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February 3, 2025

CNAPP Alone Isn’t Enough: Focusing on CDR for Real-Time Cross Domain Protection

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03
Feb 2025
This blog dives into the strengths and limitations of CNAPP, explaining how a CDR solution can enhance cloud security to identify and mitigate cross-domain threats.

Forecasts predict public cloud spending will soar to over $720 billion by 2025, with 90%[1] of organizations embracing a hybrid cloud approach by 2027. These figures could also be eclipsed as more businesses unearth the potential impact that AI can make on their productivity. The pace of evolution is staggering, but one thing hasn’t changed: the cloud security market is a maze of complexity. Filled with acronyms, overlapping capabilities, and endless use cases tailored to every buyer persona.

On top of this, organizations face a fragmented landscape of security tools, each designed to cover just one slice of the cloud security puzzle. Then there’s CNAPP (Cloud-Native Application Protection Platform) — a broad platform promising to do it all but often falling short, especially around providing runtime detection and response capabilities. It’s no wonder organizations struggle to cut through the noise and find the precision they require.

Looking more closely at what CNAPP has to offer, it can feel like as if it is all you would ever need, but is that really the case?

Strengths and limitations of CNAPP

A CNAPP is undeniably a compelling solution, originally coming from CSPM (Cloud Security Posture Management), it provided organizations with a snapshot of their deployed cloud assets, highlighting whether they were as secure as intended. However, this often resulted in an overwhelming list of issues to fix, leaving organizations unsure where to focus their energy for maximum impact.

To address this, CNAPP’s evolved, incorporating capabilities like; identifying software vulnerabilities, mapping attack paths, and understanding which identities could act within the cloud. The goal became clear: prioritize fixes to reduce the risk of compromise.

But what if we could avoid these problems altogether? Imagine deploying software securely from the start — preventing the merging of vulnerable packages and ensuring proper configurations in production environments by shifting left. This preventative approach is vital to any “secure by design” strategy, CNAPP’s again evolving to add this functionality alongside.

However, as applications grow more complex, so do the variety and scope of potential issues. The responsibility for addressing these challenges often falls to engineers, who are left balancing the pressure to write code with the burden of fixing critical findings that may never even pose a real risk to the organization.

While CNAPP serves as an essential risk prevention tool — focusing on hygiene, compliance, and enabling organizations to deploy high-quality code on well-configured infrastructure — its role is largely limited to reducing the potential for issues. Once applications and infrastructure are live, the game changes. Security’s focus shifts to detecting unwanted activity and responding to real-time risks.

Limitations of CNAPP

Here’s where CNAPP shows its limitations:

1. Blind spots for on-premises workloads

Designed for cloud-native environments, it can leave blind spots for workloads that remain on-premises — a significant concern given that 90% of organizations are expected to adopt a hybrid cloud strategy by 2027. These blind spots can increase the risk of cross-domain attacks, underscoring the need for a solution that goes beyond purely prevention but adds real-time detection and response.

2. Detecting and mitigating cross-domain threats

Adversaries have evolved to exploit the complexity of hybrid and cloud environments through cross-domain attacks. These attacks span multiple domains — including traditional network environments, identity systems, SaaS platforms, and cloud environments — making them exceptionally difficult to detect and mitigate. Attackers are human and will naturally choose the path of least resistance, why spend time writing a detailed software exploit for a vulnerability if you can just target the identity?

Imagine a scenario where an attacker compromises an organization via leaked credentials and then moves laterally, similar to the example outlined in this blog: The Price of Admission: Countering Stolen Credentials with Darktrace. If an attacker identifies cloud credentials and moves into the cloud control plane, they could access additional sensitive data. Without a detection platform that monitors these areas for unusual activity, while working to consolidate findings into a unified timeline, detecting these types of attacks becomes incredibly challenging.

A CNAPP might only point to a potential misconfiguration of an identity or for example a misconfiguration around secret storage, but it cannot detect when that misconfiguration has been exploited — let alone respond to it.

Identity + Network: Unlocking cross-domain threats

Identity is more than just a role or username; it is essentially an access point for attackers to leverage and move between different areas of a digital estate. Real-time monitoring of human and non-human identities is crucial for understanding intent, spotting anomalies, and preventing possible attacks before they spread.

Non-human roles, such as service accounts or automation tooling, often operate with trust and without oversight. In 2024, the Cybersecurity and Critical Infrastructure Agency (CISA) [2] released a warning regarding new strategies employed by SolarWinds attackers. These strategies were primarily aimed at cloud infrastructure and non-human identities. The warning details how attackers leverage credentials and valid applications for malicious purposes.

With organizations opting for a hybrid approach, combining network, identity, cloud management and cloud runtime activity is essential to detecting and mitigating cross domain attacks, these are just some of the capabilities needed for effective detection and response:

  • AI driven automated and unified investigation of events – due to the volume of data and activity within businesses digital estates leveraging AI is vital, to enable SOC teams in understanding and facilitating proportional and effective responses.
  • Real-time monitoring auditing combined with anomaly detection for human and non-human identities.
  • A unified investigation platform that can deliver a real-time understanding of Identity, deployed cloud assets, runtime and contextual findings as well as coverage for remaining on premises workloads.
  • The ability to leverage threat intelligence automatically to detect potential malicious activities quickly.

The future of cloud security: Balancing risk management with real-time detection and response

Darktrace / CLOUD's CDR approach enhances CNAPP by providing the essential detection and native response needed to protect against cross-domain threats. Its agentless, default setup is both cost-effective and scalable, creating a runtime baseline that significantly boosts visibility for security teams. While proactive controls are crucial for cloud security, pairing them with Cloud Detection and Response solutions addresses a broader range of challenges.

With Darktrace / CLOUD, organizations benefit from continuous, real-time monitoring and advanced AI-driven behavioural detection, ensuring proactive detection and a robust cloud-native response. This integrated approach delivers comprehensive protection across the digital estate.

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Download the Darktrace / CLOUD solution brief to discover how autonomous, AI-driven defense can secure your environment in real-time.

  • Achieve 60% more accurate detection of unknown and novel cloud threats.
  • Respond instantly with autonomous threat response, cutting response time by 90%.
  • Streamline investigations with automated analysis, improving ROI by 85%.
  • Gain a 30% boost in cloud asset visibility with real-time architecture modeling.
  • References

    1. https://www.gartner.com/en/newsroom/press-releases/2024-11-19-gartner-forecasts-worldwide-public-cloud-end-user-spending-to-total-723-billion-dollars-in-2025
    2. https://www.cisa.gov/news-events/cybersecurity-advisories/aa24-057a
    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.
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    Adam Stevens
    Director of Product, Cloud Security
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    February 19, 2025

    Darktrace Releases Annual 2024 Threat Insights

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    Introduction: Darktrace’s threat research

    Defenders must understand the threat landscape in order to protect against it. They can do that with threat intelligence.

    Darktrace approaches threat intelligence with a unique perspective. Unlike traditional security vendors that rely on established patterns from past incidents, it uses a strategy that is rooted in the belief that identifying behavioral anomalies is crucial for identifying both known and novel threats.

    For Darktrace analysts and researchers, the incidents detected by the AI solution mark the beginning of a deeper investigation, aiming to connect mitigated threats to wider trends from across the threat landscape. Through hindsight analysis, the Darktrace Threat Research team has highlighted numerous threats, including zero-day, n-day, and other novel attacks, showcasing their evolving nature and Darktrace’s ability to identify them.

    In 2024, the Threat Research team observed major trends around vulnerabilities in internet-facing systems, new and re-emerging ransomware strains, and sophisticated email attacks. Read on to discover some of our key insights into the current cybersecurity threat landscape.

    Multiple campaigns target vulnerabilities in internet-facing systems

    It is increasingly common for threat actors to identify and exploit newly discovered vulnerabilities in widely used services and applications, and in some cases, these vulnerability exploitations occur within hours of disclosure.

    In 2024, the most significant campaigns observed involved the ongoing exploitation of zero-day and n-day vulnerabilities in edge and perimeter network technologies. In fact, in the first half of the year, 40% of all identified campaign activity came from the exploitation of internet-facing devices. Some of the most common exploitations involved Ivanti Connect Secure (CS) and Ivanti Policy Secure (PS) appliances, Palo Alto Network (PAN-OS) firewall devices, and Fortinet appliances.

    Darktrace helps security teams identify suspicious behavior quickly, as demonstrated with the critical vulnerability in PAN-OS firewall devices. The vulnerability was publicly disclosed on April 11, 2024, yet with anomaly-based detection, Darktrace’s Threat Research team was able to identify a range of suspicious behavior related to exploitation of this vulnerability, including command-and-control (C2) connectivity, data exfiltration, and brute-forcing activity, as early as March 26.

    That means that Darktrace and our Threat Research team detected this Common Vulnerabilities and Exposure (CVE) exploitation 16 days before the vulnerability was disclosed. Addressing critical vulnerabilities quickly massively benefits security, as teams can reduce their effectiveness by slowing malicious operations and forcing attackers to pursue more costly and time-consuming methods.

    Persistent ransomware threats continue to evolve

    The continued adoption of the Ransomware-as-a-Service (RaaS) model provides even less experienced threat actors with the tools needed to carry out disruptive attacks, significantly lowering the barrier to entry.

    The Threat Research team tracked both novel and re-emerging strains of ransomware across the customer fleet, including Akira, LockBit, and Lynx. Within these ransomware attempts and incidents, there were notable trends in attackers’ techniques: using phishing emails as an attack vector, exploiting legitimate tools to mask C2 communication, and exfiltrating data to cloud storage services.

    Read the Annual 2024 Threat Report for the complete list of prominent ransomware actors and their commonly used techniques.

    Onslaught of email threats continues

    With a majority of attacks originating from email, it is crucial that organizations secure the inboxes and beyond.

    Between December 21, 2023, and December 18, 2024, Darktrace / EMAIL detected over 30.4 million phishing emails across the fleet. Of these, 70% successfully bypassed Domain-based Message Authentication, Reporting, and Conformance (DMARC) verification checks and 55% passed through all other existing layers of customer email security.

    The abuse of legitimate services and senders continued to be a significant method for threat actors throughout 2024. By leveraging trusted platforms and domains, malicious actors can bypass traditional security measures and increase the likelihood of their phishing attempts being successful.

    This past year, there was a substantial use of legitimately authenticated senders and previously established domains, with 96% of phishing emails detected by Darktrace / EMAIL utilizing existing domains rather than registering new ones.

    These are not the only types of email attacks we observed. Darktrace detected over 2.7 million emails with multistage payloads.

    While most traditional cybersecurity solutions struggle to cover multiple vectors and recognize each stage of complex attacks as part of wider malicious activity, Darktrace can detect and respond across email, identities, network, and cloud.

    Conclusion

    The Darktrace Threat Research team continues to monitor the ever-evolving threat landscape. Major patterns over the last year have revealed the importance of fast-acting, anomaly-based detection like Darktrace provides.

    For example, response speed is essential when campaigns target vulnerabilities in internet-facing systems, and these vulnerabilities can be exploited by attackers within hours of their disclosure if not even before that.

    Similarly, anomaly-based detection can identify hard to find threats like ransomware attacks that increasingly use living-off-the-land techniques and legitimate tools to hide malicious activity. A similar pattern can be found in the realm of email security, where attacks are also getting harder to spot, especially as they frequently exploit trusted senders, use redirects via legitimate services, and craft attacks that bypass DMARC and other layers of email security.

    As attacks appear with greater complexity, speed, and camouflage, defenders must have timely detection and containment capabilities to handle all emerging threats. These hard-to-spot attacks can be identified and stopped by Darktrace.

    Download the full report

    Discover the latest threat landscape trends and recommendations from the Darktrace Threat Research team.

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    The Darktrace Threat Research Team

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    February 18, 2025

    Unifying IT & OT With AI-Led Investigations for Industrial Security

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    As industrial environments modernize, IT and OT networks are converging to improve efficiency, but this connectivity also creates new attack paths. Previously isolated OT systems are now linked to IT and cloud assets, making them more accessible to attackers.

    While organizations have traditionally relied on air gaps, firewalls, data diodes, and access controls to separate IT and OT, these measures alone aren’t enough. Threat actors often infiltrate IT/Enterprise networks first then exploit segmentation, compromising credentials, or shared IT/OT systems to move laterally, escalate privileges, and ultimately enter the OT network.

    To defend against these threats, organizations must first ensure they have complete visibility across IT and OT environments.

    Visibility: The first piece of the puzzle

    Visibility is the foundation of effective industrial cybersecurity, but it’s only the first step. Without visibility across both IT and OT, security teams risk missing key alerts that indicate a threat targeting OT at their earliest stages.

    For Attacks targeting OT, early stage exploits often originate in IT environments, adversaries perform internal reconnaissance among other tactics and procedures but then laterally move into OT first affecting IT devices, servers and workstations within the OT network. If visibility is limited, these threats go undetected. To stay ahead of attackers, organizations need full-spectrum visibility that connects IT and OT security, ensuring no early warning signs are missed.

    However, visibility alone isn’t enough. More visibility also means more alerts, this doesn’t just make it harder to separate real threats from routine activity, but bogs down analysts who have to investigate all these alerts to determine their criticality.

    Investigations: The real bottleneck

    While visibility is essential, it also introduces a new challenge: Alert fatigue. Without the right tools, analysts are often occupied investigating alerts with little to no context, forcing them to manually piece together information and determine if an attack is unfolding. This slows response times and increases the risk of missing critical threats.

    Figure 1: Example ICS attack scenario

    With siloed visibility across IT and OT each of these events shown above would be individually alerted by a detection engine with little to no context nor correlation. Thus, an analyst would have to try to piece together these events manually. Traditional security tools struggle to keep pace with the sophistication of these threats, resulting in an alarming statistic: less than 10% of alerts are thoroughly vetted, leaving organizations vulnerable to undetected breaches. As a result, incidents inevitably follow.

    Darktrace’s Cyber AI Analyst uses AI-led investigations to improve workflows for analysts by automatically correlating alerts wherever they occur across both IT and OT. The multi-layered AI engine identifies high-priority incidents, and provides analysts with clear, actionable insights, reducing noise and highlighting meaningful threats. The AI significantly alleviates workloads, enabling teams to respond faster and more effectively before an attack escalates.

    Overcoming organizational challenges across IT and OT

    Beyond technical challenges like visibility and alert management, organizational dynamics further complicate IT-OT security efforts. Fundamental differences in priorities, workflows, and risk perspectives create challenges that can lead to misalignment between teams:

    Non-transferable practices: IT professionals might assume that cybersecurity practices from IT environments can be directly applied to OT environments. This can lead to issues, as OT systems and workflows may not handle IT security processes as expected. It's crucial to recognize and respect the unique requirements and constraints of OT environments.

    Segmented responsibilities: IT and OT teams often operate under separate organizational structures, each with distinct priorities, goals, and workflows. While IT focuses on data security, network integrity, and enterprise applications, OT prioritizes uptime, reliability, and physical processes.

    Different risk perspectives: While IT teams focus on preventing cyber threats and regulatory violations, OT teams prioritize uptime and operational reliability making them drawn towards asset inventory tools that provide no threat detection capability.

    Result: A combination of disparate and ineffective tools and misaligned teams can make any progress toward risk reduction at an organization seem impossible. The right tools should be able to both free up time for collaboration and prompt better communication between IT and OT teams where it is needed. However, different size operations structure their IT and OT teams differently which impacts the priorities for each team.

    In real-world scenarios, small IT teams struggle to manage security across both IT and OT, while larger organizations with OT security teams face alert fatigue and numerous false positives slowing down investigations and hindering effective communication with the IT security teams.

    By unifying visibility and investigations, Darktrace / OT helps organizations of all sizes detect threats earlier, streamline workflows, and enhance security across both IT and OT environments. The following examples illustrate how AI-driven investigations can transform security operations, improving detection, investigation, and response.

    Before and after AI-led investigation

    Before: Small manufacturing company

    At a small manufacturing company, a 1-3 person IT team juggles everything from email security to network troubleshooting. An analyst might see unusual traffic through the firewall:

    • Unusual repeated outbound traffic from an IP within their OT network destined to an unidentifiable external IP.

    With no dedicated OT security tools and limited visibility into the industrial network, they don’t know what the internal device in question is, if it is beaconing to a malicious external IP, and what it may be doing to other devices within the OT network. Without a centralized dashboard, they must manually check logs, ask operators about changes, and hunt for anomalies across different systems.

    After a day of investigation, they concluded the traffic was not to be expected activity. They stop production within their smaller OT network, update their firewall rules and factory reset all OT devices and systems within the blast radius of the IP device in question.

    After: Faster, automated response with Cyber AI Analyst

    With Darktrace / OT and Cyber AI Analyst, the IT team moves from reactive, manual investigations to proactive, automated threat detection:

    • Cyber AI Analyst connects alerts across their IT and OT infrastructure temporally mapping them to attack frameworks and provides contextual analysis of how alerts are linked, revealing in real time attackers attempting lateral movement from IT to OT.
    • A human-readable incident report explains the full scope of the incident, eliminating hours of manual investigation.
    • The team is faster to triage as they are led directly to prioritized high criticality alerts, now capable of responding immediately instead of wasting valuable time hunting for answers.

    By reducing noise, providing context, and automating investigations, Cyber AI Analyst transforms OT security, enabling small IT teams to detect, understand, and respond to threats—without deep OT cybersecurity expertise.

    Before: Large critical infrastructure organization

    In large critical infrastructure operations, OT and IT teams work in separate silos. The OT security team needs to quickly assess and prioritize alerts, but their system floods them with notifications:

    • Multiple new device connected to the ICS network alerts
    • Multiple failed logins to HMI detected
    • Multiple Unusual Modbus/TCP commands detected
    • Repeated outbound OT traffic to IT destinations

    At first glance, these alerts seem important, but without context, it’s unclear whether they indicate a routine error, a misconfiguration, or an active cyber-attack. They might ask:

    • Are the failed logins just a mistake, or a brute-force attempt?
    • Is the outbound traffic part of a scheduled update, or data exfiltration?

    Without correlation across events, the engineer must manually investigate each one—checking logs, cross-referencing network activity, and contacting operators—wasting valuable time. Meanwhile, if it’s a coordinated attack, the adversary may already be disrupting operations.

    After: A new workflow with Cyber AI Analyst

    With Cyber AI Analyst, the OT security team gets clear, automated correlation of security events, making investigations faster and more efficient:

    • Automated correlation of OT threats: Instead of isolated alerts, Cyber AI Analyst stitches together related events, providing a single, high-confidence incident report that highlights key details.
    • Faster time to meaning: The system connects anomalous behaviors (e.g., failed logins, unusual traffic from an HMI, and unauthorized PLC modifications) into a cohesive narrative, eliminating hours of manual log analysis.
    • Prioritized and actionable alerts: OT security receives clear, ranked incidents, immediately highlighting what matters most.
    • Rapid threat understanding: Security teams know within minutes whether an event is a misconfiguration or a cyber-attack, allowing for faster containment.

    With Cyber AI Analyst, large organizations cut through alert noise, accelerate investigations, and detect threats faster—without disrupting OT operations.

    An AI-led approach to industrial cybersecurity

    Security vendors with a primary focus on IT may lack insight into OT threats. Even OT-focused vendors have limited visibility into IT device exploitation within OT networks, leading to failed ability to detect early indicators of compromise. A comprehensive solution must account for the unique characteristics of various OT environments.

    In a world where industrial security is no longer just about protecting OT but securing the entire digital-physical ecosystem as it interacts with the OT network, Darktrace / OT is an AI-driven solution that unifies visibility across IT, IoT and OT, Cloud into one cohesive defense strategy.

    Whether an attack originates from an external breach, an insider threat, a supply chain compromise, in the Cloud, OT, or IT domains Cyber AI Analyst ensures that security teams see the full picture - before disruption occurs.

    Learn more about Darktrace / OT 

    • Unify IT and OT security under a single platform, ensuring seamless communication and protection for all interconnected devices.
    • Maintain uptime with AI-driven threat containment, stopping attacks without disrupting production.
    • Mitigate risks with or without patches, leveraging MITRE mitigations to reduce attack opportunities.

    Download the solution brief to see how Darktrace secures critical infrastructure.

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    About the author
    Daniel Simonds
    Director of Operational Technology
    Your data. Our AI.
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