Vectra AI Reviews

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.

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.

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.

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.

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.

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.