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February 29, 2024

Navigating Email Security Gaps Beyond DMARC

Discover Darktrace's strategies for navigating email security gaps beyond DMARC. Enhance your defenses with advanced threat detection and mitigation.
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
Carlos Gray
Senior Product Marketing Manager, Email
Written by
Stephen Pickman
Senior Vice President, Engineering
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29
Feb 2024

Email threat landscape  

Email has consistently ranked among the most targeted attack vectors, given its ubiquity and criticality to business operations. From September to December 2023, 10.4 million phishing emails were detected across Darktrace’s customer fleet demonstrating the frequency of attempted email-based attacks.

Businesses are searching for ways to harden their email security posture alongside email providers who are aiming to reduce malicious emails traversing their infrastructure, affecting their clients. Domain-based Message Authentication (DMARC) is a useful industry-wide protocol organizations can leverage to move towards these goals.  

What is DMARC?

DMARC is an email authentication protocol designed to enhance the security of email communication.

Major email service providers Google and Yahoo recently made the protocol mandatory for bulk senders in an effort to make inboxes safer worldwide. The new requirements demonstrate an increasing need for a standardized solution as misconfigured or nonexistent authentication systems continue to allow threat actors to evade detection and leverage the legitimate reputation of third parties.  

DMARC is a powerful tool that allows email administrators to confidently identify and stop certain spoofed emails; however, more organizations must implement the standard for it to reach its full potential. The success and effectiveness of DMARC is dependent on broad adoption of the standard – by organizations of all sizes.  

How does DMARC work?

DMARC builds on two key authentication technologies, Sender Policy Framework (SPF) and DomainKeys Identified Mail (DKIM) and helps to significantly improve their ability to prevent domain spoofing. SPF verifies that a sender’s IP address is authorized to send emails on behalf of a particular domain and DKIM ensures integrity of email content by providing a verifiable digital signature.  

DMARC adds to this by allowing domain owners to publish policies that set expectations for how SPF and DKIM verification checks relate to email addresses presented to users and whose authenticity the receiving mail server is looking to establish.  

These policies work in tandem to help authenticate email senders by verifying the emails are from the domain they say they are, working to prevent domain spoofing attacks. Key benefits of DMARC include:

  1. Phishing protection DMARC protects against direct domain spoofing in which a threat actor impersonates a legitimate domain, a common phishing technique threat actors use to trick employees to obtain sensitive information such as privileged credentials, bank information, etc.  
  2. Improving brand reputation: As DMARC helps to prevent impersonation of domains, it stands to maintain and increase an organization’s brand reputation. Additionally, as organizational reputation improves, so will the deliverability of emails.
  3. Increased visibility: DMARC provides enhanced visibility into email communication channels, including reports of all emails sent on behalf of your domain. This allows security teams to identify shadow-IT and any unauthorized parties using their domain.

Understanding DMARC’s Limitations

DMARC is often positioned as a way for organizations to ‘solve’ their email security problems, however, 65% of the phishing emails observed by Darktrace successfully passed DMARC verification, indicating that a significant number of threat actors are capable of manipulating email security and authentication systems in their exploits. While DMARC is a valuable tool in the fight against email-based attacks, the evolving threat landscape demands a closer look at its limitations.  

As threat actors continue to innovate, improving their stealth and evasion tactics, the number of attacks with valid DMARC authentication will only continue to increase in volume and sophistication. These can include:

  1. Phishing attacks that leverage non-spoofed domains: DMARC allows an organization to protect the domains that they own, preventing threat actors from being able to send phishing emails from their domains. However, threat actors will often create and use ‘look-a-like’ domains that closely resemble an organization’s domain to dupe users. 3% of the phishing emails identified by Darktrace utilized newly created domains, demonstrating shifting tactics.  
  2. Email Account Takeovers: If a threat actor gains access to a user’s email account through other social engineering means such as credential stuffing, they can then send phishing emails from the legitimate domain to pursue further attacks. Even though these emails are malicious, DMARC would not identify them as such because they are coming from an authorized domain or sender.  

Organizations must also ensure their inbound analysis of emails is not skewed by successful DMARC authentication. Security teams cannot inherently trust emails that pass DMARC, because the source cannot always be legitimized, like in the event of an account takeover. If a threat actor gains access to an authenticated email account, emails sent by the threat actor from that account will pass DMARC – however the contents of that email may be malicious. Sender behavior must be continuously evaluated and vetted in real time as past communication history and validated DMARC cannot be solely relied upon amid an ever-changing threat landscape.  

Security teams should lean on other security measures, such as anomaly detection tools that can identify suspicious emails without relying on historical attack rules and static data. While DMARC is not a silver bullet for email security, it is nevertheless foundational in helping organizations protect their brand identity and must be viewed as an essential layer in an organization's overall cyber security strategy.  

Implementing DMARC

Despite the criticality of DMARC for preserving brand reputation and trust, adoption of the standard has been inconsistent. DMARC can be complex to implement with many organizations lacking the time required to understand and successfully implement the standard. Because of this, DMARC set-up is often outsourced, giving security and infrastructure teams little to no visibility into or control of the process.  

Implementation of DMARC is only the start of this process, as DMARC reports must be consistently monitored to ensure organizations have visibility into who is sending mail from their domain, the volume of mail being sent and whether the mail is passing authentication protocols. This process can be time consuming for security teams who are already faced with mounting responsibilities, tight budgets, and personnel shortages. These complexities unfortunately delay organizations from using DMARC – especially as many today still view it as a ‘nice to have’ rather than an essential.  

With the potential complexities of the DMARC implementation process, there are many ways security and infrastructure teams can still successfully roll out the standard. Initial implementation should start with monitoring, policy adjustment and then enforcement. As business changes over time, DMARC should be reviewed regularly to ensure ongoing protection and maintain domain reputation.

The Future of Email Security

As email-based attacks continue to rise, the industry must recognize the importance of driving adoption of foundational email authentication protocols. To do this, a new and innovative approach to DMARC is needed. DMARC products must evolve to better support organizations throughout the ongoing DMARC monitoring process, rather than just initial implementation. These products must also be able to share intelligence across an organization’s security stack, extending beyond email security tools. Integration across these products and tools will help organizations optimize their posture, ensuring deep understanding of their domain and increased visibility across the entire enterprise.

DMARC is critical in protecting brand identity and mitigating exact-domain based attacks. However, organizations must understand DMARC’s unique benefits and limitations to ensure their inboxes are fully protected. In today’s evolving threat landscape, organizations require a robust, multi-layered approach to stop email threats – in inbound mail and beyond. Email threats have evolved – its time security does too.

Join Darktrace on 9 April for a virtual event to explore the latest innovations needed to get ahead of the rapidly evolving threat landscape. Register today to hear more about our latest innovations coming to Darktrace’s offerings. For additional insights check out Darktrace’s 2023 End of Year Threat Report.

Credit to Carlos Gray and Stephen Pickman for their contribution to this blog

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
Carlos Gray
Senior Product Marketing Manager, Email
Written by
Stephen Pickman
Senior Vice President, Engineering

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May 21, 2026

Darktrace named a Leader in the 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR) For the Second Consecutive Year

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Continued recognition in NDR  

Darktrace has been recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR), marking the second consecutive year in the Leaders quadrant.

We believe this consistency reflects sustained ability to execute, adapt, and deliver outcomes as the market evolves.

While we are immensely proud to be recognized by industry analysts as a Leader in NDR, that's just part of the story. Darktrace was also Named the Only 2025 Gartner® Peer Insights™ Customers’ Choice for Network Detection and Response based on direct customer feedback and real-world experience.

We believe the combination of these two signals is important. One reflects how the market is evaluated. The other reflects how technology performs in practice.

Why Darktrace continues to be recognized as a leader

We believe our position as a Leader for the second consecutive year reflects a combination of our sustained ability to execute in NDR, continued AI innovation, and proven delivery of security outcomes for customers and partners worldwide.

We also feel that our leadership in the NDR market is a testament to our unique and multi-layered AI approach, for which we were recognized as No.7 on Fast Company’s Most Innovative AI Companies of 2026 list, plus one of the hottest AI cybersecurity companies in CRN's AI 100.

Adapting to complex, real-world environments

Organizations are no longer protecting a single network perimeter. They are securing a mix of users, devices, applications, and data that move across hybrid environments.

Darktrace has focused on maintaining visibility and detection across these conditions, allowing security teams to understand activity as it scales.

Supporting organizations globally, not just technically

Security outcomes are shaped as much by deployment and support as they are by detection capability.

Darktrace continues to invest in regional presence across 29 countries around the world, helping organizations operationalize NDR in ways that align with local requirements, internal processes, and team structures.

Continuing to push AI beyond detection

AI in cybersecurity is often positioned as a way to improve detection accuracy. But the more important shift is how AI can influence decision-making and response.

Darktrace continues to develop models that learn from both live environments and historical incident data, combining real-time behavioral analysis with insights derived from prior attack patterns.

Using technologies such as the Incident Graph and DIGEST (Darktrace Incident Graph Evaluation for Security Threats), activity is not analyzed in isolation. Instead, relationships between users, devices, connections, and events are mapped over time, allowing the system to reconstruct how an incident is unfolding and how similar incidents have progressed in the past.

By evaluating these patterns, Darktrace can assess the likelihood that an incident will escalate, prioritizing the activity that poses the greatest risk and surfacing the most relevant context for investigation.

This shifts security operations from simply identifying anomalies to understanding their trajectory, helping teams anticipate potential impact and respond earlier with greater precision.

Why NDR is shifting from reactive detection to proactive, AI-driven security

Traditional approaches to NDR have been built around reactively identifying threats once they become clearly visible. That model is increasingly difficult to rely on.

Attackers are no longer operating in ways that stand out. They use valid credentials, trusted tools, and low-and-slow techniques that blend into everyday activity. By the time something looks obviously malicious, the impact is often already underway.

This is the core limitation of reactive detection. It depends on recognizing something that already looks like a threat.

As a result, many of the most consequential incidents today fall into a gap.

Insider activity, compromised credentials, and novel attacks rarely trigger traditional alerts because they do not follow known patterns. On the surface, they often appear legitimate, making them difficult to distinguish from normal behavior without deeper context.

This is why we believe this Gartner recognition reflects a broader shift in NDR toward autonomous, proactive and pre‑emptive security operations.

By understanding normal behavior within an environment, it is possible to identify subtle deviations rather than waiting for confirmation of threats as they are taking place.

Darktrace’s Self-Learning AI is designed for behavioral understanding. By continuously learning each organization’s normal patterns, it can detect deviations in real time, enabling a proactive and pre-emptive model of NDR where security teams can respond to early signs of risk as they emerge, reducing the window in which attacks can develop.

In multiple cases, this behavioral approach has led to early threat detection where Darktrace identified completely unknown threats, including pre-CVE zero-day activity. By detecting subtle behavioral changes before vulnerabilities were publicly disclosed or widely understood, organizations can mitigate threats before they do damage.

This shift is subtle but important. Modern NDR solutions must shift from a system that explains what happened to one that helps prevent threats from developing in the first place, and Darktrace is proud to be at the forefront of this shift - helping organizations build and maintain a state of proactive network resilience.

Continuing to innovate at the forefront of NDR

In our view, recognition as a Leader reflects where the market is today. Continuing to innovate defines what comes next.

As businesses evolve, new technologies like AI tools and agents introduce new security risks and challenges; security teams need more than simple detection. They need a complete understanding of risk as it develops, the ability to investigate it in context, and to contain threats at machine speed.  

Darktrace / NETWORK is built to deliver across that full spectrum. Its Self-Learning AI continuously adapts to each organization’s environment, identifying subtle behavioral changes that signal emerging threats. Integrated investigation and autonomous response reduce the time between detection and action, allowing teams to move with greater speed and confidence.

This combination enables organizations to detect and contain known, unknown, and insider threats as they develop, while also strengthening resilience over time.

As a two-time Leader in the Gartner® Magic Quadrant™ for NDR and the only 2025 Gartner® Peer Insights™ Customers’ Choice, we feel Darktrace continues to evolve its platform to meet the demands of modern environments, delivering a more complete and adaptive approach to network security.

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Disclaimer: The 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR) ,The 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR), Thomas Lintemuth, Charanpal Bhogal, Nahim Fazal, 18 May 2026.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved.

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Mikey Anderson
Product Marketing Manager, Network Detection & Response

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May 21, 2026

Prompt Security in Enterprise AI: Strengths, Weaknesses, and Common Approaches

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How enterprise AI Agents are changing the risk landscape  

Generative AI Agents are changing the way work gets done inside enterprises, and subsequently how security risks may emerge. Organizations have quickly realized that providing these agents with wider access to tooling, internal information, and granting permissions for the agent to perform autonomous actions can greatly increase the efficiency of employee workflows.

Early deployments of Generative AI systems led many organizations to scope individual components as self-contained applications: a chat interface, a model, and a prompt, with guardrails placed at the boundary. Research from Gartner has shown that while the volume and scope of Agentic AI deployments in enterprise environments is rapidly accelerating, many of the mechanisms required to manage risk, trust, and cost are still maturing.

The issue now resides on whether an agent can be influenced, misdirected, or manipulated in ways that leads to unsafe behavior across a broader system.

Why prompt security matters in enterprise AI

Prompt security matters in enterprise AI because prompts are the primary way users and systems interact with Agentic AI models, making them one of the earliest and most visible indicators of how these systems are being used and where risk may emerge.

For security teams, prompt monitoring is a logical starting point for understanding enterprise AI usage, providing insight into what types of questions are being asked and tasks are being given to AI Agents, how these systems are being guided, and whether interactions align with expected behavior. Complete prompt security takes this one step further, filtering out or blocking sensitive or dangerous content to prevent risks like prompt injection and data leakage.

However, visibility only at the prompt layer can create a false sense of security. Prompts show what was asked, but not always why it was asked, or what downstream actions were triggered by the agent across connected systems, data sources, or applications.

What prompt security reveals  

The primary function of prompt security is to minimize risks associated with generative and agentic AI use, but monitoring and analysis of prompts can also grant insight into use cases for particular agents and model. With comprehensive prompt security, security teams should be able to answer the following questions for each prompt:

  • What task was the user attempting to complete?
  • What data was included in the request, and was any of the data high-risk or confidential?
  • Was the interaction high-risk, potentially malicious, or in violation of company policy?
  • Was the prompt anomalous (in comparison to previous prompts sent to the agent / model)?

Improving visibility at this layer is a necessary first step, allowing organizations to establish a baseline for how AI systems are being used and where potential risks may exist.  

Prompt security alone does not provide a complete view of risk. Further data is needed to understand how the prompt is interpreted, how context is applied, what autonomous actions the agent takes (if any), or what downstream systems are affected. Understanding the outcome of a query is just as important for complete prompt security as understanding the input prompt itself – for example, a perfectly normal, low-risk prompt may inadvertently result in an agent taking a high-risk action.

Comprehensive AI security systems like Darktrace / SECURE AI can monitor and analyze both the prompt submitted to a Generative AI system, as well as the responses and chain-of-thought of the system, providing greater insight into the behavior of the system. Darktrace / SECURE AI builds on the core Darktrace methodology, learning the expected behaviors of your organization and identifying deviations from the expected pattern of life.

How organizations address prompt security today

As prompt-level visibility has become a focus, a range of approaches have emerged to make this activity more observable and controllable. Various monitoring and logging tools aim to capture prompt inputs to be analyzed after the fact.  

Input validation and filtering systems attempt to intervene earlier, inspecting prompts before they reach the model. These controls look for known jailbreak patterns, language indicative of adversarial attacks, or ambiguous instructions which could push the system off course.

Importantly, for a prompt security solution to be accurate and effective, prompts must be continually observed and governed, rather than treated as a point-in-time snapshot.  

Where prompt security breaks down in real environments

In more complex environments, especially those involving multiple agents or extensive tool use, AI security becomes harder to define and control.

Agent-to-Agent communications can be harder to monitor and trace as these happen without direct user interaction. Communication between agents can create routes for potential context leakage between agents, unintentional privilege escalation, or even data leakage from a higher privileged agent to a lower privileged one.

Risk is shaped not just by what is asked, but by the conditions in which that prompt operates and the actions an agent takes. Controls at the orchestration layer are starting to reflect this reality. Techniques such as context isolation, scoped memory, and role-based boundaries aim to limit how far a prompt’s influence can extend.  

Furthermore, Shadow AI usage can be difficult to monitor. AI systems that are deployed outside of formal governance structures and Generative AI systems hosted on unknown endpoints can fly under the radar and can go unseen by monitoring tools, leaving a critical opening where adversarial prompts may go undetected. Darktrace / SECURE AI features comprehensive detection of Shadow AI usage, helping organizations identify potential risk areas.

How prompt security fits in a broader AI risk model

Prompt security is an important starting point, but it is not a complete security strategy. As AI systems become more integrated into enterprise environments, the risks extend to what resources the system can access, how it interprets context, and what actions it is allowed to take across connected tools and workflows.

This creates a gap between visibility and control. Prompt security alone allows security teams to observe prompt activity but falls short of creating a clear understanding of how that activity translates into real-world impact across the organization.

Closing that gap requires a broader approach, one that connects signals across human and AI agent identities, SaaS, cloud, and endpoint environments. It means understanding not just how an AI system is being used, but how that usage interacts with the rest of the digital estate.

Prompt security, in that sense, is less of a standalone solution and more of an entry point into a larger problem: securing AI across the enterprise as a whole.

Explore how Darktrace / SECURE AI brings prompt security to enterprises

Darktrace brings more than a decade of AI expertise, built on an enterprise‑wide platform designed to operate in and understand the behaviors of the complex, ambiguous environments where today’s AI now lives. With Darktrace / SECURE AI, enterprises can safely adopt, manage, monitor, and build AI within their business.  

Learn about Darktrace / SECURE AI here.

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Jamie Bali
Technical Author (AI) Developer
Your data. Our AI.
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