Blog
/
/
April 8, 2025

Cloud Security Evolution: Why Security Teams are Taking the Lead

While many internal teams contribute to general cloud hygiene, the security team has increasingly taken the lead on cloud security. Learn how AI-powered cloud detection and response tools can help these teams with new responsibilities.
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
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
person on computer cybersecurityDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
08
Apr 2025

Cloud adoption is rapidly on the rise. Gartner estimates that 90% of organizations will adopt hybrid clouds through 2027 [1].  

There are many reasons why organizations are migrating on-premises infrastructure to the cloud. It can increase the speed and scale of computing resources, improve reliability and resilience, and save time by outsourcing the spinning up, patching, and updating of infrastructure.  

However, despite these benefits, it is complex to secure. Public clouds operate with a shared responsibility model, meaning that while the Cloud Service Provider (CSP) maintains the physical infrastructure and services, customer organizations are responsible for their own security and compliance in their cloud deployments.  

This customer responsibility is crucial. Gartner forecasted that through 2025, 99% of cloud security failures would be the customer’s fault [2]. As cloud environments grow, security teams are taking on a greater share of the responsibility to protect these assets.

The many teams involved in cloud security

Several teams work across the cloud, and all of them can contribute to cloud security. For example, basic cyber-hygiene and Identity and Access Management (IAM) should be practiced across teams.  

Not every organization has the same categorization of teams, but some common ones include:

  • Security: assessing and mitigating vulnerabilities, risks, and threats. This team must be ready to identify, investigate, respond, and recover from incidents.
  • Infrastructure and ITOps: deploying and maintaining resources. Security must be considered across all layers of the cloud, including gateways, identity, encryption, and attack surface.
  • Research & development: building cloud-based applications. Security must be baked into code, referenced data, access, APIs, and third-party integrations.
  • DevOps: improving the software development process. Security must be applied to code across the development and production stages.
  • Compliance: adhering to industry standards and frameworks. Security often comes up in compliance regulations.  
  • End users: working in the cloud. Security must be taught through employee training sessions to adopt best practices and increase resistance against threats like phishing or data loss.

Traditionally, many organizations left cloud security to dedicated cloud teams. However, it is becoming more and more common for security teams to take on the responsibilities of securing the cloud. This is also true of organizations undergoing cloud migration and spinning up cloud infrastructure for the first time.

The complexity of cloud security

Most organizations using the cloud today have hybrid and/or multi-cloud deployments. Hybrid deployments combine public and private cloud environments and multi-cloud deployments use a combination of public cloud providers or regions where servers are stored. In fact, Deloitte reports that as many as 85% of businesses, a vast majority, use two or more cloud platforms, and 25% use at least five [3].

While these diverse deployments can boost resiliency, they also complicate security. Multiple environments increase the attack surface and reduce architectural visibility, making misconfigurations, unmanaged access, and inconsistent policies more likely. This complexity creates gaps in security that often require specialized teams and expert personnel to address.  

Challenges driving security teams’ responsibility

The usual approaches to other types of cybersecurity can’t be applied the exact same way to the cloud. With the inherent dynamism and flexibility of the cloud, the necessary security mindset differs greatly from those for networks or data centers, with which security teams may be more familiar.

For example, IAM is both critical and distinct to cloud computing, and the associated policies, rules, and downstream impacts require intentional care. IAM rules not only govern people, but also non-human entities like service accounts, API keys, and OAuth tokens. These considerations are unique to cloud security, and established teams may need to learn new skills to reduce security gaps in the cloud.

Additionally, there are greater compliance pressures from GDPR, CCPA, and industry-specific regulations. While some companies have dedicated compliance teams, not every organization does and others are not always familiar with working in cloud environments. In these cases, responsibilities may fall to the security team.  

Finally, there has been a rise in sophisticated, cloud-based threats, such as account takeovers and misconfigurations. Preparing, responding to, and recovering from these cloud-specific threats lie with the security team as well.  

Learn more about the top risks and attacks faced in the cloud in the white paper: “Tackling the 11 Biggest Cloud Threats with AI-Powered Defense.

Solutions empowering security teams

The leading role of security teams in cloud security can put a strain on existing resources as well as exacerbate skills gaps. In response, security teams can turn to AI-powered tools like Darktrace / CLOUD to provide real-time detection and response in cloud environments.  

Darktrace uses multi-layered AI to learn normal ‘patterns of life’ for all users, technologies, and resources across the organization, enabling it to recognize the subtlest anomalies that point to an emerging threat.  

The use of AI allows for automation that reduces manual workloads and saves teams time. The self-learning capabilities also help the human team detect subtle indicators that can be hard to spot amid the immense noise of legitimate, day-to-day digital interactions.

With these, Darktrace can respond to both known and novel threats, helping security teams keep pace with today’s sophisticated threats, even if team members feel less confident in cloud environments.  

Crucially, Darktrace / CLOUD can enable proactive risk management as well. Attack Path Modeling for the cloud identifies exposed assets and highlights internal attack paths to give a dynamic view of the riskiest paths across cloud environments, network environments, and between – enabling security teams to prioritize based on unique business risk and address gaps to prevent future attacks.  

Darktrace / CLOUD dynamically adjusts its focus based on evolving risks, analyzing misconfigurations, and anomalous activity to prevent potential attacks. Its Entitlement Enumeration capability helps security teams gain visibility into all identities, roles, and permissions, allowing dynamic adjustments to stop insider threats and lateral movement.

In these ways, the AI-powered Darktrace / CLOUD can support security teams as they take on the lion’s share of responsibility in securing the cloud, regardless of any resource limitations or skills gaps.

Conclusion

Cloud security is both vital under the shared responsibility model and complex with hybrid and multi-cloud deployments and strict regulatory demands. While many teams contribute to cloud security, more and more responsibilities are shifting to security teams specifically.

AI-powered solutions that can detect and respond to threats spanning a wide range of risks and attack types can support security teams as they protect dynamic cloud environments. By adopting real-time cloud detection and response tools, security teams have more time to dedicate to proactive projects and high-level tasks as well as reduced burden on less specialized team members.  

Discover how advanced AI solutions like Darktrace / CLOUD can address evolving cloud security needs in the solution brief.  

Read more about the latest trends in cloud security in the blog “Protecting Your Hybrid Cloud: The Future of Cloud Security in 2025 and Beyond.”

References:

1. Gartner, November 19, 2024, “Cloud End-User Spending to Total $723 Billion in 2025”  

2. Gartner, October 10, 2019, “Is the Cloud Secure?

3. Deloitte, December 6, 2022, “Above the clouds: Taming multicloud chaos”  

Protect Your Hybrid Cloud

Discover how advanced AI solutions like Darktrace / CLOUD can address evolving cloud security needs in this solution brief

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
Pallavi Singh
Product Marketing Manager, OT Security & Compliance

More in this series

No items found.

Blog

/

/

October 24, 2025

Patch Smarter, Not Harder: Now Empowering Security Teams with Business-Aligned Threat Context Agents

Patch Smarter, Not Harder: Now Empowering Security Teams with Business-Aligned Threat Context Agents Default blog imageDefault blog image

Most risk management programs remain anchored in enumeration: scanning every asset, cataloging every CVE, and drowning in lists that rarely translate into action. Despite expensive scanners, annual pen tests, and countless spreadsheets, prioritization still falters at two critical points.

Context gaps at the device level: It’s hard to know which vulnerabilities actually matter to your business given existing privileges, what software it runs, and what controls already reduce risk.

Business translation: Even when the technical priority is clear, justifying effort and spend in financial terms—especially across many affected devices—can delay action. Especially if it means halting other areas of the business that directly generate revenue.

The result is familiar: alert fatigue, “too many highs,” and remediation that trails behind the threat landscape. Darktrace / Proactive Exposure Management addresses this by pairing precise, endpoint‑level context with clear, financial insight so teams can prioritize confidently and mobilize faster.

A powerful combination: No-Telemetry Endpoint Agent + Cost-Benefit Analysis

Darktrace / Proactive Exposure Management now uniquely combines technical precision with business clarity in a single workflow.  With this release, Darktrace / Proactive Exposure Management delivers a more holistic approach, uniting technical context and financial insight to drive proactive risk reduction. The result is a single solution that helps security teams stay ahead of threats while reducing noise, delays, and complexity.

  • No-Telemetry Endpoint: Collects installed software data and maps it to known CVEs—without network traffic—providing device-level vulnerability context and operational relevance.
  • Cost-Benefit Analysis for Patching: Calculates ROI by comparing patching effort with potential exploit impact, factoring in headcount time, device count, patch difficulty, and automation availability.

Introducing the No-Telemetry Endpoint Agent

Darktrace’s new endpoint agent inventories installed software on devices and maps it to known CVEs without collecting network data so you can prioritize using real device context and available security controls.

By grounding vulnerability findings in the reality of each endpoint, including its software footprint and existing controls, teams can cut through generic severity scores and focus on what matters most. The agent is ideal for remote devices, BYOD-adjacent fleets, or environments standardizing on Darktrace, and is available without additional licensing cost.

Darktrace / Proactive Exposure Management user interface
Figure 1: Darktrace / Proactive Exposure Management user interface

Built-In Cost-Benefit Analysis for Patching

Security teams often know what needs fixing but stakeholders need to understand why now. Darktrace’s new cost-benefit calculator compares the total cost to patch against the potential cost of exploit, producing an ROI for the patch action that expresses security action in clear financial terms.

Inputs like engineer time, number of affected devices, patch difficulty, and automation availability are factored in automatically. The result is a business-aligned justification for every patching decision—helping teams secure buy-in, accelerate approvals, and move work forward with one-click ticketing, CSV export, or risk acceptance.

Darktrace / Proactive Exposure Management Cost Benefit Analysis
Figure 2: Darktrace / Proactive Exposure Management Cost Benefit Analysis

A Smarter, Faster Approach to Exposure Management

Together, the no-telemetry endpoint and Cost–Benefit Analysis advance the CTEM motion from theory to practice. You gain higher‑fidelity discovery and validation signals at the device level, paired with business‑ready justification that accelerates mobilization. The result is fewer distractions, clearer priorities, and faster measurable risk reduction. This is not from chasing every alert, but by focusing on what moves the needle now.

  • Smarter Prioritization: Device‑level context trims noise and spotlights the exposures that matter for your business.
  • Faster Decisions: Built‑in ROI turns technical urgency into executive clarity—speeding approvals and action.
  • Practical Execution: Privacy‑conscious endpoint collection and ticketing/export options fit neatly into existing workflows.
  • Better Outcomes: Close the loop faster—discover, prioritize, validate, and mobilize—on the same operating surface.

Committed to innovation

These updates are part of the broader Darktrace release, which also included:

1. Major innovations in cloud security with the launch of the industry’s first fully automated cloud forensics solution, reinforcing Darktrace’s leadership in AI-native security.

2. Darktrace Network Endpoint eXtended Telemetry (NEXT) is revolutionizing NDR with the industry’s first mixed-telemetry agent using Self-Learning AI.

3. Improvements to our OT product, purpose built for industrial infrastructure, Darktrace / OT now brings dedicated OT dashboard, segmentation-aware risk modeling, and expanded visibility into edge assets and automation protocols.

Join our Live Launch Event

When? 

December 9, 2025

What will be covered?

Join our live broadcast to experience how Darktrace is eliminating blind spots for detection and response across your complete enterprise with new innovations in Agentic AI across our ActiveAI Security platform. Industry leaders from IDC will join Darktrace customers to discuss challenges in cross-domain security, with a live walkthrough reshaping the future of Network Detection & Response, Endpoint Detection & Response, Email Security, and SecOps in novel threat detection and autonomous investigations.

Continue reading
About the author

Blog

/

/

October 24, 2025

Darktrace Announces Extended Visibility Between Confirmed Assets and Leaked Credentials from the Deep and Dark Web

Darktrace Announces Extended Visibility Between Confirmed Assets and Leaked Credentials from the Deep and Dark Web Default blog imageDefault blog image

Why exposure management needs to evolve beyond scans and checklists

The modern attack surface changes faster than most security programs can keep up. New assets appear, environments change, and adversaries are increasingly aided by automation and AI. Traditional approaches like periodic scans, static inventories, or annual pen tests are no longer enough. Without a formal exposure program, many businesses are flying blind, unaware of where the next threat may emerge.

This is where Continuous Threat Exposure Management (CTEM) becomes essential. Introduced by Gartner, CTEM helps organizations continuously assess, validate, and improve their exposure to real-world threats. It reframes the problem: scope your true attack surface, prioritize based on business impact and exploitability, and validate what attackers can actually do today, not once a year.

With two powerful new capabilities, Darktrace / Attack Surface Management helps organizations evolve their CTEM programs to meet the demands of today’s threat landscape. These updates make CTEM a reality, not just a strategy.

Too much data, not enough direction

Modern Attack Surface Management tools excel at discovering assets such as cloud workloads, exposed APIs, and forgotten domains. But they often fall short when it comes to prioritization. They rely on static severity scores or generic CVSS ratings, which do not reflect real-world risk or business impact.

This leaves security teams with:

  • Alert fatigue from hundreds of “critical” findings
  • Patch paralysis due to unclear prioritization
  • Blind spots around attacker intent and external targeting

CISOs need more than visibility. They need confidence in what to fix first and context to justify those decisions to stakeholders.

Evolving Attack Surface Management

Attack Surface Management (ASM) must evolve from static lists and generic severity scores to actionable intelligence that helps teams make the right decision now.

Joining the recent addition of Exploit Prediction Assessment, which debuted in late June 2025, today we’re introducing two capabilities that push ASM into that next era:

  • Exploit Prediction Assessment: Continuously validates whether top-priority exposures are actually exploitable in your environment without waiting for patch cycles or formal pen tests.  
  • Deep & Dark Web Monitoring: Extends visibility across millions of sources in the deep and dark web to detect leaked credentials linked to your confirmed domains.
  • Confidence Score: our newly developed AI classification platform will compare newly discovered assets to assets that are known to belong to your organization. The more these newly discovered assets look similar to assets that belong to your organization, the higher the score will be.

Together, these features compress the window from discovery to decision, so your team can act with precision, not panic. The result is a single solution that helps teams stay ahead of attackers without introducing new complexities.

Exploit Prediction Assessment

Traditional penetration tests are invaluable, but they’re often a snapshot of that point-in-time, are potentially disruptive, and compliance frameworks still expect them. Not to mention, when vulnerabilities are present, teams can act immediately rather than relying solely on information from CVSS scores or waiting for patch cycles.  

Unlike full pen tests which can be obtrusive and are usually done only a couple times per year, Exploit Prediction Assessment is surgical, continuous, and focused only on top issues Instead of waiting for vendor patches or the next pen‑test window. It helps confirm whether a top‑priority exposure is actually exploitable in your environment right now.  

For more information on this visit our blog: Beyond Discovery: Adding Intelligent Vulnerability Validation to Darktrace / Attack Surface Management

Deep and Dark Web Monitoring: Extending the scope

Customers have been asking for this for years, and it is finally here. Defense against the dark web. Darktrace / Attack Surface Management’s reach now spans millions of sources across the deep and dark web including forums, marketplaces, breach repositories, paste sites, and other hard‑to‑reach communities to detect leaked credentials linked to your confirmed domains.  

Monitoring is continuous, so you’re alerted as soon as evidence of compromise appears. The surface web is only a fraction of the internet, and a sizable share of risk hides beyond it. Estimates suggest the surface web represents roughly ~10% of all online content, with the rest gated or unindexed—and the TOR-accessible dark web hosts a high proportion of illicit material (a King’s College London study found ~57% of surveyed onion sites contained illicit content), underscoring why credential leakage and brand abuse often appear in places traditional monitoring doesn’t reach. Making these spaces high‑value for early warning signals when credentials or brand assets appear. Most notably, this includes your company’s reputation, assets like servers and systems, and top executives and employees at risk.

What changes for your team

Before:

  • Hundreds of findings, unclear what to start with
  • Reactive investigations triggered by incidents

After:

  • A prioritized backlog based on confidence score or exploit prediction assessment verification
  • Proactive verification of exposure with real-world risk without manual efforts

Confidence Score: Prioritize based on the use-case you care most about

What is it?

Confidence Score is a metric that expresses similarity of newly discover assets compared to the confirmed asset inventory. Several self-learning algorithms compare features of assets to be able to calculate a score.

Why it matters

Traditional Attack Surface Management tools treat all new discovery equally, making it unclear to your team how to identify the most important newly discovered assets, potentially causing you to miss a spoofing domain or shadow IT that could impact your business.

How it helps your team

We’re dividing newly discovered assets into separate insight buckets that each cover a slightly different business case.

  • Low scoring assets: to cover phishing & spoofing domains (like domain variants) that are just being registered and don't have content yet.
  • Medium scoring assets: have more similarities to your digital estate, but have better matching to HTML, brand names, keywords. Can still be phishing but probably with content.
  • High scoring assets: These look most like the rest of your confirmed digital estate, either it's phishing that needs the highest attention, or the asset belongs to your attack surface and requires asset state confirmation to enable the platform to monitor it for risks.

Smarter Exposure Management for CTEM Programs

Recent updates to Darktrace / Attack Surface Management directly advance the core phases of Continuous Threat Exposure Management (CTEM): scope, discover, prioritize, validate, and mobilize. The new Exploit Prediction Assessment helps teams validate and prioritize vulnerabilities based on real-world exploitability, while Deep & Dark Web Monitoring extends discovery into hard-to-reach areas where stolen data and credentials often surface. Together, these capabilities reduce noise, accelerate remediation, and help organizations maintain continuous visibility over their expanding attack surface.

Building on these innovations, Darktrace / Attack Surface Management empowers security teams to focus on what truly matters. By validating exploitability, it cuts through the noise of endless vulnerability lists—helping defenders concentrate on exposures that represent genuine business risk. Continuous monitoring for leaked credentials across the deep and dark web further extends visibility beyond traditional asset discovery, closing critical blind spots where attackers often operate. Crucially, these capabilities complement, not replace, existing security controls such as annual penetration tests, providing continuous, low-friction validation between formal assessments. The result is a more adaptive, resilient security posture that keeps pace with an ever-evolving threat landscape.

If you’re building or maturing a CTEM program—and want fewer open exposures, faster remediation, and better outcomes, Darktrace / Attack Surface Management’s new Exploit Prediction Assessment and Deep & Dark Web Monitoring are ready to help.

  • Want a more in-depth look at how Exploit Prediction Assessment functions? Read more here

Committed to innovation

These updates are part of the broader Darktrace release, which also included:

1. Major innovations in cloud security with the launch of the industry’s first fully automated cloud forensics solution, reinforcing Darktrace’s leadership in AI-native security.

2. Darktrace Network Endpoint eXtended Telemetry (NEXT) is revolutionizing NDR with the industry’s first mixed-telemetry agent using Self-Learning AI.

3. Improvements to our OT product, purpose built for industrial infrastructure, Darktrace / OT now brings dedicated OT dashboard, segmentation-aware risk modeling, and expanded visibility into edge assets and automation protocols.

Join our Live Launch Event

When? 

December 9, 2025

What will be covered?

Join our live broadcast to experience how Darktrace is eliminating blind spots for detection and response across your complete enterprise with new innovations in Agentic AI across our ActiveAI Security platform. Industry leaders from IDC will join Darktrace customers to discuss challenges in cross-domain security, with a live walkthrough reshaping the future of Network Detection & Response, Endpoint Detection & Response, Email Security, and SecOps in novel threat detection and autonomous investigations.

Continue reading
About the author
Your data. Our AI.
Elevate your network security with Darktrace AI