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Security

The Intersections between Cybersecurity and Diversity

March 20, 2019 — by Kevin Harris0

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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.

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Attack Types & VectorsBotnetsSecurity

IoT Expands the Botnet Universe

March 6, 2019 — by Radware0

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

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

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

JenX

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

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

ADB Miner

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

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

Satori.Dasan

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

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

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

Memcached DDoS Attacks

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

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

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

Hajime Expands to MikroTik RouterOS

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

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

Satori IoT Botnet Worm Variant

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

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

Hakai

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

DemonBot

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

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

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

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

Always on the Hunt

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

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

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

Download Now

HacksSecurity

How Hackable Is Your Dating App?

February 14, 2019 — by Mike O'Malley0

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If you’re looking to find a date in 2019, you’re in luck. Dozens of apps and sites exist for this sole purpose – Bumble, Tinder, OKCupid, Match, to name a few. Your next partner could be just a swipe away! But that’s not all; your personal data is likewise a swipe or click away from falling into the hands of cyber criminals (or other creeps).

Online dating, while certainly more popular and acceptable now than it was a decade ago, can be risky. There are top-of-mind risks—does s/he look like their photo? Could this person be a predator?—as well as less prominent (albeit equally important) concerns surrounding data privacy. What, if anything, do your dating apps and sites do to protect your personal data? How hackable are these apps, is there an API where 3rd parties (or hackers) can access your information, and what does that mean for your safety?

Privacy? What Privacy?

A cursory glance at popular dating apps’ privacy policies aren’t exactly comforting. For example, Tinder states, “you should not expect that your personal information, chats, or other communications will always remain secure.” Bumble isn’t much better (“We cannot guarantee the security of your personal data while it is being transmitted to our site and any transmission is at your own risk”) and neither is OKCupid (“As with all technology companies, although we take steps to secure your information, we do not promise, and you should not expect, that your personal information will always remain secure”).

Granted, these are just a few examples, but they paint a concerning picture. These apps and sites house massive amounts of sensitive data—names, locations, birth dates, email addresses, personal interests, and even health statuses—and don’t accept liability for security breaches.

If you’re thinking, “these types of hacks or lapses in privacy aren’t common, there’s no need to panic,” you’re sadly mistaken.

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

Hacking Love

The fact is, dating sites and apps have a history of being hacked. In 2015, Ashley Madison, a site for “affairs and discreet married dating,” was notoriously hacked and nearly 37 million customers’ private data was published by hackers.

The following year, BeautifulPeople.com was hacked and the responsible cyber criminals sold the data of 1.1 million users, including personal habits, weight, height, eye color, job, education and more, online. Then there’s the AdultFriendFinder hack, Tinder profile scraping, Jack’d data exposure, and now the very shady practice of data brokers selling online data profiles by the millions.

In other words, between the apparent lack of protection and cyber criminals vying to get a hold of such personal data—whether to sell it for profit, publicly embarrass users, steal identities or build a profile on individuals for compromise—the opportunity and motivation to hack dating apps are high.

[You may also like: Here’s Why Foreign Intelligence Agencies Want Your Data]

Protect Yourself

Dating is hard enough as it is, without the threat of data breaches. So how can you best protect yourself?

First thing’s first: Before you sign up for an app, conduct your due diligence. Does your app use SSL-encrypted data transfers? Does it share your data with third parties? Does it authorize through Facebook (which lacks a certificate verification)? Does the company accept any liability to protect your data?

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

Once you’ve joined a dating app or site, beware of what personal information you share. Oversharing details (education level, job, social media handles, contact information, religion, hobbies, information about your kids, etc.), especially when combined with geo-matching, allows creepy would-be daters to build a playbook on how to target or blackmail you. And if that data is breached and sold or otherwise publicly released, your reputation and safety could be at risk.

Likewise, switch up your profile photos. Because so many apps are connected via Facebook, using the same picture across social platforms lets potential criminals connect the dots and identify you, even if you use an anonymous handle.

Finally, you should use a VPN and ensure your mobile device is up-to-date with security features so that you mitigate cyber risks while you’re swiping left or right.

It’s always better to be safe and secure than sorry.

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

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Attack MitigationSecurity

The Costs of Cyberattacks Are Real

February 13, 2019 — by Radware0

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Customers put their trust in companies to deliver on promises of security. Think about how quickly most people tick the boxes on required privacy agreements, likely without reading them. They want to believe the companies they choose to associate with have their best interests at heart and expect them to implement the necessary safeguards. The quickest way to lose customers is to betray that confidence, especially when it comes to their personal information.

Hackers understand that, too. They quickly adapt tools and techniques to disrupt that delicate balance. Executives from every business unit need to understand how cybersecurity affects the overall success of their businesses.

Long Lasting Impacts

In our digital world, businesses feel added pressure to maintain this social contract as the prevalence and severity of cyberattacks increase. Respondents to Radware’s global industry survey were definitely feeling the pain: ninety-three percent of the organizations worldwide indicated that they suffered some kind of negative impact to their relationships with customers as a result of cyberattacks.

Data breaches have real and long-lasting business impacts. Quantifiable monetary losses can be directly tied to the aftermath of cyberattacks in lost revenue, unexpected budget expenditures and drops in stock values. Protracted repercussions are most likely to emerge as a result of negative customer experiences, damage to brand reputation and loss of customers.

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

Indeed, expenditures related to cyberattacks are often realized over the course of several years. Here, we highlight recent massive data breaches–which could have been avoided with careful security hygiene and diligence to publicly reported system exploits:

The bottom line? Management boards and directorates should understand the impact of cyberattacks on their businesses. They should also prioritize how much liability they can absorb and what is considered a major risk to business continuity.

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

Download Now

Attack MitigationDDoSDDoS Attacks

What Do Banks and Cybersecurity Have in Common? Everything.

February 7, 2019 — by Radware0

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New cyber-security threats require new solutions. New solutions require a project to implement them. The problems and solutions seem infinite while budgets remain bounded. Therefore, the challenge becomes how to identify the priority threats, select the solutions that deliver the best ROI and stretch dollars to maximize your organization’s protection. Consultants and industry analysts can help, but they too can be costly options that don’t always provide the correct advice.

So how best to simplify the decision-making process? Use an analogy. Consider that every cybersecurity solution has a counterpart in the physical world. To illustrate this point, consider the security measures at banks. They make a perfect analogy, because banks are just like applications or computing environments; both contain valuables that criminals are eager to steal.

The first line of defense at a bank is the front door, which is designed to allow people to enter and leave while providing a first layer of defense against thieves. Network firewalls fulfill the same role within the realm of cyber security. They allow specific types of traffic to enter an organization’s network but block mischievous visitors from entering. While firewalls are an effective first line of defense, they’re not impervious. Just like surreptitious robbers such as Billy the Kid or John Dillinger, SSL/TLS-based encrypted attacks or nefarious malware can sneak through this digital “front door” via a standard port.

Past the entrance there is often a security guard, which serves as an IPS or anti-malware device. This “security guard,” which is typically anti-malware and/or heuristic-based IPS function, seeks to identify unusual behavior or other indicators that trouble has entered the bank, such as somebody wearing a ski mask or perhaps carrying a concealed weapon.

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

Once the hacker gets past these perimeter security measures, they find themselves at the presentation layer of the application, or in the case of a bank, the teller. There is security here as well. Firstly, authentication (do you have an account) and second, two-factor authentication (an ATM card/security pin). IPS and anti-malware devices work in
concert with SIEM management solutions to serve as security cameras, performing additional security checks. Just like a bank leveraging the FBI’s Most Wanted List, these solutions leverage crowd sourcing and big-data analytics to analyze data from a massive global community and identify bank-robbing malware in advance.

A robber will often demand access to the bank’s vault. In the realm of IT, this is the database, where valuable information such as passwords, credit card or financial transaction information or healthcare data is stored. There are several ways of protecting this data, or at the very least, monitoring it. Encryption and database
application monitoring solutions are the most common.

Adapting for the Future: DDoS Mitigation

To understand how and why cyber-security models will have to adapt to meet future threats, let’s outline three obstacles they’ll have to overcome in the near future: advanced DDoS mitigation, encrypted cyber-attacks, and DevOps and agile software development.

[You may also like: Agile, DevOps and Load Balancers: Evolution of Network Operations]

A DDoS attack is any cyber-attack that compromises a company’s website or network and impairs the organization’s ability to conduct business. Take an e-commerce business for example. If somebody wanted to prevent the organization from conducting business, it’s not necessary to hack the website but simply to make it difficult for visitors to access it.

Leveraging the bank analogy, this is why banks and financial institutions leverage multiple layers of security: it provides an integrated, redundant defense designed to meet a multitude of potential situations in the unlikely event a bank is robbed. This also includes the ability to quickly and effectively communicate with law enforcement. In the world of cyber security, multi-layered defense is also essential. Why? Because preparing for “common” DDoS attacks is no longer enough. With the growing online availability of attack tools and services, the pool of possible attacks is larger than ever. This is why hybrid protection, which combines both on-premise and cloud-based mitigation services, is critical.

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

Why are there two systems when it comes to cyber security? Because it offers the best of both worlds. When a DDoS solution is deployed on-premise, organizations benefit from an immediate and automatic attack detection and mitigation solution. Within a few seconds from the initiation of a cyber-assault, the online services are well protected and the attack is mitigated. However, on-premise DDoS solution cannot handle volumetric network floods that saturate the Internet pipe. These attacks must be mitigated from the cloud.

Hybrid DDoS protections aspire to offer best-of-breed attack mitigation by combining on-premise and cloud mitigation into a single, integrated solution. The hybrid solution chooses the right mitigation location and technique based on attack characteristics. In the hybrid solution, attack detection and mitigation starts immediately and automatically using the on-premise attack mitigation device. This stops various attacks from diminishing the availability of the online services. All attacks are mitigated on-premise, unless they threaten to block the Internet pipe of the organization. In case of pipe saturation, the hybrid solution activates cloud mitigation and the traffic is diverted to the cloud, where it is scrubbed before being sent back to the enterprise.

[You may also like: Choosing the Right DDoS Solution – Part IV: Hybrid Protection]

An ideal hybrid solution also shares essential information about the attack between on-premise mitigation devices and cloud devices to accelerate and enhance the mitigation of the attack once it reaches the cloud.

Inspecting Encrypted Data

Companies have been encrypting data for well over 20 years. Today, over 50% of Internet traffic is encrypted. SSL/TLS encryption is still the most effective way to protect data as it ties the encryption to both the source and destination. This is a double-edged sword however. Hackers are now leveraging encryption to create new, stealthy attack vectors for malware infection and data exfiltration. In essence, they’re a wolf in sheep’s clothing. To stop hackers from leveraging SSL/TLS-based cyber-attacks, organizations require computing resources; resources to inspect communications to ensure they’re not infected with malicious malware. These increasing resource requirements make it challenging for anything but purpose built hardware to conduct inspection.

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

The equivalent in the banking world is twofold. If somebody were to enter wearing a ski mask, that person probably wouldn’t be allowed to conduct a transaction, or secondly, there can be additional security checks when somebody enters a bank and requests a large or unique withdrawal.

Dealing with DevOps and Agile Software Development

Lastly, how do we ensure that, as applications become more complex, they don’t become increasingly vulnerable either from coding errors or from newly deployed functionality associated with DevOps or agile development practices? The problem is most cyber-security solutions focus on stopping existing threats. To use our bank analogy again, existing security solutions mean that (ideally), a career criminal can’t enter a bank, someone carrying a concealed weapon is stopped or somebody acting suspiciously is blocked from making a transaction. However, nothing stops somebody with no criminal background or conducting no suspicious activity from entering the bank. The bank’s security systems must be updated to look for other “indicators” that this person could represent a threat.

[You may also like: WAFs Should Do A Lot More Against Current Threats Than Covering OWASP Top 10]

In the world of cyber-security, the key is implementing a web application firewall that adapts to evolving threats and applications. A WAF accomplishes this by automatically detecting and protecting new web applications as they are added to the network via automatic policy generation. It should also differentiate between false positives and false negatives. Why? Because just like a bank, web applications are being accessed both by desired legitimate users and undesired attackers (malignant users whose goal is to harm the application and/or steal data). One of the biggest challenges in protecting web applications is the ability to accurately differentiate between the two and identify and block security threats while not disturbing legitimate traffic.

Adaptability is the Name of the Game

The world we live in can be a dangerous place, both physically and digitally. Threats are constantly changing, forcing both financial institutions and organizations to adapt their security solutions and processes. When contemplating the next steps, consider the following:

  • Use common sense and logic. The marketplace is saturated with offerings. Understand how a cybersecurity solution will fit into your existing infrastructure and the business value it will bring by keeping yourorganization up and running and your customer’s data secure.
  • Understand the long-term TCO of any cyber security solution you purchase.
  • The world is changing. Ensure that any cyber security solution you implement is designed to adapt to the constantly evolving threat landscape and your organization’s operational needs.

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

Download Now

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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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.

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Attack MitigationSecurity

Looking Past the Hype to Discover the Real Potential of AI

January 22, 2019 — by Pascal Geenens0

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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.

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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.

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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 MitigationAttack Types & Vectors

5 Ways Malware Defeats Cyber Defenses & What You Can Do About It

January 17, 2019 — by Radware0

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Malware is a key vector for data breaches. Research shows that 51% of data breaches include the usage of malware, whether for initial breach, expansion within the network or heisting data. Yet despite malware being a pivotal attack vector, companies are unable to defend against data-theft malware running wild in their network. In fact, some of the biggest and most well-publicized breaches ever were the result of undetected malware.

Why? Modern malware is built to evade traditional anti-malware defenses. Today’s malwares are sophisticated multi-vector attack weapons designed to elude detection using an array of evasion tools and camouflage techniques. In the game of chess between attackers and defenders, hackers constantly find new ways to stay one step ahead of existing defenses.

Modern Malware

Here are five common evasion techniques used by modern malware and how they beat traditional anti-malware defenses.

Polymorphic malware: Many traditional anti-malware defenses operate using known malware signatures. Modern data-theft malware counteracts this by constantly morphing or shapeshifting. By making simple changes to the code, attackers can easily generate an entirely new binary signature for the file.

Shapeshifting, zero-day malware beats signature-based defenses such as anti-virus, email filtering, IPS/IDS, and sandboxing.

File-less malware: Many anti-malware tools focus on static files and operating-systems (OS) processes to detect malicious activity. However, an increasingly common technique by attackers is to use file-less malware which is executed in run-time memory only, leaves no footprint on the target host and is therefore transparent to file-based defenses.

File-less malware beats IPS/IDS, UEBA, anti-virus, and sandboxing.

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Encrypted payloads: Some anti-malware defense use content scanning to block sensitive data leakage. Attackers get around this by encrypting communications between infected hosts and Command & Control (C&C) servers.

Encrypted payloads beat DLP, EDR, and secure web gateways (SWG).

Domain generation algorithm (DGA): Some anti-malware defenses include addresses of known C&C servers, and block communication with them. However, malwares with domain generation capabilities get around this by periodically modifying C&C address details and using previously unknown addresses.

Beats secure web gateways (SWG), EDR, and sandboxing.

Host spoofing: spoofs header information to obfuscate the true destination of the data, thereby bypassing defenses that target the addresses of known C&C servers.

Beats secure web gateways (SWG), IPS/IDS and sandboxing.

[You may also like: Micropsia Malware]

What Can You Do?

Beating zero-day evasive malware is not easy, but there are several key steps you can take to severely limit its impact:

Apply multi-layer defenses: Protecting your organization against evasive malware is not a one-and-done proposition. Rather, it is an ongoing effort that requires combining endpoint defenses (such as anti-virus software) with network-layer protection such as firewalls, secure web gateways and more. Only multi-layered protection ensures complete coverage.

Focus on zero-day malware: Zero-day malware accounts for up to 50% of malware currently in circulation. Zero-day malware frequently goes unrecognized by existing anti-malware defenses and is a major source of data loss. Anti-malware defense mechanisms that focus squarely on identifying and detecting zero-day malwares is a must have.

[You may also like: The Changing Face of Malware: Malware Being Used as Cryptocurrency Miners]

Implement traffic analysis: Data theft malware attacks take aim at the entire network to steal sensitive data. Although infection might originate from user endpoints, it is typically the aim of attackers to expand to network resources as well. As a result, it is important for an anti-malware solution to not just focus on  one area of the network or resource type, but maintain a holistic view of the entire network and analyze what is happening.

Leverage big data: A key ingredient in detecting zero-day malware is the ability to collect data from a broad information base amassed over time. This allows defenders to detect malware activity on a global scale and correlate seemingly unrelated activities to track malware development and evolution.

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

Download Now