Why Consolidating SIEM and XDR Is No Longer Optional

In 2025, it’s hard to imagine organizations operating without XDR and SIEM. Both solutions are necessary in keeping your organization secure from cyberattacks. 

However, the issue is that the majority of cybersecurity vendors offer SIEM and XDR separately instead of together. 

At Infopercept, we advise that you get both of these defensive solutions together. Getting them separately will prove to be a headache for your organization in the long run.

How? You may ask.

In this blog, we will show you what problems your business can face if it chooses to get XDR and SIEM separately from different vendors. 

Seven Reasons Why Getting XDR and SIEM Separately Will Create Major Problems

You are more vulnerable to cyberattacks if you get SIEM and XDR separately from different cybersecurity vendors. 

There are going to be many operational as well as integrational challenges that your business will face. 

Let’s go over them in detail in this section. 

1.Integrating SIEM and XDR is Complex In General  

Both SIEM and XDR use different data formats and APIs. This can make integration difficult. 

For example, let’s say that SIEM uses normalization engines like Splunk CIM to make logs consistent across different sources. 

But XDR sends structured, opinionated JSON logs with vendor-specific fields. 

This will create conflict as SIEM expects logs in CEF, but XDR only supports JSON over REST. 

To remedy this problem, you will need an ingestion pipeline, which will not only make everything more complex, but will also add to the risk of incomplete normalization. 

Additionally, XDR will log events using their own schemas like process_id, event_id, etc. 

But SIEM will expect these under standardized field names like pid and category. 

In this case, SIEM analytics and correlation rules will either fail or misfire if fields are missing, differently named, or are in incomplete format. 

Furthermore, every vendor platform has different authentication, rate limits, and data query models. 

If SIEM expects real-time alert push via webhook, but XDR only supports polling-based REST API—then it will lead to increased latency or dropped alerts. 

Additionally, XDR logs may be in UTC or millisecond precision, while SIEM may truncate to seconds or use local time. 

This time mismatch may cause broken correlation chains, missing attack timelines, or false negatives in detection. 

If SIEM ingest threat feeds in STIX/TAXII, but XDR only supports vendor locked IOCS or JSON formats—then the threat detection logic gets fragmented. 

IOCs flagged by XDR may not improve SIEM detections. 

Also, XDR is designed to isolate endpoints and kill processes. 

Without proper integration, SIEM may trigger playbooks via SOAR, but cannot directly trigger XDR actions. This will delay the response, which ultimately defeats the purpose of XDR automation. 

Lastly, both XDR and SIEM may send alerts on the same event but with different severity levels or contexts. 

Without deduplication, your security team will start to feel alert fatigue. Getting conflicted threat levels from both solutions will also confuse them. 

2. Lack of Unified Visibility 

Having a unified security platform gives your security team a single interface to monitor:

• Endpoint activities 
• Network traffic 
• User behavior 
• Cloud infrastructure 
• Alerts and threat intel 

If you get SIEM and XDR from different vendors, they will have no interaction with each other in real-time. 

It will silo the visibility as both tools see incomplete pictures during an incident. 

Imagine a scenario where an attack has taken place; let’s see how unified visibility fails if both SIEM and XDR are not integrated properly. 

An employee in your organization has clicked on a phishing link. 

The XDR detects the malware dropped on the endpoint. 

This malware tries to steal the credentials of the user to establish persistence. The XDR logs this activity and flags it as suspicious. 

The adversary proceeds to use stolen credentials to log in to a critical finance server via RDP. 

This login event gets captured in Windows logs, which are forwarded to the SIEM. The tool logs the event but sees it as just another login. 

The XDR knows that the endpoint is compromised.

The SIEM sees a login to a sensitive system.

However, due to poor integration, there is no correlation to the data. 

The SIEM does not trigger an alert for suspicious lateral movement. 

Why did this happen? The table below shows you why…

The consequence of this will be that SIEM never triggers an alert because it doesn’t know that the source of the login is a compromised machine. 

Your security team investigates this later by looking into the logs, but it doesn’t show the full story regarding how the adversary moved from the email to the system and then to the finance server. 

Also, it will waste a lot of time as one team member will be chasing the login alert in the SIEM while the other will be looking at the malware alert in the XDR dashboard. 

Both are unaware that it’s part of the same attack until much later, by the time when it is already too late. 

3. Threat Detection and Response Will Be Slower 

If SIEM and XDR are not properly integrated, then it will give adversaries enough time to execute their attacks. 

Speed matters a lot in cybersecurity. 

The performance of a security team is judged based on:

• MTTD (Mean time to detect): How quickly they identify a threat 
• MTTR (Mean time to respond): How quickly they contain the threat and neutralize it. 

If SIEM and XDR are integrated poorly, then data transfer will not happen in real-time. 

For example, XDR detects the threat first by scanning the endpoints, from which the attack usually begins. 

Depending on the vendor configuration, the SIEM collects the data from the XDR periodically through the REST API every 5-30 minutes. 

The SIEM is way too behind. It’s reacting to events very slowly, which can be disastrous for the organization.

Here’s why:

At 10:00 am an employee gets tricked into opening a malicious file by clicking on the phishing email. 

The XDR detects the unusual PowerShell behavior (Base64-encoded string), network call to suspicious IP, and process injection activity. 

The XDR console generates an alert immediately. 

Between 10:01—10:10 am, the malware opens a reverse shell, which gives the adversary a remote access to the system. 

They run commands, move laterally, and harvest credentials. 

The XDR continues to log these actions and update the severity. 

But SIEM still doesn’t see any of this. At 10:15 am, SIEM collects the data by making the scheduled API call to the XDR. It receives a batch of alerts from the last 15 minutes. 

Now, the SIEM console lights up with critical alerts, and the security team starts to investigate—but the adversary is already ahead of them by 15 minutes. 

By 10:16 am, all the sensitive files are already exfiltrated. The adversary uses privileged accounts to implant backdoors. The logs show the attack, but it’s too late to stop the initial breach now. 

Such delays are dangerous because: 

The consequence of delayed detection and response is that the adversary can operate undetected for minutes to hours. 

The malware will spread deeper, in which more endpoints, accounts, and data gets compromised. 

All this will increase the cost of recovery.  

4. Operational Inefficiency 

As we said previously—If SIEM and XDR are not integrated, then these tools will not share data automatically. 

Due to this issue, your security team will have to manually jump between dashboards to get a full picture of the attack.

This will not only waste precious time, but also needlessly stress out your team. 

Speed, context, and automation are necessary when responding to threats. 

Imagine your SIEM flags a login at 2 AM from a user in an unusual country. Your security team sees the username, IP address, and destination server. 

That's it! It doesn’t show any endpoint behavior. 

But now the security team opens the XDR dashboard. They manually search the endpoint to look for process behavior, file changes, registry modifications, and commands executed. 

All this is manual, slow, and disconnected. 

It wastes a lot of time.  

The SIEM logs are in UTC, but the XDR shows local time. 

XDR says the process launched at 3:45 am, but SIEM logs show login took place at 2:15 am. 

Your security team will have to make a guess if these events are connected or not. 

Furthermore, SIEM calls the field user_name, while XDR calls it principle_id. Process IDs, hostnames, and file hashes may also be named or structured differently. 

Due to such format and field mismatch, everything has to be looked up manually. 

Such inefficiencies can lead to serious consequences. The below table will give you a glimpse of it. 

5. Higher Cost of Ownership 

Buying SIEM and XDR from different vendors will also impact your budget, efficiency, and long-term scalability. 

When buying two defensive solutions from different vendors, it doesn’t just include license fees, but also training, support, maintenance, integration, upgrades, and time spent managing the tools.

You will have to pay upfront cost (CapEx) and ongoing operational costs (OpEx) over time.  

Each vendor, whether it is SIEM or XDR, has its own pricing model, which is based on the following:

• Data volume per day (GB) or events per second (EPS) for SIEM 
• Number of endpoints, devices, or users for XDR

By buying them separately, you will not get any bundle or volume discount across platforms.
Also, your business will also have to pay redundant fees for overlapping features like threat intelligence or dashboards.

Furthermore, your security team will have to be trained on both platforms as they will come with different UIs, different alert formats, and different investigation workflows. 

This will increase the onboarding time and reduce the efficiency of your team. External training will cost between $1,000-$5,000 per person. 

Additionally, two different vendors will require two support contracts. They will have different SLAs, escalation procedures, time zones, and regional support coverage. 

If any incident happens—it will waste a lot of time in figuring out which vendor owns the problem. 

Furthermore, as tools don’t natively talk to each other—you will need custom connectors, middleware, and SOAR platforms. 

You will also need integration engineers, API security audits, and periodic rework when APIs or schemas change.  

All of this may cost your organization $10,000 to $50,000, depending on the complexity. 

Over time, your business’s upfront costs and operational costs will keep ballooning. 

Higher CapEx because you will need separate platform licenses, third-party tools for integration, and developer costs. 

Your OpEx will also skyrocket as you will need additional staff time to maintain scripts or APIs and train refreshers each time vendors update their UIs or workflow. 

Also, due to longer incident response time, there will be higher risk and cost per breach. 

All of this will reduce your budget for core security needs, since it is getting eaten up by integrating both of these tools together. 
You will have less money for threat hunting, establishing advanced detection rules, performing compliance audits, and managing vulnerabilities. 

6.Security Gaps and Redundancy 

Although not interchangeable, SIEM and XDR do overlap in certain areas. If these tools aren’t connected to each other, then chances are:

• Both may duplicate detection logic as both tools are alert on the same activity independently.
  
• Miss threats by assuming the other will catch them.
  
• Failure to coordinate policy actions will delay responses. 

Imagine an adversary runs a suspicious PowerShell command—the XDR detects and logs this as suspicious behavior using its agent, whereas, the SIEM will also detect this through its own detection logic. 

But as both tools don’t de-duplicate, your security team will see it as two separate alerts, possibly at different severity levels. 

This will result in confusion: 

“Is this one incident or two?” 

Your security team will waste time assessing the same event twice, thus leading to fatigue in high-alert environments. 

There will also be gaps in the entire coverage. 

For example, let’s reverse the above scenario.

• The SIEM lacks visibility into remote shells. 

• The XDR catches the attack, but no rule exists to forward that alert to SIEM. 

• The SIEM’s correlation logic fails to see the big picture. For example, if the endpoint is pivoting to others. 

Or 

• XDR doesn’t monitor cloud apps or SaaS APIs 

• SIEM ingests logs from Microsoft 365 but has no context from the endpoint 

The end result will be that XDR sees lateral movement but not cloud login hijack, whereas SIEM sees cloud anomalies but no endpoint compromise. 

There is no stitched attack chain and no unified response. 

Lastly, there will also be disjointed policy enforcement. 

For example, the XDR is capable of isolating a device—but the SIEM detects suspicious authentication and triggers a SOAR workflow. 

Since there is no API bridge between the SIEM playbook and the XDR agent—the SOAR playbook cannot trigger host isolation. 

Even if XDR blocks a file, SIEM rules still trust the originating server, and the incidents will only be repeated. 

The end result will be a partial response, incomplete containment, and recurring alerts. 

Here is a real-world example. 

There are many reasons as to why this happens. 

Firstly, there is no correlation engine, as XDR and SIEM don’t combine events. 

Secondly, both have different detection models—with XDR being behavior-based, whereas SIEM is rule-based. 

There is also a lack of shared schema, with fields like username, pid, and cmd line being different from each other. 

Also, there is no shared policy, such as blocklists and response playbooks are not being synchronized. 

Lastly, there are asynchronous alerts—where one tool alerts instantly, but the other one does it after quite a delay. 

The end result will be that your security team will keep guessing whether to act or not. 

They will often overlook attacks by assuming that “someone else’s tool has this covered.” 

Also, due to lack of unified action—there will be no rapid containment. 

Finally, alert overload and low signal-to-noise ratio will only lead to burnout within your team. 

7. Inconsistent Threat Intelligence 

Threat intelligence provides up-to-date knowledge regarding the indicators of compromise (IOCs), like IPs, domains, file hashes, URLs, etc. 

It is a repository of all the tactics, techniques, and procedures, like the behavioral patterns.

Lastly, it is also a knowledge base of all threat actors, their motivations, targets, and which groups they belong to. 

This data empowers detection rules in SIEM and XDR, allowing them to:

• Block malicious activity in real-time, which is handled by XDR.
• Detects and correlates attacks across logs and events, which is handled by SIEM.  

Each vendor comes with different intelligence providers or builds their own threat database. 

These feeds can have different IOCs or update at different speeds. 

For example, XDR may use behavioral heuristics or ML to detect threats without needing specific IOCs, whereas SIEM may depend on static correlation rules using IOC matches. 

This will lead to uneven detection, in which one tool flags a threat, but the other does not. 

XDR platforms often push real-time updates to agents, whereas SIEM might pull IOCs from a TAXII feed every 12-24 hours. 

This will lead to XDR detecting threats faster, but SIEM sees them too late or not at all. Here is a real-world scenario of how conflicting threat intelligence plays out. 

Imagine at 10:00 am, an IP 185.45.13.9 is added to the XDR’s feed and immediately blocked by endpoints. At 10:03 am, the same IP is accessed via a VPN, and logs are sent to the SIEM.The SIEM doesn’t block or send alerts because its threat feed hasn’t updated yet, due to hourly updates. It will show benign traffic, even though the XDR prevented the connection.The end result will be that your security team will feel confused thinking, “Why is one system saying it’s safe and the other saying it’s a threat?.”

They will also have to investigate it manually. Also, false trust in one system might lead to wrong decisions.  

This inconsistency can have serious consequences. 

For example, due to missed IOCs, the SIEM doesn’t recognize an IP or hash. It won’t alert or correlate the attack.

There will also be conflicting alerts, in which XDR may say “Blocked & Malicious” while SIEM says “Normal activity.” Your security team will have to cross-check between threat intelligence feeds or systems to validate an alert. They may begin to doubt the reliability of one or both tools. Lastly, playbooks, depending on SIEM threat intelligence, may never trigger or trigger incorrectly. 

Invinsense Has Consolidated SIEM and XDR. This Eliminates All the Problems That Arise When They Operate Separately

By consolidating SIEM and XDR, Invinsense eliminates the complexity that comes with integrating two defensive modules. Not only that—Invinsense also establishes unified visibility, quicker threat detection, and efficient operations with no security gaps and redundancies. Our platform synchronizes threat intelligence. 

In this section, let’s look into it in detail how Invinsense XDR achieves all of this through its consolidated approach.  

How Invinsense Eliminates Integration Complexity

As Invinsense has consolidated SIEM and XDR—both tools speak the same data language. By having shared schemas, there’s no mismatch between field names like process_id vs. pid, or log formats like JSON vs. CEF. Furthermore, APIs are inherently compatible. There’s no need for middleware or polling schedules. Also, alerts and logs flow in real-time using internal pipelines. Things like timestamps, normalization rules, and alert structures are standardized, which eliminates broken correlation, inconsistent timelines, and missed alerts.

Thus, there is no need for ingestion pipelines, or schema conversion. There will also be no dropped detections.

How Invinsense Establishes Unified Visibility

Invinsense XDR provides a single console that combines endpoint telemetry, network and cloud activity, user behavior analytics, threat intelligence, and alert timelines and correlation graphs. 

This unified view connects events across the kill chain. 

Instead of separate dashboards showing partial views, like the malware on one, or login on another—here a single system ties everything together.

By having full attack stories visible in real time, your team can investigate quickly and accurately. 

How Invinsense Enables Quicker Threat Detection and Response

As we said earlier, speed is crucial in preventing cyberattacks. By consolidating SIEM and XDR—Invinsense enables all the threats to be detected and acted upon instantly.

If a suspicious behavior is found at the endpoint (via XDR), the SIEM gets immediately notified.

The Automated workflows will isolate hosts, terminate sessions, and improve alerts without any delays. 

There will be no polling, no syncing delays, and no dependency on third-party SOAR tools as Invinsense XDR has consolidated SOAR tools too in its umbrella. 

Invinsense consolidation helps in faster Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR), thus minimizing the time in which the adversary lurks within your systems.  

How Invinsense Improves Operational Efficiency

With both defensive modules consolidated through Invinsense—there is going to be no need to switch dashboards or manually align logs. Your security team will see process behavior, login attempts, command executions, and network connections all in one timeline.

Also, time zones, log formats, and metadata fields will be in harmony with each other. There is not going to be any mismatch.  

Our platform will also provide timelines, pivot graphs, and root cause analysis without needing any external enrichment.

This will eliminate the manual work for your security team. They will make fewer mistakes, and also not suffer from fatigueness. 

All this will lead to better decision-making under pressure.

How Invinsense Closes Security Gaps and Removes Redundancy

As we mentioned earlier, separate systems often either duplicate alerts or miss threats by relying on the other. With consolidation of XDR and SIEM through Invinsense—detection logic is coordinated, preventing duplicate alerts for the same event. The endpoint and cloud telemetry are correlated instantly. Also, policy enforcement—like host isolation, script blocking, and account lockdown—works in sync with detection.

For example, when suspicious PowerShell execution is detected, Invinsense XDR will trigger endpoint isolation and correlate it with login anomalies across the network.

There are going to be fewer false positives, fewer false negatives, and no missed lateral movements or cloud pivots.

How Invinsense Synchronizes Threat Intelligence

As SIEM and XDR are part of the same ecosystem under Invinsense—all the threat intelligence feeds are shared, thus ensuring consistent IOC matching and behavioral heuristics. 

Any new IPs, domains, or hashes are blocked and alerted across all components instantly.

Also, the Behavioral ML models and IOC-based correlation work together, not in conflict.

There will be no delay where one tool updates in real time and the other waits for a periodic refresh. The end result will be that the majority of alerts are genuine, which will reduce confusion, and your security team will be able to act on emerging threats.

To Conclude…

Purchasing SIEM and XDR from separate vendors may seem manageable at first—but over time, it introduces hidden costs, operational inefficiencies, security blind spots, and delayed responses that can cripple your organization’s cyber resilience. 

The lack of shared context, asynchronous alerting, and fragmented threat intelligence only widen the attack surface and burden your security teams.

By consolidating SIEM and XDR into a unified platform, organizations can eliminate integration headaches, reduce mean time to detect and respond, and ensure seamless visibility across endpoints, networks, and cloud environments. 

It empowers security teams with real-time context, automated workflows, and synchronized intelligence—enabling faster decisions and stronger defenses.

The future of cybersecurity isn’t about adding more tools—it’s about making them work together as one. 

A consolidated approach is no longer a luxury—it’s a necessity for staying ahead of modern threats.