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June 25, 2024
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Let the Dominos Fall! SOC and IR Metrics for ROI

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25
Jun 2024
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.

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

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.
Author
John Bradshaw
Sr. Director, Technical Marketing

John Bradshaw is Sr. Director, Technical Marketing at Darktrace. He is a security practitioner at heart having built a Customer Security/SOC operations team for (then) the largest ISP on the planet. In his vendor roles he has worked with various security solutions utilized by SOC / IR teams and conducted advanced incident investigation workshops to help organizations understand the benefits and limitations of the solutions they are using. He holds a Bachelor of Business Administration from Averett University and a Master of Science in Network Security from Capitol College.

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November 7, 2024

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Inside the SOC

Onomastics Gymnastics: How Darktrace Detects Spoofing and Business Email Compromise in Multi-Name Users

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Note: For privacy reasons, actual surnames and email addresses observed in these incidents below have been replaced with fictitious placeholder names, using the common Spanish names “Fulano” and “Mengano”.

Naming conventions

Modeling names and their variants of members of an organization is a critical component to properly detect if those same names and variants are being spoofed by malicious actors. For many predominantly English-speaking organizations, these variants can largely be captured by variants of a person’s given name (e.g. James-Jimmy-Jim) and a consistent, singular surname or family name (e.g. Smith). Naming conventions, however, are far from universal. This piece will review how Darktrace / EMAIL manages the common naming conventions of much of the Spanish-speaking world, and can use its modeling to create high-fidelity detections of multiple types of spoofing attempts.

A brief summary of the common convention across Spain and much of Spanish-speaking America: most people are given one or two given names (e.g. Roberto, Juan, María, Natalia), and their surnames are the first surname of their father, followed by the first surname of their mother. While there are various exceptions to this norm, the below graphic Wikipedia [1][2] highlights the general rule.

Example Spanish naming convention for father “José García Torres” and mother “María Acosta Gómez” for child “Pablo García Acosta”. If shortened to one surname, the convention holds the child would be referred to as “Pablo García”
Figure 1: Example Spanish naming convention for father “José García Torres” and mother “María Acosta Gómez” for child “Pablo García Acosta”. If shortened to one surname, the convention holds the child would be referred to as “Pablo García” [1].

Detection of improper name usage

Implicit in the above comment that shortening to one surname follows the convention of using the first surname, shortening to the second surname is often a tell-tale sign of someone unfamiliar with the person or their broader culture. This can be a useful corroborating feature in detecting a spoof attempt – analogous to a spelling error.

In the case of a Spanish customer, this misuse of name shortening contributed to the detection of a spoof attempt trying to solicit a response by impersonating an internal user forwarding information about ‘Data Protection’.

Figure 2: The Cyber AI Analyst summary of the Darktrace / EMAIL detections shows the use of the Gmail sender impersonating Isabel Maria Fulano Mengano, but incorrectly uses the second surname Mengano.

While the limited communication history from the sender and the nature of the text content already marks the mail as suspicious, Darktrace / EMAIL notes the personal name used in the email is similar to a high-value user (‘whale’ to use the terminology of spearphishing). The additional context provided by the detection of the attempted spoof prompted more severe actioning of this email, leading to a ‘Hold’ action instead of a less-severe ‘Unspoof’ action via a banner on the email.

The content summary of the sender showing the ‘Personal’ field of the email being ‘Isabel Mengano’, breaking from the standard name-shortening convention. The additional metrics identify features that might be anomalous about the sender.
Figure 3: The content summary of the sender showing the ‘Personal’ field of the email being ‘Isabel Mengano’, breaking from the standard name-shortening convention. The additional metrics identify features that might be anomalous about the sender.

Malicious email properly using both surnames

Misusing the name-shortening convention is not the only way that Darktrace / EMAIL can detect spoofing attempts. In the case of another Spanish customer,  Darktrace observed a whale impersonation being sent to 230 users with solicitation content, but no links or attachments. Although the name was modeled internally in the “Surname, Given-name” format, Darktrace identified the spoofing attempt targeting a high-value user and took action, blocking the series of emails from reaching end-user inboxes to prevent unsuspecting users from responding.

Cyber AI Analyst summary of a suspicious email
Figure 4: Cyber AI Analyst summary of a suspicious email. The personal field is visible as ‘juan fulano mengano’, which is consistent with the reverse-order modelled user ‘fulano mengano, juan’. The subject line ‘Urgent Request’ sent to 230 users gives an intuitive indicator of the emails potentially being part of a malicious solicitation campaign.

In Summary: A case of onomastics gymnastics

The variety in valid usage of human language can be a barrier to evaluating when a given text is benign or malicious. Despite this, Darktrace / EMAIL is designed to manage this variety, as exemplified by the detections of two spoofing attempts seen against organizations using the distinct Spanish-speaking world’s common naming convention. The scope of this design as seen in this onomastic context, extends to a wide range of detections surrounding emails and their behavioral anomalies.

Credit to Roberto Romeu (Principal Cyber Analyst), Justin Torres (Senior Cyber Analyst) and Natalia Sánchez Rocafort (Senior Analyst Consultant).

Darktrace / Email solution brief screenshot

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  • Gain up to 13 days of earlier threat detection and maximize ROI on your current email security
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  • Stop the 58% of threats bypassing traditional email security

References

[1] https://en.wikipedia.org/wiki/Naming_customs_of_Hispanic_America

[2] https://en.wikipedia.org/wiki/Spanish_naming_customs

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About the author
Roberto Romeu
Senior SOC Analyst

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October 31, 2024

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OT

Understanding the NERC-CIP015 Internal Network Security Monitoring (INSM) Requirements

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Background: NERC CIP-015

In January of 2023 the Federal Energy Regulatory Commission (FERC) released FERC Order 887 which addresses a critical security gap in Critical Infrastructure Protection (CIP) standards, the lack of internal network security monitoring (INSM).

The current NERC CIP standards only require solutions that use traditional detection systems that identify malicious code based on known rules and signatures. The new legislation will now require electric cooperatives to implement INSMs to detect malicious activity in east-west network traffic. INSMs establish a baseline of network activity and detect anomalies that would bypass traditional detection systems, improving an organization’s ability to detect novel threats. Without INSM, organizations have limited visibility into malicious activities inside their networks, leaving them vulnerable if attackers breach initial defenses like firewalls and anti-virus software.

Implementation of NERC CIP-015

Once approved, Bulk Electronic Systems (BESs) will have 36 months to implement INSM, and medium-impact BESs with external routable connectivity (ERC) will have 60 months to do so.

While the approval of the NERC CIP-015 requirements have not been finalized, preparation on the part of electric cooperatives should start as soon as possible. Darktrace is committed to helping electric cooperatives meet the requirements for INSM and help reach compliance standards.

Why is internal network security monitoring important?

NERC CIP-015 aims to enhance the detection of anomalies or unauthorized network activity within CIP environments, underscoring the importance of monitoring East-West traffic within trust zones. This approach enables faster response and recovery times.

INSMs are essential to detecting threats that bypass traditional defenses. For example, insider threats, sophisticated new attack techniques, and threats that exploit compromised credentials—such as those obtained through phishing or other malicious activities—can easily bypass traditional firewalls and antivirus software. These threats either introduce novel methods or leverage legitimate access, making them difficult to detect.

INSMs don’t rely on rules and signatures to detect anomalous activity, they spot abnormalities in network traffic and create alerts based on this activity making them vital to detecting sophisticated threats. Additionally, INSM sits behind the firewall and provides detections utilizing the passive monitoring of east west and north south traffic within the enforcement boundary.

Buyers should be aware of the discrepancies between different INSMs. Some systems require constant tuning and updating, external connectivity forcing holes in segmentation or have intrusive deployments that put sensitive OT assets at risk.

What are the NERC CIP-015 requirements?

The goal of this directive is to ensure that cyber threats are identified early in the attack lifecycle by mandating implementation of security systems that detect and speed up mitigation of malicious activity.

The requirements are divided into three sections:

  • Network security monitoring
  • Data retention for anomalous activity
  • Data protection

NERC CIP-015 emphasizes the importance of having documented processes and evidence of implementation, with a focus on risk-based monitoring, anomaly detection, evaluation, retention of data, and protection against unauthorized access. Below is a breakdown of each requirement.

R1: Network Security Monitoring

The NERC CIP-015 requires the implementation of and a documented process for monitoring networks within Electronic Security Perimeters (ESPs) that contain high and medium impact BES Cyber Systems.

Key parts:

Part 1.1: Use a risk-based rationale to implement network data feeds that monitor connections, devices, and communications.

Part 1.2: Detect anomalous network activity using the data feeds.

Part 1.3: Evaluate the anomalous activity to determine necessary actions.

M1: Evidence for R1 Implementation: Documentation of processes, including risk-based rationale for data collection, detection events, configuration settings, and network baselines.

Incorporating automated solutions for network baselining is essential for effective internal monitoring, especially in diverse environments like substations and control centers. Each environment requires unique baselines—what’s typical for a substation may differ significantly from a control center, making manual monitoring impractical.

A continuous internal monitoring solution powered by artificial intelligence (AI) simplifies this challenge by instantly detecting all connected assets, dynamically learning the environment’s baseline behavior, and identifying anomalies in real-time. Unlike traditional methods, Darktrace’s AI-driven approach requires no external connectivity or repeated tuning, offering a seamless, adaptive solution for maintaining secure operations across all environments.

R2: Data Retention for Anomalous Activity

Documented processes must be in place to retain network security data related to detected anomalies until the required actions are completed.

Note: Data that does not relate to detected anomalies (Part 1.2) is not required to be retained.

M2: Evidence for Data Retention (R2): Documentation of data retention processes, system configurations, or reports showing compliance with R2.

R3: Data Protection: Implement documented processes to protect the collected security monitoring data from unauthorized deletion or modification.

M3: Evidence for Data Protection (R3): Documentation demonstrating how network security monitoring data is protected from unauthorized access or changes.

How to choose the right INSM for your organization?

Several vendors will offer INSM, but how do you choose the right solution for your organization?

Here are seven questions to help you get started evaluating potential INSM vendors:

  1. How does the solution help with ongoing compliance and reporting including CIP-015? Or any other regulations we comply with?
  2. Does the solution provide real-time monitoring of east-west traffic across critical systems? And what kind of threats has it proven capable of finding?
  3. How deep is the traffic visibility—does it offer Layer 7 (application) insights, or is it limited to Layers 3-4?
  4. Is the solution compatible with our existing infrastructure (firewalls, IDS/IPS, SIEM, OT networks)?
  5. Is this solution inline, passive, or hybrid? What impact will it have on network latency?
  6. Does the vendor have experience with electric utilities or critical infrastructure environments?
  7. Where and how are logs and monitoring data stored?

How Darktrace helps electric utilities with INSM requirements

Darktrace's ActiveAI Security Platform is uniquely designed to continuously monitor network activity and detect anomalous activity across both IT and OT environments successfully detecting insider threats and novel ransomware, while accelerating time to detection and incident reporting.

Most INSM solutions require repeated baselining, which creates more work and increases the likelihood of false positives, as even minor deviations trigger alerts. Since networks are constantly changing, baselines need to adjust in real time. Unlike these solutions, Darktrace does not depend on external connectivity or cloud access over the public internet. Our passive network analysis requires no agents or intrusive scanning, minimizing disruptions and reducing risks to OT systems.

Darktrace's AI-driven threat detection, asset management, and incident response capabilities can help organizations comply with the requirements of NERC CIP-015 for internal network security monitoring and data protection. Built specifically to deploy in OT environments, Darktrace / OT comprehensively manages, detects, evaluates, and protects network activity and anomalous events across IT and OT environments, facilitating adherence to regulatory requirements like data retention and anomaly management.

See how INSM with Darktrace can enhance your security operations, schedule a personalized demo today.

Disclaimer

The information provided in this blog is intended for informational purposes only and reflects Darktrace’s understanding of the NERC CIP-015 INSM requirements as of the publication date. While every effort has been made to ensure the accuracy and reliability of the content, Darktrace makes no warranties or representations regarding its accuracy, completeness, or applicability to specific situations. This blog does not constitute legal or compliance advice and readers are encouraged to consult with qualified professionals for guidance specific to their circumstances. Darktrace disclaims any liability for actions taken or not taken based on the information contained herein.

References

1.     https://www.nerc.com/pa/Stand/Reliability%20Standards/CIP-015-1.pdf

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About the author
Daniel Simonds
Director of Operational Technology
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