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How Hackable Is Your Dating App?

February 14, 2019 — by Mike O'Malley — 0

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 3^rd 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.

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.

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?

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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The Costs of Cyberattacks Are Real

February 13, 2019 — by Radware — 0

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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.

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.

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What Do Banks and Cybersecurity Have in Common? Everything.

February 7, 2019 — by Radware — 0

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.

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.

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.

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.

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.

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.

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.

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HTTPS: The Myth of Secure Encrypted Traffic Exposed

February 5, 2019 — by Ben Zilberman — 0

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.

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.

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.

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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Attackers Are Leveraging Automation

January 31, 2019 — by Radware — 0

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.

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.

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.

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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The Rise in Cryptomining

January 29, 2019 — by Radware — 1

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.

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.

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).

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.

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Ensuring Data Privacy in Public Clouds

January 24, 2019 — by Radware — 0

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.

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.

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.

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.

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Here’s Why Foreign Intelligence Agencies Want Your Data

January 23, 2019 — by Mike O'Malley — 0

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.

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.

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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Looking Past the Hype to Discover the Real Potential of AI

January 22, 2019 — by Pascal Geenens — 0

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.

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.

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.

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:

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.
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.
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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Top 3 Cyberattacks Targeting Proxy Servers

January 16, 2019 — by Daniel Smith — 1

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.

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.

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.

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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Older Posts

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Privacy? What Privacy?

Hacking Love

Protect Yourself

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

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Long Lasting Impacts

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

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Adapting for the Future: DDoS Mitigation

Inspecting Encrypted Data

Dealing with DevOps and Agile Software Development

Adaptability is the Name of the Game

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

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Encrypted Application Layers

Environmental Aspects

Regulatory Limitations

Encryption Protocols

Attack Patterns

End-to-End Protection

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

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Automation for Detection and Mitigation

The Final Step: Self-Learning

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

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Always Crypto

The Malware Ecosystem

Social Propagation

Moving Forward

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

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When Your Inside Is Out, Your Outside Is In

Poor Security HYGIENE Leaves You Exposed

The Glaring Issue of Misconfiguration

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

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Could You Be A Target?

Look at the Whole Picture

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

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

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

What about politically motivated cyberattacks initiated at the national level?

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

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

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

Share this:

Attacking the CDN Proxy

Finding the Watering Holes

Attacking from the Side

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

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