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March 12, 2023

Compliance Breach Mitigation

Uncover the significance of compliance in preventing cyber threats and learn strategies for effective breach mitigation in your organization.
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
Rachel Resnekov
Cyber Analyst
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12
Mar 2023

Compliance is often an afterthought for security teams responding to cyber security incidents, with many organizations seeing compliance issues as “rule breaking employees” rather than legitimate threats to their network. However, even seemingly innocuous compliance breaches can significantly damage a company’s finances and reputation if not properly addressed.

Adhering to cyber security standards and regulatory requirements is essential, but can often result in “tick box compliance” wherein meeting standards does not result in a reduction of non-compliant activity, lacking tangible impact for many organizations. Protecting data is of paramount importance, especially given the implementation of numerous data protection laws concerned with protecting sensitive data, such as Personally Identifiable Information (PII), financial information, and Protected Health Information (PHI). However, many compliance breaches which do not result in data loss go unadressed, inevitably leading to vulnerabilities within the network that are advantageous to threat actors. Darktrace detects compliance issues in real time and escalates them accordingly, using a dedicated compliance model stack. It highlights incidents of concern, from insecure password storage to device updates, ensuring that users adhere to company standards.

Finding ways to prioritize and quickly triage through these compliance issues, rather than focusing on log auditing or more manually intensive processes, can result in immense gains for security teams.  

Darktrace Coverage of Compliance Breaches   

Incident: Outgoing Operational Technology Connection 

Compliance issues in Operational Technology (OT) are difficult to detect using traditional security measures. The OT space faces unique challenges, such as legacy systems, limited visibility, and convergence between OT and Information Technology (IT). Darktrace’s compliance stack includes an OT-specific subset, allowing users to quickly identify and remediate issues as they arise.

In early 2022, Darktrace observed a compliance incident on the network of a customer based in the energy sector when an individual inserted a mobile phone SIM card into the Human-Machine Interface (HMI) of an Industrial Control System (ICS). The HMI proceeded to access several non-compliant external endpoints, including Facebook. Typically IT and OT networks should be air-gapped to keep critical industrial infrastructure protected and operational.

In this case, Darktrace DETECT triggered a compliance model breach (ICS:: OT Compliance External Connection) and the customer was quickly able mitigate the issue before any meaningful harm could be done to the network.

Incident: Personal Email Use in Corporate Setting

The email space contains a litany of compliance standards and is one of the most common places where security standards are breached, with research demonstrating that “91% of all cyber attacks start with a phishing email.”[1]

In late October 2022, Darktrace/Email identified an email from the recipient’s personal address containing a suspicious link. As the user regularly sent emails between their corporate and personal addresses, this freemail address was a known correspondent. However, this personal email address had been compromised and sent a phishing email to the user’s corporate address. Darktrace/Email immediately identified the suspicious link and alerted the customer, recommending that their security team lock the link. Unfortunately, the customer did not have autonomous response actions for Email enabled, so the recipient was able to open the link and input their corporate credentials on the phishing page. 

Not only is Darktrace/Email able to assess and mitigate threats from personal email addresses, it can also identify suspicious links inside these emails that may have evaded traditional security measures by using a known correspondence. By enabling autonomous response actions, Darktrace/Email is able to follow this up by instantaneously locking such links, ensuring they cannot be opened and preventing the account from being compromised.

Incident: Multi-Factor Authentication for SaaS Accounts

A desire for increased efficiency and cost-effectiveness are two of the reasons underpinning the widespread adoption of cloud-based Software-as-a-Service (SaaS) solutions. However, third-party SaaS environments are not always held to the same compliance standards as traditional on-premisis network infrastructure.

Multi-factor Authentication (MFA) in SaaS environments requires users to prove their identity in at least two ways before granting them access to applications. This significantly reduces the risk of compromise,  but it is not a silver-bullet to prevent account compromise and is still not universally adopted as a baseline security practice.

In October 2022, Darktrace observed an unusual login from a rare IP address on the SaaS account of a customer that did not have MFA employed. Following this initial access, the actor created a new rule and sent emails containing suspicious links to several internal recipients. Further investigation revealed that the link directed to a fake Office365 login portal intended to harvest user credentials. Darktrace/Email and RESPOND for Apps worked in tandem to instantaneously detect this suspicious activity and force the user to log out, while alerting the customer’s security team to the incident.  As a security practice, MFA provides an additional but not guaranteed means of protecting companies from internal theft, data loss, and external access from malicious actors, but its effectiveness is contingent on its roll out across a company. Darktrace DETECT and RESPOND provide an autonomous early warning system and additional layer of security to quickly isolate and contain compromised accounts even in the absence of MFA.

Conclusion

Compliance standards are the building blocks for the cyber hygiene of any organization, but in the current cyber security landscape simply adhering to standards is not enough to close gaps from non-compliant behavior. Following up compliance standard obedience supported by additional measures and technology to tackle compliance breaches significantly reduces the risk of compromise and data breaches, in addition to financial and reputational damage. Ensuring compliance issues are not disregarded as background noise by security teams will help to ensure that minor breaches do not escalate and become legitimate threats.

Darktrace’s suite of products provides an additional layer of detection and autonomous response, alerting customers to ongoing compliance issues and preventing them from causing genuine harm or compromise to the network.

Credit to: Rachel Resznekov, Cyber Security Analyst, Roberto Romeu, Senior SOC Analyst 

Appendices

External Sources: 

hxxps[:]//www[.]comptia[.]org/content/articles/what-is-cybersecurity-compliance#\

hxxps[:]//darkcubed[.]com/compliance

hxxps[:]//www[.]zeguro[.]com/blog/cybersecurity-compliance-101

hxxps[:]//www[.]itgovernanceusa[.]com/cybersecurity-standards

hxxps[:]//www[.]linkedin[.]com/pulse/dangers-using-personal-email-work-partners-plus

hxxps[:]//www[.]metacompliance[.]com/lp/ultimate-guide-phishing

[1] hxxps[:]//www[.]metacompliance[.]com/lp/ultimate-guide-phishing

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
Rachel Resnekov
Cyber Analyst

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December 22, 2025

The Year Ahead: AI Cybersecurity Trends to Watch in 2026

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Introduction: 2026 cyber trends

Each year, we ask some of our experts to step back from the day-to-day pace of incidents, vulnerabilities, and headlines to reflect on the forces reshaping the threat landscape. The goal is simple:  to identify and share the trends we believe will matter most in the year ahead, based on the real-world challenges our customers are facing, the technology and issues our R&D teams are exploring, and our observations of how both attackers and defenders are adapting.  

In 2025, we saw generative AI and early agentic systems moving from limited pilots into more widespread adoption across enterprises. Generative AI tools became embedded in SaaS products and enterprise workflows we rely on every day, AI agents gained more access to data and systems, and we saw glimpses of how threat actors can manipulate commercial AI models for attacks. At the same time, expanding cloud and SaaS ecosystems and the increasing use of automation continued to stretch traditional security assumptions.

Looking ahead to 2026, we’re already seeing the security of AI models, agents, and the identities that power them becoming a key point of tension – and opportunity -- for both attackers and defenders. Long-standing challenges and risks such as identity, trust, data integrity, and human decision-making will not disappear, but AI and automation will increase the speed and scale of the cyber risk.  

Here's what a few of our experts believe are the trends that will shape this next phase of cybersecurity, and the realities organizations should prepare for.  

Agentic AI is the next big insider risk

In 2026, organizations may experience their first large-scale security incidents driven by agentic AI behaving in unintended ways—not necessarily due to malicious intent, but because of how easily agents can be influenced. AI agents are designed to be helpful, lack judgment, and operate without understanding context or consequence. This makes them highly efficient—and highly pliable. Unlike human insiders, agentic systems do not need to be socially engineered, coerced, or bribed. They only need to be prompted creatively, misinterpret legitimate prompts, or be vulnerable to indirect prompt injection. Without strong controls around access, scope, and behavior, agents may over-share data, misroute communications, or take actions that introduce real business risk. Securing AI adoption will increasingly depend on treating agents as first-class identities—monitored, constrained, and evaluated based on behavior, not intent.

-- Nicole Carignan, SVP of Security & AI Strategy

Prompt Injection moves from theory to front-page breach

We’ll see the first major story of an indirect prompt injection attack against companies adopting AI either through an accessible chatbot or an agentic system ingesting a hidden prompt. In practice, this may result in unauthorized data exposure or unintended malicious behavior by AI systems, such as over-sharing information, misrouting communications, or acting outside their intended scope. Recent attention on this risk—particularly in the context of AI-powered browsers and additional safety layers being introduced to guide agent behavior—highlights a growing industry awareness of the challenge.  

-- Collin Chapleau, Senior Director of Security & AI Strategy

Humans are even more outpaced, but not broken

When it comes to cyber, people aren’t failing; the system is moving faster than they can. Attackers exploit the gap between human judgment and machine-speed operations. The rise of deepfakes and emotion-driven scams that we’ve seen in the last few years reduce our ability to spot the familiar human cues we’ve been taught to look out for. Fraud now spans social platforms, encrypted chat, and instant payments in minutes. Expecting humans to be the last line of defense is unrealistic.

Defense must assume human fallibility and design accordingly. Automated provenance checks, cryptographic signatures, and dual-channel verification should precede human judgment. Training still matters, but it cannot close the gap alone. In the year ahead, we need to see more of a focus on partnership: systems that absorb risk so humans make decisions in context, not under pressure.

-- Margaret Cunningham, VP of Security & AI Strategy

AI removes the attacker bottleneck—smaller organizations feel the impact

One factor that is currently preventing more companies from breaches is a bottleneck on the attacker side: there’s not enough human hacker capital. The number of human hands on a keyboard is a rate-determining factor in the threat landscape. Further advancements of AI and automation will continue to open that bottleneck. We are already seeing that. The ostrich approach of hoping that one’s own company is too obscure to be noticed by attackers will no longer work as attacker capacity increases.  

-- Max Heinemeyer, Global Field CISO

SaaS platforms become the preferred supply chain target

Attackers have learned a simple lesson: compromising SaaS platforms can have big payouts. As a result, we’ll see more targeting of commercial off-the-shelf SaaS providers, which are often highly trusted and deeply integrated into business environments. Some of these attacks may involve software with unfamiliar brand names, but their downstream impact will be significant. In 2026, expect more breaches where attackers leverage valid credentials, APIs, or misconfigurations to bypass traditional defenses entirely.

-- Nathaniel Jones, VP of Security & AI Strategy

Increased commercialization of generative AI and AI assistants in cyber attacks

One trend we’re watching closely for 2026 is the commercialization of AI-assisted cybercrime. For example, cybercrime prompt playbooks sold on the dark web—essentially copy-and-paste frameworks that show attackers how to misuse or jailbreak AI models. It’s an evolution of what we saw in 2025, where AI lowered the barrier to entry. In 2026, those techniques become productized, scalable, and much easier to reuse.  

-- Toby Lewis, Global Head of Threat Analysis

Conclusion

Taken together, these trends underscore that the core challenges of cybersecurity are not changing dramatically -- identity, trust, data, and human decision-making still sit at the core of most incidents. What is changing quickly is the environment in which these challenges play out. AI and automation are accelerating everything: how quickly attackers can scale, how widely risk is distributed, and how easily unintended behavior can create real impact. And as technology like cloud services and SaaS platforms become even more deeply integrated into businesses, the potential attack surface continues to expand.  

Predictions are not guarantees. But the patterns emerging today suggest that 2026 will be a year where securing AI becomes inseparable from securing the business itself. The organizations that prepare now—by understanding how AI is used, how it behaves, and how it can be misused—will be best positioned to adopt these technologies with confidence in the year ahead.

Learn more about how to secure AI adoption in the enterprise without compromise by registering to join our live launch webinar on February 3, 2026.  

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December 22, 2025

Why Organizations are Moving to Label-free, Behavioral DLP for Outbound Email

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Why outbound email DLP needs reinventing

In 2025, the global average cost of a data breach fell slightly — but remains substantial at USD 4.44 million (IBM Cost of a Data Breach Report 2025). The headline figure hides a painful reality: many of these breaches stem not from sophisticated hacks, but from simple human error: mis-sent emails, accidental forwarding, or replying with the wrong attachment. Because outbound email is a common channel for sensitive data leaving an organization, the risk posed by everyday mistakes is enormous.

In 2025, 53% of data breaches involved customer PII, making it the most commonly compromised asset (IBM Cost of a Data Breach Report 2025). This makes “protection at the moment of send” essential. A single unintended disclosure can trigger compliance violations, regulatory scrutiny, and erosion of customer trust –consequences that are disproportionate to the marginal human errors that cause them.

Traditional DLP has long attempted to mitigate these impacts, but it relies heavily on perfect labelling and rigid pattern-matching. In reality, data loss rarely presents itself as a neat, well-structured pattern waiting to be caught – it looks like everyday communication, just slightly out of context.

How data loss actually happens

Most data loss comes from frustratingly familiar scenarios. A mistyped name in auto-complete sends sensitive data to the wrong “Alex.” A user forwards a document to a personal Gmail account “just this once.” Someone shares an attachment with a new or unknown correspondent without realizing how sensitive it is.

Traditional, content-centric DLP rarely catches these moments. Labels are missing or wrong. Regexes break the moment the data shifts formats. And static rules can’t interpret the context that actually matters – the sender-recipient relationship, the communication history, or whether this behavior is typical for the user.

It’s the everyday mistakes that hurt the most. The classic example: the Friday 5:58 p.m. mis-send, when auto-complete selects Martin, a former contractor, instead of Marta in Finance.

What traditional DLP approaches offer (and where gaps remain)

Most email DLP today follows two patterns, each useful but incomplete.

  • Policy- and label-centric DLP works when labels are correct — but content is often unlabeled or mislabeled, and maintaining classification adds friction. Gaps appear exactly where users move fastest
  • Rule and signature-based approaches catch known patterns but miss nuance: human error, new workflows, and “unknown unknowns” that don’t match a rule

The takeaway: Protection must combine content + behavior + explainability at send time, without depending on perfect labels.

Your technology primer: The three pillars that make outbound DLP effective

1) Label-free (vs. data classification)

Protects all content, not just what’s labeled. Label-free analysis removes classification overhead and closes gaps from missing or incorrect tags. By evaluating content and context at send time, it also catches misdelivery and other payload-free errors.

  • No labeling burden; no regex/rule maintenance
  • Works when tags are missing, wrong, or stale
  • Detects misdirected sends even when labels look right

2) Behavioral (vs. rules, signatures, threat intelligence)

Understands user behavior, not just static patterns. Behavioral analysis learns what’s normal for each person, surfacing human error and subtle exfiltration that rules can’t. It also incorporates account signals and inbound intel, extending across email and Teams.

  • Flags risk without predefined rules or IOCs
  • Catches misdelivery, unusual contacts, personal forwards, odd timing/volume
  • Blends identity and inbound context across channels

3) Proprietary DSLM (vs. generic LLM)

Optimized for precise, fast, explainable on-send decisions. A DSLM understands email/DLP semantics, avoids generative risks, and stays auditable and privacy-controlled, delivering intelligence reliably without slowing mail flow.

  • Low-latency, on-send enforcement
  • Non-generative for predictable, explainable outcomes
  • Governed model with strong privacy and auditability

The Darktrace approach to DLP

Darktrace / EMAIL – DLP stops misdelivery and sensitive data loss at send time using hold/notify/justify/release actions. It blends behavioral insight with content understanding across 35+ PII categories, protecting both labeled and unlabeled data. Every action is paired with clear explainability: AI narratives show exactly why an email was flagged, supporting analysts and helping end-users learn. Deployment aligns cleanly with existing SOC workflows through mail-flow connectors and optional Microsoft Purview label ingestion, without forcing duplicate policy-building.

Deployment is simple: Microsoft 365 routes outbound mail to Darktrace for real-time, inline decisions without regex or rule-heavy setup.

A buyer’s checklist for DLP solutions

When choosing your DLP solution, you want to be sure that it can deliver precise, explainable protection at the moment it matters – on send – without operational drag.  

To finish, we’ve compiled a handy list of questions you can ask before choosing an outbound DLP solution:

  • Can it operate label free when tags are missing or wrong? 
  • Does it truly learn per user behavior (no shortcuts)? 
  • Is there a domain specific model behind the content understanding (not a generic LLM)? 
  • Does it explain decisions to both analysts and end users? 
  • Will it integrate with your label program and SOC workflows rather than duplicate them? 

For a deep dive into Darktrace’s DLP solution, check out the full solution brief.

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About the author
Carlos Gray
Senior Product Marketing Manager, Email
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