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August 4, 2019

Lessons from the Capital One Breach on Cloud Security

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Aug 2019
Explore the implications of the Capital One breach on cloud security and strategies for improving your organization's defenses.

By all accounts, Capital One defended its customers’ data with the imposing array of cyber security tools that you’d expect from one of the largest banks in the United States. And yet a lone hacker managed to bypass those tools and obtain the sensitive personal information of more than one hundred million people, a breach that will likely cost the bank well over a hundred million dollars when all is said and done.

The hacker — a former employee of Amazon Web Services, which hosted the data that was exfiltrated — gained access to the sensitive files by exploiting a misconfiguration in one of Capital One’s application firewalls. This firewall was meant to secure a Capital One web application and when the hacker found the misconfiguration vulnerability, they were able to steal critical passwords. This initial credential compromise allowed the threat actor to escalate privileges and consequently gain access to the valuable AWS-hosted data.

Such customer-side cloud security misconfigurations have become a favorite target for cyber-criminals. In fact, Gartner predicts that 99% of cloud security failures through 2023 will have occurred in the customer’s portion of the Shared Responsibility Model.

The fundamental flaw

At a time when virtually all enterprises have adopted cloud infrastructures that expand and evolve as needed, configuring firewalls and other endpoint protections to remain properly positioned can be a daunting challenge. Moreover, modern developers now have the ability to spin up a cloud instance in minutes, often without having to consult their firm’s security team. As a consequence of the speed, scale, and complexity of development in cloud ecosystems, the overwhelming majority of organizations lack visibility over their own cloud environments.

While nearly half of organizations don’t even bother looking for malware on the cloud, Capital One had a relatively mature cloud security posture — at least by traditional standards. It is therefore all the more alarming that the bank didn’t become aware of the breach until more than three months after the fact, when it received a tip from an outsider who’d stumbled upon the stolen data. That a major financial institution was blind to this level of compromise demonstrates the urgency of rethinking cloud security.

Cloud platforms are changing the network perimeter paradigm, complexifying digital borders and creating new threat surfaces. Meanwhile, cloud security controls that offer a static, rules-based approach fail to respond to this new landscape and protect against today’s attacks.

Of course, there is no silver bullet when it comes to cyber defense — and that goes double for the cloud. Motivated attackers will inevitably find a way inside the dynamic perimeters of IaaS and SaaS environments, whether via insider knowledge, critical misconfigurations, personalized phishing emails, or mechanisms that have yet to be seen. The path forward, then, is to use artificial intelligence to understand how users behave across digital infrastructure, an understanding that shines a light on the subtle behavioral shifts indicative of a threat.

Demystifying the cloud

The latest Cyber AI security tools aim to do just that: observing traffic activity across AWS and other CSPs to learn an evolving sense how each unique company uses their cloud environment. Indeed, this ability to distinguish between normal and abnormal behavior proved decisive when a financial services company using Darktrace AI to secure their cloud ecosystem faced an attack strikingly similar to the Capital One breach. The firm was hosting a number of critical applications on virtual machines in the cloud — some of which were meant to be public-facing, some of which were not. When configuring its native cloud controls, however, the firm mistakenly left one of its private applications exposed to the Internet, rather than isolated behind a firewall.

The exposed application was eventually discovered and targeted by cyber-criminals who were scanning the Internet via Shodan, a search engine that locates Internet-connected assets. Within seconds, Darktrace’s AI detected that the application was receiving an unusual amount of incoming connection attempts from a wide range of rare external sources and alerted the security team — which had been unaware of the misconfiguration. This “unusual” volume of “rare” connections might well have been normal for a different company, application or virtual machine, but Cyber AI’s bespoke knowledge of ‘self’ for the organization revealed the activity to be anomalous in this exact case.

By employing such AI systems, we can gain the necessary knowledge of complex cloud environments to catch threats in their nascent stages — before they escalate into crises. Ultimately, the cloud promises to unlock new heights of efficiency and novel forms of collaboration, so long as we’re willing to adopt equally innovative security tools. Because while there may never be a silver bullet for safeguarding cloud services, AI does offer hope for a silver lining.

Correction: An earlier version of this blog characterized cloud infrastructure as ‘borderless’; it has since been edited with attention to the complexity of the changing network perimeter paradigm presented by cloud infrastructure.

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
Justin Fier
SVP, Red Team Operations

Justin is one of the US’s leading cyber intelligence experts, and holds the position of SVP, Red Team Operations at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years’ experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.

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April 4, 2025

Darktrace Named as Market Leader in the 2025 Omdia Market Radar for OT Cybersecurity Platforms

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We are pleased to announce that Darktrace / OT has been named a Market Leader in Omdia’s  2025 Market Radar for OT Cybersecurity Platforms. We believe this highlights our unique capabilities in the OT security market and follows similar recognition from Gartner who recently named Darktrace / OT as the sole Visionary in in the Magic Quadrant for Cyber Physical Systems (CPS) Protection Platforms market.

Historically, IT and OT systems have been managed separately, creating challenges due to the differences of priorities between the two domains. While both value availability, IT emphasizes confidentiality and integrity whereas OT focuses on safety and reliability. Organizations are increasingly converging these systems to reap the benefits of automation, efficiency, and productivity (1).

Omdia’s research highlights that decision makers are increasingly prioritizing comprehensive security coverage, centralized management, and advanced cybersecurity capabilities when selecting OT security solutions (1).

Rising productivity demands have driven the convergence of OT, IT, and cloud-connected systems, expanding attack surfaces and exposing vulnerabilities. Darktrace / OT provides a comprehensive OT security solution, purpose-built for critical infrastructure, offering visibility across OT, IoT, and IT assets, bespoke risk management, and industry-leading threat detection and response powered by Self-Learning AITM.

Figure 1: Omdia vendor overview for OT cybersecurity platforms
Figure 1: Omdia vendor overview for OT cybersecurity platforms

An AI-first approach to OT security  

Many OT security vendors have integrated AI into their offerings, often leveraging machine learning for anomaly detection and threat response. However, only a few have a deep-rooted history in AI, with longstanding expertise shaping their approach beyond surface-level adoption.

The Omdia Market Radar recognizes that Darktrace has extensive background in the AI space:

“Darktrace has invested extensively in AI research to fuel its capabilities since 2013 with 200-plus patent applications, providing anomaly detection with a significant level of customization, helping with SOC productivity and efficiency, streamlining to show what matters for OT.” (1)

Unlike other security approaches that rely on existing threat data, Darktrace / OT achieves this through Self-Learning AI that understands normal business operations, detecting and containing known and unknown threats autonomously, thereby reducing Sec Ops workload and ensuring minimal downtime

This approach extends to incident investigations where an industry-first Cyber AI AnalystTM automatically investigates all relevant threats across IT and OT, prioritizes critical incidents, and then summarizes findings in an easily understandable view—bringing production engineers and security analysts together to communicate and quickly take appropriate action.

Balancing autonomous response with human oversight

In OT environments where uptime is essential, autonomous response technology can be approached with apprehension. However, Darktrace offers customizable response actions that can be set to “human confirmation mode.”

Omdia recognizes that our approach provides customizable options for autonomous response:

“Darktrace’s autonomous response functionality enforces normal, expected behavior. This can be automated but does not need to be from the beginning, and it can be fine-tuned. Alternative step-by-step mitigations are clearly laid out step-by-step and updated based on organizational risk posture and current level of progress.” (1)

This approach allows security and production to keep humans-in-the-loop with pre-defined actions for potential attacks, enforcing normal to contain a threat, and allowing production to continue without disruption.  

Bespoke vulnerability and risk management

In the realm of OT security, asset management takes precedent as one of the key focus points for organizations. With a large quantity of assets to manage, practitioners are overwhelmed with information with no real way to prioritize or apply them to their unique environment.

Darktrace / OT is recognized by Omdia as having:

“Advanced risk management capabilities that showcase metrics on impact, exploit difficulty, and estimated cost of an attack […] Given the nascency of this capability (April 2024), it is remarkably granular in depth and insight.” (1)

Enabling this is Darktrace’s unique approach to AI extends to risk management capabilities for OT. Darktrace / OT understands customers’ unique risks by building a comprehensive and contextualized picture that goes beyond isolated CVE scoring. It combines attack path modeling with MITRE ATT&CK  techniques to provide hardening recommendations regardless of patching availability and gives you a clearer view of the potential impact of an attack from APT groups.

Modular, scalable security for industrial environments

Organizations need flexibility when it comes to OT security, some want a fully integrated IT-OT security stack, while others prefer a segregated approach due to compliance or operational concerns. The Darktrace ActiveAI Security Platform offers integrated security across multiple domains, allowing flexibility and unification across IT and OT security. The platform combines telemetry from all areas of your digital estate to detect and respond to threats, including OT, network, cloud, email, and user identities.

Omdia recognizes Darktrace’s expansive coverage across multiple domains as a key reason why organizations should consider Darktrace / OT:

“Darktrace’s modular and platform, approach offer’s integrated security across multiple domains. It offers the option of Darktrace / OT as a separate platform product for those that want to segregate IT and OT cybersecurity or are not yet in a position to secure both domains in tandem. The deployment of Darktrace’s platform is flexible—with nine different deployment options, including physical on-premises, virtual, cloud, and hybrid.” (1)

With flexible deployment options, Darktrace offers security teams the ability to choose a model that works best for their organization, ensuring that security doesn’t have to be a “one-size-fits-all” approach.

Conclusion: Why Darktrace / OT stands out in Omdia’s evaluation

Omdia’s 2025 Market Radar for OT Cybersecurity Platforms provides a technical-first, vendor-agnostic evaluation, offering critical insights for organizations looking to strengthen their OT security posture. Darktrace’s recognition as a Market Leader reinforces its unique AI-driven approach, flexible deployment options, and advanced risk management capabilities as key differentiators in an evolving threat landscape.

By leveraging Self-Learning AI, autonomous response, and real-world risk analysis, Darktrace / OT enables organizations to detect, investigate, and mitigate threats before they escalate, without compromising operational uptime.

Read the full report here!

References

  1. www.darktrace.com/resources/darktrace-named-a-market-leader-in-the-2025-omdia-market-radar-for-ot-cybersecurity-platforms
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About the author
Pallavi Singh
Product Marketing Manager, OT Security & Compliance

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Cloud

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April 2, 2025

Fusing Vulnerability and Threat Data: Enhancing the Depth of Attack Analysis

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Cado Security, recently acquired by Darktrace, is excited to announce a significant enhancement to its data collection capabilities, with the addition of a vulnerability discovery feature for Linux-based cloud resources. According to Darktrace’s Annual Threat Report 2024, the most significant campaigns observed in 2024 involved the ongoing exploitation of significant vulnerabilities in internet-facing systems. Cado’s new vulnerability discovery capability further deepens its ability to provide extensive context to security teams, enabling them to make informed decisions about threats, faster than ever.

Deep context to accelerate understanding and remediation

Context is critical when understanding the circumstances surrounding a threat. It can also take many forms – alert data, telemetry, file content, business context (for example asset criticality, core function of the resource), and risk context, such as open vulnerabilities.

When performing an investigation, it is common practice to understand the risk profile of the resource impacted, specifically determining open vulnerabilities and how they may relate to the threat. For example, if an analyst is triaging an alert related to an internet-facing Webserver running Apache, it would greatly benefit the analyst to understand open vulnerabilities in the Apache version that is running, if any of them are exploitable, whether a fix is available, etc. This dataset also serves as an invaluable source when developing a remediation plan, identifying specific vulnerabilities to be prioritised for patching.

Data acquisition in Cado

Cado is the only platform with the ability to perform full forensic captures as well as utilize instant triage collection methods, which is why fusing host-based artifact data with vulnerability data is such an exciting and compelling development.

The vulnerability discovery feature can be run as part of an acquisition – full or triage – as well as independently using a fast ‘Scan only’ mode.

Figure 1: A fast vulnerability scan being performed on the acquired evidence

Once the acquisition has completed, the user will have access to a ‘Vulnerabilities’ table within their investigation, where they are able to view and filter open vulnerabilities (by Severity, CVE ID, Resource, and other properties), as well as pivot to the full Event Timeline. In the Event Timeline, the user will be able to identify whether there is any malicious, suspicious or other interesting activity surrounding the vulnerable package, given the unified timeline presents a complete chronological dataset of all evidence and context collected.

Figure 2: Vulnerabilities discovered on the acquired evidence
Figure 3: Pivot from the Vulnerabilities table to the Event Timeline provides an in-depth view of file and process data associated with the vulnerable package selected. In this example, Apache2.

Future work

In the coming months, we’ll be releasing initial versions of highly anticipated integrations between Cado and Darktrace, including the ability to ingest Darktrace / CLOUD alerts which will automatically trigger a forensic capture (as well as a vulnerability discovery) of the impacted assets.

To learn more about how Cado and Darktrace will combine forces, request a demo today.

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About the author
Paul Bottomley
Director of Product Management, Cado
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