Vectra AI Reviews

We have a basic Vectra environment because we mainly only use the NDR for the solution's options. We do mainly filled logins, anomalies, and network flow monitoring.

Vectra AI helped improve our mean time to identify by allowing us to have visibility and reveal some hidden or unknown things.

Vectra AI has had a positive impact on the productivity of our SOC team which is an external party. It as well had a positive impact on our IT environment for detection purposes, adapting, and hardening.

The fact that we get the visualization of what's happening on our network, which is a way of improving our security in-depth is most valuable. That's because with the information we get out of Vectra, we know how to adapt and modify things in our network.

Regarding Vectra AI attack signal intelligence, it is providing us with information on how to adapt or protect ourselves against certain attack vectors. This feature is quite helpful.

I think Vectra AI's automation, reporting, and integration could be improved.

I have been using this solution for two years now.

It's stable as it performs as we expected.

If you have enough power or bandwidth to deploy another sensor, the scalability of this solution shouldn't be very complex.

I would rate the technical support of the Vectra AI solution a seven, on a scale from one to ten, with one being the worst and 10 being the best. The reason for this rating is that they always deliver what we expect and that's good enough for us. The reason that the rating is not a ten, is that we always need to let people improve themselves.

Neutral

I joined the deployment project at a later stage and I worked on deploying the sensors and tuning false positives and similar things. My experience when it comes to deployment was quite good as we had good hands-on engineers which is why the implementation went well. Our deployment was straightforward with our hands-on approach.

When it comes to ROI, in certain places we saw the return and in certain places we didn't. When it comes to security investments and tooling of security, the return on investment takes a bit longer and you always see your investment back. At one point something will happen and you will start using the tool for the reason you bought it.

Before Vectra, we didn't have any feasibility of our network net flow, so this solution gives us a better view of what has been happening on our network and this is what we're trying to solve by implementing Vectra.

We are not using the flood detection response platform.

We are not using Vectra MDR services.

Overall, I would rate this solution a seven, on a scale from one to ten, with one being the worst and ten being the best.

Our company is in the retail arena, and we have stores, warehouses, and a data center. Right now, we're using Vectra AI in our offices and the data center. The major issue we had was that we were completely blind inside our data center in terms of seeing what traffic we had. Our main focus with Vectra AI was to see what's happening inside the data center through virtual sensors.

We're going to expand it to include our stores because the franchisees requested that we monitor the networks in all of the stores. Every shop in our company is a franchise, and they can do whatever they want to in their shops. We won't have any idea as to what's on the network in the shops. By using Vectra AI, we will have visibility into the network.

We have started the proof of concept for our warehouses as well.

We discovered a lot of things in our network and are correcting several misconfigurations. We are learning how some apps work together and how some things shouldn't happen. It's also easier for us to identify the source of a brute force, whereas before, we didn't even know we had a brute force.

The platform is well-designed around the quadrant. We know quickly how to investigate, and the detections are clear. I like Vectra AI's integration with Active Directory and the fact that it's easy to take in hand.

We have had a few issues with the integration of Vectra AI with EDR. Some filters have not been working. We've also had issues with the brain not being powerful enough.

In the next release, I would like to see more triage choices. From my point of view, Vectra is missing a lot of choices. This is an area that they could focus on.

Vectra is also moving to a full cloud model, and I am not sure if going full cloud and leaving the on-premises environment is the way to go. We are not sure whether we'll move to the cloud with Vectra because it's hosted by AWS, which is one of our competitors. We don't like to work with anything that works on AWS.

We did a proof of concept two years ago and then deployed it in March, 2022.

We've had issues with stability. Vectra said that they underestimated the power we needed on our brain as it's very slow. We have delays that can be up to 40 seconds. We also had a hard drive that died. In one year, we've experienced three major issues.

We have different types of deployment that impact scalability a lot. The good part is that if we want to see everything that gets into the data center, we only need a single sensor in the data center. However, if we want to go in-depth in every store, then it will be a long process because we'll have to deploy thousands of sensors.

Right now, our license is for 10,000 IPs, and we hope to increase it to 110,000. If we deploy Vectra AI in the warehouse as well, we will need 25,000 extra. When we upgrade the brain server, Vectra AI should be able to scale accordingly.

When I contacted technical support, they usually take control of my laptop for an hour or more, and I can't do anything during that time. They do not explain anything and mute themselves for an hour or more. I don't know what they're doing or if they're even working on the issue.

However, they have been proactive because they know we have issues with our brain. If I have a bug, I've noticed that they usually respond quickly.

Thus, on a scale from one to ten, I would rate technical support at six.

Neutral

I've done four deployments in total, and Vectra AI is easy to deploy. On the admin interface, it's also easy to set up the integration with EDR.

It is an expensive solution, but it's not the most expensive we've seen. We also know how much we're going to pay, unlike with some other providers where all of a sudden our license explodes.

We will probably need to deploy over a thousand physical sensors. This means that the cost will automatically go up to millions. They do not sell the smallest sensors that they had in the past, which we would be glad to have right now.

We looked at ExtraHop, a VMware NDR solution, Carbon Black, and a solution from a French organization.

Carbon Black is oriented around VMware products. As such, it would have been okay for the data center, but we would have had to upgrade the entire physical infrastructure inside the data center. It would have been very expensive, and thus, we eliminated Carbon Black. The French competitor was eliminated because the solution was a few years behind.

We then talked with Vectra AI and were happy with what they offered us. We spoke with other companies that use it and found out that they were happy with it. Thus, Vectra AI got the opportunity to do the proof of concept.

Overall, I would rate Vectra AI an eight out of ten.

We need to move our whole data traffic over the core switches. We also want to secure our network and have it integrated into our vCenter and into our Active Directory.

We have 18,000 IP addresses, and in Recall, we have uploads from about 250 GB per day.

One year ago, we found notebooks that were compromised with Emotet. Vectra saw that the client performed search requests to the Active Directory for a keyword root and contacted domains that are known for Emotet.

Vectra AI also found that a notebook had permanent contact with a domain outside our network.

We often use the new feature to create PCAP files from the whole data traffic. It makes it much easier to find network problems such as whether the server is responding to a request. It has nothing to do with security, but it helps a lot to find other problems.

Vectra AI helped improve our mean time to identify. For example, the Sophos client doesn't recognize anything, and without Vectra AI, we wouldn't be able to identify problems. It does it quickly.

We use the Sidekick MDR service. It's very important to us because it gives us another layer of security and a second pair of eyes. We have learned a lot from the Sidekick.

For S&D account scans, it would be easier if Vectra AI could triage with users. If a client uses a lot of accounts, then it could indicate that these accounts are benign, for example. That would help a lot.

I've been using Vectra AI since 2020.

We have not had any problems with stability.

Vectra's technical support is very fast. They have been able to resolve the tickets I created very quickly. I would rate technical support a ten out of ten.

Positive

The initial deployment is easy. You have to give them an IP address, plug it into the switch, and then get started.

We have seen an ROI. The cost of security breaches outweighs the cost of Vectra AI.

Vectra AI is not a cheap solution.

We evaluated Vectra AI and CyberSense and did POCs with both. We observed that Vectra AI was better because we can see everything. CyberSense uses a different technology. For example, it creates an Active Directory that isn't used. If someone connects to this Active Directory or starts requests, then we will get an alert. However, we think Vectra uses a better way because we can see more. It also has better technology.

Overall, I would rate Vectra AI at ten on a scale from one to ten, with ten being the best.

Vectra AI is an NDR tool, and my company is using it for security and insider threat detection purposes.

What I like best about Vectra AI is that it alerts you about suspicious activities.

An area for improvement in Vectra AI is reporting because it currently lacks some details. For example, when you download a report from Vectra AI, you won't see complete information about the alerts or triggers.

Another area for improvement in the tool is that sometimes, an alert has high severity, yet it's marked as low severity. Vectra AI should have a mechanism to change the severity level from low to high or critical.

I've been using Vectra AI for two years now.

Vectra AI is a stable tool.

Vectra AI is a scalable tool.

My company has a dedicated support team for Vectra AI, so I have the support team's direct contact number and WhatsApp number.

The technical support is excellent, so my rating is five out of five.

The initial setup for Vectra AI wasn't that complex. It won't take long if your environment is ready, with all required ports open. Setting up Vectra AI would be easy.

We implemented Vectra AI together with their technical support team.

My company pays for the Vectra AI licensing fee yearly. I know the figure because my company recently renewed the license, and it's okay, at least for the financial sector.

I'm the admin of Vectra AI, a tool implemented in my company.

The tool was updated three or four months ago, but I'm unsure if I have the latest release.

My company has two SOCs in different areas, so all SOC analysts log in or use Vectra AI, with the alerts forwarded to Splunk. One person is the admin in-house, but he works with support because the tool is customized for my company, as any command can't be run in Linux.

I'd recommend Vectra AI to others looking for an NDR solution.

Vectra AI is excellent for NDR purposes, in general. I'm rating it as ten out of ten based on my experience because I'm investigating the Vectra AI alerts. It triggers alerts for suspicious activities, so it's an excellent tool.

The key challenges are employee weakness, getting alerted as soon as possible on our network and infrastructures to anything suspicious that is happening, and policy-type enforcement.

The challenge that it tends to solve is visibility. We put a lot of controls in place for what we suspect will be a risk. However, something like Vectra gives us more visibility and confidence that we have a better understanding of what is actually happening, rather than just the things that we have already planned for.

We adopted an Office 365 add-in with the product that looks over the Office 365 suite and data traversing that platform. In the future, we see this as a valuable asset that we already have in place to be able to better monitor that type of detection of information. We don't have an environment where there are many true positives, which is good. That has been consistent across the old and new. Our detections have usually been benign or more configuration-based rather than some sort of attack. Because it provides more context and raises things in a way that make it more actionable, it does help you understand the anomaly on a deeper level because it is not just a log that is being forwarded on and has context around it. Vectra AI does do a good job of providing the model information upfront about how its detections work, which is helpful.

We have an external SOC and most of the data or detections from Vectra now flows to them. The final design is that they are the recipient of those alerts in parallel with us. We also receive them directly at times, depending on the criticality. What it does for us is it improves the information and context that they are getting upfront, which means less questions for our internal IT team about what these assets are and what they are doing. Because the analysts at the SOC have more information to work from, it has reduced wasted time and improved the path that we are taking to a resolution, if there is a problem. It is more straightforward when you are getting quality information upfront about what you are actually investigating and why you are investigating it, rather than just, "This particular activity was detected on the network. Go and work out everything about it," Vectra gives you some context around it and a little bit of direction when you see these things, e.g., this is potentially what could be causing it. This improves workflow, reduces wasted time, and makes everyone's life a little bit easier.

It has given us an increased level of confidence in our information security that we have a tool like Vectra to back up some of the incidents that could take place, knowing we are going to get them detected as quickly as possible and identified to us. Nowadays, with threats on ransomware and information security types of techs, we believe that Vectra does give us a greater level of confidence that we will be able to detect those more quickly. If they do occur, we can shut them down more quickly, preventing further risks or damage to our systems or infrastructure.

Vectra AI provides visibility into behaviors across the full lifecycle of an attack in our network, beyond just the Internet gateway. It spells that out quite clearly in each detection. It is not just in the detection. You can look at detections individually, which are essentially individual events. Also, when you are looking at an asset that has multiple detections attached to it, you can see where those sit in the lifecycle of an attack. This gives you an idea of how far Vectra thinks that it has progressed. Having the ability to know where you are in an attack helps you prioritize things a bit better.

The solution correlates behaviors in our enterprise network and data centers with behaviors that we see in our cloud environment. In terms of a specific example, it links cloud identities to on-prem identities. This is something that we have never really had before, because we didn't have that visibility in our cloud environment. Now, it improves the visibility that we have of our security operations as a whole. Rather than sometimes viewing these things in silos and objects as individual objects, we are now viewing them as what they are, which is people undertaking action in our network and the pathways that they are taking to get to certain resources. By combining the cloud and on-prem data, it gives us context and helps us to get a proper view of what is actually going on.

An attractive thing about Vectra AI is the AI component that it has over the top of the detections. It will run intelligence over detections coming across in our environment and contextualize them a bit and filter them before raising them as something that the IT team or SOC need to address. 

While the device itself is deployed on-prem, the hybrid nature of what it can monitor is important to us.

Its ability to group detections for us in an easier way to better identify and investigate is beneficial. It also provides detailed descriptions on the detection, which reduces our research time into what the incident is. 

There are also some beneficial features around integration with existing products, like EDR, Active Directory, etc., where we can get some hooks to use the Vectra product to isolate devices when threats are found.

On a scale of good to bad, Vectra AI is good at having the ability to reduce alerts by rolling up numerous alerts to create a single incident or campaign for investigation. My frame of reference is another product that we had beforehand, which wasn't very good at this side of things. Vectra AI has been a good improvement in this space. In our pretty short time with it so far, Vectra AI has done a lot to reduce the noise and combine multiple detections into more singular or aggregated alerts that we can then investigate with a bit more context. It has been very good for us.

There is a level of automation that takes place where we don't have to write as many rules or be very specific around filtering data. It starts to learn, adapt, and automate some of the information coming in. It works by exception, which is really good. Initially, you get a little bit more noise, but once it understands what is normal in your environment, some of the detections are based on whether an action or activity is more than usual. It will then raise it. Initially, you are getting everything because everything is more than nothing, but now we are not getting much of that anymore because the baseline has been raised for what it would expect to see on the network.

We use the solution’s Privileged Account Analytics for detecting issues with privileged accounts. Privileged accounts are one of the biggest attack vectors that we can protect ourselves against. This is one of the few solutions that gives you true insight into where some of those privileged accounts are being used and when they are being used in an exceptional way.

We have found that Vectra AI captures network metadata at scale and enriches it with security information. We have seen that data enriched with integrations has been available and implemented. This comes back to the integration of our EDR solution. It is enriching its detection with existing products from our EDR suite, and probably some other integrations around AWS and Azure. In the future, we will see that improve even further. 

One of the core features is that Vectra AI triages threats and correlates them with compromised host devices. From a visibility perspective, we can better track the threat across the network. Instead of us potentially finding one device that has been impacted without Vectra AI, it will give us the visibility of everywhere that threat went. Therefore, visibility has increased for us.

I would like to see data processed onshore. Right now, the cloud components, like Office 365, must be processed on servers outside of Australia. I would like to see a future adoption of onshore processing. 

I have been using it for two to three months.

We have only a few months of history with it, but the solution has been rock solid. I don't think it has gone down yet.

We have the ability to add agents in Azure and AWS Cloud if we want, but we still haven't made a decision yet. We can also add more agents or sensors on-prem with the VMware virtual machine that they provide. It is scalable in that way, but at some point, you will hit the limit of the device.

One of the selling points for us was, down the track, we can just add additional agents to the box from other sources without the need for additional licensing costs.

Internal to the business, there are only two users. External to the business (the SOC), there could be a team of up to 10 people who are watching alerts day-to-day as well as using the product and logging into the product to better identify what those alerts are. Being the owners of the system, we use it when we are triggered by alerts about something significant.

We have a small IT team with fewer than 10 staff, where there are only one to two information security focused staff. We leverage an external SOC, i.e., a third-party.

Vectra AI has enabled us to do things now that we could not do before. We are able to give our SOC a tool that can both reduce their time and potentially allow them to do more on our network. Potentially, they will look into isolating the threat a lot quicker. They can use some of the integrations to turn off endpoints when a threat, which is significant, is detected.

Through the different phases of deployment that we have gone through so far, we have been mainly assigned one technical resource to assist us with everything from beginning to end. He has been very knowledgeable and responsive. I can't say anything really negative about him. 

In terms of the ongoing support, we haven't had to leverage it much yet. We are now in the production phase, so we have been handed over to the main support desk, but I haven't had to use them yet.

Through deployment, the technical support was very responsive. I think every question that I asked, if it wasn't able to be answered, got passed onto someone who could then come back with something. I think they were pretty upfront as well when the solution couldn't do what we were after. We were told that they would go away and check, then they would come back with an answer about whether what we were asking for could be done. It has all been pretty good so far.

We already had a solution like this one in place, which was another competitor's product, where the three-year contract for that product was up. We wanted to retain the level of detection that the product provided, but adapt to the way our network had changed over three years to adopt a more hybrid cloud technology. This device sits on our internal network watching for any threats to our internal network. It looks at our Office 365 threats as well.

We were previously using DarkTrace. We went to the market for reasons of maturity over time for our network. We wanted to further adapt this product to a hybrid working model. We wanted it to be able to adapt to cloud technology that we were adopting. We also wanted something commercially competitive. After three years, they came back asking for a 20% increase in their renewal fees, which wasn't acceptable.

One of the main things that Vectra has brought to the table for us, over what we were previously using, was the ability to combine our on-prem packet data that we were watching with the cloud data that we needed to start including. We have one system monitoring a hybrid environment, rather than having separate systems for separate environments. That is a key thing that Vectra does that others might not. It comes back to visibility with network monitoring.

For critical alerts, there has been a huge reduction compared to our previous solution, approximately 80% less. What our previous tool would mark as high, we wouldn't, and Vectra AI aligns with that. Vectra gave us some classifications of the threats, where our previous tool would just trigger high risks on a lot of things that to us, as a business, were not high risk. This is because of fundamentally the way that Vectra looks at detections compared to the way that our previous product did. Every detection was its own entity within the previous one. Whereas, with Vectra AI, it is all about combining the detections and getting a more complete picture. When you are looking for more than just one indicator of compromise, and you are not viewing these things in isolation, you start to realize that one indicator oftentimes doesn't mean critical. That is what Vectra does pretty well.

The initial setup was straightforward. We had the existing competitor already in place, and it was architected in a pretty similar way. Someone without a device like this one in place would need to spend a little bit of time on the setup. However, that is not so much about Vectra as it is with the type of device that it is. No matter which device does this sort of thing, when you put it in place, you will need to set certain things up.

We unboxed the device, plugged it in, and it pretty much turned on. We didn't have to do much at all. Then, there was the config after the fact, which was all supported.

The initial deployment really only took a couple of weeks to get it to the point that we were relatively comfortable with what we were receiving. In terms of getting the box plugged in, that took a day. Then, we finished the whole deployment phase of it. which was to fine tune some of our detections and config. That has really been finalized in the last few weeks.

Vectra was extremely easy and quick to get into place. It was able to run inline with DarkTrace while we were evaluating it. Also, the implementation was not heavy in any way.

We went through a proof of concept with Vectra. We had already identified our functional requirements for the product and entered into our proof of concept arrangement with Vectra to assess that they could achieve all the functional requirements that we had.

The support for deploying it was ready to assist further, if needed, with the deployment. In our case, it was very straightforward. It was very quick to implement. The support that they gave us week-to-week kept us moving. They were also able to implement it in line with us.

Development and maintenance needs a tenth of a staff member. We mostly handle this ourselves. To be effective with the alerts that you are getting, you need security staff or people who are dedicated to this kind of thing. It is one thing to maintain and deploy the device.

It is another thing to action the information that the solution is giving you. We outsource that, so we don't do it in-house.

The capturing of network metadata at scale reduces the time of investigations when researching incidents. Instead of having to look over multiple tools, that data can be somewhat aggregated, from a Vectra perspective. The time to detect and understand a threat has been reduced.

Vectra AI has reduced the time it takes us to respond to attacks. The amount of time depends on the specific detection or circumstance around it. Some things have been raised previously, then we would have good knowledge about what that detection meant and how to investigate it effectively. Other times, a detection might be viewed as more novel, where there may not be the immediate skills in place to investigate it effectively, whether that is the security team or me. There is a whole lot of research that needs to go into this to make sure that you have the knowledge to actually verify whether a thing needs to be dealt with.

Vectra AI provides you this information very well, with more context around the detection. Someone with a more general knowledge of some of these things can look at all the factors rather than just the detection to make a determination of how risky it is and how you might start investigating it. For example, with autodetection in an account, if it was just that detection, then your initial response might be to lock that account out. However, if you get a bit more context about it and can see what other activities were happening on the same asset around the same time, then you might not lock that account. You might just reach out to that user, and say, "Hey, what was this about?" because you are not so concerned about an immediate threat.

There is ongoing maturity from our security strategy, which this solution introduces. Down the track, we could look to extend this from an agent perspective to our cloud platforms in a more rigorous way than what has already been implemented. It gives us increased confidence over time as we do get these detections and alerts that are valid, so we are able to accurately resolve and stop them quite quickly. That is where we will see the bigger benefit. It will tick something and alert us as quickly as possible, then we can get to it and shut it down as quickly as possible. That means our security maturity is only strengthening, and we can respond and have visibility over events in the future.

The return on investment was passed over to our SOC. They were using our previous tool, DarkTrace, and now they are using Vectra. There will be a lot less in future reports because there will be a lot less that they are actually investigating.

From a pricing perspective, they are very commercially competitive. From a licensing perspective, just be conscious that some of their future cloud solutions come with additional subscriptions. Also, if you're outside of the US, you will get charged freight for the device back to your country. I tried to negotiate getting rid of this, but unfortunately, it just wasn't something they would take off the table.

I would like to see ways they can look to bring out new cloud functionality without introducing additional costs for them as additional subscriptions. They're about to bring out their AWS add-in, which has an additional cost. So, I would like to see them start to roll that into the product, as opposed to having it be offered as a separate subscription service. Because the more that that happens, the more it goes away from the core functionality of the product if we are just buying a lot of separate cloud processing pieces doing different functions. Why is that not being made as part of the core product?

They also have some additional threat hunting tools that I would like to at least consider leveraging, but the cost is just prohibitive.

After deploying this solution in our network, it began to add value to our security operations straightaway. We ran the Vectra product in line with DarkTrace and were watching the alerts from both. Because I was sometimes getting exactly the same detections on both platforms, the Vectra information was actually assisting me in understanding what DarkTrace was doing and what it was warning me about. Straightaway, I started to get a better understanding of the alerts that we had been receiving for a long time.

It pays to evaluate the market regularly on products like this. The industry and platforms change very rapidly, and there is always new technology coming out. Three years ago, these guys wouldn't have probably been around or been looked at. Now, they are. Therefore, going out to the market and actually assessing our existing investment, against what is out there today, was very worthwhile.

For EDR, we are using CrowdStrike.

The visibility of your threats will be easier to understand with Vectra AI. It provides you with a centralized dashboard of those threats and alerts. It gives you detailed descriptions for quicker research into what the identified threats and alerts are. It will integrate with existing products you may already be using. Overall, it reduces a lot of time spent on chasing false positives.

Right now, we are leveraging the on-prem appliance and the Office 365 Cloud component. We want to look to the future around potentially extending this to further parts of Office 365 and cloud environments, like Azure and AWS.

We haven't adopted Power Automate into our environment as of yet.

I would rate this solution as eight and a half out of 10.

In terms of deployment, we have one brain and seven physical sensors. We're currently working on deploying a large number of virtual sensors, but those aren't done yet. We also have a SIEM and an EDR.

There are a large number of difficult-to-manage devices on a network. Traditional security vendors do a great job of making sure that workstations and servers are properly protected, secured, and observed, but they fall short when we're talking about odd peripherals, such as printers, scan guns, tablets, guest devices, and things like that. That's what Vectra helps us see. I can't tell the number of employee guest phones that just show up on the network, and they're infected because they're not managed by us and people do things with their phones. Now, we're able to actually see those devices hit our internal LAN instead of our guest networks, and we can properly move them over, whereas earlier, we were blind. Now, we have some reasonable assurance that our internal tablets, scan guns, and things like that are not performing abnormal network behavior. So, that's what we use Vectra for.

We've got a centralized data center with a large number of physical locations throughout the country. So, our network is very distributed. It's very much like a campus. Vectra is really good at reducing the complication of deploying an NDR solution, and that really helps us because we have over 175 stores that we need to capture traffic from, as well as a number of sales offices, regular employee offices, and distribution centers distributed across the country. So, Vectra makes it really easy. We just drop or ship it over there, and it is up and running real quick once it gets there. Shipping takes longer than configuration. So, basically, our network is a centralized data center infrastructure with a large number of stores, distribution centers, and offices geographically dispersed around the country.

It provides visibility into behaviors across the full lifecycle of an attack in our network beyond just the internet gateway. We tap client to server, server to server, and client and server to internet traffic, and it does a good job. It doesn't have an issue with internal traffic. In terms of the full lifecycle of the attack, Vectra is not designed to interface with or inspect the host. So, we're not seeing host activity obviously. That's what our EDR is doing. Vectra does an okay job. If we get a weird detection, we're also able to see a large number of other activities that happened just before and just after the attack and relate those to it.

Before we deployed Vectra, we were not monitoring network traffic. So, there was definitely a need and a gap, and Vectra has filled it. We have reliable network logs that are readable, and it does a good job of doing a default set of detections for us. We're very happy with the gap that it has filled.

It has overall reduced the time to respond to attacks, especially with the PCAP function on the detection, where when it gets a detection, it PCAPs the session. So, we're able to get a lot of context to alerts that we were unable to get before we deployed this because we weren't doing a full PCAP. Because Vectra only PCAPs the session when it triggers a detection, we didn't have to deploy hundreds of terabytes of storage across our network. So, we saved a lot of money there. There are $50,000 to $100,000 storage cost savings because it only captures the full packet capture for traffic that triggers detections. In terms of time, it has saved hundreds of hours. I can't even explain how happy we are with the amount of time it has saved us. Imagine the amount of time it would have taken us to deploy to 175 stores plus dozens of distribution centers and dozens of remote offices. Even if it was just one hour per location for deployment, that makes it hundreds of hours. Vectra, with being so easy to deploy and so easy to maintain and administer, has saved us hundreds of hours just on deployment and standing up the environment alone. I am not counting the maintenance and administration that come along with the solution.

It does a reliable job of parsing out the logs of all the network traffic so that we can ingest them into our SIEM and utilize them for threat hunting and case investigations. It is pretty robust and reliable. The administration time that we spend maintaining it or troubleshooting it is very low. So, the labor hour overhead is probably our largest benefit from it. We spend 99% of our time in Vectra investigating cases, responding to incidents, or hunting, and only around 1% of our time is spent patching, troubleshooting, or doing anything else. That's our largest benefit from Vectra.

We've got machine learning and AI detections, but we also have the traditional ability to create our own custom detections and rules that are important to us for compliance. When we were demoing other vendors, a large number of vendors let you make your own rules, but they don't provide their own rules and ML and AI rule engine, or they provide AI and ML, but they don't allow you to make your own rules. Vectra is very nice in that sense. We have detection rules that Vectra provides that are very common to the security industry, such as whenever there's a major event like the SolarWinds event. Those rules get built and deployed for us really quickly. We can manage our own, but then we also have the ML and the AI engine. We really like that. It is one of the few platforms that we've found to be supporting all three options.

They use a proprietary logging format that is probably 90% similar to Bro Logs. Their biggest area of improvement is finishing out the remaining 10%. That 10% might not be beneficial to their ML engine, but that's fine. The industry standard is Zeek Logs or Bro Logs, or Bro or Zeek, depending on how old you are. While they have 90% of those fields, they're still missing some fields. In very rare instances, some community rules do not have the fields that they need, and we had to modify community rules for our logs. So, their biggest area of improvement would be to just finish their matching of the Zeek standard.

They could provide distributed endpoint logging capability. We have a lot of remote workers nowadays in the day of the pandemic. If they're not connected to our VPN, then we're not capturing that traffic. So, the ability to do the traffic analysis for endpoints that are distributed would be cool. I have no idea how they would do that. I'm not aware of a single vendor that does that, but it would be cool if they could do that. To my knowledge, that's not really possible with the amount of compute power it would take on endpoints. It would be ridiculous. They'd have to really invent something new and novel that doesn't exist today in order to accomplish that. If they do, that would be great. Because I'm a customer already, I would use it. 

Cost-wise, they're not cheap. They were definitely the most expensive option. Their licensing model is antiquated. We have to pay for licensing based on four different things. They need to simplify their licensing down to just one thing.

We have been using this solution for around 18 months.

I'm very happy with it. In the 18 months, I cannot recall any outage. We keep up on all the patching and maintenance, and there have been very few bugs. The SaaS product Recall has always been there when we use it. Our on-prem version has never broke. It seems very stable.

It has got no problem with scaling. We picked Vectra because it was able to scale up to our size fairly easily without scaling up the deployment and administration overhead. So, it scales really well. It has no problem handling our volume of data.

Their technical support is pretty good. They're very responsive. Nine out of 10 times, they understand my problem. They're not perfect, obviously, but at the end of the day, I got answers for the few issues for which I've had to use support. I can only think of one instance where it was painful, and that's why I say nine out of 10 instead of 10 out of 10. The guy just didn't understand what I was asking, and about seven emails later, it got triaged, and the next guy figured it out. Other than that, the first person I email in at support is able to answer my question in that initial response or just one extra email.

We did not use any similar solution. 

We have a couple of SaaS-based products. We use Cognito, Recall, and Stream. Recall is their SaaS-based product where all the logs go into their hosted elastic search instance, which allows us to search and create custom rules and everything like that, and then we pull data from that environment into our on-prem environment. In terms of the deployment of the brain, that's all on-prem. All the sensors are on-prem obviously, but we do use Recall.

In terms of the effort involved in deployment considering that some of the pieces we use are SaaS-based, it was literally just a toggle switch and an API client and key in the interface, and then it was working. We had to wait for accounting to approve it, and it added a little bit more time to our deployment because of paperwork, but technically, it was pretty simple. We told them we wanted this, and by the time that we got our paperwork done, everything at their end was stood up and ready to go for us.

It does take two to three weeks for the brain to baseline and establish its ML baseline. The moment it was done with the two-week to three-week machine learning period, it was good. So, it started providing value after three or four weeks after deployment.

Their licensing model is antiquated. I'm not a fan of their licensing model. We have to pay for licensing based on four different things. You have to pay based on the number of unique IPs, the number of logs that we send through Recall and Stream, and the size of our environment. They need to simplify their licensing down to just one thing. It should be based on the amount of data, the number of devices, or something else, but there should be just one thing for everything. That's what they need to base their licensing on. 

Cost-wise, they're not cheap. They were definitely the most expensive option, but you get what you pay for. They're not the cheapest option. I know that their prices scared away a couple of people who have demoed it in the past. Once they got their quote, they were like, "Well, see you later. We can't do this." So, that is an area that they come up short against other people.

We did evaluate other options. We evaluated rolling Bro or Zeek on our own. We evaluated Security Onion. We also evaluated Corelight and almost picked them. We also investigated a couple of solutions that are significantly more involved than Vectra, just like full managed solutions, but we decided not to do that.

The main reason for choosing Vectra over all the other solutions was twofold. One was the deployment time and routine administration costs. Its deployment was very simple. The amount of time it would take to deploy and configure was very low. The time it would take to maintain the environment was significantly lower than the other solutions and on par with Corelight.

The second reason for picking it up is that it allowed us to create our own detection rules. They build rules for us when there are major events, as well as they have the ML and AI engine. This was the only solution that was easy and fast to deploy and maintain, and that was giving us all three options for rule detection. That's why we went with them. Some of the solutions provided all three options, but they were a pain to configure and maintain, and some of them were easy to deploy and maintain, but they didn't provide all three options.

It is pretty straightforward. Plug it in and use aggregators in front of the sensors to aggregate multiple tap sources into a single sensor. The sensors can handle it. They de-duplicate everything. There is no need to purchase a sensor for every tap. Truncate all that traffic into an aggregator and have it come out one feed into the sensor. There is no issue there with the Vectra sensor being able to carve out all that. They're powerful enough to do that. Vectra recommends that. So, if someone is purchasing Vectra, they're going to hear that from them. With Vectra, you're picking reliable and fast among cheap, reliable, and fast.

In terms of Vectra's ability to reduce alerts by rolling up numerous alerts to create a single incident or campaign for investigation, we do not generate a lot of incidents. We're pretty quick off the gun on detections. We're responding to detections before subsequent detections are detected and become an incident. We maybe get one incident a week, so I don't know if I can comment on that effectively.

We don't use privileged account analytics from Vectra for detecting issues with privileged accounts. In terms of its detection model for providing security around things like Power Automate or other anomalies at a deeper level, we don't use Power Automate, but we use their anomaly detection, and it is very interesting. While it always does provide us something interesting to look at, more times than not, it is our IT admin who does anomaly detection. So, we learn a lot, and it brings odd things to our attention, but with anomaly detection, it has usually been our IT admin.

In terms of Vectra helping our network's cybersecurity and risk-reduction efforts in the future, I'm hoping that one day, we can achieve even client-to-client inspection. Vectra should stay up with the times, and they shouldn't start coasting, which I don't see at all. They fill a good gap, and they do that well. We're just going to leave them filling that gap until the time comes where that is no longer a need, which I don't foresee. So, I don't know if they're going to do anything more than inspect network traffic and provide us an alerting engine on anomalous or malicious network traffic. That's their niche, so that's what they're going to do, probably just more of it. As we grow, we'll deploy more Vectra sensors to capture that extra traffic. I see them scaling very well.

I would rate this solution a solid eight out of 10. It loses a star for not adhering to Bro Logs in my book, and there is no perfect 10.

Our primary focus lies in identifying weaknesses to address customer concerns regarding visibility into network operations. This is especially crucial due to the presence of various managed devices within the network. Detecting and managing these devices and enhancing visibility is done by Vectra AI. It also has the capability to detect potential threats and correlate diverse events that occur on the network. Hackers often target systems from different domains, requiring cross-domain correlation. Net NDR solutions, particularly Vectra, excel in fulfilling these needs using AI-driven algorithms. Over time, these algorithms learn from the data, aiding in automatic post-event analysis. 

Within Vectra, multiple models exist, including an AI model which is very important. Vectra is very compatible with various cloud providers, such as Amazon and Azure AD. This is helpful as customers often migrate their network infrastructure to the cloud. 

Additionally, Vectra provides managed detections and responses, enhancing a company's network detection capabilities. The platform also has attack signal intelligence to identify attackers based on their tactics and techniques, preventing them from compromising critical network devices. So it acts as a detection platform, essential for halting potential threats, including clouds like Amazon and Microsoft 365. 

We offer two solutions, Vectra and ExtraHop in the Qatar market. However, ExtraHop has better features that seem more advantageous when compared to Vectra. During demos, I encountered challenges with Vectra when demonstrating its capabilities, such as dealing with expired SSL certificates. Vectra AI is capable but ExtraHop is able to provide comprehensive insights and easier data querying. It excels in data query capabilities which is helpful for customers to access and manipulate their data effortlessly. This is where Vectra needs to enhance its capabilities. Customer support and handling high network traffic are additional areas that it needs to work on. There should be more flexible options to handle customers’ needs. Also, customers desire performance enhancements and integration capabilities with a single solution and cyber security. 

I have been using Vectra AI for two years. 

I would rate the stability an eight out of ten.

I would rate the scalability an eight out of ten.

We have a strong local presence and support in this market, and our company's origins in Turkey also contribute to robust local assistance. While comprehensive support is provided during major incidents and upgrades, we excel in offering immediate assistance for failover situations and downtime prevention. The team is highly specialized in cyber security and SOC technologies. We are quite strong and are able to help ourselves in the field of technical support.

Positive

The initial setup is straightforward. I would rate the setup an eight out of ten.

In the case of deployment, 70% of the public prefers the public cloud while the rest prefer private. These are the only two forms of deployment.

The initial deployment should ideally be completed within two weeks. However, due to the need for fine-tuning, false positive elimination, and deriving enhanced value, an extended period of around two months is necessary. This allows users to cover all the potential threats and risks, ensuring comprehensive coverage

The solution is low-cost and affordable. 

Vectra faces robust competition, but it substantiates its abilities. Depending on client needs, it can easily work with other IT solutions. Yet, for pure network detection and response, Vectra excels, particularly for enterprises demanding very good solutions. It offers superior detection coverage for heightened security. It has an encryption-based approach, enabling threat detection without decrypting any data. Moreover, Vectra stands out with its broad integration capabilities with third-party tools and I personally find it a successful feature.

Overall, I would rate Vectra AI an eight out of ten. 

We use Vectra AI mainly for presentations.

It's important for us that the user interface is easy to understand and that is the biggest benefit we see from Vectra AI.

When it comes to Vectra AI helping our software's productivity, it has an effect because it's faster and that is quite important.

The feature I found most valuable is the recording because it's easy to analyze logs that I need to analyze.

The rules for threats are not always precise and Vectra AI should improve this.

I have been using this solution for about eight months.

Regarding the stability of this solution, I would say that it is efficient. We've had only one issue in the past eight months with logs.

My impression is that Vectra AI is a scalable solution and that is exactly what we need, which is great. We have around 1,500 devices currently.

I would say that we have seen an ROI with Vectra AI.

We use the Threat Detection and Response platform, mainly for forensics. It's quite effective because it's easy to understand and everything is in real-time.

Overall, I would rate this solution an eight, on a scale from one to ten, with one being the worst and ten being the best.