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Application Security

HTTPS: The Myth of Secure Encrypted Traffic Exposed

February 5, 2019 — by Ben Zilberman0

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The S in HTTPS is supposed to mean that encrypted traffic is secure. For attackers, it just means that they have a larger attack surface from which to launch assaults on the applications to exploit the security vulnerabilities. How should organizations respond?

Most web traffic is encrypted to provide better privacy and security. By 2018, over 70% of webpages are loaded over HTTPS. Radware expects this trend to continue until nearly all web traffic is encrypted. The major drivers pushing adoption rates are the availability of free SSL certificates and the perception that clear traffic is insecure.

While encrypting traffic is a vital practice for organizations, cyber criminals are not necessarily deterred by the practice. They are looking for ways to take advantage of encrypted traffic as a platform from which to launch attacks that can be difficult to detect and mitigate, especially at the application layer. As encrypted applications grow more complex, the potential attack surface is larger. Organizations need to incorporate protection of the application layer as part of their overall network security strategies. Results from the global industry survey revealed a 10% increase in encrypted attacks on organizations by 2018.

Encrypted Application Layers

When planning protection for encrypted applications, it is important to consider all of the layers that are involved in delivering an application. It is not uncommon for application owners to focus on protecting the encrypted application layer while overlooking the lower layers in the stack which might be vulnerable. In many cases, protection selected for the application layer may itself be vulnerable to transport-layer attacks.

To ensure applications are protected, organizations need to analyze the following Open Systems Interconnection (OSI) layers:

  • Transport — In most encrypted applications, the underlying transport is TCP. TCP attacks come in many forms, so volumes and protection must be resilient to protect
    applications from attacks on the TCP layer. Some applications now use QUIC, which uses UDP as the underlying layer and adds reflection and amplification risks to the mix.
  • Session — The SSL itself is vulnerable. Once an SSL/TLS session is created, the server invests about 15 times more compute power than the client, which makes the session layer particularly vulnerable and attractive to attackers.
  • Application — Application attacks are the most complex type of attack, and encryption only makes it harder for security solutions to detect and mitigate them.Attackers often select specific areas in applications to generate a high request-to-load ratio, may attack several resources simultaneously to make detection harder, or may mimic legitimate user behavior in various ways to bypass common application security solutions.The size of an attack surface is determined by the application design. For example, in a login attack, botnets perform multiple login attempts from different sources to try to stress the application. The application login is always encrypted and requires resources on the application side such as a database, authentication gateway or identity service invocation. The attack does not require a high volume of traffic to affect the application, making it very hard to detect.

[You may also like: SSL Attacks – When Hackers Use Security Against You]

Environmental Aspects

Organizations also need to consider the overall environment and application structure because it greatly affects the selection of the ideal security design based on a vulnerability assessment.

  • Content Delivery Network — Applications using a content delivery network (CDN) generate a challenge for security controls which are deployed at the origin. Technologies that use the source IP for analyzing client application behavior only see the source IP of the CDN. There is a risk that the solutions will either over mitigate and disrupt legitimate users or become ineffective. High rates of false positives prove that protection based on source IP addresses is pointless. Instead, when using a CDN, the selected security technology should have the right measures to analyze attacks that originate behind it, including device fingerprinting or extraction of the original source from the application headers.
  • Application Programming Interface — Application programming interface (API) usage is common in all applications. According to Radware’s The State of Web Application Security report, a third of attacks against APIs intends to yield a denial-of-service state. The security challenge here comes from the legitimate client side. Many solutions rely on various active user validation techniques to distinguish legitimate users from attackers. These techniques require that a real browser reside at the client. In the case of an API, many times a legitimate browser is not at the client side, so the behavior and legitimate response to various validation challenges is different.
  • Mobile Applications — Like APIs, the client side is not a browser for a mobile application and cannot be expected to behave and respond like one. Mobile applications pose a challenge because they rely on different operating systems and use different browsers. Many security solutions were created based on former standards and common tools and have not yet fully adapted. The fact that mobile apps process a high amount of encrypted traffic increases the capacity and security challenges.
  • Directionality — Many security solutions only inspect inbound traffic to protect against availability threats. Directionality of traffic has significant implications on the protection efficiency because attacks usually target the egress path of the application. In such cases, there might not be an observed change in the incoming traffic profile, but the application might still become unavailable. An effective security solution must process both directions of traffic to protect against sophisticated application attacks.

[You may also like: Are Your Applications Secure?]

Regulatory Limitations

Major selection criterion for security solutions is regulatory compliance. In the case of encrypted attacks, compliance requirements examine whether traffic is decrypted, what parts of traffic are decrypted and where the decryption happens. The governing paradigm has always been that the more intrusive the solution, the more effective the security, but that is not necessarily the case here. Solutions show different levels of effectiveness for the same intrusiveness.

Encryption Protocols

The encryption protocol in use has implications toward how security can be applied and what types of vulnerabilities it represents. Specifically, TLS 1.3 generates enhanced security from the data privacy perspective but is expected to generate challenges to security solutions which rely on eavesdropping on the encrypted connection. Users planning to upgrade to TLS 1.3 should consider the future resiliency of their solutions.

[You may also like: Adopt TLS 1.3 – Kill Two Birds with One Stone]

Attack Patterns

Determining attack patterns is the most important undertaking that organizations must master. Because there are so many layers that are vulnerable, attackers can easily change their tactics mid-attack. The motivation is normally twofold: first, inflicting maximum impact with minimal cost; second, making detection and mitigation difficult.

  • Distribution — The level of attack distribution is very important to the attacker. It impacts the variety of vectors that can be used and makes the job harder for the security controls. Most importantly, the more distributed the attack, the less traffic each attacking source has to generate. That way, behavior can better resemble legitimate users. Gaining control of a large botnet used to be difficult to do and extremely costly. With the growth in the IoT and corresponding IoT botnets, it is common to come across botnets consisting of hundreds of thousands of bots.
  • Overall Attack Rates — The overall attack traffic rate varies from one vector to another. Normally, the lower the layer, the higher the rate. At the application layer, attackers are able to generate low-rate attacks, which still generate significant impact. Security solutions should be able to handle both high- and low-rate attacks, without compromising user experience and SLA.
  • Rate per Attacker — Many security solutions in the availability space rely on the rate per source to detect attackers. This method is not always effective as highly distributed attacks proliferate.
  • Connection Rates — Available attack tools today can be divided into two major classes based on their connection behavior. The first class includes tools that open a single connection and generate many. The second includes tools that generate many connections with only a single request or very few requests on each connection. Security tools that can analyze connection behavior are more effective in discerning legitimate users from attackers.
  • Session Rates — SSL/TLS session behavior has various distinct behavioral characteristics in legitimate users and browsers. The major target is to optimize performance and user experience. Attack traffic does not usually fully adhere to those norms, so its SSL session behavior is different. The ability to analyze encryption session behavior contributes to protecting both the encryption layer and the underlying application layer.
  • Application Rates — Because the application is the most complex part to attack, attackers have the most degree of freedom when it comes to application behavior. Attack patterns vary greatly from one attack to another in terms of how they appear on application behavior analyses. At the same time, the rate of change in the application itself is very high, such that it cannot be followed manually. Security tools that can automatically analyze a large variety of application aspects and, at the same time, adapt to changes quickly are expected to be more effective in protecting from encrypted application attacks.

End-to-End Protection

Protection from encrypted availability attacks is becoming a mandatory requirement for organizations. At the same time, it is one of the more complex tasks to thoroughly perform without leaving blind spots. When considering a protection strategy, it is important to take into account various aspects of the risk and to make sure that, with all good intentions, the side door is not left open.

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

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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 Types & VectorsSecurity

The Rise in Cryptomining

January 29, 2019 — by Radware1

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There are four primary motivations for cyberattacks: crime, hacktivism, espionage and war. Setting aside nation-state sponsored groups, the largest faction of attackers are cybercriminals, individuals or well-established organizations looking to turn a profit.

For the last several years, ransom-based cyberattacks and ransomware had been the financial modus operandi for hackers, but 2018 flipped the coin to unveil a new attack vector: cryptomining.

Always Crypto

Radware’s Malware Threat Research Group monitored this phenomenon throughout the year and identified two recurring trends. Some groups use cryptomining to score a quick, easy profit by infecting machines and mining cryptocurrencies. Other groups use cryptomining as an ongoing source of income, simply by reselling installations on infected machines or selling harvested data.

While there is no definitive reason why cryptomining has become popular, what is clear are some of the advantages it has over older attacks methods:

  • It’s easy – There’s no need to develop a cryptomining tool or even buy one. An attacker can just download a free tool into the victim’s machine and run it with a simple configuration that instructs it to mine the pool.
  • CPU – While Bitcoin requires a graphic processing unit (GPU) to perform effective mining, other cryptocurrency, such as Monero, require only CPU to effectively mine a machine. Since every machine has a CPU, including web cameras, smartphones, smart TVs and computers, there many potential targets.
  • Minimal footprint — Other attack types require the hackers to market their “goods” or to actively use the information they acquired for malicious purposes. In cryptomining, the money moves directly to the attacker.
  • Value — The value of cryptocurrencies skyrocketed in late 2017 and early 2018. The outbreak quickly followed. More recently, as monetary value declined, so has the number of incidences.
  • Multipurpose hack — After successfully infecting a machine, hackers can leverage the installation of the malware program for multiple activities. Stealing credentials from machines? Why not use those machines to cryptomine as well (and vice versa)? Selling data mining installations on machines to other people? Add a cryptomining tool to run at the same time.

[You may also like: Top Cryptomining Malware. Top Ransomware.]

The Malware Ecosystem

There are a few popular ways for cybercriminals to launch cryptomining attacks:

  • Information stealing — By distributing a data harvesting malware, attackers steal access credentials or files (photos, documents, etc.), and even identities found on an infected machine, its browser or inside the network. Then, the cybercriminals generally use the stolen data to steal. In the case of bank credentials, the hackers use the information to steal money from accounts. They may also sell the stolen data through an underground market on the dark web to other hackers. Credit cards, social security numbers and medical records go for just a few dollars. Social media accounts and identities are popular, as well. Facebook and Instagram accounts have been hijacked and used for propagation.
  • Downloaders — Malware is distributed with simple capabilities to download additional malware and install on other systems.The motivation is to infect as many machines as possible. The next step is to sell malware installations on those machines. Apparently, even infected machines enjoy brand premium fees — machines from a Fortune 500 company cost a lot more.
  • Ransomware — Machines are infected with a malware that encrypts files, which are usually valuable to the victim, such as photos, Microsoft files (.xlsx,.docx) and Adobe Acrobat files. Victims are then asked to pay a significant amount of money in order to get a tool to decrypt their files. This attack was first introduced against individuals but grew exponentially when hackers figured out that organizations can pay a higher premium.
  • DDoS for ransom (RDoS) — Attackers send targets a letter that threatens a DDoS attack on a certain day and time unless the organization makes a payment, usually via Bitcoin. Often hackers know the IP address of the targeted server or network and launch a small-scale attack as a preview of what could follow.

[You may also like: Malicious Cryptocurrency Mining: The Road Ahead]

Social Propagation

Malware protection is a mature market with many competitors. It is a challenge for hackers to create a one-size-fits-all zero-day attack that will run on as many operating systems, servers and endpoints as possible, as well as bypass most, if not all, security solutions. So in addition to seeking ways to penetrate protection engines, hackers are also looking for ways to bypass them.

During the past year, Radware noticed several campaigns where malware was created to hijack social network credentials. That enabled hackers to spread across the social network accessing legitimate files on the machine and private information (or computing resources, in the context of cryptomining).

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

Here are a few examples:

  • Nigelthorn – Radware first detected this campaign, which involved a malicious chrome extension, in a customer’s network. The hackers bypassed Google Chrome native security mechanisms to disguise the malware as a legitimate extension. The group managed to infect more than 100,000 machines. The purpose of the extension was cryptomining Monero currency by the host machine, as well as stealing the credentials of the victim’s Facebook and/or Instagram accounts. The credentials were abused to propagate the attack through the Facebook user’s contact network. It is also possible that the credentials were later sold on the black market.
  • Stresspaint — In this spree, hackers used a benign-looking drawing application to hijack Facebook users’ cookies. They deceived victims by using an allegedly legitimate AOL.net URL, which was actually a unicode representation. The true address is “xn--80a2a18a.net.” The attackers were building a database of users with their contact
    network, business pages and payment details. Radware suspects that the ultimate goal was to use this information to fund public opinion influence campaigns on the social network.
  • CodeFork — This campaign was also detected in some of Radware’s customers’ networks when the infected machines tried to communicate with their C&C servers. Radware intercepted the communication and determined that this group was infecting machines in order to sell their installations. The group has been active for several years during which time we have seen them distributing different malware to the infected machines. The 2018 attack included an enhancement that distributes
    cryptomining malware.

Moving Forward

Radware believes that the cryptomining trend will persist in 2019. The motivation of financial gain will continue, pushing attackers to try to profit from malicious malware. In addition, hackers of all types can potentially add cryptomining capabilities to the infected machines that they already control. Our concern is that during the next phase, hackers will invest their profits to leverage machine-learning capabilities to find ways to access and exploit resources in networks and applications.

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

Download Now

Cloud ComputingCloud Security

Ensuring Data Privacy in Public Clouds

January 24, 2019 — by Radware0

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Most enterprises spread data and applications across multiple cloud providers, typically referred to as a multicloud approach. While it is in the best interest of public cloud providers to offer network security as part of their service offerings, every public cloud provider utilizes different hardware and software security policies, methods and mechanisms, creating a challenge for the enterprise to maintain the exact same policy and configuration across all infrastructures. Public cloud providers typically meet basic security standards in an effort to standardize how they monitor and mitigate threats across their entire customer base. Seventy percent of organizations reported using public cloud providers with varied approaches to security management. Moreover, enterprises typically prefer neutral security vendors instead of over-relying on public cloud vendors to protect their workloads. As the multicloud approach expands, it is important to centralize all security aspects.

When Your Inside Is Out, Your Outside Is In

Moving workloads to publicly hosted environments leads to new threats, previously unknown in the world of premise-based computing. Computing resources hosted inside an organization’s perimeter are more easily controlled. Administrators have immediate physical access, and the workload’s surface exposure to insider threats is limited. When those same resources are moved to the public cloud, they are no longer under the direct control of the organization. Administrators no longer have physical access to their workloads. Even the most sensitive configurations must be done from afar via remote connections. Putting internal resources in the outside world results in a far larger attack surface with long, undefined boundaries of the security perimeter.

In other words, when your inside is out, then your outside is in.

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External threats that could previously be easily contained can now strike directly at the heart of an organization’s workloads. Hackers can have identical access to workloads as do the administrators managing them. In effect, the whole world is now an insider threat.

In such circumstances, restricting the permissions to access an organization’s workloads and hardening its security configuration are key aspects of workload security.

Poor Security HYGIENE Leaves You Exposed

Cloud environments make it very easy to grant access permissions and very difficult to keep track of who has them. With customer demands constantly increasing and development teams put under pressure to quickly roll out new enhancements, many organizations spin up new resources and grant excessive permissions on a routine basis. This is particularly true in many DevOps environments where speed and agility are highly valued and security concerns are often secondary.

Over time, the gap between the permissions that users have and the permissions that they actually need (and use) becomes a significant crack in the organization’s security posture. Promiscuous permissions leave workloads vulnerable to data theft and resource exploitation should any of the users who have access permissions to them become compromised. As a result, misconfiguration of access permissions (that is, giving permissions to too many people and/or granting permissions that are overly generous)
becomes the most urgent security threat that organizations need to address in public cloud environments.

[You may also like: Considerations for Load Balancers When Migrating Applications to the Cloud]

The Glaring Issue of Misconfiguration

Public cloud providers offer identity access management tools for enterprises to control access to applications, services and databases based on permission policies. It is the responsibility of enterprises to deploy security policies that determine what entities are allowed to connect with other entities or resources in the network. These policies are usually a set of static definitions and rules that control what entities are valid to, for example, run an API or access data.

One of the biggest threats to the public cloud is misconfiguration. If permission policies are not managed properly by an enterprise will the tools offered by the public cloud provider, excessive permissions will expand the attack surface, thereby enabling hackers to exploit one entry to gain access to the entire network.

Moreover, common misconfiguration scenarios result from a DevOps engineer who uses predefined permission templates, called managed permission policies, in which the granted standardized policy may contain wider permissions than needed. The result is excessive permissions that are never used. Misconfigurations can cause accidental exposure of data, services or machines to the internet, as well as leave doors wide open for attackers.

[You may also like: The Hybrid Cloud Habit You Need to Break]

For example, an attacker can steal data by using the security credentials of a DevOps engineer gathered in a phishing attack. The attacker leverages the privileged role to take a snapshot of elastic block storage (EBS) to steal data, then shares the EBS snapshot and data on an account in another public network without installing anything. The attacker is able to leverage a role with excessive permissions to create a new machine at the beginning of the attack and then infiltrate deeper into the network to share
AMI and RDS snapshots (Amazon Machine Images and Relational Database Service, respectively), and then unshare resources.

Year over year in Radware’s global industry survey, the most frequently mentioned security challenges encountered with migrating applications to the cloud are governance issues followed by skill shortage and complexity of managing security policies. All contribute to the high rate of excessive permissions.

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

Download Now

HacksSecurity

Here’s Why Foreign Intelligence Agencies Want Your Data

January 23, 2019 — by Mike O'Malley0

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The implications of the recent Marriott hack go far beyond those of your average data breach. This megabreach of 383M records doesn’t just compromise sensitive data for the sake of fraud or financial gain, it paints a frightening picture of international espionage and personal privacy.

When news broke that hackers working on behalf of a Chinese intelligence agency may be responsible for the Marriott breach, questions abounded. Why would China be interested in loyalty program data by the millions? And why hospitality data?

Could You Be A Target?

Let’s be frank: Foreign intelligence agency actors aren’t exactly interested in earning a free night’s stay at a Marriott property. The answer is potentially far more nefarious. The fact is, data collected from breaches are but one piece of a larger, darker puzzle. Stolen customer data—when combined with travel data (see Delta, Cathay Pacific, and British Airways hacks, among others) and other sources of online personal information (i.e., what we share across social media platforms)—enable intelligence agencies to build profiles on individuals. These profiles can then be leveraged to recruit potential informants, as well as check the travel of known government and intelligence officers against their own government to identify moles.

It’s also critical to note that heads of state and other political VIPs are no longer foreign intelligence agencies’ only marks; ordinary citizens are similarly targeted, especially those who may have unfettered access to troves of company Intellectual Property (IP) that a foreign government may want for their domestic economy.

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

For example, if you work for a cloud storage company whose customers’ data is in an area of interest to an intelligence agency, you may very well become an object of interest. For example, in the FBI’s most recent indictment against foreign intelligence services, Zhu Hua and Zhang Shilong were charged on acting on behalf of the Chinese Ministry of State Security for stealing personal information and IP from companies in various industries including banking and finance, telecom, consumer electronics, healthcare, biotech, automotive, oil and gas, mining and the U.S. Navy.

The Hua/Shilong case is just the latest example of foreign intelligence agencies playing a game of chess while the U.S. is playing checkers. 2018 demonstrated this multiple times: In March, the Justice Department announced that Iranians had, through years-long cyberattacks, stolen intellectual property from over 300 U.S. universities and companies. In July, several Russian agents were indicted for election hacking and in September, North Korea was accused of trying to hurt the U.S. economy through a hack. And, of course, in December, the U.S. government accused China of the Marriott megabreach.  But 2018’s record isn’t unique; France was accused of stealing U.S. IP for French companies in 2014 by the U.S. Secretary of Defense.

In the case of Marriott and other large enterprises like it, CISOs and C-suite executives are focused on individual pieces of data lost, versus the sum of what that data can reveal about an individual as a whole, putting them (and us) at a significant disadvantage. Indeed, the entirety of the digital footprint we create, which can be used to impersonate us or to profile/create leverage on us, is greater than the sum of the individual data parts. Consumers likewise don’t typically consider the bigger picture their personal data paints, regarding their travel patterns, purchasing habits, hobbies, (not so) hidden secrets, social causes and more. Add in breach burnout, wherein the public has become desensitized to countless stories of data exposure, and a perfect storm for harvesting operatives and stealing IP emerges.

[You may also like: AI Considerations in Cyber Defence Automation]

Look at the Whole Picture

Until enterprises view data holistically and realize that any company with valuable IP could be the target of a foreign government on behalf of that company’s foreign competitors, they will continue to play into the hands of transnational threat actors at the expense of consumer safety and national security.

It is critical that organizations incorporate cybersecurity into every fabric of the business, from the C-level down, including training and education, as well as seeking expertise from security service companies who understand how to protect organizations from the capabilities of foreign intelligence groups. And that education must include an understanding how personal, government and business-related information can be used by foreign intelligence agencies, and how corporate IP may be of value to foreign competitors. Whether it’s a game of chess or an intricate puzzle, individuals must look beyond the breach at hand and grasp what’s around the corner.

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

Download Now

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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Attack Types & VectorsDDoSDDoS Attacks

Top 3 Cyberattacks Targeting Proxy Servers

January 16, 2019 — by Daniel Smith0

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Today, many organizations are now realizing that DDoS defense is critical to maintaining an exceptional customer experience. Why? Because nothing diminishes load times or impacts the end user’s experience more than a cyberattack.

As a facilitator of access to content and networks, proxy servers have become a focal point for those seeking to cause grief to organizations via cyberattacks due to the fallout a successful assault can have.

Attacking the CDN Proxy

New vulnerabilities in content delivery networks (CDNs) have left many wondering if the networks themselves are vulnerable to a wide variety of cyberattacks. Here are five cyber “blind spots” that are often attacked – and how to mitigate the risks:

Increase in dynamic content attacks. Attackers have discovered that treatment of dynamic content requests is a major blind spot in CDNs. Since the dynamic content is not stored on CDN servers, all requests for dynamic content are sent to the origin’s servers. Attackers are taking advantage of this behavior to generate attack traffic that contains random parameters in HTTP GET requests. CDN servers immediately redirect this attack traffic to the origin—expecting the origin’s server to handle the requests. However, in many cases the origin’s servers do not have the capacity to handle all those attack requests and fail to provide online services to legitimate users. That creates a denial-of-service situation. Many CDNs can limit the number of dynamic requests to the server under attack. This means they cannot distinguish attackers from legitimate users and the rate limit will result in legitimate users being blocked.

SSL-based DDoS attacks. SSL-based DDoS attacks leverage this cryptographic protocol to target the victim’s online services. These attacks are easy to launch and difficult to mitigate, making them a hacker favorite. To detect and mitigate SSL-based attacks, CDN servers must first decrypt the traffic using the customer’s SSL keys. If the customer is not willing to provide the SSL keys to its CDN provider, then the SSL attack traffic is redirected to the customer’s origin. That leaves the customer vulnerable to SSL attacks. Such attacks that hit the customer’s origin can easily take down the secured online service.

[You may also like: SSL Attacks – When Hackers Use Security Against You]

During DDoS attacks, when web application firewall (WAF) technologies are involved, CDNs also have a significant scalability weakness in terms of how many SSL connections per second they can handle. Serious latency issues can arise. PCI and other security compliance issues are also a problem because they limit the data centers that can be used to service the customer. This can increase latency and cause audit issues.

Keep in mind these problems are exacerbated with the massive migration from RSA algorithms to ECC and DH-based algorithms.

Attacks on non-CDN services. CDN services are often offered only for HTTP/S and DNS applications.  Other online services and applications in the customer’s data center, such as VoIP, mail, FTP and proprietary protocols, are not served by the CDN. Therefore, traffic to those applications is not routed through the CDN. Attackers are taking advantage of this blind spot and launching attacks on such applications. They are hitting the customer’s origin with large-scale attacks that threaten to saturate the Internet pipe of the customer. All the applications at the customer’s origin become unavailable to legitimate users once the internet pipe is saturated, including ones served by the CDN.

[You may also like: CDN Security is NOT Enough for Today]

Direct IP attacks. Even applications that are served by a CDN can be attacked once attackers launch a direct hit on the IP address of the web servers at the customer’s data center. These can be network-based flood attacks such as UDP floods or ICMP floods that will not be routed through CDN services and will directly hit the customer’s servers. Such volumetric network attacks can saturate the Internet pipe. That results in degradation to application and online services, including those served by the CDN.

Web application attacks. CDN protection from threats is limited and exposes web applications of the customer to data leakage and theft and other threats that are common with web applications. Most CDN- based WAF capabilities are minimal, covering only a basic set of predefined signatures and rules. Many of the CDN-based WAFs do not learn HTTP parameters and do not create positive security rules. Therefore, these WAFs cannot protect from zero-day attacks and known threats. For companies that do provide tuning for the web applications in their WAF, the cost is extremely high to get this level of protection. In addition to the significant blind spots identified, most CDN security services are simply not responsive enough, resulting in security configurations that take hours to manually deploy. Security services are using technologies (e.g., rate limit) that have proven inefficient in recent years and lack capabilities such as network behavioral analysis, challenge-response mechanisms and more.

[You may also like: Are Your Applications Secure?]

Finding the Watering Holes

Waterhole attack vectors are all about finding the weakest link in a technology chain. These attacks target often forgotten, overlooked or not intellectually attended to automated processes. They can lead to unbelievable devastation. What follows is a list of sample watering hole targets:

  • App stores
  • Security update services
  • Domain name services
  • Public code repositories to build websites
  • Webanalytics platforms
  • Identity and access single sign-on platforms
  • Open source code commonly used by vendors
  • Third-party vendors that participate in the website

The DDoS attack on Dyn in 2016 has been the best example of the water-holing vector technique to date. However, we believe this vector will gain momentum heading into 2018 and 2019 as automation begins to pervade every aspect of our life.

Attacking from the Side

In many ways, side channels are the most obscure and obfuscated attack vectors. This technique attacks the integrity of a company’s site through a variety of tactics:

  • DDoS the company’s analytics provider
  • Brute-force attack against all users or against all of the site’s third-party companies
  • Port the admin’s phone and steal login information
  • Massive load on “page dotting”
  • Large botnets to “learn” ins and outs of a site

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 MitigationAttack Types & Vectors

How Cyberattacks Directly Impact Your Brand: New Radware Report

January 15, 2019 — by Ben Zilberman0

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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.

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Attack Types & VectorsSecurity

Threat Alert: MalSpam

January 10, 2019 — by Daniel Smith0

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Radware researchers have been following multiple campaigns targeting the financial industry in Europe and the United States. These campaigns are designed to commit fraud via credential theft by sending MalSpam, malicious spam that contains banking malware like Trickbot and Emotet, to unsuspecting users. If the users open the document, they will become infected, and the malware will harvest and extract data from the victim’s machine for fraudulent purposes. Once the data is retrieved from their c2 server, the stolen credentials will be used to commit fraud against the victim’s bank account, leveraged in a credential stuffing attack or quickly sold for profit.

One of the things that make these two pieces of banking malware stand out is their ability to evolve and consistently update their modules to allow additional capabilities. Additionally, we have seen denial of service attacks in the past that have coincided with these security events. Occasionally attackers have been known to launch a flood of malicious traffic, known as a smoke screen attack, to distract network operators from other nefarious activity such as data exfiltration. These attacks typically will not exhaust network resources since the criminals still need access.

To read the full ERT Threat Alert, click here.

Cloud ComputingCloud Security

Now or Never: Financial Services and the Cloud

January 9, 2019 — by Sandy Toplis0

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I will get straight to the point: The time is right for the financial services (FS) industry to leverage the power of the cloud. It dovetails quite nicely with retail banking’s competitive moves to provide users with more flexible choices, banking simplification and an improved, positive customer experience. Indeed, I am encouraged that roughly 70% of my financial services customers are looking to move more services to the cloud, and approximately 50% have a cloud-first strategy.

This is a departure from the FS industry’s history with the public cloud. Historically, it has shied away from cloud adoption—not because it’s against embracing new technologies for business improvement, but because it is one of the most heavily regulated and frequently scrutinized industries in terms of data privacy and security. Concerns regarding the risk of change and impact to business continuity, customer satisfaction, a perceived lack of control, data security, and costs have played a large role in the industry’s hesitation to transition to the cloud.

[You may also like: Credential Stuffing Campaign Targets Financial Services]

Embracing Change

More and more, banks are moving applications on the cloud to take advantage of scalability, lower capital costs, ease of operations and resilience offered by cloud solutions. Due to the differing requirements on data residency from jurisdiction-to-jurisdiction, banks need to choose solutions that allow them to have exacting control over transient and permanent data flows. Solutions that are flexible enough to be deployed in a hybrid mode, on a public cloud infrastructure as well as private infrastructure, are key to allowing banks to have the flexibility of leveraging existing investments, as well as meeting these strict regulatory requirements.

[You may also like: The Hybrid Cloud Habit You Need to Break]

Although the rate of cloud adoption within the financial services industry still has much room for growth, the industry is addressing many of its concerns and is putting to bed the myths surrounding cloud-based security. Indeed, multi-cloud adoption is proliferating and it’s becoming clear that banks are increasingly turning to the cloud and into new (FinTech) technology.  In some cases, banks are already using cloud services for non-core and non-critical uses such as HR, email, customer analytics, customer relationship management (CRM), and for development and testing purposes.

Interestingly, smaller banks have more readily made the transition by moving entire core services (treasury, payments, retail banking, enterprise data) to the cloud.  As these and other larger banks embrace new FinTech, their service offerings will stand out among the competitive landscape, helping to propel the digital transformation race.

What’s Driving the Change?

There are several key drivers for the adoption of multi (public) cloud-based services for the FS industry, including:

  • Risk mitigation in cloud migration. Many companies operate a hybrid security model, so the cloud environment works adjacent to existing infrastructure. Organisations are also embracing the hybrid model to deploy cloud-based innovation sandboxes to rapidly validate consumers’ acceptance of new services without disrupting their existing business. The cloud can help to lower risks associated with traditional infrastructure technology where capacity, redundancy and resiliency are operational concerns.  From a regulatory perspective, the scalability of the cloud means that banks can scan potentially thousands of transactions per second, which dramatically improves the industry’s ability to combat financial crime, such as fraud and money laundering.
  • Security. Rightly so, information security remains the number one concern for CISOs. When correctly deployed, cloud applications are no less secure than traditional in-house deployments. What’s more, the flexibility to scale in a cloud environment can empower banks with more control over security issues.
  • Agile innovation and competitive edge. Accessing the cloud can increase a bank’s ability to innovate by enhancing agility, efficiency and productivity. Gaining agility with faster onboarding of services (from the traditional two-to-three weeks to implement a service to almost instantly in the cloud) gives banks a competitive edge: they can launch new services to the market quicker and with security confidence. Additionally, the scaling up (or down) of services is fast and reliable, which can help banks to reallocate resources away from the administration of IT infrastructure, and towards innovation and fast delivery of products and services to markets.
  • Cost benefits. As FS customers move from on-prem to cloud environments, costs shift from capex to opex. The cost savings of public cloud solutions are significant, especially given the reduction in initial capex requirements for traditional IT infrastructure. During periods of volumetric traffic, the cloud can allow banks to manage computing capacity more efficiently. And when the cloud is adopted for risk mitigation and innovation purposes, cost benefits arise from the resultant improvements in business efficiency. According to KPMG, shifting back-office functions to the cloud allows banks to achieve savings of between 30 and 40 percent.

[You may also like: The Executive Guide to Demystify Cybersecurity]

A Fundamental Movement

Cloud innovation is fast becoming a fundamental driver in global digital disruption and is increasingly gaining more prominence and cogency with banks. In fact, Gartner predicts that by 2020, a corporate no-cloud policy will become as rare as a no-internet policy is today.

Regardless of the size of your business—be it Retail Banking, Investment Banking, Insurance, Forex, Building Societies, etc.—protecting your business from cybercriminals and their ever-changing means of “getting in” is essential.  The bottom line: Whatever cloud deployment best suits your business is considerably more scalable and elastic than hosting in-house, and therefore suits any organisation.

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

Download Now