, ,:O, as:O, well:O, as:O, EternalSynergy:B-SamFile, ,:O, can:O, exploit:O, the:O, CVE-2017-0143:B-SamFile, message:O, type:O, confusion:O, vulnerability:O, to:O, perform:O, memory:O, corruption:O, on:O, unpatched:O, victim:O, computers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 RTF exploits again the CVE-2017_1882 on eqnedt32.exe .' [/INST] [this:O, RTF:B-SamFile, exploits:O, again:O, the:O, CVE-2017_1882:B-Exp, on:O, eqnedt32.exe:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'And the dropper execute the iassvcs.exe to make a side loading and make the persistence .' [/INST] [And:O, the:O, dropper:B-SamFile, execute:O, the:O, iassvcs.exe:B-SamFile, to:O, make:O, a:O, side:O, loading:O, and:O, make:O, the:O, persistence:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Over the past three years , Filensfer has been deployed against organizations in Luxembourg , Sweden , Italy , the UK , and the U.S .' [/INST] [Over:O, the:O, past:O, three:O, years:O, ,:O, Filensfer:B-SamFile, has:O, been:O, deployed:O, against:O, organizations:O, in:O, Luxembourg:B-Area, ,:O, Sweden:B-Area, ,:O, Italy:B-Area, ,:O, the:B-Area, UK:I-Area, ,:O, and:O, the:B-Area, U.S:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Our analysis of this malware shows that it belongs to Hussarini , also known as Sarhust , a backdoor family that has been used actively in APT attacks targeting countries in the ASEAN region since 2014 .' [/INST] [Our:O, analysis:O, of:O, this:O, malware:O, shows:O, that:O, it:O, belongs:O, to:O, Hussarini:B-SamFile, ,:O, also:O, known:O, as:O, Sarhust:O, ,:O, a:O, backdoor:O, family:O, that:O, has:O, been:O, used:O, actively:O, in:O, APT:O, attacks:O, targeting:O, countries:O, in:O, the:O, ASEAN:B-Area, region:I-Area, since:O, 2014:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'OutExtra.exe is a signed legitimate application from Microsoft named finder.exe .' [/INST] [OutExtra.exe:B-SamFile, is:O, a:O, signed:O, legitimate:O, application:O, from:O, Microsoft:O, named:O, finder.exe:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Today , this malware is still actively being used against the Philippines .' [/INST] [Today:O, ,:O, this:O, malware:B-SamFile, is:O, still:O, actively:O, being:O, used:O, against:O, the:O, Philippines:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Xagent” is the original filename Xagent.exe whereas seems to be the version of the worm .' [/INST] [Xagent”:B-SamFile, is:O, the:O, original:O, filename:O, Xagent.exe:O, whereas:O, seems:O, to:O, be:O, the:O, version:O, of:O, the:O, worm:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Our technical analysis of the malware used in these attacks showed close ties to BS2005 backdoors from operation Ke3chang , and to a related TidePool malware family discovered by Palo Alto Networks in 2016 that targeted Indian embassies across the globe .' [/INST] [Our:O, technical:O, analysis:O, of:O, the:O, malware:B-SamFile, used:O, in:O, these:O, attacks:O, showed:O, close:O, ties:O, to:O, BS2005:B-SamFile, backdoors:I-SamFile, from:O, operation:O, Ke3chang:O, ,:O, and:O, to:O, a:O, related:O, TidePool:B-SamFile, malware:I-SamFile, family:O, discovered:O, by:O, Palo:B-SecTeam, Alto:I-SecTeam, Networks:O, in:O, 2016:B-Time, that:O, targeted:O, Indian:O, embassies:O, across:O, the:O, globe:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 actors behind the Okrum malware were focused on the same targets in Slovakia that were previously targeted by Ketrican 2015 backdoors .' [/INST] [The:O, malicious:O, actors:O, behind:O, the:O, Okrum:B-SamFile, malware:I-SamFile, were:O, focused:O, on:O, the:O, same:O, targets:O, in:O, Slovakia:B-Area, that:O, were:O, previously:O, targeted:O, by:O, Ketrican:O, 2015:O, backdoors:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We started connecting the dots when we discovered that the Okrum backdoor was used to drop a Ketrican backdoor , freshly compiled in 2017 .' [/INST] [We:O, started:O, connecting:O, the:O, dots:O, when:O, we:O, discovered:O, that:O, the:O, Okrum:B-SamFile, backdoor:I-SamFile, was:O, used:O, to:O, drop:O, a:O, Ketrican:B-SamFile, backdoor:I-SamFile, ,:O, freshly:O, compiled:O, in:O, 2017:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In 2017 , the same entities that were affected by the Okrum malware and by the 2015 Ketrican backdoors again became targets of the malicious actors .' [/INST] [In:O, 2017:O, ,:O, the:O, same:O, entities:O, that:O, were:O, affected:O, by:O, the:O, Okrum:B-SamFile, malware:I-SamFile, and:O, by:O, the:O, 2015:O, Ketrican:B-SamFile, backdoors:I-SamFile, again:O, became:O, targets:O, of:O, the:O, malicious:O, actors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 time , the attackers used new versions of the RoyalDNS malware and a Ketrican 2017 backdoor .' [/INST] [This:O, time:O, ,:O, the:O, attackers:O, used:O, new:O, versions:O, of:O, the:O, RoyalDNS:B-SamFile, malware:I-SamFile, and:O, a:O, Ketrican:B-SamFile, 2017:O, backdoor:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'According to ESET telemetry , Okrum was first detected in December 2016 , and targeted diplomatic missions in Slovakia , Belgium , Chile , Guatemala and Brazil throughout 2017 .' [/INST] [According:O, to:O, ESET:B-SecTeam, telemetry:O, ,:O, Okrum:B-SamFile, was:O, first:O, detected:O, in:O, December:B-Time, 2016:I-Time, ,:O, and:O, targeted:O, diplomatic:O, missions:O, in:O, Slovakia:B-Area, ,:O, Belgium:B-Area, ,:O, Chile:B-Area, ,:O, Guatemala:B-Area, and:O, Brazil:B-Area, throughout:O, 2017:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'According to our telemetry , Okrum was used to target diplomatic missions in Slovakia , Belgium , Chile , Guatemala , and Brazil , with the attackers showing a particular interest in Slovakia .' [/INST] [According:O, to:O, our:O, telemetry:O, ,:O, Okrum:B-SamFile, was:O, used:O, to:O, target:O, diplomatic:O, missions:O, in:O, Slovakia:B-Area, ,:O, Belgium:B-Area, ,:O, Chile:B-Area, ,:O, Guatemala:B-Area, ,:O, and:O, Brazil:B-Area, ,:O, with:O, the:O, attackers:O, showing:O, a:O, particular:O, interest:O, in:O, Slovakia:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 detection evasion techniques we observed in the Okrum malware include embedding the malicious payload within a legitimate PNG image , employing several anti-emulation and anti-sandbox tricks , as well as making frequent changes in implementation .' [/INST] [The:O, detection:O, evasion:O, techniques:O, we:O, observed:O, in:O, the:O, Okrum:B-SamFile, malware:O, include:O, embedding:B-Features, the:O, malicious:O, payload:O, within:O, a:O, legitimate:O, PNG:O, image:O, ,:O, employing:O, several:O, anti-emulation:O, and:O, anti-sandbox:O, tricks:O, ,:O, as:O, well:O, as:O, making:O, frequent:O, changes:O, in:O, implementation:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'According to ClearSky , the suspected Lazarus operatives looked to leverage a vulnerability in outdated WinRAR file-archiving software that hackers have been exploiting since it was disclosed last month .' [/INST] [According:O, to:O, ClearSky:B-SecTeam, ,:O, the:O, suspected:O, Lazarus:O, operatives:O, looked:O, to:O, leverage:O, a:O, vulnerability:O, in:O, outdated:O, WinRAR:B-SamFile, file-archiving:O, software:O, that:O, hackers:O, have:O, been:O, exploiting:O, since:O, it:O, was:O, disclosed:O, last:O, month:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 diagram below illustrates how we believe the actors behind the Sea Turtle campaign used DNS hijacking to achieve their end goals .' [/INST] [The:O, diagram:O, below:O, illustrates:O, how:O, we:O, believe:O, the:O, actors:O, behind:O, the:O, Sea:B-SamFile, Turtle:I-SamFile, campaign:O, used:O, DNS:B-Features, hijacking:I-Features, to:O, achieve:O, their:O, end:O, goals:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the user enables macro to open the xlsm file , it will then drop the legitimate script engine AutoHotkey along with a malicious script file .' [/INST] [If:O, the:O, user:O, enables:O, macro:O, to:O, open:O, the:O, xlsm:B-Tool, file:I-Tool, ,:O, it:B-SamFile, will:O, then:O, drop:B-Features, the:I-Features, legitimate:I-Features, script:I-Features, engine:O, AutoHotkey:O, along:O, with:O, a:O, malicious:O, script:O, 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: 'Create a link file in the startup folder for AutoHotkeyU32.exe , allowing the attack to persist even after a system restart .' [/INST] [Create:O, a:O, link:B-SamFile, file:I-SamFile, in:O, the:O, startup:O, folder:O, for:O, AutoHotkeyU32.exe:B-SamFile, ,:O, allowing:O, the:O, attack:O, to:O, persist:O, even:O, after:O, a:O, system:O, restart:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Such attacks highlight the need for caution before downloading files from unknown sources and enabling macro for files from unknown sources .' [/INST] [Such:O, attacks:B-SamFile, highlight:O, the:O, need:O, for:O, caution:O, before:O, downloading:B-Way, files:I-Way, from:O, unknown:O, sources:O, and:O, enabling:O, macro:O, for:O, files:O, from:O, unknown:O, sources:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Its configuration utilities like Margarita allows the NOC (Network Operation Center) to customize tools based on requirements from 'Fine Dining' questionairies .' [/INST] [Its:O, configuration:O, utilities:O, like:O, Margarita:B-SamFile, allows:O, the:O, NOC:O, (Network:O, Operation:O, Center):O, to:O, customize:O, tools:O, based:O, on:O, requirements:B-Features, from:O, 'Fine:O, Dining':O, questionairies:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Honeycomb toolserver receives exfiltrated information from the implant; an operator can also task the implant to execute jobs on the target computer , so the toolserver acts as a C2 (command and control) server for the implant .' [/INST] [Honeycomb:B-SamFile, toolserver:O, receives:O, exfiltrated:O, information:O, from:O, the:O, implant;:O, an:O, operator:O, can:O, also:O, task:O, the:O, implant:O, to:O, execute:O, jobs:O, on:O, the:O, target:O, computer:O, ,:O, so:O, the:O, toolserver:O, acts:B-Features, as:O, a:O, C2:O, (command:O, and:O, control):O, server:O, for:O, the:O, implant:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'UMBRAGE components cover keyloggers , password collection , webcam capture , data destruction , persistence , privilege escalation , stealth , anti-virus (PSP) avoidance and survey techniques .' [/INST] [UMBRAGE:B-SamFile, components:O, cover:B-Features, keyloggers:I-Features, ,:O, password:B-Features, collection:I-Features, ,:O, webcam:B-Features, capture:I-Features, ,:O, data:B-Features, destruction:I-Features, ,:O, persistence:B-Features, ,:O, privilege:B-Features, escalation:I-Features, ,:O, stealth:B-Features, ,:O, anti-virus:O, (PSP):O, avoidance:O, and:O, survey:B-Features, techniques:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: ''Improvise' is a toolset for configuration , post-processing , payload setup and execution vector selection for survey/exfiltration tools supporting all major operating systems like Windows (Bartender) , MacOS (JukeBox) and Linux (DanceFloor) .' [/INST] ['Improvise':B-SamFile, is:O, a:O, toolset:O, for:O, configuration:B-Features, ,:O, post-processing:B-Features, ,:O, payload:B-Features, setup:I-Features, and:O, execution:B-Features, vector:I-Features, selection:O, for:O, survey/exfiltration:O, tools:O, supporting:O, all:O, major:O, operating:O, systems:O, like:O, Windows:B-Way, (Bartender):O, ,:O, MacOS:B-Way, (JukeBox):O, and:O, Linux:B-Way, (DanceFloor):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This sample , similar to other Trochilus samples , was deployed using a DLL sideloading method utilizing three files , uploaded to the same folder on the victim machine as identified in US-CERT advisory TA17-117A last revised on December 20 , 2018 .' [/INST] [This:O, sample:B-SamFile, ,:O, similar:O, to:O, other:O, Trochilus:B-SamFile, samples:O, ,:O, was:O, deployed:O, using:O, a:O, DLL:B-Features, sideloading:I-Features, method:O, utilizing:O, three:O, files:O, ,:O, uploaded:B-Features, to:O, the:O, same:O, folder:O, on:O, the:O, victim:O, machine:O, as:O, identified:O, in:O, US-CERT:O, advisory:O, TA17-117A:O, last:O, revised:O, on:O, December:O, 20:O, ,:O, 2018:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 configuration file then loads the Trochilus payload into memory by injecting it into a valid system process .' [/INST] [The:O, configuration:B-SamFile, file:I-SamFile, then:O, loads:O, the:O, Trochilus:O, payload:O, into:O, memory:O, by:O, injecting:B-Features, it:O, into:O, a:O, valid:O, system:O, process:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Additionally , the same DLL sideloading technique observed in the Visma attack was used , and many of the tools deployed by the APT10 shared naming similarities as well 1.bat , cu.exe , ss.rar , r.exe , pd.exe .' [/INST] [Additionally:O, ,:O, the:O, same:O, DLL:O, sideloading:O, technique:O, observed:O, in:O, the:O, Visma:B-Tool, attack:O, was:O, used:O, ,:O, and:O, many:O, of:O, the:O, tools:O, deployed:O, by:O, the:O, APT10:B-HackOrg, shared:O, naming:O, similarities:O, as:O, well:O, 1.bat:B-Tool, ,:O, cu.exe:B-Tool, ,:O, ss.rar:B-Tool, ,:O, r.exe:B-Tool, ,:O, pd.exe:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Most interestingly , Rapid7 observed the use of the Notepad++ updater gup.exe as a legitimate executable to sideload a malicious DLL (libcurl.dll) in order to deploy a variant of the UPPERCUT backdoor also known as ANEL .' [/INST] [Most:O, interestingly:O, ,:O, Rapid7:B-SecTeam, observed:O, the:O, use:O, of:O, the:O, Notepad++:O, updater:O, gup.exe:B-SamFile, as:O, a:O, legitimate:O, executable:O, to:O, sideload:O, a:O, malicious:O, DLL:O, (libcurl.dll):O, in:O, order:O, to:O, deploy:O, a:O, variant:O, of:O, the:O, UPPERCUT:O, backdoor:O, also:O, known:O, as:O, ANEL:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Insikt Group analysis of network metadata to and from the VPN endpoint IPs revealed consistent connectivity to Citrix-hosted infrastructure from all eight VPN endpoint IPs starting on August 17 , 2018 — the same date the first authenticated login to Visma’s network was made using stolen credentials .' [/INST] [Insikt:B-HackOrg, Group:I-HackOrg, analysis:O, of:O, network:O, metadata:O, to:O, and:O, from:O, the:O, VPN:O, endpoint:O, IPs:O, revealed:O, consistent:O, connectivity:O, to:O, Citrix-hosted:B-SamFile, infrastructure:O, from:O, all:O, eight:O, VPN:B-Features, endpoint:I-Features, IPs:O, starting:O, on:O, August:B-Time, 17:I-Time, ,:O, 2018:O, —:O, the:O, same:O, date:O, the:O, first:O, authenticated:O, login:O, to:O, Visma’s:O, network:O, was:O, made:O, using: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: 'KHRAT is a backdoor trojan purported to be used with the China-linked cyberespionage group DragonOK .' [/INST] [KHRAT:B-SamFile, is:O, a:O, backdoor:B-Tool, trojan:I-Tool, purported:O, to:O, be:O, used:O, with:O, the:O, China-linked:B-Area, cyberespionage:O, group:O, DragonOK:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Rapid7 reviewed malware discovered in the victim’s environment and found implants that used Dropbox as the C2 .' [/INST] [Rapid7:B-SecTeam, reviewed:O, malware:O, discovered:O, in:O, the:O, victim’s:O, environment:O, and:O, found:O, implants:O, that:O, used:O, Dropbox:B-SamFile, as:O, the:O, C2:O, .:O] </s> |
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