June 25, 2024

Let the Dominos Fall! SOC and IR Metrics for ROI

Vendors are scrambling to compare MTTD metrics laid out in the latest MITRE Engenuity ATT&CK® Evaluations. But this analysis is reductive, ignoring the fact that in cybersecurity, there are far more metrics that matter.

Written by

John Bradshaw

Sr. Director, Technical Marketing

Inside the SOC

Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.

Written by

John Bradshaw

Sr. Director, Technical Marketing

Jun 2024

One of the most enjoyable discussions (and debates) I engage in is the topic of Security Operations Center (SOC) and Incident Response (IR) metrics to measure and validate an organization’s Return on Investment (ROI). The debate part comes in when I hear vendor experts talking about “the only” SOC metrics that matter, and only list the two most well-known, while completely ignoring metrics that have a direct causal relationship.

In this blog, I will discuss what I believe are the SOC/IR metrics that matter, how each one has a direct impact on the others, and why organizations should ensure they are working towards the goal of why these metrics are measured in the first place: Reduction of Risk and Costs.

Reduction of Risk and Costs

Every security solution and process an organization puts in place should reduce the organization’s risk of a breach, exposure by an insider threat, or loss of productivity. How an organization realizes net benefits can be in several ways:

Improved efficiencies can result in SOC/IR staff focusing on other areas such as advanced threat hunting rather than churning through alerts on their security consoles. It may also help organizations dealing with the lack of skilled security staff by using Artificial Intelligence (AI) and automated processes.
A well-oiled SOC/IR team that has greatly reduced or even eliminated mundane tasks attracts, motivates, and retains talent resulting in reduced hiring and training costs.
The direct impact of a breach such as a ransomware attack can be devastating. According to the 2024 Data Breach Investigations Report by Verizon, MGM Resorts International reported the ALPHV ransomware cost the company approximately $100 million^[1].
Failure to take appropriate steps to protect the organization can result in regulatory fines; and if an organization has, or is considering, purchasing Cyber Insurance, can result in declined coverage or increased premiums.

How does an organization demonstrate they are taking proactive measures to prevent breaches? That is where it's important to understand the nine (yes, nine) key metrics, and how each one directly influences the others, play their roles.

Metrics in the Incident Response Timeline

Let’s start with a review of the key steps in the Incident Response Timeline:

Seven of the nine key metrics are in the IR timeline, while two of the metrics occur before you ever have an incident. They occur in the Pre-Detection Stage.

‍Pre-Detection stage metrics are:

Preventions Per Intrusion Attempt (PPIA)
False Positive Reduction Rate (FPRR)

Next is the Detect and Investigate stage, there are three metrics to consider:

Mean Time to Detection (MTTD)
Mean Time to Triage (MTTT)
Mean Time to Understanding (MTTU)

This is followed by the Remediation stage, there are two metrics here:

Mean Time to Containment (MTTC)
Mean Time to Remediation / Recovery (MTTR)

Finally, there is the Risk Reduction stage, there are two metrics:

Mean Time to Advice (MTTA)
Mean Time to Implementation (MTTI)

Pre-Detection Stage

Preventions Per Intrusion Attempt

PPIA is defined as stopping any intrusion attempt at the earliest possible stage. Your network Intrusion Prevention System (IPS) blocks vulnerability exploits, your e-mail security solution intercepts and removes messages with malicious attachments or links, your egress firewall blocks unauthorized login attempts, etc. The adversary doesn’t get beyond Step 1 in the attack life cycle.

This metric is the first domino. Every organization should strive to improve on this metric every day. Why? For every intrusion attempt you stop right out of the gate, you eliminate the actions for every other metric. There is no incident to detect, triage, investigate, remediate, or analyze post-incident for ways to improve your security posture.

When I think about PPIA, I always remember back to a discussion with a former mentor, Tim Crothers, who discussed the benefits of focusing on Prevention Failure Detection.

The concept is that as you layer your security defenses, your PPIA moves ever closer to 100% (no one has ever reached 100%). This narrows the field of fire for adversaries to breach into your organization. This is where novel, unknown, and permuted threats live and breathe. This is where solutions utilizing Unsupervised Machine Learning excel in raising anomalous alerts – indications of potential compromise involving one of these threats. Unsupervised ML also raises alerts on anomalous activity generated by known threats and can raise detections before many signature-based solutions. Most organizations struggle to find strong permutations of known threats, insider threats, supply chain attacks, attacks utilizing n-day and 0-day exploits. Moving PPIA ever closer to 100% also frees your team up for conducting threat hunting activities – utilizing components of your SOC that collect and store telemetry to query for potential compromises based on hypothesis the team raises. It also significantly reduces the alerts your team must triage and investigate – solving many of the issues outlined at the start of this paper.

False Positive Reduction Rate

Before we discuss FPRR, I should clarify how I define False Positives (FPs). Many define FPs as an alert that is in error (i.e.: your EDR alerts on malware that turns out to be AV signature files). While that is a FP, I extend the definition to include any alert that did not require triage / investigation and distracts the SOC/IR team (meaning they conducted some level of triage / investigation).

This metric is the second domino. Why is this metric important? Every alert your team exerts time and effort on that is a non-issue distracts them from alerts that matter. One of the major issues that has resonated in the security industry for decades is that SOCs are inundated with alerts and cannot clear the backlog. When it comes to PPIA + FPRR, I have seen analysts spend time investigating alerts that were blocked out of the gate while their screen continued to fill up with more. You must focus on Prevention Failure Detection to get ahead of the backlog.

Detect and Investigate Stages

Mean Time to Detection

MTTD, or “Dwell Time”, has decreased dramatically over the past 12 years. From well over a year to 16 days in 2023^[2]. MTTD is measured from the earliest possible point you could detect the intrusion to the moment you actually detect it.

This third domino is important because the longer an adversary remains undetected, the more the odds increase they will complete their mission objective. It also makes the tasks of triage and investigation more difficult as analysts must piece together more activity and adversaries may be erasing evidence along the way – or your storage retention does not cover the breach timeline.

Many solutions focusing solely on MTTD can actually create the very problem SOCs are looking to solve. That is, they generate so much alerting that they flood the console, email, or text messaging app causing an unmanageable queue of alerts (this is the problem XDR solutions were designed to resolve by focusing on incidents rather than alerts).

Mean Time to Triage

MTTT involves SOCs that utilize Level 1 (aka Triage) analysts to render an “escalate / do not escalate” alert verdict accurately. Accuracy is important because Triage Analysts typically are staff new to cyber security (recent grad / certification) and may over escalate (afraid to miss something important) or under escalate (not recognize signs of a successful breach). Because of this, a small MTTT does not always equate to successful handling of incidents.

This metric is important because keeping your senior staff focused on progressing incidents in a timely manner (and not expending time on false positives) should reduce stress and required headcount.

Mean Time to Understanding

MTTU deals with understanding the complete nature of the incident being investigated. This is different than MTTT which only deals with whether the issue merits escalation to senior analysts. It is then up to the senior analysts to determine the scope of the incident, and if you are a follower of my UPSET Investigation Framework, you know understanding the full scope involves:

U = All compromised accounts

P = Persistence Mechanisms used

S = All systems involved (organization, adversary, and intermediaries)

E = Endgame (or mission objective)

T = Techniques, Tactics, Procedures (TTPs) utilized by the adversary

MTTU is important because this information is critical before any containment or remediation actions are taken. Leave a stone unturned, and you alert the adversary that you are onto them and possibly fail to close an avenue of access.

Remediation Stages

Mean Time to Containment

MTTC deals with neutralizing the threat. You may not have kicked the adversary out, but you have halted their progress to their mission objective and ability to inflict further damage. This may be through use of isolation capabilities, termination of malicious processes, or firewall blocks.

MTTC is important, especially with ransomware attacks where every second counts. Faster containment responses can result in reduced / eliminated disruption to business operations or loss of data.

Mean Time to Remediation / Recovery

The full scope of the incident is understood, the adversary has been halted in their tracks, no malicious processes are running on any systems in your organization. Now is the time to put things back to right. MTTR deals with the time involved in restoring business operations to pre-incident stage. It means all remnants of changes made by the adversary (persistence, account alterations, programs installed, etc.) are removed; all disrupted systems are restored to operations (i.e.: ransomware encrypted systems are recovered from backups / snapshots), compromised user accounts are reset, etc.

MTTR is important because it informs senior management of how fast the organization can recover from an incident. Disaster Recovery and Business Continuity plans play a major role in improving this score.

Risk Reduction Stages

Mean Time to Advice

After the dust has settled from the incident, the job is not done. MTTA deals with identifying and assessing the specific areas (vulnerabilities, misconfigurations, lack of security controls) that permitted the adversary to advance to the point where detection occurred (and any actions beyond). The SOC and IR teams should then compile a list of recommendations to present to management to improve the security posture of the organization so the same attack path cannot be used.

Mean Time to Implement

Once recommendations are delivered to management, how long does it take to implement them? MTTI tracks this timeline because none of it matters if you don’t fix the holes that led to the breach.

Nine Dominos

There are the nine dominos of SOC / IR metrics I recommend helping organizations know if they are on the right track to reduce risk, costs and improve morale / retention of the security teams. You may not wish to track all nine, but understanding how each metric impacts the others can provide visibility into why you are not seeing expected improvements when you implement a new security solution or change processes.

Improving prevention and reducing false positives can make huge positive impacts on your incident response timeline. Utilizing solutions that get you to resolution quicker allows the team to focus on recommendations and risk reduction strategies.

Whichever metrics you choose to track, just be sure the dominos fall in your favor.

‍

References

[1] 2024 Verizon Data Breach Investigations Report, p83

[2] Mandiant M-Trends 2023

‍

Written by

John Bradshaw

Sr. Director, Technical Marketing

Inside the SOC

Written by

John Bradshaw

Sr. Director, Technical Marketing

Malware Research Lead

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Blog

Proactive Security

June 2, 2026

Stopping Stealth Attacks with Precision: How Núclea Prevented a Breach Without Disruption

Núclea is a Brazilian data and technology company that supports the country’s financial system by delivering digital services exclusively to banks and financial institutions. Operating in an environment where trust, availability, and data integrity are critical, the company faces a threat landscape that has evolved rapidly—particularly with the rise of AI-driven cyberattacks.

Brazil has experienced a wave of successful cyber incidents targeting financial institutions, many of them enabled by insiders or compromised credentials. The result was a noticeable shift in attacker strategy: instead of focusing on end customers, threat actors began targeting the institutions and platforms that underpin the financial ecosystem itself.

“Attacks became far more directed and contextual,” explains Guilherme, who leads incident response within Núclea’s security platform engineering team. “They weren’t noisy or obviously malicious—they were precise, patient, and designed to blend into normal operations.”

That precision was on full display in January 2026, when Núclea faced one of the most convincing phishing attacks the team had seen.

A real attack, built on trust and context

The attack began with a seemingly routine email.

It was sent from a real Brazilian government institution, using legitimate infrastructure and valid credentials that were later confirmed to have been compromised. Núclea had an established, ongoing relationship with this organization, and the email’s language, tone, and subject matter aligned perfectly with the type of communication the recipient team handled every day.

Attached to the email was a PDF document containing content that looked entirely legitimate.

The problem? A single URL embedded inside that PDF.

“The message itself was correct. The sender was real. The context was familiar. Even the document content made sense,” Guilherme explains. “There was just one small element that didn’t belong.”

That small detail was enough to initiate a full attack chain.

What the attackers were trying to do

If clicked, the URL would have downloaded a malicious payload designed to:

Collect information about the user and device
Identify where the system was located within the financial ecosystem
Install remote access tools to maintain control
Deploy an infostealer to extract sensitive data
Execute anti-forensic scripts to erase traces of the intrusion

In other words, it was a carefully engineered operation designed for persistence and stealth, not immediate disruption.

The attack also employed urgency—a classic social engineering technique. When the link didn’t open as expected, employees requested assistance from the security team, insisting the document was important and needed to be accessed quickly.

This is precisely the kind of scenario where traditional security tools struggle: almost everything about the interaction is legitimate.

Where Darktrace made the difference

Instead of blocking the entire message or relying on known indicators of compromise, Darktrace focused on behavioral context.

Darktrace recognized:

That the sending organization was normally trusted
That the communication pattern matched historical behavior
That the PDF content itself was not suspicious

But it also identified that the URL embedded within the document deviated from established behavioral patterns.

Rather than disrupting business operations, Darktrace took precise action: it rewrote the URL, preventing the malicious download while leaving the rest of the email untouched.

“When we analyzed it afterward, it became clear how dangerous the attack would have been,” says Guilherme. “But it never progressed—because Darktrace acted at exactly the right point.”

Subsequent forensic analysis confirmed the payload’s malicious intent. The attack never succeeded.

Precision over disruption

For Núclea, this incident reinforced a critical lesson: modern attacks don’t always look malicious—they hide within normal activity.

“What stands out to me is the precision,” Guilherme says. “Darktrace doesn’t rely on big, obvious signals. It’s effective in situations that fall outside the standard patterns we all know.”

Building resilience in a high trust ecosystem

For Núclea, cybersecurity is not just a defensive measure—it’s a business enabler.

Availability failures or successful breaches in the financial ecosystem can have immediate, large-scale consequences, from financial loss to reputational damage. Preventing those outcomes protects not just Núclea, but its partners and customers as well.

“Cyber resilience means keeping the business running—even under attack,” Guilherme explains. “And that requires people, processes, and technology working together.”

As AI continues to accelerate both attacks and defenses, the role of security is evolving. Precision, behavioral understanding, and intelligent automation are no longer optional—they’re essential.

“The easy days were yesterday,” Guilherme says. “The challenges ahead are bigger. We need to be prepared—internally and with partners that help us build resilience.”

‍

About the author

Mariana Pereira

VP, Field CISO

Blog

Proactive Security

June 1, 2026

Defend What You Trust: Stories from the Front Lines of Modern Cyber Defense

Modern attacks don’t always announce themselves, follow obvious patterns, or rely on known malware. Often, they move quietly inside trusted systems, authenticated sessions, and everyday behavior.

They don’t break in. They blend in.

That’s why an AI-powered defense is essential. It turns invisible signals into actionable insights at a scale neither analysts nor traditional tools can achieve alone.

Confidence is creating risk

One of the most dangerous assumptions in cybersecurity today is that strong controls equal strong protection.

Multi-factor authentication (MFA), for example, is widely viewed as a foundational safeguard. But as the CISO for a professional sports organization explains, that confidence can be misplaced. “A lot of organizations assume that once you have MFA, those accounts are safe. That’s not true.”

In one instance, his team identified a sophisticated attack where a threat actor bypassed MFA entirely, not by breaking it, but by going around it. A user’s authenticated session was hijacked and re-used, allowing the attacker to impersonate them without triggering traditional controls.

“Darktrace picked up that a session had been re-injected by the hacker, and we were able to block it right away,” he explains.

Attackers anticipate what we miss

Even well-trained users can become entry points.

“An email bypassed our existing security tools,” shares the VP of IT at a U.S.-based risk management services provider. “The user missed one signal and entered their credentials into a malicious site. That’s what the bad guys count on.”

The organization responded quickly, but not before damage was done. Crucially, this occurred while Darktrace was in “watch mode,” before autonomous response was fully enabled. “Darktrace would have seen that and shut it down immediately,” he notes.

Mistakes and oversights like misconfigurations, forgotten machines, and missed patches can create serious vulnerabilities.

The CIO of a utility services organization shares an instance when Darktrace detected a breach to a client’s network via their ZTNA VPN due to misconfigured MFA. “Darktrace alerted us and autonomously blocked the scanning, preventing what could have been a ransomware-type incident.”

The most dangerous threats are already inside

The Head of Security at a global business services provider knows firsthand how blind spots can persist inside environments. His team uncovered evidence of dormant ransomware artifacts sitting unnoticed within a company’s environment ¬¬– long before modern detection was in place.

“During a routine file transfer, Darktrace flagged the suspicious activity, identified the ransomware, and immediately quarantined the server,” he recalls. While the attack was never executed, the implication was significant: the risk existed long before it was finally detected.

Cyber threats are also successful because they take advantage of normal human behavior, exploiting moments of cognitive overload, urgency, and trust.

The Executive Director of IT and Business Applications at a pharmaceutical lab describes the time Darktrace flagged an employee logging into Microsoft 365 from Singapore, despite him being physically located in the U.S. Darktrace immediately cut off his access and within minutes revealed that the employee’s son was using a VPN to play a video game.

While the threat was benign, it demonstrated the strength of AI to use contextual information to detect threats other tools miss. The information also saved security analysts hours of investigation and minimized downtime for the employee. “That level of precision and speed isn’t just convenient, it’s game changing.”

“Unusual” behavior is the new red flag

Detecting modern threats requires an understanding of what “normal” looks like and recognizing when something subtly deviates.

One security leader at an AI technology enterprise described a scenario in which an employee connected to a proxy service in China. The service itself was legitimate, and although traditional tools didn’t flag it, the behavior was unusual for that user specifically.

“That’s what Darktrace picked up on. The activity turned out to be benign, but without visibility into behavioral deviations, it could just as easily have been something more serious.”

AI shifts defense from reaction to anticipation

These stories point to a fundamental shift by cyber attackers, both tactically and strategically. Because traditional security tools were built to detect what’s already known, modern attacks are often:

Credential-based, not malware-based
Behavioral, not signature-based
Subtle, not overt

They may operate within the boundaries of what appears normal, exploiting what organizations trust, not what they block:

Trusted sessions
Legitimate services
Human error

This is where AI is changing the equation. Rather than relying on predefined rules or known threat signatures, AI can:

Establish a baseline of normal behavior
Detect subtle anomalies in real time
Act autonomously to contain potential threats

Resilience, not perfection, is the new security standard

As these frontline experiences show, the organizations that lead are those that move beyond reactive defense and embrace AI as a core part of their strategy.

It eliminates the blind spots and uncertainty, says the CISO of a professional sports organization. “If you lack visibility, you’re not managing risk, you’re assuming it. AI gives you the actionable insights needed to turn uncertainty into control.”

And it provides the speed and agility that are vital when seconds matter, says the Executive Director of IT and Business Applications. “When Darktrace alerted us at 3:00 am to a ransomware attack, it had already quarantined the affected systems, blocked the attacker’s access, and provided us with the critical details and time needed to investigate. That action likely saved us hundreds of thousands, if not millions, of dollars.”

The modern SOC has become a cornerstone of enterprise resilience, responsible for protecting data and operational continuity while enabling digital growth and innovation. For today’s security professional, that means success is no longer measured by what they keep out, but by what they protect: revenue, reputation, and trust.

‍

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Check out this article by Darktrace: Let the Dominos Fall! SOC and IR Metrics for ROI

Let the Dominos Fall! SOC and IR Metrics for ROI

Reduction of Risk and Costs

Metrics in the Incident Response Timeline

Pre-Detection Stage

Preventions Per Intrusion Attempt

False Positive Reduction Rate

Detect and Investigate Stages

Mean Time to Detection

Mean Time to Triage

Mean Time to Understanding

Remediation Stages

Mean Time to Containment

Mean Time to Remediation / Recovery

Risk Reduction Stages

Mean Time to Advice

Mean Time to Implement

Nine Dominos

References

Chinese APT Campaign Targets Entities with Updated FDMTP Backdoor

Stopping Stealth Attacks with Precision: How Núclea Prevented a Breach Without Disruption

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More in this series

Stopping Stealth Attacks with Precision: How Núclea Prevented a Breach Without Disruption

Defend What You Trust: Stories from the Front Lines of Modern Cyber Defense

AI-powered security for a rapidly growing grocery enterprise

Blog

Proactive Security

June 2, 2026

Stopping Stealth Attacks with Precision: How Núclea Prevented a Breach Without Disruption

A real attack, built on trust and context

What the attackers were trying to do

Where Darktrace made the difference

Precision over disruption

Blog

Proactive Security

June 1, 2026

Defend What You Trust: Stories from the Front Lines of Modern Cyber Defense

They don’t break in. They blend in.

Attackers anticipate what we miss

The most dangerous threats are already inside

“Unusual” behavior is the new red flag

AI shifts defense from reaction to anticipation

Resilience, not perfection, is the new security standard