Vectra AI Reviews

As a sector, the education industry as a whole is under threat with quite a large volume of immediate threat offenders. We've seen numerous attacks coming through brute force or DDoS. The amount of ransomware and phishing attacks is on the rise compared to that of five years ago, for instance. I see regular threat campaigns from numerous actors around the world.

Our main use case is to have Vectra AI as an addition to our security team. We have a large campus with 1,100 boarding students and about 600 staff on top of that. However, my security team only comprises myself and one other person.

Being able to detect security threats in real-time and, more importantly, being able to get rid of the noise is very important to me. That is, getting rid of the false positives and just focusing on the actual high threats that we see coming through is a great benefit for us.

The biggest feature for us, because we are heavy Microsoft users, is its integration with Office 365. On top of Vectra AI, we use all of the Microsoft security platforms, such as Defender ATP and Sentinel. Having full integration and a central platform to look at all of the threats that are coming through from the different platforms is a huge benefit for us.

With one nice front dashboard, we can look at the high-volume threats rather than all of the noise. We do get a lot of noise as our students all own their own devices. With Vectra AI, we can look at threats in a controlled manner, which saves us an extraordinary amount of time. Even if I doubled the manpower, I doubt that I would still have the same visibility that I have with the correct security platform.

Vectra AI's Threat Detection and Response platform has done remarkably well. We're well-versed in using the security dashboard from Microsoft Defender, and we're at the stage where we are checking both. We haven't fully switched to relying on only the Vectra dashboard yet.

In terms of Vectra AI Attack Signal Intelligence for empowering security analysts within our organization, we have complete faith in the data that's coming through from Vectra. If we could also have what's happening at the front-end, that is, the firewall, then it would give us the complete security front dashboard.

In education as a sector, we are looking at AI a lot in terms of how it can be used as part of the teaching and learning side of things. It would be great to have Vectra AI look at a better way to enhance the security posture related to the AI tools in our portfolio.

We've been using Vectra now for about eight months.

Vectra AI's stability has been 100%.

Vectra AI's integration team was spot-on. They helped us with a very well-defined and well-tested plan, and they worked with us to ensure that the product met all of our goals. Now that we're a customer, we have regular meet-ups with the team.

The technical support staff are very knowledgeable regardless of the type of questions we've had. It feels like they are more than just a support team. I feel like I can reach out to them whenever I need to because they're approachable and understand the challenges that we have within our industry. As such, I would give them a rating of ten out of ten.

Previously, we used Darktrace. Though it is a good platform, because there were so many false positives coming through, we found that we were neglecting it and not investigating the alerts. After less than a year of using Vectra, we've managed to tailor our dashboards to a point where we just see the high-volume or high-risk alerts coming through, and we act on those on an instant basis. Vectra AI has helped me get my time back. 

Vectra's pricing is too high. All schools will not be able to afford it. Vectra will only end up targeting higher education and higher value independence purely because of the price.

A lot of schools would love to have a product like Vectra AI, but they simply can't because they struggle to even pay the high E5 licensing from Microsoft. When you're up against that, Vectra AI is never going to be within the sector's price range.

We evaluated whether we wanted to switch to Vectra AI or whether we wanted to utilize just our existing Microsoft security stack.

Overall, I would rate Vectra AI an eight out of ten. I am basing my whole security portfolio and roadmap around Vectra, which means that in the future I need to get more automation, remove some of the cross-tracking that we do with the Microsoft security stack, and then become much more reliant on the data coming through from Vectra AI.

We've introduced Vectra AI to our clients and had it in proof of concepts with other technologies like Darktrace for network detection and response.

Vectra AI can bring the ability to detect intrusion on the network more so than legacy IDS tools. It goes beyond just doing sample packet capture as Corelight does and provides value to the customer regarding their reporting and what the tool is doing.

The solution's marketing is not good. It probably needs to refresh its branding because a lot of it is confusing. People see it as an expensive tool for what it actually does.

I have been working with Vectra AI for five years.

With tools like Vectra, the more you want to scale, the more you have to ingest, and the higher your costs are. So scalability can be there, but it also comes with an increased price.

The solution's customer support is fairly strong.

Vectra AI didn't have a SaaS model until recently. Companies don't like deploying something complex that'll turn customers away. From what I understand, Vectra AI is somewhat complex in its deployments.

The technology is strong, but everything around the technology outside of support is weak. Vectra AI needs to find a way to make it more cost-effective for customers to compete with some of the other tools on the marketplace that customers are buying. Vectra AI should do sample packet captures for clients with different use cases. They're trying to forcefully push their tool on the market when the market wants something else.

Overall, I rate Vectra AI a five out of ten.

We wanted something to understand what's happening on the network of the company, and we wanted something to protect us against attacks and cyber activities. We wanted visibility into our network and all the threats that we're facing.

It has helped improve our mean time to identify, but I don't have the metrics on time savings because we didn't have anything for that previously.

It hasn't had any effect on the productivity of our organization’s SOC, but it has had a great effect on security.

In terms of the effect of Vectra AI Attack Signal Intelligence for empowering security analysts within our organization to take intelligent action, we are looking at the right risks and nothing more. We save some time for sure, and we empower our security with it. Previously, we couldn't see anything, but now, we are seeing some of the things, and we have already stopped some attacks with it.

The automatic filtering that they provide is valuable. The logic inside that makes some detections instead of us is very useful. We are confident that if we are just looking into it and there is nothing, nothing could happen. That's great.

It's simple to implement. It's simple to analyze. The dashboard is very smart and clean. It's very easy to check something. There are a lot of tools to analyze the detections. It's great.

We got two problems that couldn't be solved because of the philosophy of the product. We are using SMB 3.0, which is an encrypted protocol. When we get some alerts or something, we cannot go deep into the protocol to see what's wrong because it's encrypted. We need to decrypt the protocol in another way, which is quite difficult. We might go back to SMB 2.0 just for this reason, but that's not a good solution.

We did some penetration tests and tried to get some hashes or encrypted passwords from Active Directory. Those hashes didn't provide alerts into Vectra. Vectra doesn't survey them, which is quite problematic because it's a very common attack. They said that it's not the only aspect that would come with that kind of attack, but when somebody tries to get a lot of hashes, we would like that there is an alert because that seems like the start of an attack.

For the hashes issue, it could be very easy for them to make the improvement. They can just change a rule, and that's it, but for encrypted protocols, it could be trickier.

We have been using this solution for two to three years.

There is no problem with stability. Sometimes, alerts can come later. For example, for Office 365, we got the alert one day late, but the problem was coming from the Microsoft side.

We just have one, and that's enough for our needs. Its scalability is good for us because we just have one with multiple probes at the same cost, so that's fine for us.

Their support is very good. They have knowledgeable people with great knowledge of cyber security and cyber risks. I'd rate them a 10 out of 10.

Positive

We weren't using any solution before. We went for Vectra AI because we wanted something to have visibility. We were completely blind to what could happen on the network. With Vectra AI, we aren't so blind.

We stopped some attacks. An attack could cost a lot more than the cost of Vectra. For example, we got an attack before that cost us $100,000. So, Vectra's cost is not so high. The cost of an attack could be worse. If we got encrypted data, it could be worse because we would have to stop the factory, which would cost a lot.

Its cost is too much. It's an investment that we can afford. It's a lot, but it's worth it.

We evaluated Darktrace and one more solution. We also evaluated some SOC and SIEM systems, but we found Vectra AI to be better in comparison to other solutions. It was simple to implement and analyze.

I'd rate Vectra AI a 10 out of 10.

We use Vectra AI to detect incidents because we have offices in 50 countries and 30 to 40 sensors around the world.

We want to be able to have a sensor or a foothold in as many offices as possible, and Vectra AI helps us achieve that goal.

Vectra AI helps us to have more visibility in terms of what happens in our network and the network at large. It increased our understanding and our ability to respond and clean up.

In terms of valuable features, I like the ability to record the traffic and the metadata in the traffic. I also like the ability to rewind the past and be able to understand what happened. Some of my colleagues like the ability to investigate incidents.

Vectra AI has had a positive effect on the productivity of our company's top teams. They use it a lot to understand what's going on. However, we still need to teach people how to use it to its full potential because it's quite a complicated product.

The Sidekick MDR service is quite important to our organization’s security monitoring and management. The Sidekick team is able to give us the ins and outs of what's going on with some incidents. They are able to triage and help us to focus on a particular part of detection. They also gave us advice on how to configure some parts of the product. The two people I worked with from the MDR service are really good at what they do, and it's quite nice to work with them.

The UI/UX and detection could be improved. More detections of specific security events could be useful. We've had a few incidents that were not detected by Vectra. The teams are working on it right now, but more detection is always better.

Vectra AI is quite good at threat detection, however, it cannot respond to threats and attacks in real time by itself. It has to have plugins with other components, such as EDR or other software, to be able to respond properly. By itself, Vectra AI cannot do much, but it's powerful enough to pilot other software.

I've been using Vectra for nine months now.

Vectra AI's stability is quite good.

Scalability-wise, we have many sensors, and Vectra AI seems to handle them all very well.

We have 30,000 devices across 50 countries with close to 2,000 offices. It's an enterprise-scale environment, and Vectra AI has not had any issues.

The engineer who deploys Vectra at my company seeks perfection, and he wasn't happy with everything. However, Vectra's technical support staff handled all of his requests quite well. I would rate them an eight out of ten.

Positive

The product is quite good, and we have a good relationship with the customer success managers and other teams as well.

Overall, I would rate Vector AI an eight on a scale from one to ten with ten being the best.

Our key challenges are:

1. People Management: It is always a struggle to coordinate the few people that we have with the necessary skills to put them on the most important topics or projects.
2. Cloud adoption complexity: You need to figure out which systems, applications, and interfaces are talking to which cloud component in terms of data flow. That is a rather complex topic and usually sold well by the external supplier in terms of marketing to a company. Practically speaking, it is very difficult to elaborate all the connection requirements, on-prem to cloud, cloud to cloud, e.g., what is running where, what should run, and what is not running as it should.

Cognito Platform: We are using the latest on-premises version and some of the cloud services too.

We are mainly operating out of Switzerland. The IT Departments are based in our headquarters.

We have a large network with a lot of points of sales and other geographical locations that are interconnected. We need visibility of all the client-initiated traffic to and from our main data centers and to the Internet. We have good network coverage. Vectra is deployed on different hotspots in our network.

We can detect systems that are not behaving right because they are not configured correctly. We detect access to malicious sites or domains that should not be there, which should have been picked up by our security services that we implement at different times at different types of levels in the network. This is kind of an add-on to all the existing prevention mechanisms and helps us with network hygiene.

Due to an optimal signal-to-noise ratio that Vectra delivers, it gives us confidence to have a realistic chance of catching and stopping real attacks on time.

One of its strongest parts is that the solution captures network metadata at scale and enriches it with security information. We forward events to our team, then we can correlate them even better.

We have almost our complete network covered. This solution is like the absolute base coverage for us. You don't get many alerts, and if you get one, you better look at it because it is a good quality alert. After verification, we respond accordingly. Vectra AI brings great visibility. Without it, we would be blind.

The solution has enabled us to do things now that we could not do before. With Streams enabled, we can easily find out who is using SMB v1, as an example. So, it is a kind of hunting in the network. If you have a detection and need proof, you have network capture. In terms of searching accounts or assets, it is a great platform that allows us to use the default search, i.e., searching for a hostname/IP or the advanced queries for complex searches. This allows you to search back in time, which is very convenient, i.e., if one specific host has had detections in the past.

Cognito Streams gives you a detailed view of what happens in the network in the form of rich metadata. It is just a super easy way to capture network traffic for important protocols, giving us an advantage. This is very helpful on a day-to-day basis. 

The Office 365 detection is a great add-on. It will not only see the local traffic, i.e., the local user but also how the user is connecting to the cloud. If communication has been initiated within our network, we would capture anomalies with on-premises mechanisms. If it is a connection from the Internet to O365 SaaS services, we gain visibility through the Vectra add-on. It depends where the communication was started, but we do have a good, complete picture in a single view.

Vectra AI is really focusing on the most critical, severe detections. That is the key point of this platform for us. It gives you enough details and data, if you need it. However, for daily operations, we are just getting the priority 1 alerts that we need, and nothing more.

We use the solution’s Privileged Account Analytics for detecting issues with privileged accounts. This is important to our organization because you need to monitor and control privileged accounts.

The detection model and correlation of events, e.g., you are only having one priority event a day, go hand in hand. They have awesome detection models and very good algorithms. Out-of-the-box, you get a decent severity matrix and great consolidation. This is what has made this platform so usable to us over the last three to four years. We can rely on these detections and on its event generating mechanism that clearly focuses on the most important priority one cases.

If you hit a certain number of rules, triage filters, or groups, the UX responds more slowly. However, we have a complex network and a lot of rules. So, our setup might not be a typical implementation example. We even had UX engineers onsite, and they looked at issues, improvements, and user feedback. Since then, it has gotten a lot better, they even built in features that we specifically requested for our company.

We know that Vectra AI sensors for cloud IaaS deployments have been released and we are planning to deploy those shortly.

We have been using it for four years.

Great! Currently, our Brain shows 190 days uptime (last reboot initiated by us). There have been no operational issues at all. I can't complain.

Scalability is another very good selling point. It is easy to deploy virtual sensors as well as other sensors, which is a big plus.

We have a team of three people, mainly security officers, who are investigating or following up on detections and alerts. We also use the Vectra AI Sidekick Services, which helps a lot by providing a skillful set of people who look into things with a great customer perspective. We have roughly 20 to 30 people who, from time to time, get details on detections or campaigns that they need to look at.

The technical support is fast, customer-oriented, and has a great skill set.

When we started with Vectra AI, we noticed certain things that could be done better from the UI experience and workflow. We had a lot of input. They built this into their software. Some of the features that customers use today are there because we said, "Well, guys do it like that because everybody can profit from that," and they said, "Well, that is a great idea. Let's do it."

Positive

We did not use another solution before Cognito.

The initial setup was straightforward. 

We already had an existing on-prem installation, so adding Office 365 detection was straightforward. It took about half an hour.

After we deployed this solution in our network, it took about two weeks for it to begin to add value to our security operations.

They brought in the requirements and said, "We need this amount of time, as well as this type of rack, space, power, and network configuration." We prepared that, then they were able to set things up in a very short manner. It took maybe a day, then we were set and traffic was flowing in. This was one of our smoothest installations in the last years. After two days, we saw all the needed network traffic. So, implementation and initial setup were very fast.

We are still a happy customer after four years.

In terms of detection, we have seen ROI from finding out stuff as well as preventing, hunting, and intelligence gathering.

Cost is a big factor, as always. However, I think we have a very good price–performance ratio.

We looked at least five different vendors, including Cisco and Darktrace, in PoCs.

Vectra AI said what they are able to do in terms of detection and performance in their sales pitch, which they proved later in their technical PoC, to the point. They were actually the only ones who could.

Vectra AI has a very short deployment time compared to other solutions that we tried.

Do a PoC. Only a PoC will show you if something works or not. I know it takes time but do a POC or a test installation. We did the PoC directly in the production network, which was the best thing to do as we got results very quickly.

Vectra AI enables you to see more. It is their visibility strength that makes the platform so great. Because they really look at severity conditions and do a great correlation, it is time invested wisely. If Vectra shows a high score threat, you must look after it.

In terms of our security stack, this is the most essential cybersecurity tool we use. We are planning to use Vectra as well in the cloud. If they are able to deliver the same performance and capabilities in the cloud sensor, then it will be a really strong foundation that everybody should have in one way or the other.

There is manual input i.e., Triaging is something that you have to do. But in terms of workflow, it has been designed by security people for security people. It provides a very smooth and fast way to set up manual rules or triage filters.

I would rate this solution as 10 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. 

Our primary use case for this solution is for security policy and to detect potential attacks on our networks.

This solution helped our mean time to identify as we can have more precise detection and documentation. At the moment, we're seeing daily detection of between 10 and 20 and if it's on the cloud, we can do 50 to 100 per day.

As we are just beginning to use Vectra AI, I find the simplicity of implementation to be quite valuable. The UI is easy to use and when we send detection to everybody, they easily understand what we are asking at the time. The sections are very precise. 

There is room for improvement in the documentation. We would like to have more details on how it detects what we see. 

I have been using Vectra AI for about four months.

This solution is stable.

This solution is quite scalable. In the beginning, we had one point of network capturing the traffic. After that, we added two points on top of it and it worked perfectly. At first, we had five gigabits per second and now we have 30 so I'll say it's a good service.

I would rate their support a ten, on a scale from one to ten, with one being the worst and ten being the best. The reason for this rating is that they were with us every step of the way to help and guide us through the process seamlessly.

Positive

Prior to Vectra AI, we used Gatewatcher and Microprobes and also the IPS/IDS firewall. Vectra AI is an additional layer of security.

My opinion – and a strong point for Vectra AI – is that the deployment is not complex and is quite straightforward. It was an easy deployment and someone from the company helped us on each point and guided us through important milestones. If I recall correctly, it lasted for about two weeks.

It's a bit expensive, as you can have a lot of different solutions for free. So, in the beginning, it's more expensive, but as time passes it gets better.

The issue Vectra AI helps us solve is threat prevention.

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. The reason for this rating is that we are still in a tuning phase and it's too early to say anything about detection, but I would put ten for support.

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 wanted to have an additional layer of protection. We have the standard IDSs and were looking for solutions that provide additional security features.

We are still in the deployment phase and hope to be in production mode soon.

I like the way that Vectra AI focuses on the internal network. Nowadays, most of the attackers are already inside, and they can be inside for many years before they start attacking. With normal monitoring, it's quite difficult to find them.

Vectra AI checks the behavior of the systems. It's much better than, for example, McAfee IDS, which also has some behavioral capabilities. With Vectra AI, it is possible to get some more hits.

What is most important for us is to have one place where we can manage a few brains because we are based on a zero-trust network. As a result, each customer needs to have a separate brain. For the SOC team, we need to have one place where the SOC analyst can go to visit the website and from that site manage all of the customers. Right now, Vectra AI doesn't have this capability, and I would really like to have this feature.

We have been using it for almost two years.

So far, the stability of Vectra has been good compared to that of McAfee IDS. I really like the automatic updates because I am the security engineer and responsible for the tools. I have less work to do, which is really nice.

In the beginning, when we had less throughput, the stability was quite nice, but now, we are reaching 25 GB of throughput. The current device is only capable of 20 GB. I do see some slowness, but I believe that it will be solved by the new brain.

To scale, you would need to know the data center and its average throughput to order the correct brain. We have around 13,000 IPs right now, but we're still growing. The only limitation I see with Vectra AI in terms of scalability is that we cannot have one place to manage all of the brains. Besides that, it's quite straightforward; at each site, we need to have a brain, a physical or virtual one.

Regarding technical support, I am in direct contact with a few people at Vectra. I enjoy cooperating with them. However, it hasn't gone that well with a ticket I created. We had to contact them after waiting for a few weeks. Overall, I'd give technical support a five out of ten.

Neutral

In the beginning, we had some problems because of a misunderstanding between my company and Vectra. During that time, it was quite challenging, but nowadays, everything is straightforward for us. For example, I'm planning the implementation of the new data center, and it's quite straightforward.

We have already deployed all of the sensors and brains. We are waiting for B101 because we need to have a bigger brain and also want to have one on standby. Once we receive the brains, we will deploy integrations with Vectra.

The pricing and licensing are quite straightforward because they're based on IP licenses. As a result, they are easy to count.

From a deployment and operations perspective, it's quite nice. Therefore, I'd give an overall rating of seven out of ten. However, I look forward to increasing the rating when we move into the production phase and see the real output from Vectra AI.