main

Attack MitigationDDoSSecurity

DDoS Protection Requires Looking Both Ways

March 26, 2019 — by Eyal Arazi0

ddos-960x540.jpg

Service availability is a key component of the user experience. Customers expect services to be constantly available and fast-responding, and any downtime can result in disappointed users, abandoned shopping carts, and lost customers.

Consequently, DDoS attacks are increasing in complexity, size and duration. Radware’s 2018 Global Application and Network Security Report found that over the course of a year, sophisticated DDoS attacks, such as burst attacks, increased by 15%, HTTPS floods grew by 20%, and over 64% of customers were hit by application-layer (L7) DDoS attacks.

Some Attacks are a Two-Way Street

As DDoS attacks become more complex, organizations require more elaborate protections to mitigate such attacks. However, in order to guarantee complete protection, many types of attacks – particularly the more sophisticated ones – require visibility into both inbound and outbound channels.

Some examples of such attacks include:

Out of State Protocol Attacks: Some DDoS attacks exploit weaknesses in protocol communication processes, such as TCP’s three-way handshake sequence, to create ‘out-of-state’ connection requests, thereby drawing-out connection requests in order to exhaust server resources. While some attacks of this type, such as a SYN flood, can be stopped by examining the inbound channel only, others require visibility into the outbound channel, as well.

An example of this is an ACK flood, whereby attackers continuously send forged TCP ACK packets towards the victim host. The target host then tries to associate the ACK reply to an existing TCP connection, and if none such exists, it will drop the packet. However, this process consumes server resources, and large numbers of such requests can deplete system resources. In order to correctly identify and mitigate such attacks, defenses need visibility to both inbound SYN and outbound SYN/ACK replies, so that they can verify whether the ACK packet is associated with any legitimate connection request.

[You may also like: An Overview of the TCP Optimization Process]

Reflection/Amplification Attacks: Such attacks exploit asymmetric responses between the connection requests and replies of certain protocols or applications. Again, some types of such attacks require visibility into both the inbound and outbound traffic channels.

An example of such attack is a large-file outbound pipe saturation attack. In such attacks, the attackers identify a very large file on the target network, and send a connection request to fetch it. The connection request itself can be only a few bytes in size, but the ensuing reply could be extremely large. Large amounts of such requests can clog-up the outbound pipe.

Another example are memcached amplification attacks. Although such attacks are most frequently used to overwhelm a third-party target via reflection, they can also be used to saturate the outbound channel of the targeted network.

[You may also like: 2018 In Review: Memcache and Drupalgeddon]

Scanning Attacks: Large-scale network scanning attempts are not just a security risk, but also frequently bear the hallmark of a DDoS attack, flooding the network with malicious traffic. Such scan attempts are based on sending large numbers of connection requests to host ports, and seeing which ports answer back (thereby indicating that they are open). However, this also leads to high volumes of error responses by closed ports. Mitigation of such attacks requires visibility into return traffic in order to identify the error response rate relative to actual traffic, in order for defenses to conclude that an attack is taking place.

Server Cracking: Similar to scanning attacks, server cracking attacks involve sending large amounts of requests in order to brute-force system passwords. Similarly, this leads to a high error reply rate, which requires visibility into both the inbound and outbound channels in order to identify the attack.

Stateful Application-Layer DDoS Attacks: Certain types of application-layer (L7) DDoS attacks exploit known protocol weaknesses or order to create large amounts of spoofed requests which exhaust server resources. Mitigating such attacks requires state-aware bi-directional visibility in order to identify attack patterns, so that the relevant attack signature can be applied to block it. Examples of such attacks are low-and-slow and application-layer (L7) SYN floods, which draw-out HTTP and TCP connections in order to continuously consume server resources.

[You may also like: Layer 7 Attack Mitigation]

Two-Way Attacks Require Bi-Directional Defenses

As online service availability becomes ever-more important, hackers are coming up with more sophisticated attacks than ever in order to overwhelm defenses. Many such attack vectors – frequently the more sophisticated and potent ones – either target or take advantages of the outbound communication channel.

Therefore, in order for organizations to fully protect themselves, they must deploy protections that allow bi-directional inspection of traffic in order to identify and neutralize such threats.

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

Download Now

Security

The Intersections between Cybersecurity and Diversity

March 20, 2019 — by Kevin Harris0

diversity-960x640.jpg

Cybersecurity and diversity are high-value topics that are most often discussed in isolation. Both topics resonate with individuals and organizations alike.

However, the intersections between cybersecurity and diversity are often overlooked. As nations and organizations seek to protect their critical infrastructures, it’s important to cultivate relationships between the two areas. Diversity is no longer only a social awareness and morality initiative; it is a core element of defending critical infrastructures.

Communities Need to Play a Greater Role in Cybersecurity

Technology careers typically pay more than other careers, providing a pathway to a quality lifestyle. With multiple entry points into the technology field — including degrees, apprenticeships and industry certifications — there are ways that varying communities can take part in technology careers, especially in cybersecurity. For instance, communities can improve cybersecurity education for women, minorities and home users.

Workforce Gaps Involving Women and Minorities Weakens Cybersecurity Defenses

Limited awareness and exposure to cybersecurity education often creates an opportunity gap for minorities and women. Failing to incorporate underserved populations limits the talent and size of our cybersecurity workforce. Without an all-inclusive cyber workforce, our critical infrastructure will have a talent gap, introducing additional system vulnerabilities.

To rectify this problem, communities must implement permanent efforts to ensure that children attending schools in underserved districts have access to technology and courses. That will better prepare them to become cyber workers.

[You may also like: Battling Cyber Risks with Intelligent Automation]

This infusion of technology talent helps to protect our nation’s vital digital assets. Organizations must make their recruitment and retention practices more inclusive. Ideally, they should provide opportunities to individuals who are either trained or are willing to undergo training to have a pathway to a successful career.

Additionally, higher education institutions should find ways to ensure that minorities and women have the support they need as they progress through their technology degrees. In addition, universities and colleges can offer cybersecurity faculty and mentors who can help these groups prepare for meaningful careers.

Cybersecurity Training Must Be Improved for Home Users

Another intersection of cybersecurity and diversity is at the user level. Most cybersecurity discussions center on the protection of government or corporate systems. Organizations spend significant portions of their budgets to prepare for and protect against cyberattacks.

Unfortunately, home users are often left out of such conversations; they are not considered part of any holistic cyber defense plan. With the large number of home users with multiple devices, the vulnerabilities of home systems provide hackers with easy attack opportunities.

[You may also like: The Costs of Cyberattacks Are Real]

Consequently, attackers access and compromise home devices, which allows them to attack other systems. In addition, these hackers can mask their true location and increase their computing power. They can then carry out their attacks more efficiently.

Compromising an individual’s personal device presents additional opportunities for attackers to access that person’s credentials as well as other sensitive workplace data. However, strong organization policies should dictate what information can be accessed remotely.

To increase home users’ threat awareness level, organizations should develop training programs as a part of community involvement initiatives. Vendors should strengthen default security settings for home users and ensure that home security protections are affordable and not difficult to configure.

[You may also like: Personal Security Hygiene]

Organizational Cultures Need to Emphasize that All Employees are Cyber Defenders

Diversity and cybersecurity also intersect at the organizational culture level. Regardless of whether or not organizations have an information systems security department, companies must foster the right type of security-minded workplace culture. All employees should be aware that they are intricate components in protecting the organization’s critical digital assets.

Educational institutions can support this effort by incorporating cyber awareness training across disciplines. This will give all graduates — regardless of their degrees — some exposure to cyber risks and their role in protecting digital assets.

[You may also like: 5 Ways Malware Defeats Cyber Defenses & What You Can Do About It]

Cybersecurity and Diversity Should Work Together, Not in Silos

Cybersecurity and diversity will continue to be important topics. The focus, however, should be on discussing the importance of their mutual support, rather than functioning in two separate silos. Improving our cyber defenses requires the best of all segments of our society, which includes minorities, women and home users.

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

Download Now

Cloud Security

Are Your DevOps Your Biggest Security Risks?

March 13, 2019 — by Eyal Arazi0

apikey-960x720.jpg

We have all heard the horror tales: a negligent (or uniformed) developer inadvertently exposes AWS API keys online, only for hackers to find those keys, penetrate the account and cause massive damage.

But how common, in practice, are these breaches? Are they a legitimate threat, or just an urban legend for sleep-deprived IT staff? And what, if anything, can be done against such exposure?

The Problem of API Access Key Exposure

The problem of AWS API access key exposure refers to incidents in which developer’s API access keys to AWS accounts and cloud resources are inadvertently exposed and found by hackers.

AWS – and most other infrastructure-as-as-service (IaaS) providers – provides direct access to tools and services via Application Programming Interfaces (APIs). Developers leverage such APIs to write automatic scripts to help them configure cloud-based resources. This helps developers and DevOps save much time in configuring cloud-hosted resources and automating the roll-out of new features and services.

[You may also like: Ensuring Data Privacy in Public Clouds]

In order to make sure that only authorized developers are able to access those resource and execute commands on them, API access keys are used to authenticate access. Only code containing authorized credentials will be able to connect and execute.

This Exposure Happens All the Time

The problem, however, is that such access keys are sometimes left in scripts or configuration files uploaded to third-party resources, such as GitHub. Hackers are fully aware of this, and run automated scans on such repositories, in order to discover unsecured keys. Once they locate such keys, hackers gain direct access to the exposed cloud environment, which they use for data theft, account takeover, and resource exploitation.

A very common use case is for hackers to access an unsuspecting cloud account and spin-up multiple computing instances in order to run crypto-mining activities. The hackers then pocket the mined cryptocurrency, while leaving the owner of the cloud account to foot the bill for the usage of computing resources.

[You may also like: The Rise in Cryptomining]

Examples, sadly, are abundant:

  • A Tesla developer uploaded code to GitHub which contained plain-text AWS API keys. As a result, hackers were able to compromise Tesla’s AWS account and use Tesla’s resource for crypto-mining.
  • WordPress developer Ryan Heller uploaded code to GitHub which accidentally contained a backup copy of the wp-config.php file, containing his AWS access keys. Within hours, this file was discovered by hackers, who spun up several hundred computing instances to mine cryptocurrency, resulting in $6,000 of AWS usage fees overnight.
  • A student taking a Ruby on Rails course on Udemy opened up a AWS S3 storage bucket as part of the course, and uploaded his code to GitHub as part of the course requirements. However, his code contained his AWS access keys, leading to over $3,000 of AWS charges within a day.
  • The founder of an internet startup uploaded code to GitHub containing API access keys. He realized his mistake within 5 minutes and removed those keys. However, that was enough time for automated bots to find his keys, access his account, spin up computing resources for crypto-mining and result in a $2,300 bill.
  • js published an npm code package in their code release containing access keys to their S3 storage buckets.

And the list goes on and on…

The problem is so widespread that Amazon even has a dedicated support page to tell developers what to do if they inadvertently expose their access keys.

How You Can Protect Yourself

One of the main drivers of cloud migration is the agility and flexibility that it offers organizations to speed-up roll-out of new services and reduce time-to-market. However, this agility and flexibility frequently comes at a cost to security. In the name of expediency and consumer demand, developers and DevOps may sometimes not take the necessary precautions to secure their environments or access credentials.

Such exposure can happen in a multitude of ways, including accidental exposure of scripts (such as uploading to GitHub), misconfiguration of cloud resources which contain such keys , compromise of 3rd party partners who have such credentials, exposure through client-side code which contains keys, targeted spear-phishing attacks against DevOps staff, and more.

[You may also like: Mitigating Cloud Attacks With Configuration Hardening]

Nonetheless, there are a number of key steps you can take to secure your cloud environment against such breaches:

Assume your credentials are exposed. There’s no way around this: Securing your credentials, as much as possible, is paramount. However, since credentials can leak in a number of ways, and from a multitude of sources, you should therefore assume your credentials are already exposed, or can become exposed in the future. Adopting this mindset will help you channel your efforts not (just) to limiting this exposure to begin with, but to how to limit the damage caused to your organization should this exposure occur.

Limit Permissions. As I pointed out earlier, one of the key benefits of migrating to the cloud is the agility and flexibility that cloud environments provide when it comes to deploying computing resources. However, this agility and flexibility frequently comes at a cost to security. Once such example is granting promiscuous permissions to users who shouldn’t have them. In the name of expediency, administrators frequently grant blanket permissions to users, so as to remove any hindrance to operations.

[You may also like: Excessive Permissions are Your #1 Cloud Threat]

The problem, however, is that most users never use most of the permissions they have granted, and probably don’t need them in the first place. This leads to a gaping security hole, since if any one of those users (or their access keys) should become compromised, attackers will be able to exploit those permissions to do significant damage. Therefore, limiting those permissions, according to the principle of least privileges, will greatly help to limit potential damage if (and when) such exposure occurs.

Early Detection is Critical. The final step is to implement measures which actively monitor user activity for any potentially malicious behavior. Such malicious behavior can be first-time API usage, access from unusual locations, access at unusual times, suspicious communication patterns, exposure of private assets to the world, and more. Implementing detection measures which look for such malicious behavior indicators, correlate them, and alert against potentially malicious activity will help ensure that hackers are discovered promptly, before they can do any significant damage.

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

Download Now

Attack Types & VectorsBotnetsSecurity

IoT Expands the Botnet Universe

March 6, 2019 — by Radware0

AdobeStock_175553664-960x607.jpg

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.

Download Now

Attack Types & VectorsBotnets

Attackers Are Leveraging Automation

January 31, 2019 — by Radware0

automation-960x681.jpg

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.

Download Now

Attack MitigationSecurity

Looking Past the Hype to Discover the Real Potential of AI

January 22, 2019 — by Pascal Geenens0

AI-960x439.jpg

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.

Download Now

Application SecurityAttack MitigationAttack Types & Vectors

How Cyberattacks Directly Impact Your Brand: New Radware Report

January 15, 2019 — by Ben Zilberman0

BinaryCodeEncryption-002-960x600.jpg

Whether you’re an executive or practitioner, brimming with business acumen or tech savviness, your job is to preserve and grow your company’s brand. Brand equity relies heavily on customer trust, which can take years to build and only moments to demolish. 2018’s cyber threat landscape demonstrates this clearly; the delicate relationship between organizations and their customers is in hackers’ cross hairs and suffers during a successful cyberattack. Make no mistake: Leaders who undervalue customer trust–who do not secure an optimized customer experience or adequately safeguard sensitive data–will feel the sting in their balance sheet, brand reputation and even their job security.

Radware’s 2018-2019 Global Application and Network Security report builds upon a worldwide industry survey encompassing 790 business and security executives and professionals from different countries, industries and company sizes. It also features original Radware threat research, including an analysis of emerging trends in both defensive and offensive technologies. Here, I discuss key takeaways.

Repercussions of Compromising Customer Trust

Without question, cyberattacks are a viable threat to operating expenditures (OPEX). This past year alone, the average estimated cost of an attack grew by 52% and now exceeds $1 million (the number of estimations above $1 million increased 60%). For those organizations that formalized a real calculation process rather than merely estimate the cost, that number is even higher, averaging $1.67 million.

Despite these mounting costs, three in four have no formalized procedure to assess the business impact of a cyberattack against their organization. This becomes particularly troubling when you consider that most organizations have experienced some type of attack within the course of a year (only 7% of respondents claim not to have experienced an attack at all), with 21% reporting daily attacks, a significant rise from 13% last year.

There is quite a range in cost evaluation across different verticals. Those who report the highest damage are retail and high-tech, while education stands out with its extremely low financial impact estimation:

Repercussions can vary: 43% report a negative customer experience, 37% suffered brand reputation loss and one in four lost customers. The most common consequence was loss of productivity, reported by 54% of survey respondents. For small-to-medium sized businesses, the outcome can be particularly severe, as these organizations typically lack sufficient protection measures and know-how.

It would behoove all businesses, regardless of size, to consider the following:

  • Direct costs: Extended labor, investigations, audits, software patches development, etc.
  • Indirect costs: Crisis management, fines, customer compensation, legal expenses, share value
  • Prevention: Emergency response and disaster recovery plans, hardening endpoints, servers and cloud workloads

Risk Exposure Grows with Multi-Dimensional Complexity

As the cost of cyberattacks grow, so does the complexity. Information networks today are amorphic. In public clouds, they undergo a constant metamorphose, where instances of software entities and components are created, run and disappear. We are marching towards the no-visibility era, and as complexity grows it will become harder for business executives to analyze potential risks.

The increase in complexity immediately translates to a larger attack surface, or in other words, a greater risk exposure. DevOps organizations benefit from advanced automation tools that set up environments in seconds, allocate necessary resources, provision and integrate with each other through REST APIs, providing a faster time to market for application services at a minimal human intervention. However, these tools are processing sensitive data and cannot defend themselves from attacks.

Protect your Customer Experience

The report found that the primary goal of cyber-attacks is service disruption, followed by data theft. Cyber criminals understand that service disruptions result in a negative customer experience, and to this end, they utilize a broad set of techniques. Common methods include bursts of high traffic volume, usage of encrypted traffic to overwhelm security solutions’ resource consumption, and crypto-jacking that reduces the productivity of servers and endpoints by enslaving their CPUs for the sake of mining cryptocurrencies. Indeed, 44% of organizations surveyed suffered either ransom attacks or crypto-mining by cyber criminals looking for easy profits.

What’s more, attack tools became more effective in the past year; the number of outages grew by 15% and more than half saw slowdowns in productivity. Application layer attacks—which cause the most harm—continue to be the preferred vector for DDoSers over the network layer. It naturally follows, then, that 34% view application vulnerabilities as the biggest threat in 2019.

Essential Protection Strategies

Businesses understand the seriousness of the changing threat landscape and are taking steps to protect their digital assets. However, some tasks – such as protecting a growing number of cloud workloads, or discerning a malicious bot from a legitimate one – require leveling the defense up. Security solutions must support and enable the business processes, and as such, should be dynamic, elastic and automated.

Analyzing the 2018 threat landscape, Radware recommends the following essential security solution capabilities:

  1. Machine Learning: As hackers leverage advanced tools, organizations must minimize false positive calls in order to optimize the customer experience. This can be achieved by machine-learning capabilities that analyze big data samples for maximum accuracy (nearly half of survey respondents point at security as the driver to explore machine-learning based technologies).
  2. Automation: When so many processes are automated, the protected objects constantly change, and attackers quickly change lanes trying different vectors every time. As such, a security solution must be able to immediately detect and mitigate a threat. Solutions based on machine learning should be able to auto tune security policies.
  3. Real Time Intelligence: Cyber delinquents can disguise themselves in many forms. Compromised devices sometimes make legitimate requests, while other times they are malicious. Machines coming behind CDN or NAT can not be blocked based on IP reputation and generally, static heuristics are becoming useless. Instead, actionable, accurate real time information can reveal malicious activity as it emerges and protect businesses and their customers – especially when relying on analysis and qualifications of events from multiple sources.
  4. Security Experts: Keep human supervision for the moments when the pain is real. Human intervention is required in advanced attacks or when the learning process requires tuning. Because not every organization can maintain the know-how in-house at all times, having an expert from a trusted partner or a security vendor on-call is a good idea.

It is critical for organizations to incorporate cybersecurity into their long-term growth plans. Securing digital assets can no longer be delegated solely to the IT department. Rather, security planning needs to be infused into new product and service offerings, security, development plans and new business initiatives. CEOs and executive teams must lead the way in setting the tone and invest in securing their customers’ experience and trust.

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

Download Now

Attack Types & VectorsDDoSDDoS Attacks

2018 In Review: Memcache and Drupalgeddon

December 20, 2018 — by Daniel Smith0

AdobeStock_199421574-960x640.jpg

Attackers don’t just utilize old, unpatched vulnerabilities, they also exploit recent disclosures at impressive rates. This year we witnessed two worldwide events that highlight the evolution and speed with which attackers will weaponize a vulnerability: Memcache and Druppalgeddon.

Memcached DDoS Attacks

In late February, Radware’s Threat Detection Network signaled an increase in activity on UDP port 11211. At the same time, several organizations began alerting to the same trend of attackers abusing Memcached servers for amplified attacks. A Memcached amplified DDoS attack makes use of legitimate third-party Memcached servers to send spoofed attack traffic to a targeted victim. Memcached, like other UDP-based services (SSDP, DNS and NTP), are Internet servers that do not have native authentication and are therefore hijacked to launch amplified attacks against their victims. The Memcached protocol was never intended to be exposed to the Internet and thus did not have sufficient security controls in place. Because of this exposure, attackers are able to abuse Memcached UDP port 11211 for reflective, volumetric DDoS attacks.

On February 27, Memcached version 1.5.6 was released which noted that UDP port 11211 was exposed and fixed the issue by disabling the UDP protocol by default. The following day, before the update could be applied, attackers leveraged this new attack vector to launch the world’s largest DDoS attack, a title previously held by the Mirai botnet.

There were two main concerns with regards to the Memcached vulnerability. The first is centered around the number of exposed Memcached servers. With just under 100,000 servers and only a few thousand required to launch a 1Tbps attack, the cause for concern is great. Most organizations at this point are likely unaware that they have vulnerable Memcached servers exposed to the Internet and it takes time to block or filter this service. Memcached servers will be vulnerable for some time, allowing attackers to generate volumetric DDoS attacks with few resources.

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

The second concern is the time it took attackers to begin exploiting this vulnerability. The spike in activity was known for several days prior to the patch and publication of the Memcached vulnerability. Within 24 hours of publication, an attacker was able to build an amplification list of vulnerable MMemcached servers and launch the massive attack.

Adding to this threat, Defcon.pro, a notorious stresser service, quickly incorporated Memcache into their premium offerings after the disclosure. Stresser services are normally quick to utilize the newest attack vector for many reasons. The first reason being publicity. Attackers looking to purchase DDoS-as-a-service will search for a platform offering the latest vectors. Including them in a service shows demand for the latest vectors. In addition, an operator might include the Memcache DDoS-as-a-service so they can provide their users with more power. A stresser service offering a Memcache DDoS-as-a-service will likely also attract more customers who are looking for volume and once again plays into marketing and availability.

[You may also like: The Rise of Booter and Stresser Services]

DDoS-as-a-service operators are running a business and are currently evolving at rapid rates to keep up with demand. Oftentimes, these operators are using the public attention created by news coverage similar to extortionists. Similarly, ransom denial-of-service (RDoS) operators are quick to threaten the use of new tools due to the risks they pose. DDoS-as-a-service will do the same, but once the threat is mitigated by security experts, cyber criminals will look for newer vectors to incorporate  into their latest toolkit or offerings.

This leads into the next example of Drupalgeddon campaign and how quickly hacktivists incorporated this attack vector into their toolkit for the purpose of spreading messages via defacements.

Drupalgeddon

In early 2018, Radware’s Emergency Response Team (ERT) was following AnonPlus Italia, an Anonymous-affiliated group that was engaged in digital protests throughout April and May. The group–involved in political hacktivism as they targeted the Italian government–executed numerous web defacements to protest war, religion, politics and financial power while spreading a message about their social network by abusing the content management systems (CMS).

On April 20, 2018 AnonPlus Italia began a new campaign and defaced two websites to advertise their website and IRC channel. Over the next six days, AnonPlus Italia would claim responsibility for defacing 21 websites, 20 of which used the popular open-source CMS Drupal.

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

Prior to these attacks, on March 29, 2018, the Drupal security team released a patch for a critical remote code execution (RCE) against Drupal that allowed attackers to execute arbitrary code on unpatched servers as a result of an issue affecting multiple subsystems with default or common module configurations. Exploits for CVE-2018-7600 were posted to Github and Exploit-DB under the guise of education purposes only. The first PoC was posted to Exploit DB on April 13, 2018. On April 14, Legion B0mb3r, a member of the Bangladesh-based hacking group Err0r Squad, posted a video to YouTube demonstrating how to use this CVE-2018-7600 to deface an unpatched version of Drupal. A few days later, on April 17, a Metasploit module was also released to the public.

In May, AnonPlus Italia executed 27 more defacements, of which 19 were Drupal.

Content management systems like WordPress and Joomla are normally abused by Anonymous hacktivists to target other web servers. In this recent string of defacements, the group AnonPlus Italia is abusing misconfigured or unpatched CMS instances with remote code exploits, allowing them to upload shells and deface unmaintained websites for headline attention.

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

Download Now

Application SecurityAttack MitigationDDoS AttacksSecurity

2018 In Review: Healthcare Under Attack

December 12, 2018 — by Daniel Smith0

Healthcare-Under-Attack-960x568.jpg

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.

Download Now

Attack Types & VectorsCloud SecurityDDoS AttacksSecurity

2019 Predictions: Will Cyber Serenity Soon Be a Thing of the Past?

November 29, 2018 — by Daniel Smith0

AdobeStock_227784320-2-960x600.jpg

In 2018 the threat landscape evolved at a breakneck pace, from predominantly DDoS and ransom attacks (in 2016 and 2017, respectively), to automated attacks. We saw sensational attacks on APIs, the ability to leverage weaponized Artificial Intelligence, and growth in side-channel and proxy-based attacks.

And by the looks of it, 2019 will be an extension of the proverbial game of whack-a-mole, with categorical alterations to the current tactics, techniques and procedures (TTPs). While nobody knows exactly what the future holds, strong indicators today enable us to forecast trends in the coming year.

The public cloud will experience a massive security attack

The worldwide public cloud services market is projected to grow 17.3 percent in 2019 to total $206.2 billion, up from $175.8 billion in 2018, according to Gartner, Inc. This means organizations are rapidly shifting content to the cloud, and with that data shift comes new vulnerabilities and threats. While cloud adoption is touted as faster, better, and easier, security is often overlooked for performance and overall cost. Organizations trust and expect their cloud providers to adequately secure information for them, but perception is not always a reality when it comes to current cloud security, and 2019 will demonstrate this.

[You may also like: Cloud vs DDoS, the Seven Layers of Complexity]

Ransom techniques will surge

Ransom, including ransomware and ransom RDoS, will give way to hijacking new embedded technologies, along with holding healthcare systems and smart cities hostage with the launch of 5G networks and devices. What does this look like? The prospects are distressing:

  • Hijacking the availability of a service—like stock trading, streaming video or music, or even 911—and demanding a ransom for the digital return of the devices or network.
  • Hijacking a device. Not only are smart home devices like thermostats and refrigerators susceptible to security lapses, but so are larger devices, like automobiles.
  • Healthcare ransom attacks pose a particularly terrifying threat. As healthcare is increasingly interwoven with cloud-based monitoring, services and IoT embedded devices responsible for administering health management (think prescriptions/urgent medications, health records, etc.) are vulnerable, putting those seeking medical care in jeopardy of having their healthcare devices that they a dependent on being targeted by malware or their devices supporting network being hijacked.

[You may also like: The Origin of Ransomware and Its Impact on Businesses]

Nation state attacks will increase

As trade and other types of “soft-based’ power conflicts increase in number and severity, nation states and other groups will seek new ways of causing widespread disruption including Internet outages at the local or regional level, service outages, supply chain attacks and application blacklisting by government in attempted power grabs. Contractors and government organizations are likely to be targeted, and other industries will stand to lose millions of dollars as indirect victims if communications systems fail and trade grinds to a halt.

More destructive DDoS attacks are on the way

Over the past several years, we’ve witnessed the development and deployment of massive IoT-based botnets, such as Mirai, Brickerbot, Reaper and Haijme, whose systems are built around thousands of compromised IoT devices.  Most of these weaponized botnets have been used in cyberattacks to knock out critical devices or services in a relatively straightforward manner.

Recently there has been a change in devices targeted by bot herders. Based on developments we are seeing in the wild, attackers are not only infiltrating resource-constrained IoT devices, they are also targeting powerful cloud-based servers. When targeted, only a handful of compromised instances are needed to create a serious threat. Since IoT malware is cross-compiled for many platforms, including x86_64, we expect to see attackers consistently altering and updating Mirai/Qbot scanners to include more cloud-based exploits going into 2019.

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

Cyber serenity may be a thing of the past

If the growth of the attack landscape continues to evolve into 2019 through various chaining attacks and alteration of the current TTP’s to include automated features, the best years of cybersecurity may be behind us. Let’s hope that 2019 will be the year we collectively begin to really share intelligence and aid one another in knowledge transfer; it’s critical in order to address the threat equation and come up with reasonable and achievable solutions that will abate the ominous signs before us all.

Until then, pay special attention to weaponized AI, large API attacks, proxy attacks and automated social engineering. As they target the hidden attack surface of automation, they will no doubt become very problematic moving forward.

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

Download Now