Blog
/
OT
/
October 31, 2024

Understanding NERC CIP-015 Requirements

Learn about NERC CIP-015 and its internal network security monitoring requirements. Discover how to ensure compliance and enhance your security posture.
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
Daniel Simonds
Director of Operational Technology
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
31
Oct 2024

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

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
Daniel Simonds
Director of Operational Technology

More in this series

No items found.

Blog

/

Identity

/

July 3, 2025

Top Eight Threats to SaaS Security and How to Combat Them

Default blog imageDefault blog image

The latest on the identity security landscape

Following the mass adoption of remote and hybrid working patterns, more critical data than ever resides in cloud applications – from Salesforce and Google Workspace, to Box, Dropbox, and Microsoft 365.

On average, a single organization uses 130 different Software-as-a-Service (SaaS) applications, and 45% of organizations reported experiencing a cybersecurity incident through a SaaS application in the last year.

As SaaS applications look set to remain an integral part of the digital estate, organizations are being forced to rethink how they protect their users and data in this area.

What is SaaS security?

SaaS security is the protection of cloud applications. It includes securing the apps themselves as well as the user identities that engage with them.

Below are the top eight threats that target SaaS security and user identities.

1.  Account Takeover (ATO)

Attackers gain unauthorized access to a user’s SaaS or cloud account by stealing credentials through phishing, brute-force attacks, or credential stuffing. Once inside, they can exfiltrate data, send malicious emails, or escalate privileges to maintain persistent access.

2. Privilege escalation

Cybercriminals exploit misconfigurations, weak access controls, or vulnerabilities to increase their access privileges within a SaaS or cloud environment. Gaining admin or superuser rights allows attackers to disable security settings, create new accounts, or move laterally across the organization.

3. Lateral movement

Once inside a network or SaaS platform, attackers move between accounts, applications, and cloud workloads to expand their foot- hold. Compromised OAuth tokens, session hijacking, or exploited API connections can enable adversaries to escalate access and exfiltrate sensitive data.

4. Multi-Factor Authentication (MFA) bypass and session hijacking

Threat actors bypass MFA through SIM swapping, push bombing, or exploiting session cookies. By stealing an active authentication session, they can access SaaS environments without needing the original credentials or MFA approval.

5. OAuth token abuse

Attackers exploit OAuth authentication mechanisms by stealing or abusing tokens that grant persistent access to SaaS applications. This allows them to maintain access even if the original user resets their password, making detection and mitigation difficult.

6. Insider threats

Malicious or negligent insiders misuse their legitimate access to SaaS applications or cloud platforms to leak data, alter configurations, or assist external attackers. Over-provisioned accounts and poor access control policies make it easier for insiders to exploit SaaS environments.

7. Application Programming Interface (API)-based attacks

SaaS applications rely on APIs for integration and automation, but attackers exploit insecure endpoints, excessive permissions, and unmonitored API calls to gain unauthorized access. API abuse can lead to data exfiltration, privilege escalation, and service disruption.

8. Business Email Compromise (BEC) via SaaS

Adversaries compromise SaaS-based email platforms (e.g., Microsoft 365 and Google Workspace) to send phishing emails, conduct invoice fraud, or steal sensitive communications. BEC attacks often involve financial fraud or data theft by impersonating executives or suppliers.

BEC heavily uses social engineering techniques, tailoring messages for a specific audience and context. And with the growing use of generative AI by threat actors, BEC is becoming even harder to detect. By adding ingenuity and machine speed, generative AI tools give threat actors the ability to create more personalized, targeted, and convincing attacks at scale.

Protecting against these SaaS threats

Traditionally, security leaders relied on tools that were focused on the attack, reliant on threat intelligence, and confined to a single area of the digital estate.

However, these tools have limitations, and often prove inadequate for contemporary situations, environments, and threats. For example, they may lack advanced threat detection, have limited visibility and scope, and struggle to integrate with other tools and infrastructure, especially cloud platforms.

AI-powered SaaS security stays ahead of the threat landscape

New, more effective approaches involve AI-powered defense solutions that understand the digital business, reveal subtle deviations that indicate cyber-threats, and action autonomous, targeted responses.

[related-resource]

Continue reading
About the author
Carlos Gray
Senior Product Marketing Manager, Email

Blog

/

Proactive Security

/

July 2, 2025

Pre-CVE Threat Detection: 10 Examples Identifying Malicious Activity Prior to Public Disclosure of a Vulnerability

Default blog imageDefault blog image

Vulnerabilities are weaknesses in a system that can be exploited by malicious actors to gain unauthorized access or to disrupt normal operations. Common Vulnerabilities and Exposures (or CVEs) are a list of publicly disclosed cybersecurity vulnerabilities that can be tracked and mitigated by the security community.

When a vulnerability is discovered, the standard practice is to report it to the vendor or the responsible organization, allowing them to develop and distribute a patch or fix before the details are made public. This is known as responsible disclosure.

With a record-breaking 40,000 CVEs reported for 2024 and a predicted higher number for 2025 by the Forum for Incident Response and Security Teams (FIRST) [1], anomaly-detection is essential for identifying these potential risks. The gap between exploitation of a zero-day and disclosure of the vulnerability can sometimes be considerable, and retroactively attempting to identify successful exploitation on your network can be challenging, particularly if taking a signature-based approach.

Detecting threats without relying on CVE disclosure

Abnormal behaviors in networks or systems, such as unusual login patterns or data transfers, can indicate attempted cyber-attacks, insider threats, or compromised systems. Since Darktrace does not rely on rules or signatures, it can detect malicious activity that is anomalous even without full context of the specific device or asset in question.

For example, during the Fortinet exploitation late last year, the Darktrace Threat Research team were investigating a different Fortinet vulnerability, namely CVE 2024-23113, for exploitation when Mandiant released a security advisory around CVE 2024-47575, which aligned closely with Darktrace’s findings.

Retrospective analysis like this is used by Darktrace’s threat researchers to better understand detections across the threat landscape and to add additional context.

Below are ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

Trends in pre-cve exploitation

Often, the disclosure of an exploited vulnerability can be off the back of an incident response investigation related to a compromise by an advanced threat actor using a zero-day. Once the vulnerability is registered and publicly disclosed as having been exploited, it can kick off a race between the attacker and defender: attack vs patch.

Nation-state actors, highly skilled with significant resources, are known to use a range of capabilities to achieve their target, including zero-day use. Often, pre-CVE activity is “low and slow”, last for months with high operational security. After CVE disclosure, the barriers to entry lower, allowing less skilled and less resourced attackers, like some ransomware gangs, to exploit the vulnerability and cause harm. This is why two distinct types of activity are often seen: pre and post disclosure of an exploited vulnerability.

Darktrace saw this consistent story line play out during several of the Fortinet and PAN OS threat actor campaigns highlighted above last year, where nation-state actors were seen exploiting vulnerabilities first, followed by ransomware gangs impacting organizations [2].

The same applies with the recent SAP Netweaver exploitations being tied to a China based threat actor earlier this spring with subsequent ransomware incidents being observed [3].

Autonomous Response

Anomaly-based detection offers the benefit of identifying malicious activity even before a CVE is disclosed; however, security teams still need to quickly contain and isolate the activity.

For example, during the Ivanti chaining exploitation in the early part of 2025, a customer had Darktrace’s Autonomous Response capability enabled on their network. As a result, Darktrace was able to contain the compromise and shut down any ongoing suspicious connectivity by blocking internal connections and enforcing a “pattern of life” on the affected device.

This pre-CVE detection and response by Darktrace occurred 11 days before any public disclosure, demonstrating the value of an anomaly-based approach.

In some cases, customers have even reported that Darktrace stopped malicious exploitation of devices several days before a public disclosure of a vulnerability.

For example, During the ConnectWise exploitation, a customer informed the team that Darktrace had detected malicious software being installed via remote access. Upon further investigation, four servers were found to be impacted, while Autonomous Response had blocked outbound connections and enforced patterns of life on impacted devices.

Conclusion

By continuously analyzing behavioral patterns, systems can spot unusual activities and patterns from users, systems, and networks to detect anomalies that could signify a security breach.

Through ongoing monitoring and learning from these behaviors, anomaly-based security systems can detect threats that traditional signature-based solutions might miss, while also providing detailed insights into threat tactics, techniques, and procedures (TTPs). This type of behavioral intelligence supports pre-CVE detection, allows for a more adaptive security posture, and enables systems to evolve with the ever-changing threat landscape.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO), Emma Fougler (Global Threat Research Operations Lead), Ryan Traill (Analyst Content Lead)

References and further reading:

  1. https://www.first.org/blog/20250607-Vulnerability-Forecast-for-2025
  2. https://cloud.google.com/blog/topics/threat-intelligence/fortimanager-zero-day-exploitation-cve-2024-47575
  3. https://thehackernews.com/2025/05/china-linked-hackers-exploit-sap-and.html

Related Darktrace blogs:

*Self-reported by customer, confirmed afterwards.

**Updated January 2024 blog now reflects current findings

Continue reading
About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO
Your data. Our AI.
Elevate your network security with Darktrace AI