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January 14, 2025

Why AI-powered Email Protection Became Essential for this Global Financial Services Leader

Hear the cybersecurity transformation story of this leading money transmitter, who facilitates more than $9 billion in remittances via thousands of agent locations across the US serving more than two million active customers.
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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14
Jan 2025

When agile cyber-attackers don’t stop, but pivot  

When he first joined this leading financial services provider, it was clear to the CISO that email security needed to be a top priority. The organization provides transfer services to millions of consumers via a network of thousands of agent locations across the US. Those agents are connected to hundreds of thousands of global payers to complete consumer transfers, ranging from leading financial institutions to small local businesses.

With this vast network of agents and payers, the provider relies on email as its primary communications channel. Transmitting billions of dollars every year, the organization is a prime target for cyber criminals looking to steal credentials, financial assets, and sensitive data.

Vulnerable to attacks with gaps in email security and visibility

The CISO discovered that employees were under constant attack by phishing emails impersonating his company’s own executives. The business email compromise (BEC) attacks were designed to deceive employees into sharing credentials or clicking on malicious links.

Upon discovering that their Microsoft 365 tenant lacked secure configuration, the CISO implemented necessary changes to strengthen the service, including enabling authentication controls. While his efforts significantly reduced BEC attacks, cyber criminals changed their tactics, sending employees malicious phishing emails from seemingly valid email accounts from trusted domains like Google and Yahoo. The emails passed through the organization’s native email filters without detection.

The CISO also sought to strengthen defenses against third-party supply chain attacks that could originate with any of the hundreds of thousands of third-party agents and payers the company works with around the world. While the larger institutions typically have sophisticated email security strategies in place, the smaller businesses may lack the cybersecurity expertise needed to effectively secure and manage their data, putting the organization at risk.

While the CISO knew the company was vulnerable to phishing and third-party threats, he didn’t have visibility across the flow of email. Without access to key metrics and valuable data, he couldn’t get the crucial insights needed to quickly identify possible threats and adjust security protocols.  

Skilled analysts bogged down with low-level tasks

Like many enterprise organizations, this leading financial services provider relied on a crew of highly skilled analysts to respond to alerts and analyze and triage emails most of their workday. “That shouldn’t be how we operate,” said the CISO. “My role and the role of my staff should be to focus on more strategic projects, support the business, and work on important new product development.”

Balancing user experience with mitigating threats

Enabling greater email security measures without negatively impacting the business, user experience, and customer satisfaction was a daunting challenge the CISO and his security team faced. Imposing restrictions that are too stringent could restrict communication, delay the delivery of important messages, or block legitimate emails – potentially slowing down money transfers, frustrating customers, affecting employee productivity, and impacting revenue. However, maintaining controls that are too permissive could result in serious outcomes like data theft, financial fraud, operational disruption, compliance penalties, and customer attrition.  

Self-Learning AI is a game changer

After conducting a thorough POC with several modern security solution providers, this global financial services provider chose the Darktrace / EMAIL an AI-driven email security platform. The CISO said they chose the solution for two key reasons:

First, Darktrace / EMAIL offers modern capabilities

  • Self-Learning AI uses business data to recognize anomalies in communication patterns and user behavior to stop known and unknown threats
  • Secures the organization’s entire mailflow across all inbound, outbound, and lateral email
  • Protects against account takeover attacks by identifying subtle anomalies in cloud SaaS
  • Catches sophisticated threats like impersonations, session token misuse, adversary-in-the-middle attacks, credential theft, and data exfiltration

Second, they pointed to Darktrace’s experience, innovation, and expertise

  • Deep cybersecurity and industry knowledge
  • Demonstrated customers successes worldwide
  • At the forefront of innovation and research, establishing new thresholds in cybersecurity, with technology advances backed by over 200 patents and pending applications

Moreover, and most importantly, this organization trusted Darktrace to deliver on its promises.  And according to the CISO, that’s just what happened.

Significantly reduced phishing threats and business risk

Since implementing Darktrace / EMAIL, the threat posed by BEC attacks has dropped sharply. “Phishing is not an issue that concerns me anymore. I estimate we are now identifying and blocking more than 85% of threats our previous solution was missing,” said the CISO. The biggest factor contributing to this success? The power of AI.

With Darktrace / EMAIL, this leadingglobal financial services provider is identifying and blocking more than 85% ofthe phishing email threats its previous solution missed.

AI wasn’t originally on the financial service provider’s list of criteria. But after seeing AI in action and understanding its potential to vastly scale their detection and response capabilities–without adding headcount, the CISO determined AI wasn’t an option but an imperative. “AI is essential when it comes to email security, it’s an absolute necessity,” he said.  

Darktrace / EMAIL’s Self-Learning AI is uniquely powerful because it learns the content and context of every internal and external user and can spot the subtle differences in behavioral patterns that point to possible social engineering attacks. Through patented behavioral anomaly detection, Darktrace / EMAIL continuously learns about the organization’s business and users, based on its own operations and data, adjusting security protocols accordingly.  

For example, when clients are transferring large amounts of money, they are required to send photos of their driver’s licenses and passports via email to the organization for verification – accounting for a large percentage of its’ inbound email. Darktrace / EMAIL recognizes that it’s normal for customers to send this sensitive information, and it also knows that it’s not normal for that same sensitive information to leave the organization via outbound mail. In addition, Darktrace identifies patterns in user behavior, including who employees communicate with and what kind of information they share. When user behavior falls outside of established norms, such as an email sent from the CFO to employees the CEO would not typically communicate with, Darktrace can take the appropriate action to remove the threat.  

“After the implementation, we gave the solution two weeks to ingest our data and learn the specifics of our business. After that, it was perfect, just amazing,” said the CISO.  

Boosted team productivity and elevated value to the business

With Darktrace / EMAIL, the organization has successfully scaled its detection and response efforts without scaling personnel. The security team has reduced the number of emails requiring manual investigation by 90%. And because analysts now have the benefit of Darktrace / EMAIL’s analytics and reporting, the investigation process is much easier and faster. “The impact of this solution on my team has been very positive,” said the CISO. “Darktrace / EMAIL essentially manages itself, freeing up time for our skilled analysts–and for myself–to focus on more important projects.”  

The security team has scaled its detection and response efforts without scaling personnel,reducing the number of emails it manually investigates by 90%

Increased visibility delivers business-critical insights

You can’t control what you can’t see, and with zero visibility into critical data and metrics, this financial services provider was at a serious disadvantage. That has all changed. “Something that I love about Darktrace / EMAIL is the visibility that it provides into key metrics from a single dashboard. We can now understand the behavior of our email flow and data traffic and can make insight-driven decisions to continuously optimize our email security. It’s awesome,” said the CISO.  

An efficient user interface also improves productivity and reduces mean time to action by enabling teams to easily visualize key data points and quickly evaluate what actions need to be taken. Darktrace / EMAIL was developed with that experience in mind, allowing users to access data and take quick action without having to constantly log into the solution.

Keeping the business focused on cybersecurity

The leadership of this global organization takes information security very seriously, understanding that cyber-attacks aren’t just an IT problem but a business problem. When it came to evaluating Darktrace, the CISO said numerous stakeholders were involved including C-level executives, infrastructure, and IT, which operates separately from information security. The CISO initially identified the need, conducted the market research, engaged the target vendors, and then brought the other decision makers into the process for the solution evaluation and final decision. “Our IT group, infrastructure team, CTO and CEO are all involved when it comes to making major cybersecurity investments. We always try to make these decisions jointly to ensure we are taking everything into consideration.”

The organization has reached a higher level of maturity when it comes to email cybersecurity. The ability to automate routine email detection and investigation tasks has both strengthened the organization’s cyber resilience and enabled the CISO and his team to contribute more to the business. His advice for other IT leaders facing the same email security and visibility challenges he once experienced: “For those companies that need greater insight and control over their email but have limited resources and people, AI is the answer.”  

Darktrace / Email solution brief screenshot

Secure Your Inbox with Cutting-Edge AI Email Protection

Discover the most advanced cloud-native AI email security solution to protect your domain and brand while preventing phishing, novel social engineering, business email compromise, account takeover, and data loss.

  • Gain up to 13 days of earlier threat detection and maximize ROI on your current email security
  • Experience 20-25% more threat blocking power with Darktrace / EMAIL
  • Stop the 58% of threats bypassing traditional email security

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
The Darktrace Community

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August 5, 2026

Testing a Prompt injection Attack Against an Enterprise AI Agent

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Key takeaways

  • Darktrace successfully detected and quarantined a prompt injection email before it could be processed by an enterprise AI agent.  
  • Prompt injection attacks increasingly rely on natural language rather than traditional malware, making behavioral analysis an important complement to signature-based detection.  
  • Organizations deploying AI agents should combine model guardrails with behavioral monitoring to reduce the risk of malicious instructions reaching enterprise systems.

How behavioral detection helps stop prompt injection attacks

A Darktrace customer running a Gemini AI agent in Google Cloud asked us two simple questions:

“If my agent can read inbound emails and access internal data, what stops an attacker from hiding malicious instructions in the message? Couldn’t the agent be tricked into deleting or exfiltrating sensitive data?”

The scenario centers on an indirect prompt injection attack, where malicious instructions are hidden inside content that an AI model later interprets as trusted input. The same weakness was exposed by  EchoLeak (CVE-2025-32711), a zero-click Microsoft 365 Copilot vulnerability enabled data exfiltration from a single well-crafted email..

This blog follows the Darktrace team’s investigation of the customer’s hypothesis and examines how the attack interacted with their existing security stack. The results highlight which defenses held, where gaps emerged, and how behavioral detection mattered more than guardrails. This investigation also demonstrates why behavioral detection is becoming increasingly important for AI security, as prompt injections often contain no traditional indicators of compromise.  

How do prompt injection attacks work?

Prompt injection works by carefully crafting the content and structure of the prompt to alter the LLM’s behavior or output in unintended ways. This can cause models to violate guardrails, generate harmful content or enable unauthorised access.

Prompt injection attack example

The well-known example, EchoLeak (CVE-2025-32711), was a zero-click vulnerability in Microsoft 365 Copilot that relied on a carefully crafted email containing hidden instructions that the AI system interpreted as commands rather than content, creating a pathway for unauthorized access to sensitive information without any user interaction.

While Darktrace / SECURE AI is designed to prevent agents from producing unintended outcomes, we wanted to see if we could catch and prevent this threat type earlier in the attack life-cycle, at the email security layer.

How we tested prompt injection attacks on an enterprise agent

Summary:

  1. Claude generated a prompt injection payload.  
  2. Hidden instructions were embedded in an email.  
  3. The email passed traditional validation checks.  
  4. Darktrace analyzed the language and sender behavior.  
  5. The email was quarantined before the AI agent could process it.

To test Darktrace / EMAIL against this attack class, we opened Claude, gave it the customer's context and problem statement (Gemini agent with inbox access, internal tool calls), told it we were validating Darktrace / EMAIL's detection of prompt injections, and asked for a test payload. See below:

Figure 1
Figure 2

Despite the guardrails supposedly built into the model, Claude surprisingly gave us the entire exploit in plaintext (albeit very basic), illegible to a human as the text was sent in white text (see Figure 1) but framed as an authoritative override for anything downstream reading the mail programmatically (i.e. the Gemini agent).

How Darktrace detected a prompt injection attack

We then sent the Claude-crafted email from a freemail address to the target recipient’s inbox. Despite the email containing no malicious payload, the freemail address having no malicious reputation, and the validation checks all passing, Darktrace  /EMAIL flagged the email as a 93/100 anomaly and moved it to junk, out of scope for the AI agent.

Figure 3: The test email sent with the hidden prompt injection
Figure 4: The email analysis in Darktrace / EMAIL 
Figure 5: Darktrace / EMAIL detection of malicious activity

The interesting part is what triggered the detection (see Figure 5)

  • Possible machine prompt content: text in the body detected as instructions written for a machine to execute, not for a human to read
  • Possible machine prompt content + basic suspicious correspondence: the same content, correlated with sender-side anomalies: freemail domain (yahoo[.]com), unknown correspondent, no prior mail history with the recipient, and suspicious references to payment information

Neither of those is a signature match. Nothing in the email was on a blacklist. There was no malware, no link and no attachment. Darktrace analyzed the context in which the email was delivered and flagged it as likely risky.  The anomalous language features and the context of the sender relative to the recipient's normal behavior, combined with the unusual hidden text (prompt) were enough for Darktrace / EMAIL to act on the risk.

Result: Darktrace / EMAIL autonomously junked the email, out of scope for any AI agent parsing the inbox.

Why behavioral security makes a difference detecting prompt injection attacks

Cyberattacks don't look like traditional exploits anymore. They now operate in natural language, not strictly code.

That breaks the traditional stack. AV, firewalls, static scanning and signature-based SEGs all assume a payload to inspect.  

A prompt injection has no payload. It's just an instruction, written in natural language, dressed up as anything the attacker wants: an invoice, an HR request, a calendar invite, some simple PowerPoint slides.

EchoLeak proved that hidden instructions can sit inside an email invisible to the user but fully readable by the LLM, and the LLM will follow them blindly.  

This test and GTG-1002 proved that the LLM itself can be socially engineered. Tell it you're an authorized tester and it will hand you the attack.

Rules and static classifiers can catch the obvious cases. But natural language has infinite variants, and the attack surface is the model's innate functionality to comply.  

The deeper problem here is intent: an LLM can't reliably tell whether an instruction in its context came from its developer, its user, or an attacker who slipped it into an email. To the LLM, everything reads as language and looks like a legitimate ask. This is why behavioural detection wins, as you become aware of intent when you look at the context of an interaction. Does this sender normally send this kind of message to this recipient? Does this prompt fit the user's normal pattern? Is this agent behaving the way this agent normally behaves?  

Intent can't be read off a single email, it emerges from behavioral context. Which is how Darktrace enables threat detection, through behavioral understanding.

Why enterprise AI security requires more than guardrails

Claude didn't roll over immediately… the first section of the response was a (slight) pushback, but then it wrote the payload anyway without having to ask twice.

Here the framing of the prompt did all the work. The “testing security capabilities” angle moved the model from refusal to unquestioned compliance to the user prompt.

This isn't the first time this has happened, of course. Anthropic disclosed in November 2025 that a Chinese state-sponsored group they tracked as GTG-1002 ran the first documented AI-orchestrated espionage campaign against ~30 targets by posing as employees of a legitimate cybersecurity firm doing authorised penetration testing.

The takeaway isn't that AI guardrails are ineffective. They raise the cost of low-effort attacks and remain an important first layer of defense. However, for most organizations today, they’re the only line of defense when deploying AI agents. If a prompt injection bypasses those controls, organizations still need a way to detect and stop malicious behavior elsewhere in the attack chain.

Attackers will continue to have working prompt injections easily and quickly. The question is what stops one when it lands in an inbox your agent is reading.

That's where behavioral detection comes in.

How Darktrace detects prompt injection attacks in emails

Two things Darktrace does that a model-level guardrail or static rules and signatures can't:

Natural language analysis at the email or prompt layer. The email is assessed on its own merits: is this content shaped like instructions for a machine, regardless of what the receiving agent decides to do about it?

Behavioral context around the language. An AI agent behaves like an extremely agreeable human, and it will go above and beyond to comply with the user’s request. That's exactly why you must consider the business context, such sender behaviour, mailing history, and organisational norms, as these matter even more when the recipient is an AI.

Darktrace has been perfecting behavioral anomaly detection for over a decade; the same self-learning approach that catches BEC and account takeover applies directly to prompt injection delivery. Our multi-layered AI stack extracts content from the message, builds behavioural understanding through social graphing and Pattern of Life analysis, and then combines natural language, topic, inducement, sender relationship and anomaly signals before deciding what action to take.  

This matters for prompt injection because the threat is not the plain language itself, but the intent behind the language that can cause an AI agent to respond in unexpected ways.

How to secure enterprise AI operations from prompt injection attacks

Email was the entry point in this case, but it is only one of many possible vectors.  

Anywhere an agent can retrieve information, an attacker can potentially introduce a prompt injection.

Emails, documents, SharePoint sites, web pages, knowledge bases, chat platforms, and third-party integrations all provide opportunities to influence an agent's behavior. Wherever an agent finds its orders, a prompt injection opportunity exists.

This is why securing AI requires more than blocking malicious inputs. Organizations also need visibility into how agents behave after consuming information from across their environment. If an agent begins accessing unexpected data, taking unusual actions, or operating outside its normal patterns, those behaviors may provide the strongest signal that something has gone wrong.

Effective AI security requires defense in depth: reducing the likelihood of malicious instructions reaching the agent while maintaining the ability to detect and investigate suspicious behavior if they do.

The challenge isn't protecting a single entry point. It's recognizing that, in an AI-powered environment, every source of information is also a potential source of influence.

Are you deploying autonomous agents across your enterprise and want to see this tested in your environment? Let's talk.

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Carlo Loregian
Solutions Engineer

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August 4, 2026

Extending AI Security Visibility with Darktrace and Microsoft Agent 365

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AI agents are rapidly becoming embedded in everyday business operations, helping employees automate workflows, access information, and accelerate decision-making. As organizations embrace agentic AI, security teams face a growing challenge: understanding how AI is being used, what agents can access, and where risk may emerge.

As agents take on more business-critical work, security teams often need to move across multiple portals to understand risks spanning identity, data, and threat activity. This fragmented view can make it difficult to assess an agent's overall risk posture and determine where attention is needed. Organizations need a way to bring these signals together without disrupting existing security investments or workflows.

Today, Darktrace is announcing an integration between Darktrace / SECURE AI and Microsoft Agent 365 that brings Darktrace's Adaptive AI-driven risk signals directly into the Microsoft 365 Admin Center. By extending the visibility and risk understanding provided by Darktrace / SECURE AI into the Microsoft ecosystem, organizations can gain a more unified understanding of AI agent risk across their environments.

As one of the first security companies to partner with Microsoft to contribute third-party risk signals to the Agent Registry, Darktrace is helping shape how organizations understand and manage AI agent risk.

Extending visibility into the Microsoft Agent 365 experience

Microsoft Agent 365 provides administrators with a centralized registry of AI agents operating within their environment. As organizations expand their use of AI agents, this centralized visibility becomes increasingly important for governance and oversight.

This new integration extends that visibility by allowing Darktrace-generated risk signals to be surfaced directly within the Microsoft Agent 365 experience. By combining Microsoft's agent management and security capabilities with Darktrace's AI-powered risk analysis, organizations gain greater awareness of potential security concerns associated with AI agents operating across their environments.

By integrating Darktrace telemetry into Agent 365, customers can:  

  • Surface Darktrace-detected risks and signals alongside Microsoft-native signals in a single interface
  • Identify potentially compromised or anomalous AI agents more quickly
  • Gain unified understanding of context and agent behavior  

This approach reinforces a single control plane for AI security while allowing organizations to continue leveraging existing investments across both platforms.  

Why unified visibility of AI agent risk signals matters

As AI adoption accelerates across Microsoft environments, organizations must manage new forms of behavior, access patterns, and risk. Security teams need more than inventories and permissions. They need visibility into how AI systems operate and how risk evolves over time.  

This integration addresses a critical gap: how to bring behavioral AI security insights into the same control plane as identity, access, and agent management.  

With Darktrace and Microsoft Agent 365 together, organizations benefit from:  

  • Unified visibility: A single pane of glass for understanding AI agent risk signals across Microsoft and Darktrace signals  
  • Faster detection of abnormal agent behavior: Darktrace's Adaptive AI highlights deviations that may not be captured by static controls  
  • Operational efficiency: Security teams can triage and prioritize risk signals without switching between systems
  • Stronger trust in AI deployments: Clear attribution, context, and investigation pathways improve confidence in AI agent usage

Extending Microsoft's AI security model, not replacing it

Securing AI requires a layered approach that combines governance, visibility, threat detection, and risk management. This integration is designed to complement Microsoft's security capabilities, not duplicate them.  

Through Darktrace / SECURE AI, Darktrace contributes:  

  • Identification of risk via advanced prompt analysis  
  • Behavioral anomaly detection across AI agents  
  • Cross-environment threat correlation  
  • Autonomous insight into emerging or unknown risks  

Microsoft provides:  

  • Centralized agent management
  • Identity and access governance
  • Native detection of risk signals and enforcement capabilities

Together, these capabilities create a more complete, layered approach to securing AI-driven enterprises. Organizations gain the governance and policy controls needed to manage AI adoption while benefiting from continuous visibility into how AI is used across the business.

Building the future of secure AI

As AI agents become more deeply embedded in business processes, organizations need more than inventories and static controls. They need to understand how AI is being used, how agents behave, and where risk is emerging across the enterprise.

Darktrace / SECURE AI delivers that understanding through continuous visibility into AI activity, helping security teams assess intent, identify behavioral drift, and uncover emerging risk across both human and agent-driven workflows. Powered by Adaptive AI, it provides the context needed to secure AI as it evolves.  

The integration with Microsoft Agent 365 extends those insights into the workflows organizations already use. Agent 365 provides a unified control plane for governing and securing AI agents, while Darktrace contributes complementary behavioral risk signals that can be surfaced within the Agent 365 experience. Together, they give customers broader context on agent activity and risk while preserving the value of their existing Microsoft and Darktrace investments.

As enterprises move from AI experimentation to AI-powered execution, Microsoft and Darktrace help bring together governance, compliance, behavioral understanding, and oversight in a unified approach to AI security. For organizations adopting Microsoft 365 E7, Darktrace / SECURE AI further strengthens that foundation by providing continuous visibility into AI activity, agent behavior, and emerging risk as AI adoption scales.

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