Vectra AI Reviews

The key challenge we face is visibility, things that happen in isolated and pocketed environments where visibility is limited. Silos and isolated networks exist across the environment, and it's difficult to control it completely. Blind spots are the main challenges.

With this solution, the focus has changed from reactive to more proactive, because all the other SOAR and EDR solutions, firewalls, and IPSs are generally reactive. With those tools, when most things are triggered, it means you are already slightly late. With Vectra, we become more proactive than reactive. More often than not, we pick things up before the actual damage can start. It picks up things that none of our other tools pick up because it's designed to detect things before harm is done, at the initial stages. This is one of the main benefits and the biggest business justification and use case for us.

It reduces the time it takes to respond to attacks because we find out about a threat in the beginning so we can stop it before it can cause harm, rather than reacting when the damage is done and significantly more effort is needed.

And since it is not preventive, it does not trigger any adverse reactions. For example, sometimes we have seen, with certain kinds of malware or ransomware, that they tend to get more aggressive if they realize that something is stopping them, but that doesn't happen with detection tools like Vectra.

For capturing network metadata at scale and enriching it with security information, that's where the second product comes in, Cognito Recall. It takes enriched network metadata and keeps that information available for you to access, whether it triggers a detection or not. For example, if you want to check who is using SSL version 3, TLS version 1.0, SNMP version 1, SNMP version 2, or who is using clear text passwords, even though they don't trigger a detection in Cognito Detect, that metadata is available. Of course, the duration of that data is dependent on how much storage we can buy from Vectra. That's a financial constraint and we have opted for one month. We might look at expanding that further.

That metadata helps in closing vulnerabilities. For instance, if there is a TLS version or an encryption level that we want to deprecate, it is very useful for us, because we can also generate reports. We know which systems are using SNMP version 1 or SNMP version 2. Even though it has more features and you can create custom detections through Recall, we've not gone that far. For us, this has been our most common use case: protocols and communications that we would like to stop or close. This provides useful data.

The solution also provides visibility into behaviors across the full lifecycle of an attack, beyond just the internet gateway. It provides the whole MITRE Framework and the key chain—recon, command and control. It has detections under each of those categories, and it picks them up within the network. In fact, most of the detections are internal. Internet-based detections comprise 25 to 30 percent, and those are based on encrypted traffic. And most of the time when we validate, we see that it's genuine because it's a call from a support vendor where large files need to be uploaded. That gives us an opportunity to validate with that end-user as well: What was happening, what did you transfer?

We used to have SIEM and antivirus solutions and we would get a lot of alerts. Those alerts resulted in a lot of effort to refine them and yet we still needed a lot of effort to analyze the information. Vectra does all of that automatically for us, and what it produces, in the end, is something that can easily be done by one person. In fact, you don't even need one.

The most useful feature is the anomaly detection because it's not signature-based. It picks up the initial part of any attack, like the recon and those aspects of the kill chain, very well. We've had numerous red team and penetration exercises and, at the initial stage, when the recon is happening and credentials are used and lateral movement is attempted, our existing tools don't pick it up because it has not yet been "transformed" into something malicious. But Vectra, at that stage, picks it up 80 to 90 percent of the time. That has been one of the biggest benefits because it picks up what other things don't see, and it picks them up at the beginning when attackers are trying to do something rather than when the damage is already done.

The ability to roll up numerous alerts to create a single incident or campaign for investigation takes a bit of effort in the beginning because you'll always have misconfigurations, such as wrong passwords, that could trigger brute force and SMB-types of alerts. And you'll have genuine behaviors in your environment that tend to be suspicious, such as vulnerability assessment and scanning tools, that are not noise, per se. Even if they're non-malicious, it always tends to point to events like misconfigurations and security tools. It's been very useful in that sense, in that, once we do the initial triaging, indicating that this is a security tool, or that is a misconfiguration we need to correct, it reduces the noise quite significantly. We don't get more than 10 to 20 events, maximum, generated per day.

Vectra shows what it does in terms of noise reduction, and we can see that it is down to only 1 percent, and sometimes even less than 1 percent, of what actually requires a person to act on.

It becomes quite easy for a SOC analyst to handle things without being overburdened. And, obviously, it's at the initial stage because it picks things up before the damage happens. It's not the kind of prevention tool that has signatures and that only tells you something bad has already happened. It tells you that something is not right or is suspicious. It says there is a behavior that we have not seen before, and it has always been effective in the red team exercises that we periodically conduct.

Also, we have privileged account management, but we don't have a separate analytics tool. Still, Vectra also picks that up. This is also something that has come up during red team exercises. If there's an account that is executing an escalated privilege or running a service that it normally doesn't run, it gets flagged. It tells us about lateral movements and privilege escalations; things that constitute non-standard usage. It's quite effective at catching these. I have yet to see a red team exercise that doesn't generate any alerts in Vectra. We see a jump, and it's very easy to identify the account and the system that is the source.

It also triages threats and correlates them with the compromised host devices, because it maps both ways. It maps the host, the account, and the detection, and vice versa. You can also go to the detection and see how many affected hosts there are. In addition, if there's a particular detection, is there an existing campaign? How many hosts are also doing the same thing? These are the kinds of visibility the tool provides.

The reporting from Cognito Detect is very limited and doesn't give you too many options. If I want to prepare a customized report on a particular host, even though I see the data, I have to manually prepare the report. The reporting features that are built into the tool are not very helpful. They are very generic and broad. That's one main area that I keep telling Vectra they need to improve. 

Also, whenever there's a software upgrade and new detections are introduced and the intelligence improves, there is a short period at the beginning where there's a lot of noise. Suddenly, you will get a burst of detections because it's a new detection. It's a new type of intelligence they've introduced and it takes some time to learn. We get worried and we always check whether an upgrade has happened. Then we say, "Okay, that must be the reason." I would like to see an improvement wherein, whenever they do an upgrade, that transition is a bit smoother. It doesn't happen all the time, but sometimes an upgrade triggers noise for some time until it settles down.

We've been using the Vectra AI for over three years.

In the beginning, there is a struggle to fine-tune it because it will generate noise for the reasons I mentioned. But once that learning phase is complete, it's quite reliable. We have been using the hardware for more than three years and there have been no failures or RMAs

Upgrades happen automatically. We have never gone into the appliance to do an upgrade, even though it's on-prem. It all happens automatically and seamlessly in the background. 

Initially, we had some problems with the Recall connection to the cloud, to establish the storage connectivity. But again, these kinds of things are at the beginning. After that, it is quite stable. We've not had any problems.

Scalability for the cloud solution is straightforward. For the on-prem solution, you need to take care of the capacity and the function itself, because the capacity of the same hardware varies, depending on what you use it for. From a capacity point of view, there is some effort required in the design.

Looking forward to the future, the tool integrates with more and more solutions outside of its existing intelligence. It's not something that we have yet embarked on, but that's an interesting area in which we would like to invest some time.

The cloud solution is something that has limited visibility because PaaS and SaaS in the cloud are always a challenge in terms of cyber security. And in the future, even though we have taken the Vectra SaaS for O365, they're also coming up with a PaaS visibility tool. It is currently under testing, and we are one of the users that have been chosen to participate in the beta testing of that. That's another thing in the future that would add a lot of value in terms of visibility.

Currently, we have about 8,000 users.

The support is directly from the device or we get a response via email. The response is okay. Because the product is stable, we have not been in a situation where we urgently needed something and we wanted support right now. We have never tested that kind of fast response. They take some time to respond, but whenever we have requested something, it has not been urgent. 

We do get a response and issues always get resolved. We haven't had any lingering issues. They have all been closed.

Positive

We did not have any tools in the same league. We had security tools, but not with anomaly detection as part of the feature set.

Cognito Detect is on-prem and Cognito Recall is in the cloud, as is the O365 and Azure AD protection.

The cloud setup is extremely simple. The on-prem takes some effort. There is the sizing, depending on what model. The throughput varies. Those kinds of on-prem design considerations create a bit of complexity in the beginning, but the cloud is straightforward. All it needs is the requisite access to the tenant. Once it gets that, it starts its work. 

In the beginning, there is some effort in fine-tuning things, but that comes as part of the package with the solution. They have a success manager and tech analyst assigned to support you in the beginning. Once that is done, the product is very stable.

For us, there were an initial four to eight weeks of triaging and clearing the noise, in terms of misconfiguration issues or known security tools. After that time, we started seeing value.

We only used the people from Vectra.

Vectra is a bit on the higher side in terms of price, but they have always been transparent. The reason that they are this good is that they invest, so they need to charge accordingly. They are above average when it comes to price. They're not very economical but it's for a good reason. As long as we get quality, we are okay with paying the extra amount.

We did a PoC with Darktrace recently as part of our regular exercise of giving other solutions an opportunity, but the PoC didn't meet our requirements. It didn't detect what Vectra detects in a red team situation.

The deployment time is similar because they all need the same thing. They need the network feed for a copy of the network traffic. The base requirements are the same.

My advice is that you need to size it right and identify what your capacity will be. And you need to place it right, because it's as helpful as what it can see, so you need to have an environment that supports that. What we did, as part of implementing Vectra, was implement an effective packet broker solution in our environment. It needs that support system to function properly. It needs copies of your traffic for detection because it doesn't have an agent sitting anywhere. The positioning and packet brokering are critical allies for this solution.

We have it deployed on-premises. However, we are in the process of acquiring O365 and Azure AD as well. When it comes to Power Automate and other deeper anomalies, these are things that we have on the cloud in Azure. In the new module, it lets us know if any automation, scripts, or large, sudden downloads, or access from a country that is different from where the user has normally been, are happening. But this is a very new tool. We are yet to familiarize ourselves with it and do the fine-tuning. We don't have any automation or any such functions happening on-prem.

In terms of correlating behaviors in the enterprise network and data centers with behaviors in the cloud environment, because we have taken the O365 module, it gives us good correlation between an on-prem user and his behavior in the cloud. We have seen that sometimes it detects that an account is disabled, for example, on-prem, and it says somebody downloaded a lot of data just a few days before that or uploaded large data a few days before that. It does those kinds of correlations.

We have one SOC but it's based overseas. It's an offsite managed service and it covers the gambit of incident detection and response. It's an always-available service. The SIEM we are using is RSA NetWitness, and the EDR solution we use is McAfee.

Vectra has some automation features, in the sense of taking action through the firewalls or other integrations, but that's a journey that we have not yet embarked on. As long as we have a continuously available SOC that rapidly responds to the alerts it generates, we are okay. In general, I'm not comfortable with the automation part. Accurate detection is more important for me. Prevention, when something is picked up too late, as is the case with some of the other solutions I mentioned, is a different case. But here, when it is at the preliminary stage, prevention seems a bit too harsh.

The original use case was because we had some legacy stuff that doesn't do encryption at rest. Compliancy-wise, we had to put in some additional mitigating actions to protect it. That was the start of it. Then, we extended it to check other devices/servers within our network as well.

We are on the latest version.

It is doing some artificial intelligence. If it sees a server doing a lot of things, then it will assume that is normal. So, it is looking for anomalous behavior, things that are out of context which helps us reduce time. Therefore, we don't have to look in all the logs. We just wait for Vectra to say, "This one is behaving strange," then we can investigate that part.

We have implemented it fully now. We have done some training and filtering on it. Now, every alert that we see means that we need to investigate. It sees roughly 300 events a day. The majority are normal behavior for our company. So, there are about 10 to 15 events a day that we need to investigate.

The solution triages threats and correlates them with compromised host devices. It looks at a certain IP address, and if you're doing something strange, then it will give us an alert. E.g., normally John Doe is logged into it for four days, going to server XYZ. If all of a sudden, it's in a different timescale, going to server B, then it will send us an alert.

We have privileged accounts. They have a specific names, and if I see those names, then I investigate a bit more thoroughly. That's our policy. I don't know whether Vectra does anything different with them.

The solution gives us more tickets. If we did not have Vectra, we wouldn't have those tickets. So, it's actually increasing them. However, it is improving our security with a minimum amount of work. That's the whole purpose of the device. We have 10 to 15 events that we need to look into a day, and that is doable.

The solution creates more work for us, but it is work that we are supposed to do. We need more FTEs because we need more security.

We mainly use it for the detection types, checking dark IPS or command-and-control traffic. 

We bought Recall so we can have more information. Recall is an addition onto Vectra. We haven't enabled Recall yet, but we will. So, if there is an incident, we can investigate it a bit further with Vectra devices before going into other tools and servers. This gives us the metadata for network traffic. So, if we have a detection, we can check with Recall what other traffic we are seeing from that device, if there is anything else. It's mainly a quick and dirty way of looking at it and getting some extra information to see whether it's malicious.

We found that the solution captures network metadata at scale and enriches it with security information. This is one of the reasons why we added Recall, so the alert gives us information on where we need to look, then we can investigate a bit further. For example, a certain device is sending data to command-and-control server, then we can investigate whether that is really happening or just a false alarm with the metadata in Recall. It makes it easier to find out.

We would like to see more information with the syslogs. The syslogs that they send to our SIEM are a bit short compared to what you can see. It would be helpful if they send us more data that we can incorporate into our SIEM, then can correlate with other events. We have mentioned this to Vectra.

It does some things that I find strange, which might be the artificial intelligence. E.g., sometimes you have a username for a device, then it makes another. It detects the same device with another name, and that's strange behavior. This is one of the things that we have with Vectra support at the moment, because the solution is seeing the device twice. 

We started the pilot roughly a year ago. So, we started small with a pilot on part of the systems, then with two other vendors. Afterwards, we decided to buy it.

Now, it's almost in production. It's still a project in the end phase, as we are still implementing it. But, most of it has been running for a year.

So far, the stability has been good. There are no issues. It's never been down. It has been updating automatically on a regular basis and there are no issues with that where it has stopped working.

One person will be responsible for the deployment, maintenance, and physical upkeep; a person from the service delivery team will keep the device up and running. The security analysts (my team) deal with the alerts and filtering.

The part that we designed is not really scalable. They have options, and there is some room for improvement. If we need to scale up, which we have no intention of doing, then the physical devices need to be swapped over for a bigger one. Other than that, we have some leeway. This came up in the design with, "What are your requirements?" and those requirements have been met, so that's fine. They will probably be met for the foreseeable future.

At the moment, we don't have Tier 1 and Tier 2. Instead, we have a small team who does everything. I am mostly using it. There will be three security analysts. Then, we have a number of information security officers (ISOs) who will have a read-only role, where they can see alerts to keep an eye on them, if they want, and be able to view the logging and see if they need more information. But, there are three people who will be working with Vectra alerts.

We are in contact with the Vectra service desk. If you send them ideas, they talk about them and see if they can incorporate them.

We decided that we wanted to have an alert within 30 minutes, which is doable with this solution. It fulfills our needs. However, we didn't have this before, so it has increased our time, but for things we need to do.

The initial setup is relatively straightforward. They have security on a high level. There are a lot of logins with passwords and very long passwords. This made it go a bit longer. However, the implementation is relatively easy compared to other devices.

We made a design. That's what we implemented.

Initially, it was set up in conjunction with Vectra. When we put it into production, the majority was done by me, then checked by a Vectra engineer. If I had issues, I just contacted Vectra support and they guided me through the rest of it.

The Vectra team is nice and helpful. The service desk is fast. They know what they are doing, so I have no complaints on that part. We have a customer service person who knows about our environment and can ask in-depth questions. He came over as well for the implementation to check it, and that was fine. The work was well done.

The solution has reduced the time it takes us to respond to attacks. It sends an email to our SIEM solution. From that SIEM solution, we get emails and tickets. Therefore, the time between an alert coming up and a ticket is reduced. This is for tickets that we monitor regularly. Within 15 to 20 minutes, it gives us an alert for the things that we want. Thus, it has greatly reduced our measurable baseline.

The return of investment is we have tested it so sometimes we have auditors who do pen tests and see them. That's the goal. It seems to be working. We haven't found any actual hackers yet, so I'm not completely a 100 percent certain. However, we found auditors who are trying to do pen tests, which essentially the same thing.

The license is based on the concurrent IP addresses that it's investigating. We have 9,800 to 10,000 IP addresses. 

There are additional features that can be purchased in addition to the standard licensing fee, such as Cognito Recall and Stream. We have purchased these, but have not implemented them yet. They are part of the licensing agreement.

We investigated Darktrace, Vectra, and Cisco Stealthwatch.

Darktrace and Vectra plus Recall were similar in my opinion. Darktrace was a bit more expensive and complex. Vectra has a very nice, clean web GUI. It easier to understand and cheaper, which is one of the main reasons why we chose Vectra over Darktrace.

Darktrace and Vectra are very different, but eventually for what we wanted it to do, they almost did the same thing. Because Darktrace was a bit more expensive, it was a financial decision in the end.

I did the comparison between Darktrace and Vectra. They did almost the same thing. Sometimes, there are differences that Darktrace did detect and Vectra didn't. For the majority, we didn't find any actual hackers. So, it's all false positives, eventually. Both of them are very similar. The big thing is the hacker activity. They both detected it in the same way. But, in the details, they were different.

The options for Stealthwatch were a bit limited in our opinion for what we wanted it to do. Stealthwatch is network data, and that's it.

Start small and simple. Work with the Vectra support team.

The solution’s ability to reduce false positives and help us focus on the highest-risk threats is the tricky part because we are still doing the filtering. The things it sees are out of the ordinary and anomalous. In our company, we have a lot of anomalous behavior, so it's not the tool. Vectra is doing what it's supposed to do, but we need to figure out whether that anomalous behavior is normal for our company. 

The majority of the findings are misconfigurations of servers and applications. That's the majority of things that I'm investigating at the moment. These are not security risks, but need to be addressed. We have more of those than I expected, which is good, but not part of my job. While it's good that Vectra detects misconfiguratons, there are not our primary goal.

The solution is an eight (out of 10). 

We don't investigate our cloud at the moment.

We started with it as a replacement for the functionality we had in our SIEM solution. We mainly wanted a detection metric and something that was smart enough to detect some of the more complex attacks because we can have flow data and do nothing with it. We wanted to have some strong alerting capabilities on that. We were looking to get a detailed attack and AI perspective on it. We didn't want something that only sees something as malicious and can alert on it but also detect things that are a little bit out of the ordinary, which was something we could get with this.

It has definitely improved our mean time to identify. In some specific cases, it's making it a lot easier because the enrichment features do help in getting a more detailed view of what's going on. For example, if we see a certain connection or something that's potentially a command and control channel, we can look at who logged in last and what other processes are there. We also have a connection to our SIEM solution, so we can check what's going on there as well. So, it really helps, but it's hard to measure the time savings because we previously didn't have a solution that had the same capabilities as Vectra AI.

It has definitely had an impact on our productivity. Previously, we did have some issues with getting a more detailed view of the network because we could only do it through event-based logs from the network devices, such as firewalls and switches that were providing us with additional information. Now, because it's more detailed and also across the branch offices—which was a big point for us—we do have a more efficient structure. We don't need to do that much additional effort to get to the root cause of problems, which was an issue before.

One of the things that we didn't expect to happen was that our network team also jumped on it faster than we thought. In most cases, if it's a security tool that's working on the network part, they can also use it to find out certain flaws that have been in the system. Certain flaws, related to some legacy stuff, were already there for quite a few years, which they couldn't explain at first, but we could explain them based on the timing of certain things. For example, there were about 200 SSH connections within a night. They had seen the traffic, but they couldn't relate it to anything specifically, whereas because we saw it, we knew that it was one of our main Unix machines. We knew it was doing some kind of backup at that time. We then went to talk to the system engineer, and he could confirm that he was using a badly written script that was doing 200 connections instead of just one and sending all 200 files across it.

It's well-built, so it does its thing as a Threat Detection and Response platform for detecting and responding to threats and attacks in real-time. We use the detections that come out of Vectra, and we send them over to our SIEM solution. Especially when it comes to high alerts or alerts with high certainty and high impact, we look at them immediately, and then someone also goes through it every day to clean up. If there are certain things that we need to check, we will check them anyway. Anything that's lower on the priority list is taken care of later in the day.

One of the things that we are missing a bit is the capability to add our own rules to it. At the moment, the tech engine does its thing, but we have some cool ideas to make additional rules. There should be an option in the platform to add custom rules, or there should be some kind of user group where we can suggest them for the roadmap and see if they get evaluated and get transparent communication on whether they will be implemented in the product or not. I understand that not everything can be implemented in the product, but if everyone presses the plus one button, then you know that there's a need for it. 

There is the concept of groups within Vectra. You have IP groups, host groups, and domain groups. Wild cards would be very handy there, or side ranges would be a good one to start with. One of the big things that some of our operational people complain about is that if it's an IP and it has reverse look-ups, why do they need to make two groups—an IP group and a hostname group—just to get the same feature set?

It has been almost three years, so it has been a while.

We haven't had any issues. It's very stable, so no problem.

Their support is pretty good. They follow up fast. It's not like most other support centers we've seen in the past. They are really focused on getting us faster input.

I'd rate them a nine out of ten because there is always a little bit of room for improvement, but normally, they follow up really nicely. As opposed to others, where you mostly hear good product, bad support, in this case, it's good product, good support. That's something to keep in mind.

Positive

We had a SIEM solution that was mainly focused on event-based logging, not necessarily on the network part. We were looking at more of a network IDS solution, and that's where Vectra came in. We wanted something that was easy to use as we didn't want too much platform maintenance. We wanted something to plug into the box and make it work. At first, we didn't believe that we would be able to find something like that after we had seen Darktrace, their biggest competitor, but in the end, Vectra was a perfect fit for us because it made it very easy to insert it into our branch offices as well.

We started from scratch. Three years ago, it was harder to start with than nowadays because back then, it was still in the beginning. The Belgian team that helped us with it also didn't have the experience at that time, whereas now, it's definitely not hard to set up. It's just a matter of knowing the right things, but the support portal really helps. There's good documentation on the setup as well.

From a security perspective, it's always hard to find a return on investment. If you look from the risk mitigation perspective and what's the worst that can happen, if we can stop attacks sooner, it would result in lesser costs on remediation afterward because we were fast on the initial attack.

From a licensing perspective, the Vectra detect platform is pretty doable. Also, the hardware prices are nothing that we're not used to. The stream part is a little overpriced compared to the detect part. The reason is that you need to stream data to detect events anyway, so the data is in there. The only thing that's not available is the UI to be able to look at the stream data, which is also on the appliances but is just not activated. That's mainly the thing that we want to improve on.

We looked at the SIEM solutions and flow-capturing devices. At the time, there was also an open-source product, but I don't remember the name. It was Suricata-based, but it fell off pretty quickly because of the high platform maintenance that would have come with it.

At the moment, we don't let them do intelligent blocks. We do it ourselves, so we are still putting a manual process in place for that. We also haven't yet used Vectra MDR services.

I'd rate Vectra AI an eight out of ten. They can still move a little bit further with the streams. Especially now that ChatGPT and AI have come into the picture, we all need to up our game on the AI part.

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

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

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

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

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

Vectra AI is a stable tool.

Vectra AI is a scalable tool.

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

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

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

We implemented Vectra AI together with their technical support team.

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

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

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

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

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

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

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

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

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

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

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

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

I've been using this solution for six months.

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

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

One of the reasons we went with this solution was because there is less that we have to customize; it's more commercial off the shelf. Therefore, my team can spend their time doing what's most beneficial for the university, which is protecting it, not upgrading custom software.

We use it to inspect and look for malicious, abusive, or other types of forbidden behavior with our north-south and east-west traffic. We not only look at traffic from our campus to the Internet, but we look at traffic internally in our network as it does network AI. It not only looks when a specific event happens, but whether, "Is this a normal event? Or is it normal for the host to do that?" 

The Privileged Account Analytics for detecting issues with privileged accounts is very important because, like any organization, we have people from low-privileged, regular users all the way to administrators who have very high levels of privilege. Therefore, a regular student, on their own machine, may run Coinminer on it, which might be something that the student is experimenting with for higher ed. However, it's a very different use case when a staff user on their work issued machine is running it. Cognito will let us discover that very easily and contextualize it, "Is this really the criticality of an alert or a behavior?" It does this not only for the user, but it also lets us see through the DNS and machine name, whether it's a university asset, etc. Also, you can target those users who have a very high level of access by really enriching your analysis of alerts, such as, "I know that this administrative account does do PowerShell stuff because that's one of the main jobs of that sysadmin." Then, if I see that sort of PowerShell behavior from another account that I wouldn't expect it from, then that's a reason for concern.

The solution captures network metadata at scale and enriches it with security information. This provides us context upfront which helps us prioritize.

The solution provide visibility into behaviors across the full lifecycle of an attack in our network, beyond just the Internet gateway. It makes our security operations much more effective because we are now looking not just at traffic on the border, but we're looking at east-west internal traffic. Now, not only will we see if an exploit kit is being downloaded, but we would be able to see then if that exploit kit was then laterally distributed into our environment.

The solution’s ability to reduce false positives and help us focus on the highest-risk threats is very good. The additional context and ability to take other factors that we can feed into it, like our threat intelligence feed or the user identity, helps with running down whether behaviors are legitimate or pose a big risk. It also helps us eliminate false positives where appropriate, such as some of our system admins running PowerShell in a way that looks very suspicious if you saw it from a regular user.

It has reduced the type of analysis needed to run down and get to the bottom of what's really happening. On the flip side, it doesn't miss as much as a human only or more signature oriented approach would. While I don't want to give a false impression that it's going to result in less work, I think the work that we're doing is more efficient. We can do a lot more to protect, because we're able to react and look at what's important. It may not directly translate into, "Oh, well we spend less time on threat hunting and investigating a suspicious behavior," but we're seeing what we need to look at more effectively.

It's easier to get an analyst up to speed and be effective. The solution has helped move approximately 25 percent of the work from our Tier 2 to Tier 1 analysts.

I find the network artificial intelligence and machine learning to be most valuable because we have also significantly increased the amount of traffic that we inspect. This has kind of lowered the burden of creating ways to drink from that fire hose of data. The artificial intelligence and machine learning help bubble up to the top things that we should go look at which are real deviations from the norm.

I would assess the solution’s ability to reduce alerts by rolling up numerous alerts to create a single incident or campaign for investigation very highly. Rather than relying on signatures and a human to look if, "Host X has hit these four different signatures," which is probably an indicator of a fairly high confidence that something's not right, the analytics, artificial intelligence, and machine learning in this product tie those events together. It also looks for new events that are out of the ordinary, then gathers those together and tells us to look at specific hosts. This is rather than an analyst having to sift through a bunch of signature hits, and say, "Oh, this host needs to be looked at."

Also, there is a much lower operational burden of maintenance. We used to use open source monitoring tools, which are very good, but they take a lot of work to maintain and leverage. We really like the commercial off the shelf type of approach of the software, not brewing our own.

Some of their integrations with other sources of data, like external threat feeds, took a bit more work than I had hoped to get integrated. I think the company has been very responsive, willing to take our feedback, and look at addressing our concerns.

I have asked that they give direct packets capabilities.

About a year and a half.

It is very stable and easy to maintain compared to the Linux open source solution that we previously used for a long time.

Maintaining the solution isn't even a full FTE, probably more like a quarter. We have to coordinate if we want to get more data into it, as there are some integrations that we do with our threat intelligence feed from our ISAC.

We have talked to several other customers who have much larger environments than ours, so it is very scalable. We have applied it in excess of probably 20,000 devices. We have probably 50,000 to 60,000 active users who might see traffic from it. We have hundreds of thousands in our directory total, but some of those are alumni or adjunct faculty, so they may not be active all the time. We have on order of 700 servers and hundreds of applications. We're not huge, but we're not tiny.

One of the things that is really exciting about partnering with Vectra is they have solutions for the cloud, both Azure and AWS. This will get us that same type of visibility we're getting now with things on our physical campus using cloud services. This is probably where our increased usage will be concentrated on.

Vectra's technical support is very good.

We switched from an open source solution to Cognito because there was a lower operational maintenance burden and it provided more visibility into our environment. It also has more analysis and initial triage done by the network AI and machine learning.

Vectra enables us to answer investigate questions faster than our open source solutions previously did.

The initial setup was straightforward.

Our initial deployment with north-south and a bit of east-west for our first virtual sensor probably took two to three days at most. 

Long-term, we now have it deployed on every VMware server that is in our environment and it's monitoring probably 500 to 600 inter-server communications (between different servers). That took a little longer because we had to first work with our colleagues here onsite. It wasn't an issue with Vectra. It just took time and we had to arrange some work with internal partners. We did the reference and first setup in a day.

For our implementation strategy, we turned up north-south visibility immediately and brought up a single virtual sensor for our VMware environment. Then, after three months, we revisited it with a team who operates VMware and their servers. We made sure they were comfortable with the resource demands and how well the solution was working. Finally, we were able to have them turn it on for all the VMware servers.

We had very knowledgeable people from the vendor work with our networking group to get the correct traffic to its sensors. This was done remotely/virtually, but it was done very well.

Hopefully, this is a sunk cost. We are mitigating risk. We are not expecting to make money on this solution.

The solution has reduced the time it takes us to respond to attacks by approximately 20 percent.

We looked at some of Vectra's competitors. We had Snort and also used Bro. We also used Argus and NetFlow collector. Therefore, we looked at what were the products out there that could sort of replicate the things we were doing with a commercial off the shelf product that had artificial intelligence, but not open source.

We looked at Corelight, which was more grow only. We also looked at ExtraHop.

We didn't do a formal RFP with this one. We developed some relationships with the management at Vectra, who really wanted to partner with us. We looked at their technology and other competitors in the area, then decided it was a worthwhile (based on their commitment) for us to work with them.

Usually, I'll go to the Gartner Security & Risk Summits and look around at what different vendors are coming out with. That's a very useful venue for learning about new vendors.

We don't have that big of a cloud presence yet. However, the solution would correlate behaviors in our enterprise network and data centers with behaviors we see in our cloud environment because part of our east-west visibility includes our dedicated connections to cloud instances. If it goes over to our commodity Internet, it should see it there too.

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

All opinions in this review are my own.

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

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

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

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

I have been using Vectra AI for two years. 

I would rate the stability an eight out of ten.

I would rate the scalability an eight out of ten.

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

Positive

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

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

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

The solution is low-cost and affordable. 

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

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

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

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

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

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

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

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

I have been using this solution for two years now.

It's stable as it performs as we expected.

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

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

Neutral

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

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

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

We are not using the flood detection response platform.

We are not using Vectra MDR services.

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