"Carlton Red. Um maço por dia. Danem-se as campanhas com fotos chocantes. Restaurantes sem alas de fumantes são sumariamente eliminados da minha lista.(...). Mas repito aqui o que meu falecido avô costumava dizer: "prefiro viver pouco fazendo tudo o que gosto a viver muito privado dos pequenos prazeres que meus vícios proporcionam".
Social engineering is a nontechnical method of breaking into a system or network. It's the process of deceiving users of a system and convincing them to perform acts useful to the hacker, such as giving out information that can be used to defeat or bypass security mechanisms. Social engineering is important to understand because hackers can use it to attack the human element of a system and circumvent technical security measures. This method can be used to gather information before or during an attack.
A social engineer commonly uses the telephone or Internet to trick people into revealing sensitive information or to get them to do something that is against the security policies of the organization. By this method, social engineers exploit the natural tendency of a person to trust their word, rather than exploiting computer security holes. It's generally agreed that users are the weak link in security; this principle is what makes social engineering possible.
The most dangerous part of social engineering is that companies with authentication processes, firewalls, virtual private networks, and network monitoring software are still wide open to attacks, because social engineering doesn't assault the security measures directly. Instead, a social-engineering attack bypasses the security measures and goes after the human element in an organization.
Types of Social Engineering-Attacks
There are two types of Social Engineering attacks
Human-Based
Human-based social engineering refers to person-to-person interaction to retrieve the desired information. An example is calling the help desk and trying to find out a password.
Computer-Based
Computer-based social engineering refers to having computer software that attempts to retrieve the desired information. An example is sending a user an email and asking them to reenter a password in a web page to confirm it. This social-engineering attack is also known as phishing.
Human-Based Social Engineering
Human-Based further categorized as follow:
Impersonating an Employee or Valid User
In this type of social-engineering attack, the hacker pretends to be an employee or valid user on the system. A hacker can gain physical access by pretending to be a janitor, employee, or contractor. Once inside the facility, the hacker gathers information from trashcans, desktops, or computer systems.
Posing as an Important User
In this type of attack, the hacker pretends to be an important user such as an executive or high-level manager who needs immediate assistance to gain access to a computer system or files. The hacker uses intimidation so that a lower-level employee such as a help desk worker will assist them in gaining access to the system. Most low-level employees won't question someone who appears to be in a position of authority.
Using a Third Person
Using the third-person approach, a hacker pretends to have permission from an authorized source to use a system. This attack is especially effective if the supposed authorized source is on vacation or can't be contacted for verification.
Calling Technical Support
Calling tech support for assistance is a classic social-engineering technique. Help desk and technical support personnel are trained to help users, which makes them good prey for social-engineering attacks.
Shoulder Surfing
Shoulder surfing is a technique of gathering passwords by watching over a person's shoulder while they log in to the system. A hacker can watch a valid user log in and then use that password to gain access to the system.
Dumpster Diving
Dumpster diving involves looking in the trash for information written on pieces of paper or computer printouts. The hacker can often find passwords, filenames, or other pieces of confidential information.
Computer-Based Social Engineering
Computer-based social-engineering attacks can include the following:
Email attachments
Fake websites
Pop-up windows
Insider Attacks
If a hacker can't find any other way to hack an organization, the next best option is to infiltrate the organization by getting hired as an employee or finding a disgruntled employee to assist in the attack. Insider attacks can be powerful because employees have physical access and are able to move freely about the organization. An example might be someone posing as a delivery person by wearing a uniform and gaining access to a delivery room or loading dock. Another possibility is someone posing as a member of the cleaning crew who has access to the inside of the building and is usually able to move about the offices. As a last resort, a hacker might bribe or otherwise coerce an employee to participate in the attack by providing information such as passwords.
Identity Theft
A hacker can pose as an employee or steal the employee's identity to perpetrate an attack. Information gathered in dumpster diving or shoulder surfing in combination with creating fake ID badges can gain the hacker entry into an organization. Creating a persona that can enter the building unchallenged is the goal of identity theft.
Phishing Attacks
Phishing involves sending an email, usually posing as a bank, credit card company, or other financial organization. The email requests that the recipient confirm banking information or reset passwords or PINs. The user clicks the link in the email and is redirected to a fake website. The hacker is then able to capture this information and use it for financial gain or to perpetrate other attacks. Emails that claim the senders have a great amount of money but need your help getting it out of the country are examples of phishing attacks. These attacks prey on the common person and are aimed at getting them to provide bank account access codes or other confidential information to the hacker.
Online Scams
Some websites that make free offers or other special deals can lure a victim to enter a username and password that may be the same as those they use to access their work system. The hacker can use this valid username and password once the user enters the information in the website form. Mail attachments can be used to send malicious code to a victim's system, which could automatically execute something like a software keylogger to capture passwords. Viruses, Trojans, and worms can be included in cleverly crafted emails to entice a victim to open the attachment. Mail attachments are considered a computer-based social-engineering attack.More information
Microsoft today released its June 2020 batch of software security updates that patches a total of 129 newly discovered vulnerabilities affecting various versions of Windows operating systems and related products. This is the third Patch Tuesday update since the beginning of the global Covid-19 outbreak, putting some extra pressure on security teams struggling to keep up with patch management
How do I get started with bug bounty hunting? How do I improve my skills?
These are some simple steps that every bug bounty hunter can use to get started and improve their skills:
Learn to make it; then break it! A major chunk of the hacker's mindset consists of wanting to learn more. In order to really exploit issues and discover further potential vulnerabilities, hackers are encouraged to learn to build what they are targeting. By doing this, there is a greater likelihood that hacker will understand the component being targeted and where most issues appear. For example, when people ask me how to take over a sub-domain, I make sure they understand the Domain Name System (DNS) first and let them set up their own website to play around attempting to "claim" that domain.
Read books. Lots of books. One way to get better is by reading fellow hunters' and hackers' write-ups. Follow /r/netsec and Twitter for fantastic write-ups ranging from a variety of security-related topics that will not only motivate you but help you improve. For a list of good books to read, please refer to "What books should I read?".
Join discussions and ask questions. As you may be aware, the information security community is full of interesting discussions ranging from breaches to surveillance, and further. The bug bounty community consists of hunters, security analysts, and platform staff helping one and another get better at what they do. There are two very popular bug bounty forums: Bug Bounty Forum and Bug Bounty World.
Participate in open source projects; learn to code. Go to https://github.com/explore or https://gitlab.com/explore/projects and pick a project to contribute to. By doing so you will improve your general coding and communication skills. On top of that, read https://learnpythonthehardway.org/ and https://linuxjourney.com/.
Help others. If you can teach it, you have mastered it. Once you discover something new and believe others would benefit from learning about your discovery, publish a write-up about it. Not only will you help others, you will learn to really master the topic because you can actually explain it properly.
Smile when you get feedback and use it to your advantage. The bug bounty community is full of people wanting to help others so do not be surprised if someone gives you some constructive feedback about your work. Learn from your mistakes and in doing so use it to your advantage. I have a little physical notebook where I keep track of the little things that I learnt during the day and the feedback that people gave me.
Learn to approach a target. The first step when approaching a target is always going to be reconnaissance — preliminary gathering of information about the target. If the target is a web application, start by browsing around like a normal user and get to know the website's purpose. Then you can start enumerating endpoints such as sub-domains, ports and web paths.
A woodsman was once asked, "What would you do if you had just five minutes to chop down a tree?" He answered, "I would spend the first two and a half minutes sharpening my axe." As you progress, you will start to notice patterns and find yourself refining your hunting methodology. You will probably also start automating a lot of the repetitive tasks.
theharvester program (already available in Kali Linux)
So what does theharvester harvest? Well it harvests email addresses. theharvester is an Information gathering tool. If you want a list of emails to spam you can get that easily from theharvester tool and go on Spamming (I'm joking its illegal). It's a security tool that helps you in pentesting an organization (as always it can be used for evil as well). You can gather emails from an organization and look for potential victims to attack or use brute-force techniques to get their passwords or Social Engineer them into doing something that will let you compromise some or all systems in the organization. Uhh there are so many things that you can do when you have access to someone's email address. OK stop talking and start doing. Fire up a terminal in your kali box and type this command: theharvester -d hotmail.com -l 50 -b google In a small amount of time you'll see your terminal flooded with 200 hotmail.com email address. What does this command mean?
theharvester is the tool name that we are using -d <domain_name> specifies the domain (or website) who's email addresses we're looking for, in our case it was hotmail.com -l <number> specifies the number of results that we want in the output, I limited it to 50 -b <source> specifies the source on which to look for email addresses, I specified google as the source Besides google we can specify any of the follow as source: google, googleCSE, bing, bingapi, pgp, linkedin, google-profiles, people123, jigsaw, twitter, googleplus, all Here the last entry all means look in every available source. Let's say you wanted to look in every available source they you should specify the following command: theharvester -d hotmail.com -b all
-f is another great flag which can be utilized to save the output in case we want to SPAM them later (just kidding) or for other reasons (I'm thinking positive). -f flag saves the result in html or xml format. Let's do just that: theharvester -d gmail.com -l 50 -b google -f emailaddresses.html here -f flag is followed by the location where we want to store the file and the name of file, in our case we stored it in our pwd (present working directory) with the name emailaddresses.html.
Above picture shows an html output generated by harvester. That's it for this tutorial hope to see you next time!
Bob was tasked to break into XYZcorporation, so he pulled up the facility on google maps to see what the layout was. He was looking for any possible entry paths into the company headquarters. Online maps showed that the whole facility was surrounded by a security access gate. Not much else could be determined remotely so bob decided to take a drive to the facility and get a closer look.
Bob parked down the street in view of the entry gate. Upon arrival he noted the gate was un-manned and cars were rolling up to the gate typing in an access code or simply driving up to the gate as it opening automatically.Interestingly there was some kind of wireless technology in use.
How do we go from watching a car go through a gate, to having a physical device that opens the gate?
We will take a look at reversing a signal from an actual gate to program a remote with the proper RF signal.Learning how to perform these steps manually to get a better understanding of how RF remotes work in conjunction with automating processes with RFCrack.
In the the previous blogs, we sniffed signals and replayed them to perform actions. In this blog we are going to take a look at a signal and reverse it to create a physical device that will act as a replacement for the original device. Depending on the scenario this may be a better approach if you plan to enter the facility off hours when there is no signal to capture or you don't want to look suspicious.
Recon:
Lets first use the scanning functionality in RFCrack to find known frequencies. Weneed to understand the frequencies that gates usually use. This way we can set our scanner to a limited number of frequencies to rotate through. The smaller rage of frequencies used will provide a better chance of capturing a signal when a car opens the target gate. This would be beneficial if the scanning device is left unattended within a dropbox created with something like a Kali on a Raspberry Pi. One could access it from a good distance away by setting up a wifi hotspot or cellular connection.
Based on research remotes tend to use 315Mhz, 390Mhz, 433Mhz and a few other frequencies. So in our case we will start up RFCrack on those likely used frequencies and just let it run. We can also look up the FCID of our clicker to see what Frequencies manufactures are using. Although not standardized, similar technologies tend to use similar configurations. Below is from the data sheet located at https://fccid.io/HBW7922/Test-Report/test-report-1755584 which indicates that if this gate is compatible with a universal remote it should be using the 300,310, 315, 372, 390 Frequencies. Most notably the 310, 315 and 390 as the others are only on a couple configurations.
RFCrack Scanning:
Since the most used ranges are 310, 315, 390 within our universal clicker, lets set RFCrack scanner to rotate through those and scan for signals.If a number of cars go through the gate and there are no captures we can adjust the scanner later over our wifi connection from a distance.
Currently Scanning: 433000000 To cancel hit enter and wait a few seconds
Example of logging output:
From the above output you will see that a frequency was found on 390. However, if you had left this running for a few hours you could easily see all of the output in the log file located in your RFCrack/scanning_logs directory.For example the following captures were found in the log file in an easily parseable format:
Analyzing the signal to determine toggle switches:
Ok sweet, now we have a valid signal which will open the gate. Of course we could just replay this and open the gate, but we are going to create a physical device we can pass along to whoever needs entry regardless if they understand RF. No need to fumble around with a computer and look suspicious.Also replaying a signal with RFCrack is just to easy, nothing new to learn taking the easy route.
The first thing we are going to do is graph the capture and take a look at the wave pattern it creates. This can give us a lot of clues that might prove beneficial in figuring out the toggle switch pattern found in remotes. There are a few ways we can do this. If you don't have a yardstick at home you can capture the initial signal with your cheap RTL-SDR dongle as we did in the first RF blog. We could then open it in audacity. This signal is shown below.
Let RFCrack Plot the Signal For you:
The other option is let RFCrack help you out by taking a signal from the log output above and let RFCrack plot it for you.This saves time and allows you to use only one piece of hardware for all of the work.This can easily be done with the following command:
From the graph output we see 2 distinct crest lengths and some junk at either end we can throw away. These 2 unique crests correspond to our toggle switch positions of up/down giving us the following 2 possible scenarios using a 9 toggle switch remote based on the 9 crests above:
Possible toggle switch scenarios:
down down up up up down down down down
up up down down down up up up up
Configuring a remote:
Proper toggle switch configuration allows us to program a universal remote that sends a signal to the gate. However even with the proper toggle switch configuration the remote has many different signals it sends based on the manufacturer or type of signal.In order to figure out which configuration the gate is using without physically watching the gate open, we will rely on local signal analysis/comparison.
Programming a remote is done by clicking the device with the proper toggle switch configuration until the gate opens and the correct manufacturer is configured. Since we don't have access to the gate after capturing the initial signal we will instead compare each signal from he remote to the original captured signal.
Comparing Signals:
This can be done a few ways, one way is to use an RTLSDR and capture all of the presses followed by visually comparing the output in audacity. Instead I prefer to use one tool and automate this process with RFCrack so that on each click of the device we can compare a signal with the original capture. Since there are multiple signals sent with each click it will analyze all of them and provide a percent likelihood of match of all the signals in that click followed by a comparing the highest % match graph for visual confirmation. If you are seeing a 80-90% match you should have the correct signal match.
Note:Not every click will show output as some clicks will be on different frequencies, these don't matter since our recon confirmed the gate is communicating on 390Mhz.
In order to analyze the signals in real time you will need to open up your clicker and set the proper toggle switch settings followed by setting up a sniffer and live analysis with RFCrack:
Open up 2 terminals and use the following commands:
#Setup a sniffer on 390mhz Setup sniffer:python RFCrack.py -k -c -f 390000000.
#Monitor the log file, and provide the gates original signal Setup Analysis: python RFCrack.py -c -u 1f0fffe0fffc01ff803ff007fe0fffc1fff83fff07ffe0007c -n.
Cmd switches used
-k = known frequency
-c = compare mode
-f = frequency
-n = no yardstick needed for analysis
Make sure your remote is configured for one of the possible toggle configurations determined above. In the below example I am using the first configuration, any extra toggles left in the down position: (down down up up up down down down down)
Analyze Your Clicks:
Now with the two terminals open and running click the reset switch to the bottom left and hold till it flashes. Then keep clicking the left button and viewing the output in the sniffing analysis terminal which will provide the comparisons as graphs are loaded to validate the output.If you click the device and no output is seen, all that means is that the device is communicating on a frequency which we are not listening on.We don't care about those signals since they don't pertain to our target.
At around the 11th click you will see high likelihood of a match and a graph which is near identical. A few click outputs are shown below with the graph from the last output with a 97% match.It will always graph the highest percentage within a click.Sometimes there will be blank graphs when the data is wacky and doesn't work so well. This is fine since we don't care about wacky data.
You will notice the previous clicks did not show even close to a match, so its pretty easy to determine which is the right manufacture and setup for your target gate. Now just click the right hand button on the remote and it should be configured with the gates setup even though you are in another location setting up for your test.
For Visual of the last signal comparison go to ./imageOutput/LiveComparison.png
----------Start Signals In Press--------------
Percent Chance of Match for press is: 0.05
Percent Chance of Match for press is: 0.14
Percent Chance of Match for press is: 0.14
Percent Chance of Match for press is: 0.12
----------End Signals In Press------------
For Visual of the last signal comparison go to ./imageOutput/LiveComparison.png
----------Start Signals In Press--------------
Percent Chance of Match for press is: 0.14
Percent Chance of Match for press is: 0.20
Percent Chance of Match for press is: 0.19
Percent Chance of Match for press is: 0.25
----------End Signals In Press------------
For Visual of the last signal comparison go to ./imageOutput/LiveComparison.png
----------Start Signals In Press--------------
Percent Chance of Match for press is: 0.93
Percent Chance of Match for press is: 0.93
Percent Chance of Match for press is: 0.97
Percent Chance of Match for press is: 0.90
Percent Chance of Match for press is: 0.88
Percent Chance of Match for press is: 0.44
----------End Signals In Press------------
For Visual of the last signal comparison go to ./imageOutput/LiveComparison.png
Graph Comparison Output for 97% Match:
Conclusion:
You have now walked through successfully reversing a toggle switch remote for a security gate. You took a raw signal and created a working device using only a Yardstick and RFCrack.This was just a quick tutorial on leveraging the skillsets you gained in previous blogs in order to learn how to analyzeRF signals within embedded devices. There are many scenarios these same techniques could assist in.We also covered a few new features in RF crack regarding logging, graphing and comparing signals.These are just a few of the features which have been added since the initial release. For more info and other features check the wiki.
In this post we present the new version of the Burp Suite extension EsPReSSO - Extension for Processing and Recognition of Single Sign-On Protocols. A DTD attacker was implemented on SAML services that was based on the DTD Cheat Sheet by the Chair for Network and Data Security (https://web-in-security.blogspot.de/2016/03/xxe-cheat-sheet.html). In addition, many fixes were added and a new SAML editor was merged. You can find the newest version release here: https://github.com/RUB-NDS/BurpSSOExtension/releases/tag/v3.1
New SAML editor
Before the new release, EsPReSSO had a simple SAML editor where the decoded SAML messages could be modified by the user. We extended the SAML editor so that the user has the possibility to define the encoding of the SAML message and to select their HTTP binding (HTTP-GET or HTTP-POST).
Redesigned SAML Encoder/Decoder
Enhancement of the SAML attacker
XML Signature Wrapping and XML Signature Faking attacks have already been part of the previous EsPReSSO version. Now the user can also perform DTD attacks! The user can select from 18 different attack vectors and manually refine them all before applying the change to the original message. Additional attack vectors can also be added by extending the XML config file of the DTD attacker. The DTD attacker can also be started in a fully automated mode. This functionality is integrated in the BurpSuite Intruder.
DTD Attacker for SAML messages
Supporting further attacks
We implemented a CertificateViewer which extracts and decodes the certificates contained within the SAML tokens. In addition, a user interface for executing SignatureExclusion attack on SAML has been implemented.
Additional functions will follow in later versions.
Currently we are working on XML Encryption attacks.
This is a combined work from Nurullah Erinola, Nils Engelbertz, David Herring, Juraj Somorovsky, and Vladislav Mladenov.
The research was supported by the European Commission through the FutureTrust project (grant 700542-Future-Trust-H2020-DS-2015-1).
AlienSpy Java based cross platform RAT is another reincarnation of ever popular Unrecom/Adwind and Frutas RATs that have been circulating through 2014.
It appears to be used in the same campaigns as was Unrccom/Adwind - see the references. If C2 responds, the java RAT downloads Jar files containing Windows Pony/Ponik loader. The RAT is crossplatform and installs and beacons from OSX and Linux as well. However, it did not download any additional malware while running on OSX and Linux.
The samples, pcaps, and traffic protocol information are available below.
File information
I File: DB46ADCFAE462E7C475C171FBE66DF82_paymentadvice.jar Size: 131178 MD5: DB46ADCFAE462E7C475C171FBE66DF82
Original jar attachment files B2856B11FF23D35DA2C9C906C61781BA_purchaseorder.jar DB46ADCFAE462E7C475C171FBE66DF82_paymentadvice.jar 79e9dd35aef6558461c4b93cd0c55b76_Purchase Order.jar
Alienspy RAT The following RAT config strings are extracted from memory dumps. Alienspy RAT is a reincarnated Unrecom/Adwind << Frutas RAT and is available from https://alienspy.net/ As you see by the config, it is very similar to Unrecom/Adwind File: paymentadvice.jar Size: 131178
%USERPROFILE%\Application Data\evt88IWdHO\CnREgyvLBS.txt <<MD5: abe6ef71e44d2e145033800d0dccea57 << strings are here (by classes) %USERPROFILE%\Application Data\evt88IWdHO\Desktop.ini %USERPROFILE%\Local Settings\Temp\asdqw15727804162199772615555.jar << Strings are here %USERPROFILE%\Local Settings\Temp\iWimMQLgpsT2624529381479181764.png (seen Transfer.jar in the stream) <<MD5: fab8de636d6f1ec93eeecaade8b9bc68 Size: 755017 << Strings are here
The following fields are part of the serialization protocol and are 'benign" and common.
AC ED(¬í) - Java Serialization protocol magic STREAM_MAGIC = (short)0xaced. 00 05 - Serialization Version STREAM_VERSION 75 (u) - Specifies that this is a new array - newArray: TC_ARRAY 72 (r) - Specifies that this is a new class - newClassDesc: TC_CLASSDESC 00 02 - Length of the class name 5B 42 AC F3 17 F8 06 08 54 E0 ([B¬ó.ø..Tà) This is a Serial class name and version identifier section but data appears to be encrypted 02 00 - Is Serializable Flag - SC_SERIALIZABLE 78 70 (xp) - some low-level information identifying serialized fields 1f 8b 08 00 00 00 00 00 00 00 - GZIP header as seen in the serialization stream
As you see, all Windows traffic captures have identical fields following the GZIP stream, while OSX traffic has different data. The jar files that had Pony Downloader payload did not have other OSX malware packaged and I saw no activity on OSX other than calling the C2 and writing to the randomly named timestamp file (e.g VblVc5kEqY.tmp - updating current timestamp in Unix epoch format)
Combination of the Stream Magic exchange, plus all other benign fields in this order will create a usable signature. However, it will be prone to false positives unless you use fields after the GZIP header for OS specific signatures
Another signature can be based on the transfer. jar download as seen below
DB46ADCFAE462E7C475C171FBE66DF82 - downloading fab8de636d6f1ec93eeecaade8b9bc68 iWimMQLgpsT2624529381479181764.png (seen Transfer.jar in the stream) , which contains 15555.jar in Manifest.mf, which contains 15555.exe (Pony loader) in its' Manfest.mf
IHEAKA _000C297 << IHEAKA is the name of the RAT client, it is different in each infection.
000ABBA0 00 09 00 00 00 31 35 35 35 35 2e 6a 61 72 74 97 .....155 55.jart. 000ABBB0 43 70 26 8c a2 44 63 db 9c d8 b6 9d 7c b1 6d db Cp&..Dc. ....|.m. 000ABBC0 c6 c4 b6 6d db b6 6d db 99 d8 76 f2 fe e5 dd bc ...m..m. ..v.....
Pony downloader traffic
HTTP requests URL: http://meetngreetindia.com/scala/gate.php TYPE: POST USER AGENT: Mozilla/4.0 (compatible; MSIE 5.0; Windows 98) URL: http://meetngreetindia.com/scala/gate.php TYPE: GET USER AGENT: Mozilla/4.0 (compatible; MSIE 5.0; Windows 98) DNS requests meetngreetindia.com (50.28.15.25) TCP connections 50.28.15.25:80
IP:50.28.15.25 Decimal:840699673 Hostname:mahanadi3.ewebguru.net ISP:Liquid Web Organization:eWebGuru State/Region:Michigan City:Lansing
II 79E9DD35AEF6558461C4B93CD0C55B76 Purchase order.jar IP:38.89.137.248 Decimal:643402232 Hostname:38.89.137.248 ISP:Cogent Communications Country:United States us flag
III 2856B11FF23D35DA2C9C906C61781BA Purchase order.jar installone.no-ip.biz IP Address: 185.32.221.17 Country: Switzerland Network Name: CH-DATASOURCE-20130812 Owner Name: Datasource AG From IP: 185.32.220.0 To IP: 185.32.223.255 Allocated: Yes Contact Name: Rolf Tschumi Address: mgw online service, Roetihalde 12, CH-8820 Waedenswil Email: rolf.tschumi@mgw.ch Abuse Email: abuse@softplus.net
Virustotal
https://www.virustotal.com/en/file/02d1e6dd2f3eecf809d8cd43b5b49aa76c6f322cf4776d7b190676c5f12d6b45/analysis/SHA256:02d1e6dd2f3eecf809d8cd43b5b49aa76c6f322cf4776d7b190676c5f12d6b45 MD5 db46adcfae462e7c475c171fbe66df82 SHA1 2b43211053d00147b2cb9847843911c771fd3db4 SHA256 02d1e6dd2f3eecf809d8cd43b5b49aa76c6f322cf4776d7b190676c5f12d6b45 ssdeep3072:VR/6ZQvChcDfJNBOFJKMRXcCqfrCUMBpXOg84WoUeonNTFN:LdvCGJN0FJ1RXcgBpXOjOjSNTFN File size 128.1 KB ( 131178 bytes ) File type ZIP Magic literalZip archive data, at least v2.0 to extract TrIDZIP compressed archive (100.0%) File name:Payment Advice.jar Detection ratio:6 / 54 Analysis date:2014-11-16 20:58:08 UTC ( 1 day, 4 hours ago ) IkarusTrojan.Java.Adwind20141116 TrendMicroJAVA_ADWIND.XXO20141116 TrendMicro-HouseCallJAVA_ADWIND.XXO20141116 DrWebJava.Adwind.320141116 KasperskyHEUR:Trojan.Java.Generic20141116 ESET-NOD32a variant of Java/Adwind.T20141116
