Protecting Endpoints From Day One

Deploying and managing endpoint protection shouldn’t be difficult. However, customers of traditional endpoint protection products complain about day-to-day management, database maintenance, agent updates, and constant tuning to eliminate false positives and keep resource utilization in check. Worst, even with all this work, endpoints still get compromised.

A customer who was evaluating Traps put it into “listen mode” to see if it would catch anything the customer’s existing endpoint protection product could not. Within minutes of deploying agents, a domain controller lit up the Traps management service console with alerts. When the incident response team pulled up the console, they immediately identified a piece of targeted malware that had been running on that server for some time. This was an eye opener, and the customer immediately realized the simplicity and power Traps offers, even from day one.

Traps Management Service

As new malware variants pop up around the globe, and as new software bugs and vulnerabilities are discovered, it can be challenging to ensure your endpoints remain secure. With the cloud-based Traps management service, you save the time and cost of building out your own global endpoint security infrastructure. Its simplified deployment requires no server licenses, databases or other infrastructure to get started, enabling you to start protecting your endpoints from day one.

Palo Alto Networks deploys and manages the Traps management service security infrastructure globally to manage the endpoint security policy for local and remote endpoints, ensuring the service is secure, resilient, up to date and available when you need it. This allows you to focus on defining the polices to meet your corporate usage guidelines instead of deploying and managing the infrastructure.

Traps management service comprises the following components:

  • Traps management service web interface is a cloud-based security infrastructure service designed to minimize the operational challenges of protecting your endpoints. From the Traps management service, you can manage your endpoint security policy, review security events as they occur and perform additional analysis of associated logs.
  • Traps agents protect each local or remote endpoint. The agent enforces your security policy on the endpoint and reports when it detects a threat. Agents communicate securely with Traps management service using Transport Layer Security 1.2.
  • Logging Service is a cloud-based logging infrastructure that allows you to centralize the collection and storage of Traps agent logs, regardless of location. Traps agents and Traps management service forward all logs to the Logging Service. You can view these logs in Traps management service, and with the Log Forwarding app, you can forward logs to an external syslog receiver.

Integrated with Traps, WildFire malware prevention service identifies previously unknown malware and generates signatures that Palo Alto Networks next-generation firewalls and the Traps management service can use to detect and block the malware. When a Traps agent detects an unknown sample, Traps management service can automatically forward it to WildFire for analysis. Based on the properties, behaviors and activities the sample displays when analyzed and executed in the WildFire sandbox, WildFire delivers a verdict: benign, grayware, phishing or malicious. WildFire then generates signatures to recognize any newly discovered malware and makes the signatures globally available in as few as five minutes.

Traps management service provides out-of-the-box protection for all registered endpoints, with a default security policy for each type of platform.

Traps Security Profiles

Out of the box, Traps management service provides default security profiles you can use to begin protecting your endpoints from threats immediately. Although security rules enable you to block or allow execution of files on your endpoints, security profiles help you customize and reuse settings across different groups of endpoints. When Traps detects a behavior that matches a rule defined in your security policy, it applies the security profile attached to the rule for further inspection. You can enjoy immediate protection from multiple security profiles:

  • Exploit profiles block attempts to exploit system flaws in browsers and operating systems. These help protect against exploit kits, illegal code execution, and other attempts to exploit process and system vulnerabilities.
  • Malware profiles protect against the execution of malware, including Trojans, viruses, worms and grayware. Malware profiles serve to define how to treat behavior common with malware, such as ransomware or script-based attacks, and how to treat known malware and unknown files.
  • Restrictions profiles limit where executable files can run on an endpoint. For example, you can restrict files from running from removable media or specific, local folders.
  • Agent settings profiles let you customize settings that apply to the Traps application, such as the disk space quota for log retention. For Mac® and Windows® platforms, you can also customize user interface options for the Traps console, such as accessibility and notifications.

 

Conclusion 

Security built solely to protect virtual endpoints often lacks the broader contextual intelligence critical to effective enterprise security architecture. Integrated threat intelligence, including data on the tactics, techniques and procedures of new and previously seen cyberattacks, is often critical to successfully defend systems and networks.

As an integral part of the Palo Alto Networks Security Operating Platform, Traps prevents cyberattacks automatically and in real time, regardless of the nature of the endpoints and the systems you have deployed. In concert with WildFire, Traps and the entire Security Operating Platform benefit from increased contextual visibility into – and protection against – correlated threat actors and campaigns, wherever they may try to attack.

 

Customers depend on Traps to ensure endpoints are protected, whether online or off, on-site or remote. IT teams must be able to confidently apply policies that control access to critical resources, and you need confidence in the integrity and configuration of the devices being used to connect to your network, whenever and wherever that may be. Protection cannot depend on full-time network access – it should just work, out of the box, from day one.

Watch the webinar “5 Endpoint Protection Best Practices” to learn the essential requirements for endpoint protection, and how Traps advanced endpoint protection is simple to deploy and manage, providing a prevention-first approach that protects endpoints from malware, exploits and ransomware.

 and 

Source: https://researchcenter.paloaltonetworks.com/2019/01/protecting-endpoints-day-one/

[Palo Alto Networks Research Center]

What Does It Mean to Be “5G-Ready”?

With regard to security, it’s critical.

We keep hearing about products and technologies that are “5G-ready.” But what does that mean? Mobile Service Providers will undoubtedly require 5G equipment that is scalable in terms of capacity and throughput, but does that alone mean the networks will be 5G-ready?

In late February at Mobile World Congress 2019, we can certainly expect to see demos of 5G core networks, network slicing, New Radios (5G-NR), and other 5G-ready network components. But what about security? Mobile networks will not be 5G-ready unless the necessary security capabilities are baked into these networks by design.

Tom Wheeler, former chairman of the Federal Communications Commission, accurately points out in a recent NY Times op-ed:  “Leadership in 5G technology is not just about building a network, but also about whether that network will be secure enough for the innovations it promises.”  Wheeler goes on to state, “The simple fact is that our wireless networks are not as secure as they could be because they weren’t designed to withstand the kinds of cyberattacks that are now common. This isn’t the fault of the companies that built the networks, but a reflection that when the standards for the current fourth-generation (4G) technology were set years ago, cyberattacks were not a front-and-center concern.”

 

A New Approach for Security Is Needed

With 5G, everything changes. Critical applications like remote healthcare, remote monitoring and control over our power grids, and self-driving automobiles will all rely on 5G technologies. The networks will become more distributed, and many critical applications will be hosted at the edge of 5G networks and across edge clouds. Opportunities for threat actors will emerge if they are allowed to go unchecked, as they will use automation to wage multi-stage attacks and find the least secure portions of the 5G networks to exploit. For mobile networks to be 5G-ready, a new approach for security is required.

 

Even though standards and network architectures are still being defined, mobile operators not only have the opportunity to build the right set of security capabilities into these network evolutions by design, they have no choice but to do it. Today’s cyberattacks are already capable of evading mobile networks, and their continued evolution is indeed a front-and-center concern.

To truly be 5G-ready, mobile operators need to adopt a robust and comprehensive end-to-end security strategy with:

  • Complete visibility, inspection, and controls that are applied across all layers of the network – application, signaling, and data planes.
  • Cloud-based threat analytics – powered by machine learning (ML) – that are leveraged across the different mobile network locations and environments.
  • A cloud-ready platform that ensures consistent security enforcement across all network locations.

With these necessary security capabilities in place, mobile networks will be able to evolve as 5G-ready with a data-driven threat prevention posture that provides contextual security outcomes. Mobile operators will be able to automate processes to proactively identify infected devices and prevent device-initiated attacks. They will be able to capture advanced multi-stage attacks that will naturally look to leverage different signaling and control layers across the 5G networks. They will be able to automatically identify advanced threats, correlate these with specific devices/users, and isolate/remove infected devices from their networks. They will also be able to differentiate themselves as “secure business enablers.”

These 5G networks are set to become the backbone of transformational services that will positively alter our lives for generations to come. Whether it’s autonomous vehicles, remote surgery, smart utilities, or the multitude of other technological advancements that will enable us to benefit from 5G, as Wheeler states: “Innovators, investors and users need confidence in the network’s cybersecurity if its much-heralded promise is to be realized.”

 

Meet with us at Mobile World Congress for an exclusive, executive 5G security briefing

Email us at:  mwc@paloaltonetworks.com

 

References:

Palo Alto Networks: A New Approach for 5G Security

Lee Klarich Interview on 5G Cyber Security

Webinar:  5G Security:  A New Approach is Needed

 

Source: https://researchcenter.paloaltonetworks.com/2019/01/what-does-it-mean-to-be-5g-ready/

[Palo Alto Networks Research Center]

Google’s GDPR Fine Reinforces Need for Intentional Data Governance

For those of us who work in information security, data privacy and governance, we seem to traverse daily from one headline to another. A new corporate victim announces they were breached to the tune of 100 million records. A regulatory body announces a financial and oversight settlement with a company for failure to adequately protect data. On and on we go.

Because of this constant onslaught, nobody was terribly surprised to hear about the €50 million fineleveled against Google by French data privacy regulators for violations of GDPR. We all knew a big enforcement was coming, and that the early, large fines would be against a social media or tech giant.  Check and check. But what does this mean to organizations on a broader scale?

As I draft this post on Data Privacy Day, trying to find the larger meaning in this first-of-many large fines, I am faced with many possibilities. Could the message be about regulatory muscle-flexing, or is it about corporate arrogance and gamesmanship? Is this a legitimate assertion of individual rights against a corporate giant, or is it an attack against a successful tech company and its profit model? In GDPR, are we looking at the shape of tomorrow’s global data environment, or are we seeing a regulatory trend that risks stifling innovation and “free” service delivery? Of course, the answer is all of the above.

The regulatory authorities across the EU who are charged with enforcing GDPR must, at some point, exercise their authority. No regulation can be effective until it is applied, tested and, ultimately, proven or defeated in practice. At the same time, some organizations may look at the details of the regulation and make a risk-based assessment that they have done enough to comply with their interpretation of the regulation, reasoning “We have taken some [less-than-perfect] actions, let’s see what happens.” The rights to one’s personal data are becoming more widely accepted as a given, but many consumers still are willing to casually or selectively trade some of those rights for convenience or services. With data privacy and security laws and regulators proliferating and evolving, data-centric business activities and profit models must be more carefully engineered and scrutinized. All of the above.

This recent and highly publicized enforcement activity is likely to spur additional compliance efforts from many organizations. Few can absorb a fine with that many zeros in it. On a strategic level, however, it may well contribute to the gradual paradigm shift away from the whack-a-mole approach to security and privacy regulations, and toward a philosophy of intentional data governance and strategy.

There are many financial and organizational benefits to proper data governance, including lower infrastructure costs, better litigation readiness, smaller cyberattack footprint, and better visibility for regulatory compliance. But sometimes it takes a negative result occurring to somebody else to make us ask the right questions and do the right things. Time will tell if a hefty fine is enough to move the behavioral needle for Google, or for the rest of us.

Editor’s note: For more on this topic, read “Maintaining Data Protection and Privacy Beyond GDPR Implementation.”

Andrew Neal, C|CISO, CISM, CRISC, CCFP, CIFI, LPI, President, Information Security & Compliance Services, TransPerfect Legal Solutions, and ISACA conference speaker

Source: https://www.isaca.org/Knowledge-Center/Blog/Lists/Posts/Post.aspx?ID=1139

[ISACA Now Blog]

The Need for Endpoint Protection in Critical Infrastructure

As cyberattacks against ICS and SCADA systems become commonplace, the need for robust endpoint protection grows. The rapid growth of the internet, with its ever-increasing need for data, has made it almost mandatory that information be made available at all times. This gluttony of data results in the need for corporations to provide connections to devices within their process control networks without fully understanding the potential outcome of such actions.

Reasons for the increase in attacks

Thanks to trends like the internet of things, aka IoT, and Industry 4.0, the rise in attacks against critical infrastructure is becoming more prolific and targeted. This is seen in both the recently unsuccessful attack against a petrochemical company in Saudi Arabia during 2018 and the infamously successful Ukraine power grid breach of 2016. Cyberattacks against critical infrastructure are becoming prevalent, partially due to the increased number of networks connected and business-accessible devices, along with the need for the data they generate. Combine this with the demand placed on companies to do more with less staffing and more outsourcing as they attempt to lower yearly operational expense, and the potential for gaps in security grows – in some instances exponentially resulting in a number of worst-case scenarios for operators. With the need for remote access for employees and third-party support, businesses are facing more access to the environment and missing or misconfigured security policies that provide hackers with ideal attack vectors.

It has also come to light that critical infrastructure assets are becoming easier to find and identify, without any direct interaction from potential attackers. Using open source intelligence-gathering techniques, internet databases like Shodan, and geo-stalking, attackers are able to find these assets without exposing themselves or their intent – a clear example of too much information being readily available and unsecure.

Regardless of the reason for the lapse in security, all incidents of breach of a controls network shows us just how disruptive and dangerous these endpoints can be to our daily lives when under the control of those with malicious intent.

Why attack ICS and SCADA endpoints

Motives for attacking these systems can be grand in scope, ranging from corporate espionage with the intent to destroy a competitor’s brand to political in nature, such as the intent to influence the inner workings of a rival nation’s government. We also see examples of attacks that have a more simplistic purpose like financial gain or a script kiddie proving he or she can take control, earning them bragging rights. Regardless of the attacker’s motivation, the need to protect these critical infrastructure assets is of the utmost importance for the companies that run them and the community at large.

Current research into the matter shows that the number of vulnerabilities related to ICS and SCADA systems is doubling on a yearly cadence. As of this year, the estimated number of identified critical infrastructure-related vulnerabilities is roughly around 400, a number that will continue to grow due to the nature of how these systems operate and the security challenge they create. Legacy operating systems and the high uptime mandates of these systems make them some of the most difficult to secure.

There is hope

Despite all the advancements attackers are making to breach and control critical infrastructure, it is possible to defend and protect these highly targeted assets.

True advanced endpoint protection must be capable of preventing known and unknown threats by leveraging features such as:

  • Machine learning, which is capable of providing an instant verdict on an unknown executable before it runs on any of the systems in a process network.
  • Virtual sandboxing technology that can determine if an executable file is malicious before it executes on the machine.
  • Identifying software packages from vendors that are trusted in the environment and blocking those that are not.
  • Support for the various operating systems that controls systems run, including some that are end-of-life.
  • Cloud-readiness.

ICS/SCADA systems require advance endpoint protection capable of disrupting known and unknown cyberattacks while not impacting production. The approach must be lightweight, scalable, innovative and capable of integrating both existing and new technologies while complementing other best practice procedures and offerings. Most importantly, it must be powerful and ICS/SCADA-friendly.

To learn how Palo Alto Networks can help operators of ICS and SCADA networks protect their critical infrastructure, download this whitepaper on advanced endpoint protection for ICS/SCADA systems.

[Palo Alto Networks Research Center]

Cloud Security, Yes – But Is AI Ready for Its Cybersecurity Spotlight?

In today’s world, speed, agility and scalability are essential for organizations and businesses if they want to become successful and stay relevant. On-premises IT can’t provide them with the speed, agility and scalability cloud environments can, so the continued embrace of cloud is inevitable.

Unfortunately, the same characteristics – speed, agility and scalability – also apply to the bad guys. We now see, for example:

  • Production of malware via sites that offer ransomware as a service
  • Proliferation of non-distributing multi-scanners
  • An explosion of available exploit kits based on cloud computing capabilities

These developments signify a serious need to change the approach to securing organizations.

Effective security can no longer rely on a point product approach, for which the acquisition, implementation and training might take weeks or even months. In the cloud era, that’s no longer a viable tactic because the manual use of these point products makes organizations slow and reactive. In other words, we simply cannot defend our organizations against highly sophisticated, automated and agile threats by using old-fashioned, non-automated and non-integrated security.

Cybersecurity technology companies understand this and have for some years been investing in cloud computing, including ways to secure cloud environments and deliver security via cloud-based services. An example of a cloud-delivered security service is a threat intelligence capability in the cloud, which uses the speed and scalability of the cloud model for its software analysis process and can deliver the protection needed within a very short time frame.

The core of what will make cloud computing capabilities continually useful is big data analytics. Without big data analytics, it’s impossible to apply machine learning, which is essential for automation and the required speed of operations. Unfortunately, the terms ‘big data analytics’, ‘machine learning’ and ‘artificial intelligence’ are often confused and used interchangeably. Several cybersecurity companies claim to use artificial intelligence for their services, but they probably mean big data analytics and machine learning. To explain this in simple words, here are the definitions I use to clarify these terms:

  • Big data analytics refers to analyzing large volumes of data with the aim to uncover patterns and connections that might otherwise be invisible, and that might provide valuable insights.[1]
  • Machine learning is a software-development technique used to teach a computer to do a task without explicitly telling the computer how to do it.[2]
  • Artificial intelligence is software that becomes aware of its own existence and can make thoughtful decisions.[3]

How are big data analytics, machine learning, artificial intelligence or the combination of these capabilities best used to protect organizations from cyberattacks?

Unfortunately, there’s no silver bullet yet in this context, although large amounts of data can be better and more quickly handled by machines than by humans (see the threat intelligence example above). The challenge is that AI, especially, is being over-marketed for cybersecurity, but the technology has its limitations: AI is never designed to work in adversarial environments. It works quite well in games like chess or go, where the rules are well-defined and deterministic.[4] But in cybersecurity, these rules don’t apply, and the ‘bad guys’ are constantly evolving and adapting their techniques. At this moment, AI is less suitable because it cannot adapt to the fast and unpredictable environment. This will no doubt improve in the future.

Analyzing data kept in one place also means that place is a single point of failure. An attacker only needs to make subtle, almost unnoticeable changes to the data in this one data location, which could undermine the way an AI algorithm works.[5] Therefore, it’s essential to understand how big data analytics, machine learning and AI work; recognize the limitations; and act accordingly, not on hype.

In today’s world, the use of big data analytics, machine learning and AI provides several advantages in the cybersecurity domain – especially in the threat intelligence, behavioral analytics and cyber forensics areas – but there’s still a long way to go before we can completely rely on these capabilities in cybersecurity. When we get them right, we will truly maximize our investments in cloud.

  1. “Big Data Analytics,” Techopedia, accessed October 27, 2018. https://www.techopedia.com/definition/28659/big-data-analytics.
  2. Rick Howard, “The Business of AI and Machine Learning,” SecurityRoundtable.org, October 11, 2017, https://www.securityroundtable.org/the-business-of-ai-and-machine-learning/.
  3. Rick Howard, “The Business of AI and Machine Learning,” SecurityRoundtable.org, October 11, 2017, https://www.securityroundtable.org/the-business-of-ai-and-machine-learning/.
  4. Jane Bird, “AI is not a ‘silver bullet’ against cyber attacks,” Financial Times, last modified September 25, 2018, https://www.ft.com/content/14cd2608-869d-11e8-9199-c2a4754b5a0e.
  5. Ibid.

Source: https://researchcenter.paloaltonetworks.com/2018/10/cloud-security-yes-ai-ready-cybersecurity-spotlight/

[Palo Alto Networks Research Center]

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