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Application SecuritySecurity

How to Prevent Real-Time API Abuse

April 18, 2019 — by Radware1

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The widespread adoption of mobile and IoT devices, and increased use of cloud systems are driving a major change in modern application architecture. Application Programming Interfaces (APIs) have emerged as the bridge to facilitate communication between different application architectures. However, with the widespread deployment of APIs, automated attacks on poorly protected APIs are mounting. Personally Identifiable Information (PII), payment card details, and business-critical services are at risk due to automated attacks on APIs.

API. application programming interface, cybersecurity, technology

So what are key API vulnerabilities, and how can you protect against API abuse?

Authentication Flaws

Many APIs only check authentication status, but not if the request is coming from a genuine user. Attackers exploit such flaws through various ways (including session hijacking and account aggregation) to imitate genuine API calls. Attackers also target APIs by reverse-engineering mobile apps to discover how it calls the API. If API keys are embedded into the app, this can result in an API breach. API keys should not be used alone for user authentication.

[You may also like: Are Your DevOps Your Biggest Security Risks?]

Lack of Robust Encryption

Many APIs lack robust encryptions between API client and API server. Attackers exploit such vulnerabilities through man-in-the-middle attacks. Attackers also intercept unencrypted or poorly protected API transactions between API client and API server to steal sensitive information or alter transaction data.

What’s more, the ubiquitous use of mobile devices, cloud systems, and microservice design patterns have further complicated API security as now multiple gateways are involved to facilitate interoperability among diverse web applications. The encryption of data flowing through all these channels is paramount.

[You may also like: HTTPS: The Myth of Secure Encrypted Traffic Exposed]

Business Logic Vulnerability

APIs are vulnerable to business logic abuse. Attackers make repeated and large-scale API calls on an application server or slow POST requests that result in denial of service. A DDoS attack on an API can result in massive disruption on a front-end web application.

Poor Endpoint Security

Most IoT devices and micro-service tools are programmed to communicate with their server through API channels. These devices authenticate themselves on API servers using client certificates. Hackers attempt to get control over an API from the IoT endpoint and if they succeed, they can easily re-sequence API order that can result in a data breach.

[You may also like: The Evolution of IoT Attacks]

How You Can Prevent API Abuse

A bot management solution that defends APIs against automated attacks and ensures that only genuine users have the ability to access APIs is paramount. When evaluating such a solution, consider whether it offers
broad attack detection and coverage, comprehensive reporting and analytics, and flexible deployment options.

Other steps you can (and should) take include:

  • Monitor and manage API calls coming from automated scripts (bots)
  • Drop primitive authentication
  • Implement measures to prevent API access by sophisticated human-like bots
  • Robust encryption is a must-have
  • Deploy token-based rate limiting equipped with features to limit API access based on the number of IPs, sessions, and tokens
  • Implement robust security on endpoints

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

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Security

Bot Managers Are a Cash-Back Program For Your Company

April 17, 2019 — by Ben Zilberman0

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In my previous blog, I briefly discussed what bot managers are and why they are needed. Today, we will conduct a short ROI exercise (perhaps the toughest task in information security!).

To recap: Bots generate a little over half of today’s internet traffic. Roughly half of that half (i.e. a quarter, for rusty ones like myself…) is generated by bad bots, a.k.a. automated programs targeting applications with the intent to steal information or disrupt service. Over the years, they have gotten so sophisticated, they can easily mimic human behavior, perform allegedly uncorrelated violation actions and essentially fool most of application security solutions out there.

Bot, bot management, traffic

These bots affect each and every arm of your business. If you are in the e-commerce or travel industries, no need to tell you that… if you aren’t, go to your next C-level executive meeting and look for those who scratch their heads the most. Why? Because they can’t understand where the money goes, and why the predicted performance didn’t materialize as expected.

Let’s go talk to these C-Suite executives, shall we?

Chief Revenue Officer

Imagine you are selling product online–whether that’s tickets, hotel rooms or even 30-pound dog food bags–and this is your principal channel for revenue generation. Now, imagine that bots act as faux buyers, and hold the inventory “hostage” so genuine customers can not access them.

[You may also like: Will We Ever See the End of Account Theft?]

Sure, you can elapse the process every 10 minutes, but as this is an automated program, it will re-initiate the process in a split second. And what about CAPTCHA? Don’t assume CAPTCHA will weed out all bots; some bots activate after a human has solved it. How would you know when you are communicating with a bot or a human? (Hint: you’d know if you had a bot management solution).

Wondering why the movie hall is empty half the time even though it’s a hot release? Does everybody go to the theater across the street? No. Bots are to blame. And they cause direct, immediate and painful revenue loss.

[You may also like: Bots 101: This is Why We Can’t Have Nice Things]

Chief Marketing Officer

Digital marketing tools, end-to-end automation of the customer journey, lead generation, and content syndication are great tools that help CMOs measure ROI and plan budgets. But what if the analysis they provide are false? What if half the clicks you are paying for are fictitious, and you were subject to a click-fraud campaign by bots? What if a competitor uses a bot to scrape data of registrants out of your landing pages? Unfortunately, bots often skew the analysis and can lead you to make wrong decisions that result in poor performance. Without bot management, you’re wasting money in vain.

Chief Operations Officer/Chief Information Officer

Does your team complain that your network resources are in the “red zone,” close to maximum performance, but your customer base isn’t growing at the same pace?

Blame bots.

[You may also like: Disaster Recovery: The Big, Bad Bot Problem]

Obviously some bots are “good,” like automated services that help accelerate and streamline your business, analyze data quickly and help you to make better decisions. However, bad bots (26% of the total traffic you are processing) put a load on your infrastructure and make your IT staff cry for more capacity. So you invest $200-500K in bigger firewalls, ADCs, and broader internet pipes, and upgrade your servers.

Next thing you know, a large DDoS attack from IoT botnets knocks everything down. If only you had invested $50k upfront to filter out the bad traffic from the get-go… That could’ve translated to $300k cash back!

Chief Information Security Officer

Every hour, a new security vendor knocks on your door with another solution for a 0.0001% probability what-if scenario… your budget is all over the place, spent on multiple protections and a complex architecture trying to take an actionable snapshot of what’s going on at every moment. At the end of the day, your task is to protect your company’s information assets. And there are so many ways to get a hold of those precious secrets!

[You may also like: CISOs, Know Your Enemy: An Industry-Wise Look At Major Bot Threats]

Bad bots are your enemy. They can scrape content, files, pricing, and intellectual property from your website. They can take over user accounts by cracking their passwords or launch a credential stuffing attack (and then retrieve their payment info). And they can take down service with DDoS attacks and hold up inventory, as I previously mentioned.

You can absolutely reduce these risks significantly if you could distinguish human versus bot traffic (remember, sophisticated bots today can mimic human behavior and bypass all sorts of challenges, not only CAPTCA), and more than that, which bot is legitimate and which is malicious.

[You may also like: Bot or Not? Distinguishing Between the Good, the Bad & the Ugly]

Bot management equals less risk, better posture, stable business, no budget increases or unexpected expenses. Cash back!

Chief Financial Officer

Your management peers could have made better investments, but now you have to clean up their mess. This can include paying legal fees and compensation to customers whose data was compromised, paying regulatory fines for coming up short in compliance, shelling out for a crisis management consultant firm, and absorbing costs associated with inventory hold up and downed service.

If you only had a bot management solution in place… so much cash back.

The Bottom Line

Run–do not walk–to your CEO and request a much-needed bot management solution. Not only does s/he have nothing to lose, s/he has a lot to gain.

* This week, Radware integrates bot management service with its cloud WAF for a complete, fully managed, application security suite.


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

Download Now

Application Delivery

Application SLA: Knowing Is Half the Battle

April 4, 2019 — by Radware0

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Applications have come to define the digital experience. They empower organizations to create new customer-friendly services, unlock data and content and deliver it to users at the time and device they desire, and provide a competitive differentiator over the competition.

Fueling these applications is the “digital core,” a vast plumbing infrastructure that includes networks, data repositories, Internet of Things (IoT) devices and more. If applications are a cornerstone of the digital experience, then managing and optimizing the digital core is the key to delivering these apps to the digitized user. When applications aren’t delivered efficiently, users can suffer from a degraded quality of experience (QoE), resulting in a tarnished brand, negatively affecting customer loyalty and lost revenue.

Application delivery controllers (ADCs) are ideally situated to ensure QoE, regardless of the operational scenario, by allowing IT to actively monitor and enforce application SLAs. The key is to understand the role ADCs play and the capabilities required to ensure the digital experience across various operational scenarios.

Optimize Normal Operations

Under normal operational conditions, ADCs optimize application performance, control and allocate resources to those applications and provide early warnings of potential issues.

[You may also like: 6 Must-Have Metrics in Your SLA]

For starters, any ADC should deliver web performance optimization (WPO) capabilities to turbocharge the performance of web-based applications. It transforms front-end optimization from a lengthy and complex process into an automated, streamlined function. Caching, compression, SSL offloading and TCP optimization are all key capabilities and will enable faster communication between the client and server while offloading CPU intensive tasks from the application server.

Along those same lines, an ADC can serve as a “bridge” between the web browsers that deliver web- based applications and the backend servers that host the applications. For example, HTTP/2 is the new standard in network protocols. ADCs can serve as a gateway between the web browsers that support HTTP/2 and backend servers that still don’t, optimizing performance to meet application SLAs.

Prevent Outages

Outages are few and far between, but when they occur, maintaining business continuity is critical via server load balancing, leveraging cloud elasticity and disaster recovery. ADCs play a critical role across all three and execute and automate these processes during a time of crisis.

[You may also like: Security Pros and Perils of Serverless Architecture]

If an application server fails, server load balancing should automatically redirect the client to another server. Likewise, in the event that an edge router or network connection to the data center fails, an ADC should automatically redirect to another data center, ensuring the web client can always access the application server even when there is a point of failure in the network infrastructure.

Minimize Degradation

Application SLA issues are most often the result of network degradation. The ecommerce industry is a perfect example. A sudden increase in network traffic during the holiday season can result in SLA degradation.

Leveraging server load balancing, ADCs provide elasticity by provisioning resources on-demand. Additional servers are added to the network infrastructure to maintain QoE, and after the spike has passed, returned to an idle state for use elsewhere. In addition, virtualized ADCs provide an additional benefit, as they provide scalability and isolation between vADC instance at the fault, management and network levels.

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

Finally, cyberattacks are the silent killers of application performance, as they typically create degradation. ADCs play an integrative role in protecting applications to maintain SLAs at all times.   They can prevent attack traffic from entering a network’s LAN and prevent volumetric attack traffic from saturating the Internet pipe.

The ADC should be equipped with security capabilities that allow it to be integrated into the security/ DDoS mitigation framework. This includes the ability to inspect traffic and network health parameters so the ADC serves as an alarm system to signal attack information to a DDoS mitigation solution. Other interwoven safety features should include integration with web application firewalls (WAFs), ability to decrypt/encrypt SSL traffic and device/user fingerprinting.

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

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Application SecurityAttack Types & VectorsBotnetsSecurity

Are Connected Cows a Hacker’s Dream?

April 3, 2019 — by Mike O'Malley0

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Humans aren’t the only ones consumed with connected devices these days. Cows have joined our ranks.

Believe it or not, farmers are increasingly relying on IoT devices to keep their cattle connected. No, not so that they can moo-nitor (see what I did there?) Instagram, but to improve efficiency and productivity. For example, in the case of dairy farms, robots feed, milk and monitor cows’ health, collecting data along the way that help farmers adjust techniques and processes to increase milk production, and thereby profitability.

The implications are massive. As the Financial Times pointed out, “Creating a system where a cow’s birth, life, produce and death are not only controlled but entirely predictable could have a dramatic impact on the efficiency of the dairy industry.”

From Dairy Farm to Data Center

So, how do connected cows factor into cybersecurity? By the simple fact that the IoT devices tasked with milking, feeding and monitoring them are turning dairy farms into data centers – which has major security implications. Because let’s face it, farmers know cows, not cybersecurity.

Indeed, the data collected are stored in data centers and/or a cloud environment, which opens farmers up to potentially costly cyberattacks. Think about it: The average U.S. dairy farm is a $1 million operation, and the average cow produces $4,000 in revenue per year. That’s a lot at stake—roughly $19,000 per week, given the average dairy farm’s herd—if a farm is struck by a ransomware attack.

[You may also like: IoT Expands the Botnet Universe]

It would literally be better for an individual farm to pay a weekly $2,850 ransom to keep the IoT network up. And if hackers were sophisticated enough to launch an industry-wide attack, the dairy industry would be better off paying $46 million per week in ransom rather than lose revenue.

5G Cows

Admittedly, connected cows aren’t new; IoT devices have been assisting farmers for several years now. And it’s a booming business. Per the FT, “Investment in precision ‘agtech’ systems reached $3.2bn globally in 2016 (including $363m in farm management and sensor technology)…and is set to grow further as dairy farms become a test bed for the wider IoT strategy of big technology companies.”

[You may also like: Securing the Customer Experience for 5G and IoT]

But what is new is the rollout of 5G networks, which promise faster speeds, low latency and increased flexibility—seemingly ideal for managing IoT devices. But, as we’ve previously discussed, with new benefits come new risks. As network architectures evolve to support 5G, security vulnerabilities will abound if cybersecurity isn’t prioritized and integrated into a 5G deployment from the get-go.

In the new world of 5G, cyberattacks can become much more potent, as a single hacker can easily multiply into an army through botnet deployment. Indeed, 5G opens the door to a complex world of interconnected devices that hackers will be able to exploit via a single point of access in a cloud application to quickly expand an attack radius to other connected devices and applications. Just imagine the impact of a botnet deployment on the dairy industry.

[You may also like: IoT, 5G Networks and Cybersecurity: A New Atmosphere for Mobile Network Attacks]

I don’t know about you, but I like my milk and cheeses. Here’s to hoping dairy farmers turn to the experts to properly manage their security before the industry is hit with devastating cyberattacks.

2018 Mobile Carrier Ebook

Read “Creating a Secure Climate for your Customers” today.

Download Now

Attack Types & VectorsBotnetsSecurity

IoT Expands the Botnet Universe

March 6, 2019 — by Radware1

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In 2018, we witnessed the dramatic growth of IoT devices and a corresponding increase in the number of botnets and cyberattacks. Because IoT devices are always-on, rarely monitored and generally use off-the-shelf default passwords, they are low-hanging fruit for hackers looking for easy ways to build an army of malicious attackers. Every IoT device added to the network grows the hacker’s tool set.

Botnets comprised of vulnerable IoT devices, combined with widely available DDoS-as-a-Service tools and anonymous payment mechanisms, have pushed denial-of-service attacks to record-breaking volumes. At the same time, new domains such as cryptomining and credentials theft offer more opportunities for hacktivism.

Let’s look at some of the botnets and threats discovered and identified by Radware’s deception network in 2018.

JenX

A new botnet tried to deliver its dangerous payload to Radware’s newly deployed IoT honeypots. The honeypots registered multiple exploit attempts from distinct servers, all located in popular cloud hosting providers based in Europe. The botnet creators intended to sell 290Gbps DDoS attacks for only $20. Further investigation showed that the new bot used an atypical central scanning method through a handful of Linux virtual private servers (VPS) used to scan, exploit and load malware onto unsuspecting IoT victims. At the same time, the deception network also detected SYN scans originating from each of the exploited servers indicating that they were first performing a
mass scan before attempting to exploit the IoT devices, ensuring that ports 52869 and 37215 were open.

[You may also like: IoT Botnets on the Rise]

ADB Miner

A new piece of malware that takes advantage of Android-based devices exposing debug capabilities to the internet. It leverages scanning code from Mirai. When a remote host exposes its Android Debug Bridge (ADB) control port, any Android emulator on the internet has full install, start, reboot and root shell access without authentication.

Part of the malware includes Monero cryptocurrency miners (xmrig binaries), which are executing on the infected devices. Radware’s automated trend analysis algorithms detected a significant increase in activity against port 5555, both in the number of hits and in the number of distinct IPs. Port 5555 is one of the known ports used by TR069/064 exploits, such as those witnessed during the Mirai-based attack targeting Deutsche Telekom routers in November 2016. In this case, the payload delivered to the port was not SOAP/HTTP, but rather the ADB remote debugging protocol.

Satori.Dasan

Less than a week after ADB Miner, a third new botnet variant triggered a trend alert due to a significant increase in malicious activity over port 8080. Radware detected a jump in the infecting IPs from around 200 unique IPs per day to over 2,000 malicious unique IPs per day. Further investigation by the research team uncovered a new variant of the Satori botnet capable of aggressive scanning and exploitation of CVE-2017-18046 — Dasan Unauthenticated Remote Code Execution.

[You may also like: New Satori Botnet Variant Enslaves Thousands of Dasan WiFi Routers]

The rapidly growing botnet referred to as “Satori.Dasan” utilizes a highly effective wormlike scanning mechanism, where every infected host looks for more hosts to infect by performing aggressive scanning of random IP addresses and exclusively targeting port 8080. Once a suitable target is located, the infected bot notifies a C2 server, which immediately attempts to infect the new victim.

Memcached DDoS Attacks

A few weeks later, Radware’s system provided an alert on yet another new trend — an increase in activity on UDP port 11211. This trend notification correlated with several organizations publicly disclosing a trend in UDP-amplified DDoS attacks utilizing Memcached servers configured to accommodate UDP (in addition to the default TCP) without limitation. After the attack, CVE2018-1000115 was published to patch this vulnerability.

Memcached services are by design an internal service that allows unauthenticated access requiring no verification of source or identity. A Memcached amplified DDoS attack makes use of legitimate third-party Memcached servers to send attack traffic to a targeted victim by spoofing the request packet’s source IP with that of the victim’s IP. Memcached provided record-breaking amplification ratios of up to 52,000x.

[You may also like: Entering into the 1Tbps Era]

Hajime Expands to MikroTik RouterOS

Radware’s alert algorithms detected a huge spike in activity for TCP port 8291. After near-zero activity on that port for months, the deception network registered over 10,000 unique IPs hitting port 8291 in a single day. Port 8291 is related to a then-new botnet that exploits vulnerabilities in the MikroTik RouterOS operating system, allowing attackers to remotely execute code on the device.

The spreading mechanism was going beyond port 8291, which is used almost exclusively by MikroTik, and rapidly infecting other devices such as AirOS/Ubiquiti via ports: 80, 81, 82, 8080, 8081, 8082, 8089, 8181, 8880, utilizing known exploits and password-cracking attempts to speed up the propagation.

Satori IoT Botnet Worm Variant

Another interesting trend alert occurred on Saturday, June 15. Radware’s automated algorithms alerted to an upsurge of malicious activity scanning and infection of a variety of IoT devices by taking advantage of recently discovered exploits. The previously unseen payload was delivered by the infamous Satori botnet. The exponential increase in the number of attack sources spread all over the world, exceeding 2,500 attackers in a 24-hour period.

[You may also like: A Quick History of IoT Botnets]

Hakai

Radware’s automation algorithm monitored the rise of Hakai, which was first recorded in July. Hakai is a new botnet recently discovered by NewSky Security after lying dormant for a while. It started to infect D-Link, Huawei and Realtek routers. In addition to exploiting known vulnerabilities to infect the routers, it used a Telnet scanner to enslave Telnet-enabled devices with default credentials.

DemonBot

A new stray QBot variant going by the name of DemonBot joined the worldwide hunt for yellow elephant — Hadoop cluster — with the intention of conscripting them into an active DDoS botnet. Hadoop clusters are typically very capable, stable platforms that can individually account for much larger volumes of DDoS traffic compared to IoT devices. DemonBot extends the traditional abuse of IoT platforms for DDoS by adding very capable big data cloud servers. The DDoS attack vectors supported by DemonBot are STD, UDP and TCP floods.

Using a Hadoop YARN (Yet-Another-Resource-Negotiator) unauthenticated remote command execution, DemonBot spreads only via central servers and does not expose the wormlike behavior exhibited by Mirai-based bots. By the end of October, Radware tracked over 70 active exploit servers that are spreading malware
and exploiting YARN servers at an aggregated rate of over one million exploits per day.

[You may also like: Hadoop YARN: An Assessment of the Attack Surface and Its Exploits]

YARN allows multiple data processing engines to handle data stored in a single Hadoop platform. DemonBot took advantage of YARN’s REST API publicly exposed by over 1,000 cloud servers worldwide. DemonBot effectively harnesses the Hadoop clusters in order to generate a DDoS botnet powered by cloud infrastructure.

Always on the Hunt

In 2018, Radware’s deception network launched its first automated trend-detection steps and proved its ability to identify emerging threats early on and to distribute valuable data to the Radware mitigation devices, enabling them to effectively mitigate infections, scanners and attackers. One of the most difficult aspects in automated anomaly detection is to filter out the massive noise and identify the trends that indicate real issues.

In 2019, the deception network will continue to evolve and learn and expand its horizons, taking the next steps in real-time automated detection and mitigation.

Read “The Trust Factor: Cybersecurity’s Role in Sustaining Business Momentum” to learn more.

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Mobile SecurityService Provider

Here’s How Carriers Can Differentiate Their 5G Offerings

February 28, 2019 — by Mike O'Malley0

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Much of the buzz surrounding this year’s Mobile World Congress has focused on “cool” tech innovations. There are self-driving cars, IoT-enhanced bee hives, smart textiles that monitor your health, realistic human chatbots, AI robots, and so forth. But, one piece of news that has flown relatively under the radar is the pending collaboration between carriers for 5G implementation.

A Team Effort

As Bloomberg reported, carriers from Vodafone Group Plc, Telecom Italia SpA and Telefonica SA are willing to call “a partial truce” to help each other build 5G infrastructure in an attempt “to avoid duplication and make scarce resources go further.”

Sounds great (who doesn’t love a solid team effort?!)…except for one thing: the pesky issue of competing for revenue streams in an industry fraught with financial challenges. As the Bloomberg article pointed out, “by creating more interdependent and overlapping networks, the risk is that each will find it harder to differentiate their offering.”

[You may also like: Securing the Customer Experience for 5G and IoT]

While this is certainly a valid concern, there is an obvious solution: If carriers are looking for differentiation in a collaborative environment, they need to leverage security as a competitive advantage.

Security as a Selling Point

As MWC19 is showing us in no uncertain terms, IoT devices—from diabetic smart socks to dairy milking monitors—are the way of the future. And they will largely be powered by 5G networks, beginning as early as this year.

Smart boot and sock monitor blood sugar, pulse rate, temperature and more for diabetics.

Which is all to say, although carriers are nervous about setting themselves apart while they work in partnership to build 5G infrastructure, there’s a huge opportunity to differentiate themselves by claiming ownership of IoT device security.

[You may also like: Don’t Be A “Dumb” Carrier]

As I recently wrote, IoT devices are especially vulnerable because of manufacturers’ priority to maintain low costs, rather than spending more on additional security features. If mobile service providers create a secure environment, they can establish a competitive advantage and reap financial rewards.

Indeed, best-of-breed security opens the possibility for capturing new revenue streams; mobile IoT businesses will pay an additional service premium for the peace of mind that their devices will be secure and can maintain 100% availability. And if a competing carrier suffers a data breach, for example, you can expect their customer attrition to become your win.

My words of advice: Collaborate. But do so while holding an ace—security—in your back pocket.

2018 Mobile Carrier Ebook

Read “Creating a Secure Climate for your Customers” today.

Download Now

Mobile SecurityService Provider

Securing the Customer Experience for 5G and IoT

February 21, 2019 — by Louis Scialabba1

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5G is set to bring fast speeds, low latency and more data to the customer experience for today’s digitized consumer. Driven by global demand for 24×7 high-speed internet access, the business landscape will only increase in competitiveness as service providers jockey to deliver improved network capabilities.

Although the mass roll-out of the cutting-edge technology is expected around 2020, the race to 5G deployment has already begun. In addition to serving as the foundation for the aforementioned digital transformation, 5G networks will also deliver the integral infrastructure required for increased agility and flexibility.


But with new benefits come new risks. As network architectures evolve to support 5G, it will leave security vulnerabilities if cybersecurity isn’t prioritized and integrated into a 5G deployment from the get-go to provide a secure environment that safeguards customers’ data and devices.

Cybersecurity for 5G shouldn’t be viewed as an additional operational cost, but rather as a business opportunity/competitive differentiator that is integrated throughout the overall architecture. Just as personal data has become a commodity in today’s world, carriers will need the right security solution to keep data secure while improving the customer experience via a mix of availability and security.

For more insight into how service providers can mitigate the business risks of 5G deployment, please read our white paper.

2018 Mobile Carrier Ebook

Read “Creating a Secure Climate for your Customers” today.

Download Now

Mobile SecurityService Provider

Don’t Be A “Dumb” Carrier

February 12, 2019 — by Mike O'Malley0

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By next year, it is estimated that there will be 20.4 billion IoT devices, with businesses accounting for roughly 7.6 billion of them. While these devices are the next wireless innovation to improve productivity in an ever-connected world, they also represent nearly 8 billion opportunities for breaches or attacks.

In fact, 97% of companies believe IoT devices could wreak havoc on their organizations, and with good reason. Security flaws can leave millions of devices vulnerable, creating pathways for cyber criminals to exfiltrate data—or worse. For example, a July 2018 report disclosed that nearly 500 million IoT devices were susceptible to cyberattacks at businesses worldwide because of a decade old web exploit.

A New Attack Environment

In other words, just because these devices are new and innovative doesn’t mean your security is, too. To further complicate matters, 5G networks will begin to roll out in 2020, creating a new atmosphere for mobile network attacks. Hackers will be able to exploit IoT devices and leverage the speed, low latency and high capacity of 5G networks to launch unprecedented volumes of sophisticated attacks, ranging from standard IoT attacks to burst attacks, and even smartphone infections and mobile operating system malware.

Scary stuff.

[You may also like: IoT, 5G Networks and Cybersecurity: A New Atmosphere for Mobile Network Attacks]

So, who is responsible for securing these billions of devices to ensure businesses and consumers alike are protected?  Well, right now, nobody. And there’s no clear agreement on what entity is—or should be—held accountable. According to Radware’s 2017-2018 Global Application & Network Security Report, 34% believe the device manufacturer is responsible, 11% believe service providers are, 21% think it falls to the private consumer, and 35% believe business organizations should be liable.

Ownership Is Opportunity

Indeed, no one group is raising its hand to claim ownership of IoT device security. But if service providers want to protect their networks and customers, they should jump at the chance to take the lead here. While service providers technically don’t own the emerging security issues, it is ultimately the operators who are best positioned to deal with and mitigate attack traffic. While many may view this as an operational cost, it is, in actuality, a business opportunity.

In fact, the Japanese government is so concerned about a large scale IoT attack disrupting the 2020 Tokyo Olympics, they just passed a law empowering the government to intentionally identify and hack vulnerable IoT devices.  And who is the government asking to secure the list of devices they find vulnerable? Consumers? Businesses? Manufacturers?  No, No, and NO.  They are asking service providers to secure these devices from attacks.

[You may also like: IoT, 5G Networks and Cybersecurity: Safeguarding 5G Networks with Automation and AI]

Think about it: Every device connected to a network is another potential security weakness. And as we’ve written about previously, IoT devices are especially vulnerable because of manufacturers’ priority to maintain low costs, rather than spending more on additional security features. If mobile service providers create a secure environment that satisfies the protection of customer data and devices, they can establish a competitive advantage and reap financial rewards.

From Opportunity to Rewards

This translates to the potential for capturing new revenue streams. If your mobile network is more secure than your competitors’, it stands to reason that their customer attrition becomes your win. And mobile IoT businesses will pay an additional service premium for the knowledge that their IoT devices won’t be compromised and can maintain 100% availability.

[You may also like: The Rise of 5G Networks]

What’s more, service providers need to be mindful of history repeating itself. After providers lost the war with Apple and Google to control apps (and their associated revenue), they earned the unfortunate reputation of being “dumb pipes.” Conversely, Apple and Google were heralded for capturing all the value of the explosion of mobile data apps. Apple now sits with twice the valuation as AT&T and Verizon, COMBINED.  Now, as we are on the precipice of a similar explosion of IoT apps that enterprises will buy, the question again arises over whether service providers will just sell “dumb pipes” or whether they will get involved in the value chain.

A word to the wise: Don’t be a “dumb” carrier. Be smart.  Secure the customer experience and reap the benefits.

2018 Mobile Carrier Ebook

Read “Creating a Secure Climate for your Customers” today.

Download Now

Attack Types & VectorsBotnets

Attackers Are Leveraging Automation

January 31, 2019 — by Radware0

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Cybercriminals are weaponizing automation and machine learning to create increasingly evasive attack vectors, and the internet of things (IoT) has proven to be the catalyst driving this trend. IoT is the birthplace of many of the new types of automated bots and malware.

At the forefront are botnets, which are increasingly sophisticated, lethal and highly automated digitized armies running amok on corporate networks. For example, hackers now leverage botnets to conduct early exploitation and network reconnaissance prior to unleashing an attack.

The Mirai botnet, which was made famous by its use in the 2016 attack on DNS provider Dyn, along with its subsequent variants, embodies many of these characteristics. It leverages a network-scanning and attack architecture capable of identifying “competing” malware and removing it from the IoT device to block remote administrative control. In addition, it leverages the infamous Water Torture attack to generate randomized domain names on a DNS infrastructure. Follow-up variants use automation to allow the malware to craft malicious queries in real time.

[You may also like: A Quick History of IoT Botnets]

Modern-day malware is an equally sophisticated multi-vector cyberattack weapon designed to elude detection using an array of evasion tools and camouflage techniques. Hackers now leverage machine learning to create custom malware that defeats anti-malware defenses. One example is Generative Adversarial Network algorithms
that can bypass black-box machine-learning models. In another example, a cybersecurity company adapted Elon Musk’s OpenAI framework to create forms of malware that mitigation solutions couldn’t detect.

Automation for Detection and Mitigation

So how does a network security team improve its ability to deal with these increasingly multifarious cyberattacks? Fight fire with fire. Automated cybersecurity solutions provide the data-processing muscle to mitigate these advanced threats.

Executives clearly understand this and are ready to take advantage of automation. According to Radware’s C-Suite Perspectives: Trends in the Cyberattack Landscape, Security Threats and Business Impacts report, the vast majority of executives (71%) report shifting more of their network security budget into technologies that employ machine learning and automation. The need to protect increasingly heterogeneous infrastructures, a shortage in cybersecurity talent and increasingly dangerous
cyberthreats were indicated as the primary drivers of this fiscal shift.

In addition, the trust factor is increasing. Four in 10 executives trust automated systems more than humans to protect their organization against cyberattacks.

[You may also like: Looking Past the Hype to Discover the Real Potential of AI]

Traditional DDoS solutions use rate limiting and manual signature creation to mitigate attacks. Rate limiting can be effective but can also result in a high number of false positives. As a result, manual signatures are then used to block offending traffic to reduce the number of false positives. Moreover, manual signatures take time to create because identifying offending traffic is only possible AFTER the attack starts. With machine-learning botnets now breaching defenses in less than 20 seconds, this hands-on strategy does not suffice.

Automation and, more specifically, machine learning overcome the drawbacks of manual signature creation and rate-limiting protection by automatically creating signatures and adapting protections to changing attack vectors. Machine learning leverages advanced mathematical models and algorithms to look at baseline network parameters, assess network behavior, automatically create attack signatures and adapt security configurations and/or policies to mitigate attacks. Machine learning transitions an organization’s DDoS protection strategy from manual, ratio- and rate-based protection to behavioral-based detection and mitigation.

The Final Step: Self-Learning

A market-leading DDoS protection solution combines machine-learning capabilities with negative and positive security protection models to mitigate automated attack vectors, such as the aforementioned DNS Water Torture attacks made notorious by Mirai. By employing machine learning and ingress-only positive protection models, this sort of an attack vector is eliminated, regardless of whether the protected DNS infrastructure is an authoritative or a recursive DNS.

The final step of automated cybersecurity is automated self-learning. DDoS mitigation solutions should leverage a deep neural network (DNN) that conducts post-analysis of all the generated data, isolates known attack information and feeds those data points back into the machine learning algorithms. DNNs require massive amounts of storage and computing power and can be prohibitively expensive to house and manage within a privately hosted data center.

[You may also like: Are Application Testing Tools Still Relevant with Self Learning WAFs?]

As a result, ideally a DNN is housed and maintained by your organization’s DDoS mitigation vendor, which leverages its network of cloud-based scrubbing centers (and the massive volumes of threat intelligence data that it collects) to process this information via big data analytics and automatically feed it back into your organization’s DDoS mitigation solution via a real-time threat intelligence feed.This makes the input of thousands of malicious IPs and new attack signatures into an automated process that no SOC team could ever hope to accomplish manually.

The result is a DDoS mitigation system that automatically collects data from multiple sources and leverages machine learning to conduct zero-day characterization. Attack signatures and security policies are automatically updated and not reliant on a SOC engineer who is free to conduct higher-level analysis, system management and threat analysis.

Automation is the future of cybersecurity. As cybercriminals become more savvy and increasingly rely on automation to achieve their mischievous goals, automation and machine learning will become the cornerstone of cybersecurity solutions to effectively combat the onslaught from the next generation of attacks. It will allow organizations to improve the ability to scale network security teams, minimize human errors and safeguard digital assets to ensure brand reputation and the customer experience.

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

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Attack MitigationSecurity

Looking Past the Hype to Discover the Real Potential of AI

January 22, 2019 — by Pascal Geenens1

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How can organizations cut through the hype around AI to understand the most important issues they should be addressing? How can they incorporate AI into their security strategies now to take advantage of the technology’s ability to detect and mitigate attacks that incorporate the same capabilities? Pascal Geenens, Radware’s EMEA security evangelist, weighs in.

What is the threat landscape, and how disruptive is it likely to be?

In the near term, cybercriminals will mainly use AI to automate attacks and improve evasion capabilities against detection systems and to increase the scale and reach of the threats. Expect to see AI used to automatically breach defenses and generate more sophisticated phishing attacks from information scraped from publicly accessible web sources. The scale of attacks will quickly escalate to volumes that we have never experienced before.

On the evasive side, machine-learning systems such as generative adversarial networks (GANs) can automatically create malware that is harder to detect and block. This technique has already been demonstrated by researchers. The MalGAN research project proposed a GAN to create evasive malware that goes undetected by all modern anti-malware systems, even the systems based on deep learning.

[You may also like: How Cyberattacks Directly Impact Your Brand: New Radware Report]

In the first phase, AI will be used to improve current attack tools to make them more harmful and difficult to detect.

Machine learning and automation can be leveraged to find new vulnerabilities, especially in large public clouds where cloud native systems are being built based on widely reused open-source software frameworks. Platforms running this software will become primary targets for vulnerability scanning.

Given that open-source code is readable and accessible by both criminals and security researchers, this platform may become the next battlefield with an associated “arms race” to  discover, abuse or fix vulnerabilities.  Deep learning will provide an advantage  in discovering new vulnerabilities based on code. While open source is an easier target, even closed-source software will not escape automated attacks based on the learning process of the attack program.

Looking further ahead, I can imagine large cybercrime organizations or nation-states using AI. Where machine learning was previously used mainly for automating attacks, now AI systems such as genetic algorithms and reinforced learning will be used to automatically generate new attack vectors and breach all kinds of systems, whether cloud, IoT or ICS. Then, combine this capability with the automation of the first stage. We will face a fully automated, continuously evolving attack ecosystem that will hack, crack and improve itself over time with no limits in scale or endurance.

[You may also like: DevOps: Application Automation? The Inescapable Path]

Cybercriminals could move from being the actual hackers, performing the real attack and penetrating defenses, to becoming maintainers and developers of the automated AI hacking machine. Machines will do the hacking; humans will focus on improving efficiency of the machines.

What vulnerabilities will make targets more attractive to criminals once AI is incorporated in their tools? How will it affect corporate espionage?

Ultimately every organization will be digitally transformed and become a primary target for automated attacks. Which targets are chosen will be solely dependent on the objective of the attack. For ransom and extortion, every organization is a good candidate target. For corporate espionage, it depends how much organizations are willing to pay to secure intellectual property in certain areas. It’s fair to say that, by definition, every organization can — and, at some point, will — be a target.

What about politically motivated cyberattacks initiated at the national level?

We’ve already witnessed attacks meant to influence public  opinion and the political landscape. Such attacks are likely to grow and become more difficult to identify early in the process and to protect against once attackers leverage deep learning and broader AI technologies. Attackers have already produced automatically generated messages and discussions, as well as “deep fake” videos that are created by AI algorithms.

[You may also like: Hacking Democracy: Vulnerable Voting Infrastructure and the Future of Election Security]

Influencing what topics are important and  manipulating opinions are becoming new weapons of choice for nation-states. Social platform providers need to take a stance and remain as clean as possible by dedicating much of their own AI-assisted automated detection systems to stay ahead of cybercriminals and others that create and improve AI-assisted automated systems for fake content creation.

From a defense perspective, what types of AI-based products will be used to combat more technologically savvy cybercriminals?

There’s a saying in our industry that “you cannot stop what you cannot detect.” Cybersecurity has become automated for the sake of the detection of new, increasingly complex and continuously adapting threats, and deep learning is improving that capability. AI, in the broad sense of the term, will probably come into play in the near-term future rather than immediately. The current state of AI in the defense discussion is confined to the traditional machine learning, and while deep learning shows a lot of promise, it is still too challenged to be used for automated mitigation. More intelligent and self-adaptive systems, the domain of AI, are still further out when it comes to automating our cyberdefenses.

Will the use of AI-based attacks by cybercriminals drive adoption of AI-based mitigation solutions by enterprises, organizations and institutions?

Yes, but not necessarily at the same pace. There are three factors to consider — the attack vector, its speed and its evasion technique:

  1. For example, using AI for phishing does not affect the victim in terms of change in attack vector, but it does increase the scale and number of targets, compelling every organization to improve its This protection might include AI-based systems, but not necessarily.
  2. On the other hand, as attacks get more automated, organizations will have to automate their security to ensure that they keep on top of the rising number and accelerated speed of attacks.
  3. When new evasion techniques based on AI are leveraged by cybercriminals, it will ultimately lead to the use of better detection systems that are based on AI.

Read “The Trust Factor: Cybersecurity’s Role in Sustaining Business Momentum” to learn more.

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