Vectra AI Reviews

I'm a SOC analyst, and I use Vectra AI to detect and respond to security incidents. My team manages the critical detections, and another team takes the low-priority detections. They also use Vectra to hunt for the system root.

We use the Threat Detection and Response platform, and it's quite good at detecting and responding to threats and attacks in real-time. I really like the UI experience because it's simple to use, and we get quite a lot of information very quickly.

Some valuable features of Vectra AI are that it is very intuitive and that there are only a small amount of false positives. Therefore, it's an effective solution.

Another benefit that is unrelated to security is that it allows us to see misconfigurations or things that should not be happening in terms of compliance.

As SOCs, we concentrate on the OS side, and with Vectra AI, we can now see the network from an endpoint point of view. It gives us new alerts and does bring some work because we now have more visibility. However, it's opening up a wide range of things for us.

We have a lot of system solutions and integrations with system solutions. Vectra is a type of black box. It implements AI-informed detection mechanisms, but we cannot create system detections. I understand that the product is designed this way, but it would be great if we could create our own detections as well.

I've been using this solution for six months.

From my point of view, Vectra AI's stability has been quite good. We have never had any issues.

On a scale from one to ten, I would give Vectra AI an overall rating of eight.

Our primary use cases for this solution are detection and then investigation afterward.

Vectra AI helped our team be more productive and save time. We have less work thanks to it.

We have not had any real threats so far.

Vectra AI helped improved our mean time to identify.

One of the things I am not so happy about when it comes to Vectra is the scoring board. 

In Darktrace, you can point or click on any client and see any connections that have been made directly in the dashboard. You don't have to go to recall. This is likely why Darktrace isn't as fast as Vectra, but it would still be nice to see this feature in Vectra. In addition, Darktrace has an advanced mode, but you are also able to see it directly in the main dashboard. This would be great to see in Vectra as well. 

We started implementing the tool around November. It is a step-by-step process for us because we have several locations and my team was not implementing it independently. We have another team that has to drive to the location. We finished the last location in mid-January.

Vectra AI is a stable solution. It works. 

Vectra AI's scalability is fine. We have a brain, we have a lot of centers, and the solution is easy to implement. Everything works.

The tech support is great. Whenever we had a problem, we got an answer immediately. This helps with having a general feeling that everything works in a solution.

Positive

We previously used a different tool, Darktrace. We used it for four years. The management told us to look for other tools. This was after we switched our main network hardware. We contacted Vectra and took the next step. We were just comparing different tools when we decided to go with Vectra. There were many different tools that were similar but we ultimately chose Vectra. Compared to Darktrace, Vectra's UI is much cleaner, there is less noise, and the performance is way better in the graphical interface. We get much fewer false positives. We also have to put less work into this tool, which is great for companies with small teams.

I was involved in the deployment from start to finish. It was fairly straightforward. The support we received was very good. When we had questions, they were answered immediately by the support engineer assigned to us.

I can't speak to whether or not we have seen a return on investment with this solution because we have not had any real threats so far.

As far as pricing goes, my only reference point is Darktrace. Their pricing is pretty even, which is a fair price.

We have not yet tested the whole tool in a penetration test. However, I would nonetheless give it at least an eight out of ten, with one being the worst and ten being the best. 

Right now, we have a good understanding of the UI and I know that there have been improvements to the visualization. The scoring redirects your focus to things that you should be looking at. The tool we used before Vectra was Darktrace. It was similar to where Vectra is heading now. With the scoring system, Vectra is a better solution.

From our research network in Sweden, we use it to communicate to and from the Internet. The deployment is on our Internet-facing services. We facilitate monitoring for universities who need this as well.

One of the biggest challenges facing us today is data growth and the continual diversification of the IT landscape. It is a very heterogeneous model, where you have on-premises, hybrid, and cloud solutions, as well as service providers, where everything is communicating back and forth towards each other.

We just have one SOC in Sweden.

It keeps up with the network traffic, which is a good thing. It provides more context to plain alerts compared to using an older system. So, it helps an analyst reduce the information overload. 

Vectra AI triages threats and correlates them with the compromised host device. That is how the functionality works. It helps us prioritize which hosts to look into.

It works over the hours when an analyst is not available, so the work keeps going. It can help you prioritize certain traffic patterns and things that you need to handle.

It is a good system that goes hand in hand for both junior and senior analysts. I see it as a nice add-on there.

I would like more integrations with IOCs and threats currently on the Internet. I would also like to know which threats are based on zero-day attacks, current botnets, etc. Therefore, I would like more information on external threats.

We have been using it for evaluation and collaboration together with our customers for the past two years. We have had it in our own production environment for half a year.

We haven't had any major disruptions. We had one hardware error after delivery, but that was taken care of.

Not much maintenance is needed.

It scales nicely since they separate the sensor node from the brain node.

You can scale up to sensors and separate the architecture as you grow. So, you can define your initial steps first. then have a more mature hardware later on.

We are a team of less than 10 people. We have network engineers, security analysts, incident handlers, and operators. We have a broad team.

We have only had direct contact with the customer success team, and that has been great.

Positive

We previously used open-source SIEM models. We switched to Vectra AI to help with the automation of alerts.

The initial setup was fairly straightforward.

The deployment was done over the pilot phase. We changed the links and aggregation a bit on the networking side, but the work was fairly quick.

We had a good dialogue with Vectra regarding the initial setup.

After deploying Vectra AI in our network, it began to add value to our security operations within a week.

We have not yet seen ROI, but we are growing our usage. We need to offload at least one analyst or have it do the work of a couple of analysts over time. 

We had a pricing meeting for the solution, where we set up a certain set of requirements that Vectra could fit on both price and quality.

We evaluated three or four different solutions.

Vectra's licensing model could scale to our research network, which has multiple, 100-gigabit links. Other competitors could not scale that for us. 

Set up specific threat scenarios that you are looking into, then monitor and evaluate on that. For example, it could be a botnet or certain user behavior. Also, the solution works best within an enterprise.

We are currently evaluating upgrading our SIEM and EDR technologies. When we extend our scope of the traffic that we are monitoring, Vectra AI will possibly enable us to do things that we could not do before, which would be a nice side effect.

There are still quite a lot of alarms coming in. It helps to reduce the amount of alerts that an older IDS-based system would have had. While there are still a lot of alarms, there are less alarms than the traditional IDS.

I would rate the solution as nine out of 10.

We use it to monitor what is happening on our network, especially to protect our network from malicious activity.

We also have the sensor into Office 365, so we can also monitor everything that is happening in there.

At the moment, we use it to monitor all our endpoints.

The solution's Privileged Account Analytics for detecting issues with privileged accounts is critical for our organization. Because of risk, we scan our entire network. We have a lot of segmented networks where clients can almost do nothing. If we just look into everything, then sometimes there is a bit of noise. When you select your privileged hosts or accounts, you can see how many things are left over and which are the most critical that need to be solved as soon as possible.

It notifies us if our Office 365 has been compromised. Even after business hours, I get personal emails. This is a temporary solution because we are working doing repetitive alerting, but that's a work in process. We are working on an integration with our authentication system that will be able to detect an account or device. We want to automate that process so the account will be locked out for a period of time.

Vectra is a detection system on top of our protection system. We do a lot of protection on our network, but that protection is a configuration based on human interaction, where there can also be human faults or errors in the system. 

The solution captures network metadata at scale and enriches it with security information, e.g., we have sensors for Symantec antivirus and our virtual infrastructure. We are looking into extra sensors for enabling some things from Microsoft Defender. We integrated it into our Active Directory so we can do some user correlations, etc. It enriches the metadata on hosts and accounts, but that is mainly informative. It is good for us when making a final decision about some detections.

It has helped us to organize our security. We get a better overview on what is happening on the network, which has helped us get quicker responses to users. If we see malicious activity, then we can quickly take action on it. Previously, we weren't getting an overview as fast as we are now, so we can now provide a quicker response.

The visibility is much greater because of the behavior analysis and details that sometimes we have to put into it. On the firewall that we already have, sometimes we do manual lookups and check if everything is okay, then do research into it. Now, we put less effort into trying to manually do things to ensure that we have a good security model. We can see more how behavior changes with time, but that also requires us to put more time into the solution.

The solution gives us a baseline for users and their behaviors. We are able to establish which users have risky behaviors, then reach out to them and recommend better ways of doing things.

The hosts are critical hosts, which are really good when used to look up things as fast as you can because these could be very risky situations. Furthermore, within detections, we try to clean up a lot of things that are low in priority. It is same thing for the accounts within Office 365: Everything that is critical has to be solved as fast as possible.

The triaging is very interesting because we can do more with less work. We have more visibility, without too many false positives. It is a work in process because there are a lot of clients in the network, and everything has to be researched to see if it is valid, but most alerts and detections are solved with a bit of triaging.

The interface is very intuitive and easy to use. It gives a good overview, and it is important to understand what is happening on the network.

The integration within our virtualization infrastructure allows us to see the traffic that is going between virtual machines, even within our host. That gives us a lot more insights.

The solution’s ability to reduce false positives and help you focus on the highest-risk threats is mostly good. It is still a bit of work in process, but I can give feedback to the company from the help desk. There is follow-up from the Vectra team who follows it closely. We can also give a lot of inputs to make it still a better product. It's already a very good product, but in comparison with a lot of systems I used in the past, the false positives are really a burden because they are taking a lot of time at this moment.

The Office 365 integration is still a pretty new feature. I also have seen some improvements, and they email us with every step in the improvement process. I think that this integration will grow.

Every area has room from improvement. Security is an ongoing process. It is important for Vectra to keep updating their system based on new behaviors.

We would like to see the combination of the cloud with on-premise, e.g., what's happening in the cloud versus what's happening in the on-premise situation. If there is a phishing mail in the cloud, then the phishing mail comes in and a colleague clicks on that mail. Normally, it would be blocked by the system. However, when it's not blocked, then there can be malware on the system locally. We think it's important to get the integration of what's happening on Office 365 with phishing mails. 

Sometimes, it is a bit noisy on the dashboard because all the systems are on one field. On the dashboard, we have a complete overview of high, medium, and low risks. However, it would be more interesting for us if they could split that dashboard into high, medium, and low devices. For example, there is a dashboard on a device with a complete overview specifically for high-risk.

It has been operational for a few months.

It runs very smoothly. It is stable.

We haven't had any issues in regards to the stability or performance. The interface works very quickly. There is no latency on the traffic.

It scales well. 

For end users, we have about 10,00. On the administrative side, there are five to 10 system admins who use the information from the system for configuration and monitoring tasks.

The technical support is very good with fast responses. They reach out if they see there might be more questions. So, if you have a simple question, it could be that they elevate it to a more complex question to see what you really mean.

Seeing all the malware reaching out to CMC services from within our network, we reach out to those people via the help desk, and tell them, "Maybe you can scan this or that because those systems are managed by us." We get a lot of thanks from those people, which are often saying, "I did have some strange behavior on our systems, but I didn't know what it was. I wasn't doing anything about it, but thank you. It helps when you scan it, and the system is running better at the moment." In a completely unmanaged network with a lot of devices bring your own devices), it helps everybody.

The way that we can work with support to add feature requests is very interesting because it is an evolving world.

We didn't have a solution like Vectra previously.

The initial setup was completely straightforward. I didn't need any help. They delivered the device within the first weeks of COVID-19. The system is preconfigured from Vectra. I placed it in the server home, configured the network, and moved the Internet traffic out of the mailboxes, then I put it onto network so it was visible. In 30 minutes to an hour, everything was running.

We can sleep better.

As long as there is no full cycle attack, we will earn our money back.

Efficiency increased. There is less technical work to be done to ensure that nothing is happening from threats. Now, the system gives us the transparency that we need.

The solution has reduced the time it takes us to respond to attacks. In the past, it was difficult to know if something was happening because we didn't have an overview. Now, we know it very quickly because we have an overview of what is happening.

The pricing is high. 

Darktrace was also pricey.

We also evaluated Darktrace. We made a decision to stop testing Darktrace very early on, so it is difficult to compare to Vectra.

We chose Vectra because of the solution's simplicity; it is more straightforward. Also, we liked Vectra's support, visibility, and implementation. The solution comes to a conclusion within Vectra about some detections. It was easier to find the technical details which were interesting without looking too deep. The correlation was good too. At the end of the proof of a concept, Vectra added some extra features. However, for finding the way into the system, it took us a lot more time. 

We found that Vectra enables us to answer investigative questions that other solutions are unable to address. They provide a checklist regarding what we can do about detections. Because of this visibility, we don't have to do more investigations. 

We have other systems, like Office 365, which do behavior analysis and some signature behavior analysis. However, Vectra does not gives that many false positives in comparison with other solutions. Also, we are now able to see the entire network and cloud.

If you are looking into this type of solution and have the money, then you certainly need to look into Vectra.

The campaigns are interesting when looking at the beginning of a campaign. The scope of false positives is a real issue in a network that continuously has a lot of new hosts, but we can cope with it. We have given some feedback to the help desk regarding coping with this matter.

We hope that we can keep it so we don't see a complete lifecycle of an attack.

We are planning to use more features of the solution in the future, e.g., automation. We also want to integrate it with more advanced client security features.

I would rate this solution as an eight of 10. There is still a lot of development going on with it.

Vectra AI sits across our entire estate, we have an outsource provider for a lot of our backend systems. It sits in theirs and it sits in our own estates. It's deployed across our other numerous offices across the country. It sits across our entire state.

We don't have very much in the way of IDS or IPS on our estate, so we're relying on Vectra AI to do that sort of work for us. We're allowing that to look at our traffic and to flag up to us on our system. It helps my analysts investigate other things. We might get other alerts in the estate, Vectra AI is one of the first tools that they'll jump onto, to do further investigation of alerts that are raised up to them. It's a really good tool, not just for what it throws up, but for us to dig into our network as well.

What is pretty good is the unknown unknowns. It's the anomalies to the norm and the intelligence behind it that helps us to dig through a mountain of data and find the stuff that's important to us.

It allows us to understand what our normal traffic is, then pulls out the anomalies for us. For instance, a recent use case of it would be that it suddenly picked up that a file transfer was happening out of our estate that we weren't aware of. It hadn't been there before. There was a file transfer that suddenly appeared, that was actually in our estate that hadn't been there before. We would never have been able to see that normally, it's just that Vectra AI saw it. It was okay, it was going to a third-party and it allowed us to investigate it and find it but we would never have seen that without a notification. It understands what should be happening and then usually says "This isn't normal," and it allows us to flag it up and dig deeper into that.

It is very good at reducing alerts by rolling up numerous sellers to create a single incident or campaign for investigation. Although it doesn't reduce, it actually increases our alerts because we wouldn't have seen the stuff in the first place, but when it does create an alert, it pulls all investigative information together. We're not getting hundreds of alerts, we're getting alerts that contain all of the relevant components.

Vectra AI captures network metadata at scale and enriches it with security information. Although, we don't make the most of that, but we've never had a problem with its captures and it captures the correct data for what we want it to do. I think we could be using it better.

The information affects investigations by our security team by allowing them to be more effective and quicker in their investigations.

Vectra AI provides visibility into behaviors across the full life cycle of an attack in our network, beyond just the internet gateway. Although, we found it's flagging up early, so it's not developing to that further stage of that because it's flagging up at an early stage.

Its ability to reduce false positives takes quite a bit of tuning. We've had to put a lot of effort into tuning out false positives, so that's something that we've had to invest our time into. Obviously it's getting better and better as time goes on, but we still have to spend time tuning it.

We've seen our tuning has lessened those processes, but we're still getting more than we would want. That's probably some of our fault. It could be some issues with the way it's set up in certain areas. But, once we tune them out, they're staying tuned out.

It hasn't reduced the security analyst workload in our organization but that was never the purpose of it for us. It's an additional tool in our armory, so it hasn't reduced our workload, but it's made us more efficient.

It makes the team more efficient in speed of response. I would say it makes them more efficient in the breadth of their coverage of what they can respond to. It makes us have a more proactive response to incidents.

It has reduced the time it takes to respond to attacks. That comes back to the proactive point. It makes us able to lower down in the kill chain. We can react now, rather than reacting to incidents that happened, we can see an instant, in some cases, as it's being implemented, or as it's being launched.

It's not all attacks, but I would say that it's a shift less on the material chain. It's things that we might not even have spotted if it hadn't been for Vectra AI, so it's difficult to know how we would quantify that as an amount.

The false positives and the tuning side of it are some things that could use improvement but that could be from our side. 

I don't want to criticize the product for performance with our role out of it. It does what it says it's going to do very well. We've got issues with the way we've deployed it in some places, but the support we've had in that is very good as well, so I'm very happy with the support we get.

My company has been using Vectra AI for three years. I've been here for eight or nine months now, but the company has just been using it for three years.

We've had absolutely no issues with stability at all.

Scalability is obviously based around the size of the clients that we have. We have had some issues around scalability but that's only because when it was implemented before my time but I know it is scalable. Obviously, we have to put some thought into that, some planning into that from our side, but it is limited on the size of the boxes. To summarize, yes, it is scalable, but it needs planning.

We have four users who use it in my company who are cybersecurity analysts.

Vectra AI is on everything apart from the clouds. Now we're on a journey towards more and more cloud. At least 70% of our company is covered by it. 

We do have plans to increase usage. We want to move to the cloud. 

The support is excellent. We've had really good technical support from Vectra AI all the time. We have very regular catch-ups with them. They always pick the right people to do the calls, and we even have deep-dive sessions with our analysts with them and provide us with training. They've been excellent.

We didn't have anything in place before Vectra AI. 

I have used another solution in the past. I used Darktrace where I was before. It compares very favorably with Darktrace. I wouldn't say it was any better or worse.

The UI is quite different, but apart from that, there are obviously slight differences in the analytics behind it, but I'd be struggling to say that one of them was better than the other. They both seem to do what I do well. Vectra AI is a little bit more honest about their capabilities than Darktrace is.

I don't think Vectra AI enables us to answer investigative questions that other solutions are unable to address. I know that there are other solutions that could do it as well. They're as good as everything else out there, but I wouldn't go and say they're massively better. The thing that sells it for me is that the support has been very good. That's one of the bits that keeps me with them.

ROI depends on how you quantify that in security. It's really difficult to quantify what you find to a monetary value. We do see a return on investment because it's a good tool that we're using well and it's helping us to keep the company secure. It's really difficult to quantify a monetary value on that or say that you've got return on your investment. I wouldn't want to be without it. You can't put a price on security.

They compare very favorably against the competition in terms of price. Nothing in this area is cheap. There is a lot of value in the products that you're buying, but they have come in at the right price for us in comparison to others. I would say that they're competitive in their pricing.

My advice would be to make sure it is planned and deployed properly. That's a problem with my organization, not a problem with Vectra AI. Otherwise, if you don't build it to the specifications that you were told to, you're going to spend your whole life trying to fix a problem that shouldn't be there. My advice would be the plan and implement as per the plan.

I would rate Vectra AI a nine out of ten. 

We have two use cases. The first is that Vectra's platform allows us to get visibility into anomalous behavior, which, previously, we never really had access to, for threat hunting and incident response. We use it in support of our incident response operations to help supplement our investigations on hosts. We use it to correlate any suspicious activities, which is something that Vectra has been extremely accurate in, when used the right way. 

The second use case is that we've used the Vectra Cognito Recall and Cognito Stream devices. With these integrations, it's given us instant visibility into all the network data as well. That enables us to conduct our own hunts on our network data, data you'd see on a security information and event management (SIEM) solution. It also gives us the ability to correlate with our playbooks because it gives us access to the data itself in much more depth and detail.

The solution captures network metadata at scale and enriches it with security information. We store metadata for three months. Just to be able to scale the amount of information that we collect on the networks is a problem in itself. We have our SIEM solution that collects all of these logs. Making sure these logs are still sending, that these devices are still sending to our main SIEM, are issues. For Vectra AI, even with three months of retention, with the environment we have, we have never had issues accessing this network data. On top of that, if there are any issues, the support team is amazing in providing feedback and fixing them.

It has actually increased our security analyst workload, but in a good way. It has reduced the amount of stuff that we used to look at, and has allowed us to re-approach our C-CERT from signature-based detections to more behavioral-based detections. It has reduced the amount of boring work and work that is on the host, to more thought-provoking work based on behavioral data. We're now able to approach our C-CERT from a risk perspective and a numbers perspective.

It has reduced that boring work drastically and it reduces the time to investigate incidents in general. While it has definitely added a bunch of incidents for us to look at, it has reduced the workload of how we work those incidents. It makes them not only much easier to engage with and easier to visualize, but also enables us, as analysts, to work in a much more efficient and simple way.

Vectra has also helped move work from our Tier 2 to our Tier 1 analysts. Eighty percent of our Tier 1 analysts are doing Tier 2 work.

Finally, the solution has reduced the time it takes us to respond to attacks. It has gone from on the order of hours to less than 10 minutes to 30 minutes.

The most valuable features are Cognito Recall and Cognito Detect.

I didn't think Vectra AI actually provided this functionality, but essentially it gives you access, with Recall, to instant visibility into your network through something like a SIEM solution. For us, being able to correlate all of this network data without having to manage it, has provided immediate value. It gives us the ability to really work on the stuff where I and my team have expertise, instead of having to manage a SIEM solution, as that is a whole undertaking in itself. It has expedited all our investigations and hunting activities because it's all there and available, and they manage it.

We use their Privileged Account Analytics for detecting issues with privileged accounts. Given that we're a global company with over 35,000 machines, the machine learning-type of analysis or visibility into baselining behavior in privileged accounts in the environment is something Vectra does amazingly. It's amazing the visibility that I get. Not only is it providing a baseline to understand the behaviors of how IT, for example, is acting globally and in all these different regions, but it also gives me an ability to get much more granular and understand more of the high-risk behaviors, rather than the behaviors that we expect from IT. Usually, malware attackers and normal IT activities look the same. It's about discerning what's outside of baseline, and Vectra does this amazingly, incorporating not only the account privileges but the context of what these accounts are doing on hosts, on top of that.

The solution also provides visibility into behaviors across the full life cycle of an attack, visibility into the attacker kill-chain. I personally do red-team testing and threat hunting and, in addition to the detections which Vectra has already caught, it's been able to outline a full attack from an external red team that came in and tested with us. Not only did it show exactly what they did, but it was even able to provide a profile of the type of behavior that this exhibited, which was an external actor. In my own attacks that I've conducted on the network, it's been able to detect everything and properly align it in a kill-chain fashion. That is extremely helpful in investigations because it helps align the host data a little bit when you have visibility of the network in such a way.

Vectra also triages threats and correlates them with compromised host devices.

Some of the customization could be improved. Everything is provided for you as an easy solution to use, but working with it and doing specific development could be worked on a bit more in the scope of an incident response team. In my opinion, it's built as a solution for everything, instead of it being part of a bunch of other tools.

For example, we have a source solution which will orchestrate the ability for us to use a host EDR and the ability for us to use Vectra. We see Vectra from a purely network standpoint. Therefore, we don't want it to be the incident manager where we have to fill in specific things to be fixed. We think the integration with source solutions could be better. It tries to treat itself as an incident resolution platform.

I have been using Vectra AI for three to four years.

It has never crashed. It's always working. And they always resolve any issue before you can act. They'll alert you of an issue and then they'll report that it's fixed. They're very proactive.

In terms of instant access to the data and scalability, we've never seen issues with the platform at all. We use it everywhere, across all our regions across over 35,000 devices. We have plans to increase usage of the solution and the capacity.

We have less than 10 people working with the solution and they're all C-CERT incident responders and investigators. And we have one person, a C-CERT specialist, for maintenance of the solution but he is barely doing that anymore because they have a support team that helps alert us to any issues.

I've found that Vectra in general, away from the platform, has been extremely helpful and given me any support that I need on investigations or in trying to reduce the amount of noise. They have allowed me to do this, but it requires a lot of work upfront.

Looking back at the setup now, it was straightforward because of the support that they provided. I'm not sure how long the overall deployment took but it may have taken a couple of months.

We had to install specific brains in multiple regions. We were given instructions on where to install specific network nodes and sensors to be able to collect information where the brains were located. All of this configuration was provided directly from them. They sent the devices over to our data centers along with documentation to support the devices.

We have definitely seen return on our investment (ROI). While our analysts are working on "more" incidents, the efficiency of the way they're working, due to the way that Vectra has broken down its platform and its data, has exponentially decreased the response times to incidents. It has also trained them indirectly because with the story-lining, the way that it creates these detections, analysts receive them and pick them up much quicker than they would in a normal security class.

We evaluated other options. I wasn't the person who decided on Vectra AI at the time, but we were looking at Darktrace and other machine learning-type solutions.

Vectra fit the niche of what we needed, from the perspective of the former C-CERT manager. Also the feedback we got from their team and the support we've had with them really pushed us to work with them. They were very collaborative and we believed in what they were doing when they initially started working with us all those years ago.

My advice would be to really utilize the support and collaborate with Vectra. The solution requires heavy usage and customization to your environment. They provide the guidelines and you just have to be able to fill in the specifics. If you don't do that, it's not an effective tool. It is a really hands-on tool.

Vectra has done a really good job of giving you visibility into the type of behavior into which you want visibility. But reducing the number of alerts really depends more on the analyst who is operating it and working with it.

As for its ability to reduce false positives and help us focus on the highest-risk threats, the term "false positive," especially in this scope of machine learning, doesn't seem to me to apply. Vectra gives you visibility into what you want to see. It gives us visibility into the exact behaviors which we sometimes have issues trying to create detections for on the host. And on the network it's collected and brought it all together. We get really good visibility into all of the risky behaviors. Vectra provides the whole context, on the network, of what it sees in terms of a risky behavior and provides a story with it.

In comparison to some of the other tools that I've come across in this category, I would definitely give it a 10 out of 10.

We use Vectra with the assumption that our other defensive controls are not working. We rely on it to be able to detect anomalous activities on our network and trigger investigation activities. It's a line of detection assuming that a breach occurred or has been successful in some way. That's our primary use case.

We have it in some of other use cases, like anomalous network activity and detection for things. E.g., we are trying to refine or improve suspicious internal behaviours because we are a development technology company. We have developers doing suspicious things all the time. Therefore, we use it to help us identify when they are not behaving correctly and improve our best practices.

We have it predominantly on-prem, which is a combination of physical and virtual sensors. We also have a very minor element on the cloud where we are trialing a couple of components that are not fully deployed. For the cloud deployment, we are using Azure.

We are on the latest version of Cognito.

We have a limited use of Vectra Privileged Account Analytics for detecting issues with privileged accounts at the moment. That is primarily due to the fact that our identity management solution is going through a process of improving our privileged account management process, so we are getting a lot of false positives in that area. Once our privilege account management infrastructure is fully in place and live, then we will be taking on more privileged account detections and live SOC detections to investigate. However, at the moment, it has limited applicability.

We have a lot of technically capable people with privilege who are able to do things they should or should not be able to do, as they're not subject-matter experts when it comes to things like security. They may make a decision to implement or download a piece of software, implement a script, or do something that gets the job done for them. However, this opens us up to major security risk. These are the types of activities that the tool has been able to identify, enabling us to improve communication with those individuals or teams so they improve their business process to a more secure or best practice approach. This is a good example of how the solution has enabled us to identify when people are engaging in legitimate risky activities, and we're able to identify and engage with them to reduce risk within the network.

It has enabled our security analysts to have more time to look at other tools. We have many tools in place, and Vectra is just one of them. Their priority will always be to deal with intrusion attempt type of alerts, such as malware compromise or misuse of credentials. Vectra was able to simplify the process of starting a threat hunting or investigation activity on an anomaly. Previously, we weren't able to do this because the amount of alerts and volume of data were just too large. Within our security operations, they can now review large volumes of data that provide us with indicators of compromise or anomalous behaviour. 

By reducing false positives, we are able to take on more procedures and processes. We have about seven different tools providing alerts and reporting to the SOC at any one time. These range from network-based to host-based to internet-based alerts and detections. We are more capable to cover the whole spectrum of our tooling. Previously, we were only able to deal with a smaller subset due to the sheer workload. 

In some regards, I find that Vectra probably create more investigative questions. E.g., we need to find answers from other solutions. So, it is raising more questions than it is specifically answering. However, without Vectra, we wouldn't know the questions to ask in the first place. We wouldn't know what anomalies were occurring on our network.

Vectra data provides us with an element of enrichment for other detections. For example, if we see a detection going onto a single host, we could then look at that activity in Vectra to see whether there are suspicious detections occurring. This would give us the high percentage of confidence that the compromise was more severe than a normal malware alert, e.g., destructive malware or commander control malware enabling someone to pivot horizontally across the network. Vectra provides us with that insight. This enables us to build up an enriched view quickly.

One of the most valuable features of the platform is its ability to provide you with aggregated risk scores based on impact and certainty of threats being detected. This is both applied to individual and host detections. This is important because it enables us to use this platform to prioritize the most likely imminent threats. So, it reduces alert fatigue follow ups for security operation center analysts. It also provides us with an ability to prioritize limited resources.

It aggregates information on a host and host basis so you can look at individual detections and how they are occurring over time. Then, you can have a look at the host scores too. One of the useful elements of that is it is able to aggregate scores together to give you a realistic view of the current risk that the host plays in your network. It also ages out detections over time. Then, if that host is not been seeing doing anything else that fits into suspicious detection, it will reduce its risk score and fall off of the quadrant where you are monitoring critical content for hosts that you're trying to detect. 

When you are analyzing and triaging detections and looking for detection patterns, you are able to create filters and triage detections out. Then, in the future, those types of business usual or expected network behaviours don't create false positive triggers which would then impact risk scores. 

Without the detection activities that come from Vectra, we wouldn't have been able to identify the true cause of an event's severity by relying on other tools. This would have slipped under the radar or taken a dedicated analyst days to look for it. Whereas, Vectra can aggregate the risk of multiple detections, and we are able to identify and find them within a couple of hours. 

You are always limited with visibility on the host due to the fact that it is a network based tool. It gives you visibility on certain elements of the attack path, but it doesn't necessarily give you visibility on everything. Specifically, the initial intrusion side of things that doesn't necessarily see the initial compromise. It doesn't see stuff that goes on the host, such as where scripts are run. Even though you are seeing traffic, it doesn't necessarily see the malicious payload. Therefore, it's very difficult for it to identify these type of host-driven complex attacks.

It only shows us a view of suspicious behaviours. It doesn't show us a view of key or regularly attacked company targets. This could be because we don't have one of the other tools or products that Vectra provides, such as Stream or Recall. 

My challenge with the detection alerting platform, Cognito, is it tells us this host is behaving suspiciously and is targeting these other machines, but it won't give you a view when a host is the target of multiple attacks. This because you may have a key assets, such as domain controllers or configuration management servers. These are key assets which may get targeted. If you're a savvy attacker, you spread out your attack across multiple sources to try and hide them across the network. That is where the solution falls a bit short. It is trying to build that chain of relationships across detections and also trying to show detections from a perspective of a victim rather than the perspective of an attacker. I have expressed these concerns to Vectra and they are currently in as feature requests.

There is another feature in place which takes additional data feeds, such as DHCP IP allocation data. Their inputs are taken from Windows event logs, and that's the format they have in place. They use that to provide them with a more accurate view of host identities. If you are only relying on IP addresses, and IP addresses change over time, it's sometimes very difficult to show a consistent view of a system behaviour over time, as the IP can change per month. Unfortunately, because their DHCP data is taken from Windows host events and our DHCP data is taken from a Palo Alto system that generates the IP leasing, the formats are incompatible. I think taking different formats for that type of data is something else we have a feature request in for. At the moment, we don't have an accurate view, or confidence, that they are resolving when an IP address changes from host to host. So, we may be missing an accurate view of risk on some of those hosts. 

We also have the same problem with VPN and Citrix. E.g., if you're on the network and on IP address A, then you come in via the VPN, you're now on IP address B. Thus, if you're spreading your suspicious behaviour across both the internal network and VPN, then across Citrix, we don't get to join all that information up. They are seen as three different systems, so it causes a bit of a problem trying to correlate that type of event data.

If you include the proof of concept, I have been using Vectra for three years.

There are no concerns regarding the stability. It seems to be very reliable. I've had one sensor in two and a half years become corrupt and need to be rebuilt. That's it.

Day-to-day maintenance takes half an FTE to one FTE a day. There is no maintenance really required on the platform. All we need to do is monitor for when a health alarm occurs (a sensor is not working), then we raise the relevant request with the teams to investigate. Maintaining the health of the platform requires a feed into our operations team to be able to look at our monitor to determine when the health is degrading. Doing general health, like detection filters, triage filters, reviewing, looking for patterns and anomalies, and creating new filters, needs a daily dedicated FTE.

The scalability is brilliant. It is able to cope with virtual sensors. You can increase the hardware that supports the image and it will work with the high bandwidth of the data going through. There are no concerns in terms of the scalability.

It does create capture network data at scale because we have it deployed at over a 100 geographically split sites. We have over 8000 users on cloud. So, it's able to deal with the network traffic very easily, providing us with additional information. If we were just relying on things like firewalls and packet capture applications, we wouldn't get to that enrichment of a security context put on top of normal network traffic. 

Mainly, there are five people dedicated to using the platform: Tier 2 security analysts and an operations director. However, that is widen out to whomever we are raising the support requirements to, like the Tier 3s. When raised, we also enable the shared link so they can go into the platform and look at the data associated with the detection on that host. So, there is a wider volume of people who use the solution to get information for specifically requested cases. 

The technical support is very good. They always respond within a short amount of time to provide expert information and have always been helpful in trying to work through problems to find a good solution.

Previously, we had a general sensor solution taking logs. We didn't have an equivalent detection platform for our network nor did we have a tool capable of providing us with competent intrusion detection capabilities post-breach. Our main SIEM logging platform was generating over a 1000 alerts a day. It was bloated and unusable when trying to identify events/anomalies that were occurring. Once we implemented Vectra, it was able to give us a refined view and tell us which things we need to prioritize so we were able to reduce our workload from a 1000 alerts a day down to 10.

The initial setup was relatively straightforward. It was pretty much plug and play.

The initial pilot deployment took weeks, but that was because the scope kept on changing. However, the initial deployment only took hours. 

It has not helped us move work from our Tier 2 to Tier 1 analysts, but this is a fault in our implementation. The structure of our organization hasn't necessarily changed. We don't have Tier 1 security analysts. Therefore, we don't have the capacity or capability for them to deal with these types of detections. We have to leave our Vectra detection and activities with our Tier 2s.

We now have an implementation strategy. We have virtualized sensors in most locations rather than physical sensors. We only have physical sensors in the areas where there is high bandwidth traffic, such as key internal data centers. The virtual centers for local offices are sufficient for the volume of traffic there. We only deploy in areas that are key risks. We also only deploy and monitor network zones which are of significant risk, so we don't monitor our guest WiFi subnet nor do we monitor our development network subnets. Therefore, we keep our segregated networks and zoning structure consistent so we are able to only monitor for priority areas.

Vectra had an engineer come down. They plugged the device in and set it up. Since the firewall rules were already in place, it was working.

Assuming the firewall rules are already in place for the physical sensor, it needs one person plugging it in and putting it into a rack. If it is a virtual sensor, then it is just somebody who can deploy the virtual image onto the virtual infrastructure and switch it on. It takes two dedicated people to deploy. If you have a network team and a server team, then you will need one of each of those skill sets to be able to deploy the tool. It all depends on how your organization is structured.

It has increased our security efficiency because we can now do more with the tool. E.g., if we had a data analyst who was creating models and searching the data to identify the same types of the numbers/behaviours within Vectra, we would need at least two or three FTEs.

Vectra has reduced the time it takes us to respond to attacks. In 2019, we conducted a red team activity. The Vectra appliance was able to alert the red team on activity within three hours of the test starting. Prior tests to that, in real life or red team scenarios, we were potentially looking at days. However, we also tightened controls prior to that testing period. While Vectra has done an amazing job in reducing the time to respond, there are so many other things that we also have put in place which have contributed towards it.

Vectra has saved us weeks, if not months, in terms of the ability to identify a breach. Our process has been reduced down to hours, which is a potentially massive return on investment, if we were compromised. From an insurance perspective, the return investment is fantastic. 

From an FTE perspective, while it reduces the number of events that we have to look up and the number of alerts, we now have very specific things where we need to ask questions. Therefore, it's creating more work which we weren't capable of doing. 

At the time of purchase, we found the pricing acceptable. We had an urgency to get something in place because we had a minor breach that occurred at the tail end of 2016 to the beginning of 2017. This indicated we had a lack of ability to detect things on the network. Hence, why we moved quickly to get into the tool in place. We found things like Bitcoin mining and botnets which we closed quickly. In that regard, it was worth the money. Three years later, the license is now due for renewal so we will need to review it and see how competitive it is versus other solutions.

When we implemented the physical sensors, there were costs for support in terms of detection review sessions. We had a monthly session where an analyst would talk through the content, types of detections that they were seeing, etc. 

We have a desire to increase our use. However, it all comes down to budget. It's a very expensive tool that is very difficult to prove business support for. We would like to have two separate networks. We have our corporate network and PCI network, which is segregated due to payment processing. We don't have it for deployed in the PCI network. It would be good to have it fully deployed there to provide us with additional monitoring and control, but the cost associated with their licensing model makes it prohibitively expensive to deploy.

We did review the marketplace and look around. For example, we looked online at Darktrace, but we didn't run a side by side comparison to see which one would work better.

Vectra was the only tool in which we did a physical pilot or proof of concept. Vectra stood out for its simplicity and the general confidence that I had with the people whom I was engaging and having conversations with at that time. I am very much a people person. If I talk to people and don't get the impression they know what they're talking about, then that will reduce my confidence in their product. E.g., our initial engagement with Darktrace wasn't good enough to provide confidence in their platform, and we had to move quickly.

Make sure you have a dedicated resource committed to daily use of the tool. Because the selling point is it frees up your time, reducing the amount of time you need to spend on it so you don't have to commit resources. Then, you find yourself in an implementation two years later and you don't have committed resources who use it daily or are committed to it full-time. This means you don't maintain things like the triad rules and filters. Even though the sales material says it makes it easier and reduces alert fatigue, it doesn't give more time. You still need to have a dedicated resource to operate the tool, which we never committed at the beginning.

Having an established mature team structure is really important as well. Making sure people are aware of their role and how their role fits into the use of the tool is key. Whereas, we were building a security operation center (SOC) at the same time that we took on the tool, so our analyst activities have evolved around the incorporation of the tool into the organization and it's not necessarily a mature approach.

I would rate this solution as an eight (out of 10).

I work as an analyst who determines how our services should be built and integrated. We use Vectra to address a lack of visibility in our client environments. The tool has the potential to solve problems in a few areas, with new features on the way. We're exploring ways to build our services on top of the Vectra platform. 

We are considering the various integration options and how we can build a solid portfolio using this suite of products in future services. We have other tools like Palo Alto, and we hope to leverage our services on other platforms. There are several internal integration challenges that we need to examine.

Vectra gives my clients a sense of comfort. For example, in some of our cases last year, Vectra enabled us to understand each exploit's phases of attack, helping us to segment those phases. We knew how the phases were executed, so we could search for all those signs. It put the client at ease to know we could see signs of successful exploitation and demonstrated our value to them. 

We're software clients building services on top of Vectra for our customers. It's crucial for us to get the alerts we need and decide which quarter should be our focus. We're still trying to navigate the solution, but we're getting closer to determining how we want to build our services. We know how to deliver the services, but there are nuanced ways we can improve. However, learning the cloud UI and new scoring models has been an adjustment. 

The core product provides excellent visibility, but my favorite feature is Vectra Recall. It enables us to use archived data to address current or active threats that may not have been detected.

I have yet to see real-time attacks, and I'm the kind of person who needs hands-on experience. At the same time, they are triggering alerts on our regular scanning tools like Nessus. It triggers if they are noisy enough. Vectra's Threat Lab showcases this, but I need a case to work with to know from experience. 

Vectra Recall could be utilized much more, and I'm seeing some indications of that today with the investigative components. I use the visualize feature to visualize components and dashboards a lot. I'm interested in new ways to build automated searches or having them leveraged already from Vectra.

I have used Vectra AI for around a year.

Vectra AI is stable on the sensor side. It doesn't create a heavy maintenance burden on our team. There is a thin line between what we need to do and what our client needs to do. The client has an outsourcing partner doing things for them, and there aren't many issues with the detection platform. Recall sometimes goes down when we make too many queries, but it comes back up quickly. 

Vectra AI is highly scalable. Our clients vary in size, ranging from 400 IPs to massive deployments with upwards of 20,000 IPs. So it's just a matter of getting the initial scoping and what type of visibility you want to have.

I rate Vectra customer support ten out of ten. They're excellent, and they'll find the correct answer even if they don't know it at first. We use tech support and the customer success team. They are top-notch and responsive to any suggestions we have as an MSP. 

Positive

I have some personal experience with one of Vectra's main competitors, but I won't mention them by name. I'm trying to go beyond all the marketing hype, and I have huge respect for both tools. As an analyst, I want to find the bad guys at the end of the day, and I've had good experiences with both. We have more experience with the other tool, and I'm comfortable detecting threats on both. They're equally capable in this field.

Vectra AI has advantages, including a more extensive list of attack and defense references. Vecta has better at-a-glance integration options with EDR tools like CrowdStrike. There are nuanced differences between the products, and one might be more suitable depending on your needs. 

There are more dimensions than detection capabilities. It depends on the partner model and the market. Vectra covers many of those areas, and it's our primary vendor. 

Our platform team was responsible for implementing Vectra. The greatest challenge was getting the initial scoping a hundred percent correct. Sometimes the client comes from Vectra, and/or they come from us. The handover must be hundred percent because we know exactly what we will deliver. Existing and future clients need to ensure the scoping is perfect. 

The scope is sometimes unclear and isn't apparent until you start. The scoping needs to be right for you to have a good deployment. You know your integration options and will connect X of these sensors.

Once the scoping is correct, everything else is straightforward for our team to implement. 

I haven't gotten much feedback about the return on investment. Because nothing is happening yet, we need some reassurance that we can see when it does. We must feel confident that it will actively respond when something happens. 

We can use Vectra to create visibility, like Microsoft coming out with end-of-life PCERPC integrations. We can help the clients even though it's not on the security operations team. You can utilize the network data once you have it and we can build the services to provide assistance above and beyond detection.

I rate Vectra AI a nine out of ten.