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Category Archive for ‘Predictive Analytics’

How to counter-punch botnets, viruses, ToR and more with Netflow (Pt. 2)

Data Retention Compliance

End-Point Profiling

Hosts that communicate with more than one known threat type should be designated a high risk and repeated threat breaches with that hosts or dependent hosts can be marked as repeat offenders and provide an early warning system to a breach or an attack.

It would be negligent of me not to mention that the same flow-based End-Point threat detection techniques can be used as part of Data Retention compliance. In my opinion this enables better individual privacy with the ability to focus on profiling known bad end-points and be used to qualify visitors to such known traffic end-points that are used in illicit p2p swap sessions or access to specific kinds of subversive or dangerous sites that have been known to host such traffic in the past.

Extreme examples of end-point profiling could be to identify a host who is frequently visiting known jihadist web sites or pedophiles using p2p to download from peers that have been identified by means of active agents to carry child abuse material. The individual connection could be considered a coincidence but multiple visitations to multiple end-points of a categorized suspicious nature can be proven to be more than mere coincidence and provide cause for investigation.

Like DDoS attack profiles there may be a prolific amount of end-points involved and an individual conversation is difficult to spot but analysis of the IP’s involved in multiple transactions based on the category of the end-point will allow you to uncover the “needles in the haystack” and to enable sufficient evidence to be uncovered.

Profiling Bad traffic

End-Point Threat detection on its own is insufficient to detecting threats and we can’t depend on blacklists when a threat morphs faster than a reputation list can be updated. It is therefore critical to concurrently analyze traffic using a flow behavior anomaly detection engine.

This approach should be able to learn the baselines of your network traffic and should have the flexibility to baseline any internal hosts that your risk management teams deem specifically important or related such as a specific group of servers or high-risk interfaces and so-forth enabling a means to quantify what is normal and to identify baseline breaches and to perform impact analysis.

This is where big-data machine learning comes into play as to fully automate the forensics process of analyzing a baseline breach automating baselines and automatically running diagnostics and serving up the Predictive AI Baselining analytics needed to quickly identify the IP’s that are impacting services to provide extreme visibility and if desired mitigation.

Automated Diagnostics enable security resources to be focused on the critical issues while machine learning processes continue to quantify the KPI’s of ongoing issues bringing them to the foreground quickly taking into account known blacklists, whitelists and repeat offenders.

As a trusted source of deep network insights built on big data analysis capabilities, Netflow provides NOCs with an end-to-end security and performance monitoring and management solution. For more information on Netflow as a performance and security solution for large-scale environments, download our free Guide to Understanding Netflow.

Cutting-edge and innovative technologies like CySight delivers the deep end-to-end network visibility and security context required assisting in speedily impeding harmful attacks.

Performance Monitoring & Security Forensics: The 1-2 Punch for Network and IT Infrastructure Visibility

Integrated Cyber Network Intelligence: Your Network has been infiltrated. How do you know where and what else is impacted?

Why would you need Granular Network Intelligence?

“Advanced targeted attacks are set to render prevention-centric security strategies obsolete and that information must become the focal point for our information security strategies.” (Gartner)

In this webinar we take a look at the internal and external threat networks pervasive in todays enterprise and explore why organizations need granular network intelligence.

Webinar Transcription:

I’m one of the senior engineers here with CySight. I’ll be taking you through the webinar today. It should take about 30 to 40 minutes, I would say and then we will get to some questions towards the end. So let’s get started.

So the first big question here is, “Why would you need something like this? Why would you need Granular Network Intelligence?” And the answer, if not obvious already, is that, really, in today’s connected world, every incident response includes a communications component. What we mean by that is in a managed environment, whether it’s traditional network management or security management, anytime that there’s an alert or some sort of incident that needs to be responded to, a part of that response is always going to be communications, who’s talking to who, what did they do, how much bandwidth did they use, who did they talk to?

And in a security particular environment, we need to be looking at things like whether external threats or internal threats, was there a data breach, can I look at the historical behavior or patterns, can I put this traffic into context as per the sort of baseline of that traffic? So that insight into how systems have communicated is critical.

Just some background industry kind of information. According to Gartner, targeted attacks are set to render prevention-centric security strategies obsolete by 2020. Basically, what that means is there’s going to be a shift. They believe there’s going to be a shift to information and end-user-centric security focused on an infrastructure’s end-points and away from sort of the blocking and tackling of firewalls. They believe that there’ll be three big trends continuous compromise, meaning that an increased in level of advanced attacks, targeted attacks. It’s not going to stop. You’re never going to feel safe that someone won’t be potentially trying to attack you.

And most of those attacks will become financially motivated attacks, attempts to steal information and attempts to gather credit card data, if you have that, intellectual property, ransomware-type attacks. So this is not necessarily, “Hey, I’m just going to try and bring down your website or something,” in a traditional world where maybe people are playing around a little bit. This is more organized attacks specifically designed to either elicit a ransom or a reward or just steal information that could be turned into money out in a black market and it’s going to be more and more difficult for IT to have control over those end-user’s devices.

Again, very few organizations just have people sitting at their desks with desktop computers anymore. Everybody’s got laptops. Everybody’s got a phone or other tablet that’s moving around. People work from home. They work from the road. They’re connecting in to network resources from anywhere in the world at any time and it becomes more and more challenging for IT to sort of control those pathways of communications. So if you can’t control it, then you have to certainly be able to monitor it and react to it and the reaction is really in three major ways; determining the origin of the attack, the nature of the attack, and the damage incurred.

So we’re certainly assuming that there are going to be attacks, and we need to know where they’re coming from, what they’re trying to do, and have they been able to get there? You know, have we caught it in time or has something already been infected or has information been taken away from the network and that really leads us into this little graphic that we have about not being in denial. Understanding that, unfortunately, many people, in terms of their real visibility into the network, are somewhere in the blind or limited-type area. They don’t know what they don’t know, they think they should know but they don’t know, and etc.

But where they really need to be is at, “There’s nothing they don’t know.” And they need tools to be able to move them from wherever they are into this upper left-hand quadrant and certainly, that’s what our product is designed to do. So just kind of looking at the entire landscape of information flow from outside and inside and really understanding that there are new kinds of attacks, crawlers, botnets, ransomware, ToR, DoS and DDoS attacks that have been around for a while.

Your network may be used to download or host illicit material, leak intellectual property, be part of an attack, you know, something that’s command and controlled from somewhere else and your internal assets have become zombies and are being controlled by outside. There are lots of different threats. They’re all coming at you from all over the place. They’re all trying to get inside your network to do bad things and those attacks or that communication needs to be tracked.

Gartner also believes that 60% of enterprise security budgets will be allocated for rapid detection and response by 2020, up from less than 10% just a few years ago. What they believe is that too much of the spending has gone into prevention and not enough has gone into monitoring and response. So the prevention is that traditional firewalling, intrusion detection or intrusion prevention, things like that, which certainly is important. I’m not saying that those things aren’t useful or needed. But what we believe and what other industry analysts certainly believe is that that’s not enough, basically. There needs to be more than the simple sort of “Put up a wall around it and no one will be able to get in” kind of situation. If that were the case, then there would be no incidents anywhere because everybody’s got a firewall; large companies, small companies. Everybody’s got that today, and yet, you certainly don’t go more than a couple of days without hearing about new hacks, new incidents.

Here in the United States, we just came through an election where they’re still talking about people from other countries hacking into one party or another’s servers to try and change the election results. You know, on the enterprise side, there are lots and lots of businesses. Yahoo recently in the last couple of months certainly had a major attack that they had to come clean about it and of course both of those organizations, certainly Yahoo, you know, they’re an IT system. They have those standard intrusion prevention and firewall-type systems, but obviously, they aren’t enough.

So when you are breached, you need to be able to look and see what happened, “What can I still identify, what can I still control, and how do I get visibility as to what happened.” So for us, we believe that the information about the communication is the most important focal point for a security strategy and we can look at a few different ways to do that without a signature-based mechanism. So there’s ways to look at normal traffic and be able to very rapidly identify deviation from normal traffic. There’s ways to find outliers and repeat offenders. There’s ways to find nefarious traffic by correlating real-time threat feeds with current flows and we’re going to be talking about all of these today so that a security team can identify what was targeted, what was potentially compromised, what information may have left the building, so to speak.

There’s a lot of challenges faced by existing firewalls, SIEM, and loosely-coupled toolsets. The level of sophistication, it’s going up and up again. It’s becoming more organized. It’s an international crime syndicate with very, very intelligent people using these tactics to try and gain money. As we’ve talked about, blocking attack, laying end-point solutions are just not enough anymore and of course, there’s a huge cost in trying to deploy, trying to maintain multiple solutions.

So being able to try and have some tools that aren’t incredibly expensive, that do give you valuable information really, can become the best way to go. If you look at, say, what we’re calling sensors; packet captures, DPI-type systems. They, certainly, can do quite a lot, but they’re incredibly expensive to deploy across a large organization. If you’re trying to do packet capture, it’s very, very prohibitive. You can get a lot of detail, but trying to put those sensors everywhere is just… unless you’ve got an unlimited budget, and very few people do, that becomes a really difficult proposition to swallow.

But that doesn’t mean NetFlow can’t still use that kind of information. What we have found and what’s really been a major trend over the last couple of years is that existing vendors, on their devices, Check Point, Cisco, Palo Alto, packet brokers like Ixia, or all of the different people that you see up here, and more and more all the time, are actually adding that DPI information into their flow data. So it’s not separate from flow data. It’s these devices that have the packets going through them that can look at them all the way to layer seven and then include that information in the NetFlow export out to a product like ours that can collect it and display that.

So you can look into payload and classify according to payload content identifying traffic on port 80 or what have you, that you can connect the dots between inside and outside when there’s NAT. To be able to read the URLs and quickly analyze where they’re going and what they’re being used for. Getting specialized information like MAC address information or, if it’s a firewall, getting denial information or AAA information, if it’s a wireless LAN controller, getting SSID information, and other kinds of things that can be very useful to track down where people were talking.

So different types of systems are adding different kinds of information to the exports, but all of them, together, really effectively give you that same capability as if you had those sniffing products all over the place or packet capture products all over the place. But you can do it right in the devices, right from the manufacturer, send it through NetFlow, to us, and still get that quality information without having to spend so much money to do it.

The SANS organization, if you’re not familiar with them, great organization, provide a lot of good information and whitepapers and things like that. They have, very often, said that NetFlow might be the single most valuable source of evidence in network investigations of all sorts, security investigations, performance investigations, whatever it may be.

The NetFlow data can give you very high value intelligence about the communications. But the key is in understanding how to get it and how to use it. Some other benefits of using NetFlow, before packet capture is the lack of need for huge storage requirements. Certainly, as compared to traditional packet capture, NetFlow is much skinnier than that and you can store much longer-term information than you could if you had to store all of the packets. The cost, we’ve talked about.

And there are some interesting things like legal issues that are mitigated. If you are actually capturing all packets, then you may run into compliance issues for things like PCI or HIPAA. In certain different countries and jurisdictions around the world have very strict regulations about maintaining the end-data and keeping that data. NetFlow, you don’t have that. It’s metadata. Even with the new things that you can get, that we talked about a couple of slides ago, it’s still the metadata. It’s still data about the data. It’s not the actual end information. So even without that content, NetFlow still provides an excellent means of guiding the investigations, especially in an attack scenario.

So here, if you bundle everything that we’ve talked about so far into one kind of view and relate it to what we do here at CySight. You would see it on this screen. There are the end-users of people/content and things today, the Internet of things. So you’ve got data coming from security cameras and Internet-connected vehicles and refrigerators. It could be just about anything, environmental-type information. It’s all producing data. That data is traversing the network through multiple different types of platforms, or routers, switches, servers, wireless LAN controllers, cloud-based systems and so forth, all of which can provide correlation of the information and data. We call that the correlation API.

We then take that data into CySight. We combine it with outside big data, we’re going to talk about that in a minute, so not only the data of the connections but actual third-party information that we have related to known bad actors in the world and then we can use that information to provide you, the user, multiple benefits, whether it’s anomaly detection, threat intelligence, security performance, network accounting, all of the sort of standard things that you would do with NetFlow data.

And then lastly, integrate that data out to other third-party systems, whether it’s your managed service provider or security service provider. It could be upstream event collectors, trappers, log systems, SOAPA ecosystems, whether that’s on-premise or in the cloud or hybrid cloud. All of that is available via our product. So it starts at the traffic level. It goes through everything. It provides the data inside our product and as well as integrates out to third-party systems.

So let’s actually look into this a little more deeply. So the threat intelligence information is one of the two major components of our cyber security areas. One, the way this works is that threat data is derived from a large number of sources. So we maintain a list, effectively, a database of known bad IP addresses, known bad actors in the world. We collect that data through honeypots, and threat feeds, and crowd sources, and active crawlers, and our own internal user cyber feedback from our customers and all of that information combined allows us to maintain a very robust list of known bads, basically. Then we can combine that cyber intelligence data with the connection data, the flow data, the session data, inside and outside of your network, you know, the communications that you’re having, and compare the two.

So we have the big data threats. We can process that data along with what’s happening locally in your network to provide extreme visibility, to find who’s talking to who, what conversations are your users having with bad actors, ransomware, botnets, ToR, hacking, malware, whatever it may be and we then provide, of course, that information to you directly in the product. So we’re constantly monitoring for that communication and then we can help you identify it and remediate it as soon as possible.

As we look into this a little bit   zoomed in here a little bit, you can see that that threat information can be seen in summary or in detail. We have it categorized by different threat levels, types, severities, countries of origin, affected IPs, threat IPs. As anyone who’s used our product in the past knows, we always provide an extreme amount of flexibility to really slice and dice the data and give you a view into it in any way that is best consumed by you. So you can look at things by type, or by affected IP, or by threat IP, or by threat level, or whatever it may be and of course, no matter where you start, you can always drill in, you can filter, you can re-display things to show it in a different view.

Here’s an example of identifying some threat. These are ransomware threats, known ransomware IPs out there. I can very easily just right-click on that and say, “Show me the affected IP.” So I see that there’s ransomware. Who’s affected by that? Who is actually talking to that? And it’s going to drill right down into that affected IP or maybe multiple affected IPs that are known to be talking to those ransomware systems outside. You could see when it happened. You can see how much traffic.

Certainly, in this example our top affected IP here certainly has a tremendous amount of data, 307 megs over that time period, much more than the next ones below that and so that’s clearly one that needs to be identified or responded to very quickly. It can be useful to look at this way, to see if, “Hey,” you know, “Is this one system that’s been infiltrated or is it now starting to spread? Are there multiple systems? Where is it starting? Where is it going and how can I then sort of stem that tide?” It very easy to get that kind of information.

Here’s another example showing all ransomware attack, traffic, traversing a large ISP over a day. So whether you’re an end-user or certainly a service provider, we have many, many service provider customers that use this to monitor their customer’s traffic and so this could be something that you look at to say “Across all of my ISP, where is that ransomware traffic going? Maybe it’s not affecting me but it’s affecting one of my customers.” Then we can be able to drill into that and to alert and alarm on that, potentially block that right away as extra help to my customers.

Ransomware is certainly one of the most major scary sort of things that’s out there now. It’s happening every day. There are reports of police stations having to pay ransom to get their data back, hospitals having to pay ransom to get their data back. It’s kind of interesting that, to our knowledge, there has never been a case where the ransomers, the bad guys out there haven’t actually released the information back to their customers and supply the decryption key. Because they want the money and they want people to know, “Hey, if you pay us, we will give you your data back,” which is really, really frightening, actually. It’s happening all the time and needs to be monitored very, very carefully. This is certainly one of the major threats that exist today.

But there are other threats as well; peer-to-peer traffic, ToR traffic, things like that. Here’s an example of looking at a single affected IP that is talking to multiple different threat IPs that are known to have been hosting illicit content over this time period. You could see that, clearly, it’s doing something. You know, if there is one host that is talking to one outside illicit threat IP, okay, maybe that’s a coincidence or maybe it’s not an indication of something crazy going on. But when you can see that, in this case, there’s one internal IP talking to 89 known bad threat IPs who have been known to host illicit traffic, okay, that’s not a coincidence anymore. We know that something’s happening here. We can see when it happened. We know that they’re doing something. Let’s go investigate that. So that’s just another way of kind of giving you that first step to identify what’s happening and when it’s happening.

You know, sometimes, illicit traffic may just look like some obscured peer-to-peer content but it actually…Auditor, our product allows you to see it for full forensic evidence. You know, you could see what countries are talking to, what kind of traffic it is what kind of threat level it is. It really gives you that full-detailed data about what’s happening.

Here’s another example of a ToR threat. So people who are trying to use ToR to anonymize their data or get around any kind of traffic analysis-type system will use ToR to try and obfuscate that data. But we have, as part of our threat data, a list of ToR exits and relays and proxies, and we can look at that and tell you, again, who’s sending data into this sort of the ToR world out there, which may be an indication of ransomware and other malware because they often use ToR to try and anonymize that data. But it, also, could be somebody inside the organization that’s trying to do something they shouldn’t be doing, get data out which could be very nefarious. You never want to think the worst of people but it does happen. It happens every day out there. So again, that’s another way that we can give you some information about threats.

We, also, can help you visualize the threats. Sometimes, it’s easier for those to understand by looking at a nice graphical depiction. So we can show you where the traffic is moving, with the volume of traffic, how it’s hopping around in, in this case a ToR endpoint. ToR is weird. The point of ToR is that it’s very difficult to find an endpoint from another single endpoint. But being able to visualize it together actually allows you to kind of get a hand on where that traffic may be going.

In really large service providers where, certainly, people who are interested in tracking this stuff down, they need a product that can scale. We’ve got a very, very great story about our massive scalability. We can use a hierarchical system. We can add additional collectors. We can do a lot of different things to be able to handle a huge volume of traffic, even for Tier 1-type service providers, and still provide all of this data and detail that we’ve shown so far.

A couple other examples, we just have a number of them here, of different ways that you can look at the traffic and slice and dice it. Here’s an example of top conversations. So looking for that spike in traffic, we could see that there was this big spike here, suddenly. Almost 200 gig in one hour, that’s very unusual and can be identified very, very quickly and then you can try and say, “Okay, what were you doing during that time period? How could it possibly be that that much information was being sent out the door in such a short period of time?”

We also have port usage. So we can look at individual ports that are known threats over whatever time period you’re interested in. We could see this is port 80 traffic but it’s actually connecting to known ToR exits. So that is not just web surfing. You can visualize changes over time, you can see how things are increasing over time, and you can identify who is doing that to you.

Here’s another example of botnet forensics. Understanding a conversation to a known botnet command and control server and so many times, those come through, initially, as a phishing email. So they’ll just send millions of spam emails out there hoping for somebody to click on it. When they do click on it, it downloads the command and control software and then away it goes. So you can actually kind of see the low-level continual spam happening, and then all of a sudden, when there’s a spike, you actually get that botnet information, the command and control information that starts up and from there all kinds of bad things can happen.

So identifying impacted systems that have more than one infection is a great way to really sort of prioritize who you should be looking at. We can give you that data. I could see this IP has got all kinds of different threats that it’s been communicating to and with. You know, that is certainly someone that you want to take a look at very quickly.

I talked about visualization, some. Here are a few more examples of visualizations in the product. Many of our customers use this. It’s kind of the first way that they look at the data and then drill into the actual number part of the data, sort of after the visualization. Because you could see, from a high-level, where things are going and then say, “Okay, let me check that out.”

Another thing that we do as part of our cyber bundle, if you will, is anomaly detection and what we call “Two-phased Anomaly Detection.” Most of what I’ve talked about so far has been related to threat detection, matching up those known bads to conversations or communications into and out of your network. But there are other ways to try and identify security problems as well. One of those is anomaly detection.

So anomaly detection is an ability of our product to baseline traffic in your network, lots of different metrics on the traffic. So it’s counts, and flows, and packets, and bytes, and bits per second, and so forth, TCP flags, all happening all the time. So we’re baselining all the time, hour over hour, day over day and week over week to understand what is normal and then use our sophisticated behavior-based anomaly detection, our machine learning ability to identify when things are outside the norm.

So phase one is we baseline so that we know what is normal and then alert or identify when something is outside the norm and then phase two is running a diagnostic process on those events, so understanding what was that event, when did it happen, what kind of traffic was involved, what IPs and ports were involved, what interfaces did the traffic go through, what does it possibly pretend, was it a DDoS-type attack, was it port sweeper or crawler-type attack – what was it? And then the result of that is our alert diagnostic screen like you can see in the background.

So it qualifies the cause and impact for each offending behavior. It gives you the KPI information. It generates a ticket. It allows you to integrate with other third-party SNMP traps, trap receivers so we can send our alerts and diagnostic information out as a trap to another system and so everything can be rolled up into a more manager and manager-type system, if you wish. You can intelligently whitelist traffic that is not really offensive traffic that we may have identified as an anomaly. So of course, you want to reduce the amount of false positives out there and we can help you do that.

So to kind of summarize…I think we’re just about at the end of the presentation now. To summarize, what can CySight do in our cyber intelligence? It really comes down to forensics, anomaly detection, and that threat intelligence. We can record and analyze, on a very granular level, network data even in extremely complex, large, and challenging environments. We can evaluate what is normal versus what is abnormal. We can continually monitor and benchmark your network and assets. We can intelligently baseline your network to detect activity that deviates from those baselines. We can continuously monitor for communication with IPs of poor reputation and remediate it ASAP to reduce the probability of infection and we can help you store and compile that flow information to use as evidence in the future.

You’re going to end up with, then, extreme visibility into what’s happening. You’re going to have three-phase detection. You have full alerting and reporting. So any time any of these things do happen, you can get an alert. That alert can be an email. It can be a trap out to another system as I mentioned earlier. Things can be scheduled. They’re running in the background 24/7 keeping our software’s eyes on your network all the time and then give you that forensics drill-down capability to quickly identify what’s happened, what’s been impacted, and how you can stop its spread.

The last thing we just want to say is that everything that we’ve shown today is the result of a large development effort over the last number of years. We’ve been in business for over 10 years, delivering NetFlow-based Predictive AI Baselining analytics. We’ve really taken a very heavy development exercise into security over the last few years and we are constantly innovating. We’re constantly improving. We’re constantly listening to what our customers want and need and building that into future releases of the product.

So if you are an existing customer listening to this, we’d love to hear your feedback on what we can do better. If you are potentially a new customer on this webinar, we’d love your ideas from what you’ve seen as to if that fits with what you need or if there’s other things that you would like to see in the product. We really do listen to our customers quite extensively and because of that, we have a great reputation with our customers.

We have a list of customers up here. We’ve got some great quotes from our customers. We really do play across an entire enterprise. We play across service providers and we love our customers and we think that they know that and that’s why they continue to stay with us year after year and continue to work with us to make the product even better.

So we want to thank everybody for joining the webinar today. We’re going to just end on this note that we believe that our products offer the most cost-effective approach to detect threats and quantify network traffic ubiquitously across everything that you might need in the security and cyber network intelligence arena and if you have any interest in talking to us, seeing a demo, live demo of the product, getting a 30-day evaluation of the product, we’re very happy to talk to you. Just contact us.

If you’ve got a salesperson and you want to get threat intelligence, we’re happy to enable it on your existing platform. If you are new to us, hit our website, please, at cysight.ai. Fill out the form for a trial, and somebody will get to you immediately and we’ll get you up in the system and running very, very quickly and see if we can help you identify any of these security threats that you may have. So with that, we appreciate your time and look forward to seeing you at our webinar in the future. Bye.

8 Keys to Understanding NetFlow for Network Security, Performance & Overall IT Health

The Strategic Value of Advanced Netflow for Enterprise Network Security

With thousands of devices going online for the first time each minute, and the data influx continuing unabated, it’s fair to say that we’re in the throes of an always-on culture.

As the network becomes arguably the most valuable asset of the 21st century business, IT departments will be looked at to provide not just operational functions, but, more importantly, strategic value.

Today’s network infrastructures contain hundreds of key business devices across a complex array of data centers, virtualized environments and services. This means Performance and Security Specialists are demanding far more visibility from their monitoring systems than they did only a few years ago.

The growing complexity of modern IT infrastructure is the major challenge faced by existing network monitoring (NMS) and security tools.

Expanding networks, dynamic enterprise boundaries, network virtualization, new applications and processes, growing compliance and regulatory mandates along with rising levels of sophistication in cyber-crime, malware and data breaches, are some of the major factors necessitating more granular and robust monitoring solutions.

Insight-based and data-driven monitoring systems must provide the deep visibility and early warning detection needed by Network Operations Centre (NOC) teams and Security professionals to manage networks today and to keep the organization safe.

For over two decades now, NetFlow has been a trusted technology which provides the data needed to enable the performance management of medium to large environments.

Over the years, NetFlow analysis technology has evolved alongside the networks it helps optimize to provide information-rich analyses, detailed reporting and data-driven network management insights to IT departments.

From traffic accounting, to performance management and security forensics, NetFlow brings together both high-level and detailed insights by aggregating network data and exporting it to a flow collector for analysis. Using a push-model makes NetFlow less resource-intensive than other proprietary solutions as it places very little demand on network devices for the collection and analysis of data.

NetFlow gives NOCs the information they need for pervasive deep network visibility and flexible Predictive AI Baselining analytics, which substantially reduces management complexity. Performance and Security Specialists enjoy unmatched flexibility and scalability in their endeavors to keep systems safe, secure, reliable and performing at their peak.

Although the NetFlow protocol promises a great deal of detail that could be leveraged to the benefit of the NOC and Security teams, many NetFlow solutions to date have failed to provide the contextual depth and flexibility required to keep up with the evolving network and related systems. Many flow solutions simply cannot scale to archive the necessary amount of granular network traffic needed to gain the visibility required today. Due to the limited amount of usable data they can physically retain, these flow solutions are used for only basic performance traffic analysis or top talker detection and cannot physically scale to report on needed Predictive AI Baselining analytics making them only marginally more useful than an SNMP/RMON solution.

The newest generation of NetFlow tools must combine the granular capability of a real-time forensics engine with long-term capacity planning and data mining abilities.

Modern NetFlow applications should also be able to process the ever expanding vendor specific flexible NetFlow templates which can provide unique data points not found in any other technology.

Lastly, the system needs to offer machine-learning intelligent analysis which can detect and alert on security events happening in the network before the threat gets to the point that a human would notice what has happened.

When all of the above capabilities are available and put into production, a NetFlow system become an irreplaceable application in an IT department’s performance and security toolbox.

Performance Monitoring & Security Forensics: The 1-2 Punch for Network and IT Infrastructure Visibility

Benefits of a NetFlow Performance Deployment in Complex Environments

Since no two environments are identical and no network remains stagnant in Network Monitoring today, the only thing we can expect is the unexpected!

The network has become a living dynamic and complex environment that requires a flexible approach to monitor and analyze. Network and Security teams are under pressure to go beyond simple monitoring techniques to quickly identify the root causes of issues, de-risk hidden threats and to monitor network-connected things.

A solution’s flexibility refers to not only its interface but also the overall design.

From a user interface perspective, flexibility refers to the ability to perform analysis on any combination of data fields with multiple options to view, sort, cut and count the analysis.

From a deployment perspective, flexibility means options for deployment on Linux or Windows environments and the ability to digest all traffic or scale collection with tuning techniques that don’t fully obfuscate the data.

Acquiring flexible tools are a superb investment as they enrich and facilitate local knowledge retention. They enable multiple network centric teams to benefit from a shared toolset and the business begins to leverage the power of big data Predictive AI Baselining analytics that, over time, grows and extends beyond the tool’s original requirements as new information becomes visible.

What makes a Network Management System (NMS) truly scalable is its ability to analyze all the far reaches of the enterprise using a single interface with all layers of complexity to the data abstracted.

NetFlow, sFlow, IPFIX and their variants are all about abstracting routers, switches, firewalls or taps from multiple vendors into a single searchable network intelligence.

It is critical to ensure that abstraction layers are independently scalable to enable efficient collection and be sufficiently flexible to enable multiple deployment architectures to provide low-impact, cost-effective solutions that are simple to deploy and manage.

To simplify deployment and management it has to work out the box and be self-configuring and self-healing. Many flow monitoring systems require a lot of time to configure or maintain making them expensive to deploy and hard to use.

A flow-based NMS needs to meet various alerting, Predictive AI Baselining analytics, and architectural deployment demands. It needs to adapt to rapid change, pressure on enterprise infrastructure and possess the agility needed to adapt at short notice.

Agility in provisioning services, rectifying issues, customizing and delivering alerts and reports and facilitating template creation, early threat detection and effective risk mitigation, all assist in propelling the business forward and are the hallmarks of a flexible network management methodology.

Here are some examples that require a flexible approach to network monitoring:

  • DDoS attack behavior changes randomly
  • Analyze Interface usage by Device by Datacenter by Region
  • A new unknown social networking application suddenly becomes popular
  • Compliance drives need to discover Insider threats and data leakages occurring under the radar
  • Companies grow and move offices and functions
  • Laws change requiring data retention suitable for legal compliance
  • New processes create new unplanned pressures
  • New applications cause unexpected data surges
  • A vetted application creates unanticipated denials of service
  • Systems and services become infected with new kinds of malicious agents
  • Virtualization demands abruptly increase
  • Services and resources require a bit tax or 95th percentile billing model
  • Analyzing flexible NetFlow fields supported by different device vendors such as IPv6, MPLS, MAC, BGP, VPN, NAT paths, DNS, URL, Latency etc.
  • Internet of Things (IoT) become part of the network ecosystem and require ongoing visibility to manage

Performance Monitoring & Security Forensics: The 1-2 Punch for Network and IT Infrastructure Visibility

Hunt SUNBURST and Trojans with Turbocharged Netflow.

US: December 13 of 2020 was an eye-opener worldwide as Solarwinds software Orion, was hacked using a trojanized update known as SUNBURST backdoor vulnerability. The damage reached thousands of customers, many of which are world leaders in their markets like Intel, Microsoft, Lockheed, Visa, and several USA  governmental agencies. The extent of the damage has not been fully quantified as still more is being learned, nevertheless, the fallout includes real-world harm.

The recent news of the SolarWinds Orion hack is very unfortunate. The hack has left governments and customers who used the SolarWinds Orion tools especially vulnerable and the fallout will still take many months to be recognized. This is a prime example of an issue where a flow metadata tool has the inability to retain sufficient records, causing ineffective intelligence, and that the inability to reveal hidden issues and threats is now clearly impacting organizations’ and government networks and connected assets.

Given what we already know and that more is still being learned, it makes good sense to investigate an alternative solution.

 
 

What Is the SUNBURST Trojan Attack?

SUNBURST, as named by FireEye, is a kind of malware that acts as a trojan horse designed to look like a safe and trustworthy update for Solarwinds customers. To accomplish such infiltration to seemingly well-protected organizations, the hackers had to first infiltrate the Solarwinds infrastructure. Once Solarwinds was successfully hacked, the bad actors could now rely on the trust between Solarwinds and the targeted organizations to carry out the attack. The malware, which looked like a routine update, was in fact creating a back door, compromising the Solarwinds Orion software and any customer who updates their system.

How was SUNBURST detected?

Initially, SUNBURST malware was completely undetected for some time. The attackers started to install a remote access tool malware into the Solarwinds Orion software all the way back in March of 2020, essentially trojaning them. On December 8, 2020, FireEye discovered their own red team tools have been stolen and started to investigate while reporting the event to the NSA. The NSA, also a Solarwinds software user, who is responsible for the USA cybersecurity defense, was unaware of the hack at the time. A few days later, as soon as the information became more public, different cybersecurity firms began to work on reverse engineering and analyzing the hack.

IT’S WHAT WE DON’T SEE THAT POSES THE BIGGEST THREATS AND INVISIBLE DANGERS!

You may be surprised to learn that most well-known tools lack the REAL Visibility that could have prevented attacks on a network and its local and cloud-connected assets. There are some serious shortcomings in the base designs of other flow solutions that result in their inability to scale in retention. This is why smart analysts are realizing that Threat Intelligence and Flow Analytics today is all about having access to long term granular intelligence.

From a forensics perspective, you would appreciate that you can only analyze the data you retain, and with large and growing network and cloud data flows most tools (regardless of their marketing claims) actually cannot scale in retention and choose to drop records in lieu of what they believe is salient data.

Funnel_Loss_Plus_Text
Imputed outcome data leads to misleading results and missing data causes high risk and loss!​

A simple way to think about this is if you could imagine trying to collect water from a blasting fire hose into a drinking cup. You just simply cannot collect very much!

Many engineers build scripts to try to attain the missing visibility and do a lot of heavy lifting and then finally come to the realization that no matter how much lifting you do that if the data ain’t there you can’t analyze it.

We found that over 95% of network and cyber visibility tools retain as little as 2% to 5% of all information collected resulting in completely missed analytics, severely misleading analytics, and risk!
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How does Netflow Auditor hunt SUNBURST and other Malware?

It’s often necessary to try and look back with new knowledge that we become aware of to analyze.

For a recently discovered Ransomware or Trojan, such as SUNBURST, it is helpful to see if it’s been active in the past and when it started. Another example is being able to analyze all the related traffic and qualify how long a specific user or process has been exfiltrating an organization’s Intellectual Property and quantify the risk.

SUNBURST enabled the criminals to install a Remote Access Trojan (RAT). RATs, like most Malware, are introduced as part of legitimate-looking files. Once enabled they allow the hacker to view a screen or a terminal session enabling them to look for sensitive data like customer’s credit cards, intellectual property or sensitive company or government secrets.

Even though many antivirus products can identify many RAT signatures, the software and protocols used to view remotely and to exfiltrate files continues to evade many malware detection systems. We must therefore turn to traffic analytics and machine learning to identify traffic behaviors and data movements that are out of the ordinary.

Anonymity by Obscurity

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In order to evade detection, hackers try to hide in plain sight and use protocols that are not usually blocked like DNS, HTTP, and Port 443 to exfiltrate your data.

Sharding_who_what_where_when

Many methods are used to exfiltrate your data. An often-used method is to use p2p technologies to break files into small pieces and slowly send the data unnoticed by other monitoring systems. Due to Netflow Auditor’s small footprint Dropless Collection you can easily identify sharding and our anomaly detection will identify the outlier traffic and quickly bring it to your attention. When used in conjunction with a packet broker partner such as Keysight, Gigamon, nProbe or other supported packet metadata exporter, Netflow Auditor provides the extreme application intelligence to help you with complete visibility to control the breach.

Identifying exposure

Onion_routing_Malware_phone_home

In todays connected world every incident has a communications component

You need to keep in mind that all Malware needs to “call home” and today this is going to be through onion routed connections, encrypted VPNs, or via zombies that have been seeded as botnets making it difficult if not impossible to identify the hacking teams involved which may be personally, commercially or politically motivated bad actors.

Multi-focal threat hunting

Multifocal_threat_drilldown

Threat hunting for SUNBURST or other Malware requires multi-focal analysis at a granular level that simply cannot be attained by sampling methods. It does little good to be alerted to a possible threat without having the detail to understand context and impact. The Hacker who has control of your system will likely install multiple back-doors on various interrelated systems so they can return when you are off guard.

Netflow Auditor Turbocharges Flow and Cloud analytics for SecOps and NetOps

As with all Netflow Auditor analytics and detection, you don’t have to do any heavy lifting. We do it all for you!

There is no need to create or maintain special groups with Sunburst or other Malware IP addresses or domains. Every Netflow Auditor instance is built to keep itself aware of new threats that are automatically downloaded in a secure pipe from our Threat Intelligence qualification engine that collects, collates and categorizes threats from around the globe or from partner threat feeds.

Netflow Auditor Identifies your systems conversing with Bad Actors and allows you to back track through historical data to see how long it’s been going on.

Distributed_threat_collection

Using Big Data threat feeds collated from multiple sources, thousands of IPs of bad reputation are correlated in real-time with your traffic against threat data that is freshly derived from many enterprises and sources to provide effective visibility of threats and attackers.

  • Cyber feedback

  • Global honeypots

  • Threat feeds

  • Crowd sources

  • Active crawlers

  • External 3rd Party

So how exactly do you go about turbocharging your Flow and Cloud metadata?

IdeaData’s Netflow Auditor software is capable of the highest level of granularity, scalability, and flexibility available in the network and cloud flow metadata market. Lack of granular visibility is one of, if not the main flaw in such products today as they retain as little as 2% to 5% of all information collected, due to inefficient design, severely impacting visibility and risk as a result of missing and misleading analytics, costing organizations greatly.

Netflow Auditor’s Intelligent Visibility, Dropless Collection, automation, and machine intelligence reduce the heavy lifting in alerting, auditing, and discovering your network making performance analytics, anomaly detection, threat intelligence, forensics, compliance, and IP accounting a breeze!

Let us help you today. Please schedule a time to meet https://NetFlowAuditorMeet.as.me/

The Internet of Things (IoT) – pushing network monitoring to its limits

In the age of the Internet of Things (IoT), billions of connected devices – estimated at 20 billion by the year 2020 – are set to permeate virtually every aspect of daily life and industry. Sensors that track human movement in times of natural disasters, kitchen appliances reminding us to top up on food supplies and even military implementations such as situational awareness in wartime are just a few examples of IoT in action.

Exciting as these times may be, they also highlight a new set of risk factors for Security Specialists who need to answer the call for more vigorous, robust and proactive security solutions. Considerations around security monitoring and management are set to expand far beyond today’s norms as entry points, data volumes and connected hardware multiply at increasing rates in the age of hyper-interconnectedness.

Security monitoring will need to take a more preemptive stance in the age of IoT

With next-generation smart products being used in industries such as utilities, manufacturing, transportation, insurance, and logistics, networks will become exposed to new security vulnerabilities as IoT and enterprises intersect. Smart devices connected to the enterprise can easily act as a bridge to the network, potentially exposing organizations’ information assets. Apply this scenario to a world where virtually every device can communicate with the network from practically anywhere, and the need for more forward-thinking security monitoring becomes apparent. Device-to-device communications will need stronger encryption and ways for network teams to monitor and understand communications, behavior and data patterns. With more “unmanned” computers, appliances and devices coming on-line, understanding new network anomalies will be a challenge.

Networks will become far more heterogeneous

Embedded firmware, operating systems, shorter life-cycles, expanding capabilities and security considerations unique to IoT devices, will make networks far more complex and expansive than what they are today. IoT will hasten more heterogeneous environments, which security teams must be prepared for. The device influx will also drive IPv6 adoption and introduce new protocols. According to Technology.org, “Enterprises will have to look for solutions capable of guarding data gateways in IoT devices using tailored protocol filters and policy capabilities. Besides, regular security updates and patches will become integral to product lifecycle to eliminate every possibility of a compromise.”  This will increase reliance on technologies such as granular Netflow collection that provides forensics and anomaly detection, which offers enterprises, trusted security solutions that are both easily deployed and capable of evolving organically alongside new technologies as they are introduced to environments.

IoT will introduce new types of data into the enterprise

Traffic signal systems, power stations, water sanitation plants and other services vital to society are all incorporating IoT to some degree. Device security in a physical and non-physical context will be important as enterprises need to look at ways of preventing unauthorized entry into the network. Gartner asserts that, “IoT objects possess the ability to change the state of the environment around them, or even their own state (for example, by raising the temperature of a room automatically once a sensor has determined it is too cold, or by adjusting the flow of fluids to a patient in a hospital bed based on information about the patient’s medical records)”.

Considering the risk to human life inherent in hacks into systems of this nature, the level of monitoring and surveillance for compliance is becoming more pertinent each day as these kinds of threats are starting to occur. This will place a high demand on end-point security solutions to be both timely and accurate in its correlation of network data to give Security Teams the needed granularity to provide context around current and evolving risks.

The now infamous Chrysler hack is a primary example of the potentialities of IoT-based breaches and the threats they pose to human safety.

The role of Netflow in forearming the enterprise in the age of IoT

Monitoring systems will be required to identify, categorize and alert Network Operations Centers (NOCs) on a plethora of new datasets, demanding big data capabilities from their network monitoring solutions. NetFlow, if used correctly, can offer an opportunity to provide enterprises with substantial intelligence and an early warning mechanism to assist them in managing the steady move toward IoT and take a forearmed stance in security operations. Netflow’s ability to match to the scale at which the enterprise will grow means NOCs will neutralize the threat of being overwhelmed in a deluge of devices that will generate volumes of data that require around the clock monitoring.

They can achieve deep visibility – central to security in an IoT world – with a NetFlow monitoring, reporting and analysis tool that provides the ability to perform deep security forensics and intelligent baselining, anomaly detection, diagnostics and endpoint threat detection. NetFlow end-point solutions speak to the changing needs of the large environments by reducing Mean Time to Know (MTTK), which in turn shrinks Mean Time to Repair and Resolve (MTTR).

For more information on how CySight is helping organizations build comprehensive network security, performance and management solutions, contact us, or download a free copy of our guide on 8 Keys to Understanding NetFlow for Network Security, Performance & Overall IT Health.

 8 Keys to Understanding NetFlow for Network Security, Performance & Overall IT Health

How to Achieve Security and Data Retention Compliance Obligations with Predictive AI Cyber Flow Analytics

Information retention, protection and data compliance demands are an important concern for modern organizations. And with data being generated at staggering rates and new entry points to networks (mobile devices, wireless network, etc.) adding their own levels of complexity, adherence to compliance obligations can prove challenging. In addition, when considering high profile network hacks such as the Sony, Dropbox and Target intrusions, it quickly becomes clear that no organization is immune to the possibility of having their systems compromised. This backdrop demonstrates the importance of finding a suitable network monitoring solution that is able to navigate the tightrope between meeting regulatory requirements without placing too much strain on hardware resources.

In this blog we’ll touch on two of these regulatory standards: the Health Insurance Portability and Accountability Act (HIPAA) and Supervisory Control and Data Acquisition (SCADA), and look at how Network Specialists can leverage NetFlow’s ability to provide insightful metrics that aid in the building of a water-tight security apparatus.

NetFlow and HIPAA

Few have greater concerns around information privacy than the health care industry. If compromised, medical records containing patients’ sensitive information can lead to disaster for both health care organizations and individuals. The Privacy Rule, as stipulated by HIPAA, addresses the data retention compliance and protection measures expected of health care organizations to ensure critical patient records remain safe, uncompromised and reliable.

One of these protection measures is the continuous monitoring of information systems to prevent security breaches or unintended exposure of information to the wrong people. NetFlow is ideal for monitoring and enforcing security by giving detailed insight into both local, inbound and outbound traffic. It also allows you to easily identify the nature of the traffic and see how traffic flows between devices as it traverses your environment.

NetFlow’s ability to detect and report on anomalies through analysis by a NetFlow analyzer can give health care organizations unmatched network visibility and data granularity. Its availability on most networking devices makes it ideal for deployment in and monitoring of large-scale environments such as hospitals and other health care facilities. Also, flow exports to NetFlow analyzers are comparatively lightweight, which makes it possible for organizations to collect and store network audit data for extended periods of time.

NetFlow and SCADA

SCADA is a standard that facilitates communication channels between remote equipment as a means to control their functions. Examples of SCADA at work are remote management of Heating Ventilation and Air Conditioning (HVAC) systems, industrial equipment and Closed Circuit Television systems. SCADA is a type of industrial control system (ICS). Security around SCADA-enabled systems are paramount to human safety, as typical utilization of SCADA include sewerage systems, power plant and water treatment facilities. Also, these management systems typically communicate via the Internet, making them vulnerable to hackers who may seek to use them as entry points into corporate networks.

NetFlow provides built-in support for SCADA and facilitates real-time monitoring and management of communication between remote devices, making it possible to take corrective action on-the-fly if needs be. It also enables users to make operational decisions based on both real-time and historic data that gives context to anomalies and events as they occur. Users are also able to perform functions remotely without visiting sites to perform updates and other maintenance tasks. By providing detailed and up-to-date information on business-critical systems, NetFlow is enabling businesses to be more proactive in the monitoring, management and maintenance of remote devices and systems.

Employing the right NetFlow reporting tool is key to manage compliance obligations

The missing link in leveraging the power of NetFlow in data retention and protection efforts is a powerful, comprehensive and robust NetFlow reporting tool. When considering your regulatory obligations, ensure that your choice of NetFlow reporting tool gives you the detailed, granular and contextual information you need to make insightful, data-driven decisions around the security, integrity and stability of your information assets.

8 Keys to Understanding NetFlow for Network Security, Performance & Overall IT Health