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July 18, 2023

How Darktrace SOC Thwarted a BEC Attack

Discover how Darktrace's SOC detected and stopped a Business Email Compromise in a customer's SaaS environment.
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
Nicole Wong
Cyber Security Analyst
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18
Jul 2023

What is Business Email Compromise (BEC)?

Business Email Compromise (BEC) is the practice of tricking an organization into transferring funds or sensitive data to a malicious actor.

Although at face value this type of attack may not carry the same gravitas as the more blockbuster, cloak-and-dagger type of attack such as ransomware [1], the costs of BEC actually dwarf that of ransomware [2]. Moreover, among UK organizations that reported a cyber breach in 2023, attacks related to BEC – namely phishing attacks, email impersonation, attempted hacking of online back accounts, and account takeover – were reported as the most disruptive, ahead of ransomware and other types of cyber-attack [3].  

What makes a BEC attack successful?

BEC attacks are so successful and damaging due to the difficulty of detection for traditional security systems, along with their ease of execution.  BEC does not require much technical sophistication to accomplish; rather, it exploits humans’ natural trust in known correspondents, via a phishing email for example, to induce them to perform a certain action.

How does a BEC attack work?

BEC attacks typically begin with a phishing email to an employee of an organization. Traditional email gateways may be unable to block the initial phishing email, as the email often appear to have been sent by a known correspondent, or it may contain minimal payload content.

The recipient’s interaction with the initial phishing email will likely result in the attacker gaining access to the user’s identity. Once access is obtained, the attacker may abuse the identity of the compromised user to obtain details of the user’s financial relations to the rest of the organization or its customers, eventually using these details to conduct further malicious email activity, such as sending out emails containing fraudulent wire transfer requests.  Today, the continued growth in adoption of services to support remote working, such as cloud file storage and sharing, means that the compromise of a single user’s email account can also grant access to a wide range of corporate sensitive information.

How to protect against BEC attacks

The rapid uptake of cloud-based infrastructure and software-as-a-service (SaaS) outpaces the adoption of skills and expertise required to secure it, meaning that security teams are often less prepared to detect and respond to cloud-based attacks.  

Alongside the adoption of security measures that specialize in anomaly-based detection and autonomous response, like Darktrace DETECT™ and Darktrace RESPOND™, it is extremely beneficial for organizations to have an around the clock security operations center (SOC) in place to monitor and investigate ongoing suspicious activity as it emerges.

In June 2023, Darktrace’s SOC alerted a customer to an active BEC attack within their cloud environment, following the successful detection of suspicious activity by Darktrace’s AI, playing a fundamental role in thwarting the attack in its early stages.

Darktrace Mitigates BEC Attack

Figure 1: Screenshot of the SaaS Console showing location information for the compromised SaaS account.  The ability to visualize the distance between these two locations enables a SOC Analyst to deduce that the simultaneous activity from London and Derby may represent impossible travel’.

It was suspected the attack began with a phishing email, as on the previous day the user had received a highly anomalous email from an external sender with which the organization had not previously communicated. However, the customer had configured Darktrace/Email™ in passive mode, which meant that Darktrace was not able to carry out any RESPOND actions on this anomalous email to prevent it from landing in the user’s inbox. Despite this, Darktrace/Apps was able to instantly detect the subsequent unusual login to the customer’s SaaS environment; its anomaly-based approach to threat detection allowed it to recognize the anomalous behavior even though the malicious email had successfully reached the user.

Following the anomalous ExpressVPN login, Darktrace detected further account anomalies originating from another ExpressVPN IP (45.92.229[.]195), as the attacker accessed files over SharePoint.  Notably, Darktrace identified that the logins from ExpressVPN IPs were performed with the software Chrome 114, however, activity from the legitimate account owner prior to these unusual logins was performed using the software Chrome 102. It is unusual for a user to be using multiple browser versions simultaneously, therefore in addition to the observed impossible travel, this further implied the presence of different actors behind the simultaneous account activity.

Figure 2: Screenshot of the Event Log for the compromised SaaS account, showing simultaneous login and file access activity on the account from different browser versions, and thus likely from different devices.

Darktrace identified that the files observed during this anomalous activity referenced financial information and personnel schedules, suggesting that the attacker was performing internal reconnaissance to gather information about sensitive internal company procedures, in preparation for further fraudulent financial activity.

Although the actions taken by the attacker were mostly passive, Darktrace/Apps chained together the multiple anomalies to understand that this pattern of activity was indicative of movement along the cyber kill chain. The multiple model breaches generated by the ongoing unusual activity triggered an Enhanced Monitoring model breach that was escalated to Darktrace’s SOC as the customer had subscribed to Darktrace’s Proactive Threat Notification (PTN) service.  Enhanced Monitoring models detect activities that are more likely to be indicative of compromise.  

Subsequently, Darktrace’s SOC triaged the activity detected on the SaaS account and sent a PTN alert to the customer, advising urgent follow up action.  The encrypted alert contained relevant technical details of the incident that were summarized by an expert Darktrace Analyst, along with recommendations to the customer’s internal SOC team to take immediate action.  Upon receipt and validation of the alert, the customer used Darktrace RESPOND to perform a manual force logout and block access from the external ExpressVPN IP.

Had Darktrace RESPOND been enabled in autonomous response mode, it would have immediately taken action to disable the account after ongoing anomalies were detected from it. However, as the customer only had RESPOND configured in the manual human confirmation model, the expertise of Darktrace’s SOC team was critical in enabling the customer to react and prevent further escalation of post-compromise activity.  Evidence of further attempts to access the compromised account were observed hours after RESPOND actions were taken, including failed login attempts from another rare external IP, this time associated with the VPN service NordVPN.

Figure 3: Timeline of attack and response actions from Darktrace SOC and Darktrace RESPOND.

Because the customer had subscribed to Darktrace’s PTN service, they were able to further leverage the expertise of Darktrace’s global team of cyber analysts and request further analysis of which files were accessed by the legitimate account owner versus the attacker.  This information was shared securely within the same Customer Portal ticket that was automatically opened on behalf of the customer when the PTN was alerted, allowing the customer’s security team to submit further queries and feedback, and request assistance to further investigate this alert within Darktrace. A similar service called Ask the Expert (ATE) exists for customers to draw from the expertise of Darktrace’s analysts at any time, not just when PTNs are alerted.

Conclusion

The growing prevalence and impact of BEC attacks amid the shift to cloud-based infrastructure means that already stretched internal security teams may not have the sufficient human capacity to detect and respond to these threats.

Darktrace’s round-the-clock SOC thwarted a BEC attack that had the potential to result in significant financial and reputational damage to the legal services company, by alerting the customer to high priority activity during the early stages of the attack and sharing actionable insights that the customer could use to prevent further escalation.  Following the confirmed compromise, the support and in-depth analysis provided by Darktrace’s SOC on the files accessed by the attacker enabled the customer to effectively report this breach to the Information Commissioner’s Office, to maintain compliance with UK data protection regulations. [4].  

Although the attacker used IP addresses that were local to the customer’s country of operations and did not perform overtly noisy actions during reconnaissance, Darktrace was able to identify that this activity deviated from the legitimate user’s typical pattern of life, triggering model breaches at each stage of the attack as it progressed from initial access to internal reconnaissance. While Darktrace RESPOND triggered an action that would have prevented the attack autonomously, the customer’s configuration meant that Darktrace’s SOC had an even more significant role in alerting the customer directly to take manual action.

Credit to: Sam Lister, Senior Analyst, for his contributions to this blog.

Appendices

Darktrace DETECT/Apps Models Breached:

  • SaaS / Access / Unusual External Source for SaaS Credential Use
  • SaaS / Compromise / Login From Rare Endpoint While User Is Active
  • SaaS / Unusual Activity / Activity from Multiple Unusual IPs
  • SaaS / Unusual Activity / Multiple Unusual SaaS Activities
  • SaaS / Access / Suspicious Login Attempt
  • SaaS / Compromise / SaaS Anomaly Following Anomalous Login (Enhanced Monitoring Model)

Darktrace RESPOND/Apps Models Breached:

  • Antigena / SaaS / Antigena Unusual Activity Block
  • Antigena / SaaS / Antigena Suspicious SaaS Activity Block

MITRE ATT&CK Mapping

Tactic Techniques
Reconnaissance • T1598 – Phishing for Information
Initial Access • T1078.004 – Valid Accounts: Cloud Accounts
Collection • T1213.002 – Data from Information Repositories: Sharepoint

References

[1] Rand, D. (2022, November 10). Why Business Email Compromise Costs Companies More Than Ransomware Attacks. Retrieved from Tanium: https://www.tanium.com/blog/whybusiness-email-compromise-costs-companies-more-than-ransomware-attacks/

[2] Federal Bureau of Investigation. (2022). 2022 IC3 Report. Retrieved from IC3.gov: https://www.ic3.gov/Media/PDF/AnnualReport/2022_IC3Report.pdf

[3] Department for Science, Innovation & Technology. (2023, April 19). Cyber security breaches survey 2023. Retrieved from gov.uk: https://www.gov.uk/government/statistics/cyber-security-breaches-survey-2023/cybersecurity-breaches-survey-2023

[4] ICO. (2023). Personal data breaches: a guide. Retrieved from Information Commissioner's Office: https://ico.org.uk/for-organisations/report-a-breach/personal-data-breach/personal-data-breaches-a-guide/#whatbreachesdo

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
Nicole Wong
Cyber Security Analyst

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May 5, 2026

When Trust Becomes the Attack Surface: Supply-Chain Attacks in an Era of Automation and Implicit Trust

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Software supply-chain attacks in 2026

Software supply-chain attacks now represent the primary threat shaping the 2026 security landscape. Rather than relying on exploits at the perimeter, attackers are targeting the connective tissue of modern engineering environments: package managers, CI/CD automation, developer systems, and even the security tools organizations inherently trust.

These incidents are not isolated cases of poisoned code. They reflect a structural shift toward abusing trusted automation and identity at ecosystem scale, where compromise propagates through systems designed for speed, not scrutiny. Ephemeral build runners, regardless of provider, represent high‑trust, low‑visibility execution zones.

The Axios compromise and the cascading Trivy campaign illustrate how quickly this abuse can move once attacker activity enters build and delivery workflows. This blog provides an overview of the latest supply chain and security tool incidents with Darktrace telemetry and defensive actions to improve organizations defensive cyber posture.

1. Why the Axios Compromise Scaled

On 31 March 2026, attackers hijacked the npm account of Axios’s lead maintainer, publishing malicious versions 1.14.1 and 0.30.4 that silently pulled in a malicious dependency, plain‑crypto‑[email protected]. Axios is a popular HTTP client for node.js and  processes 100 million weekly downloads and appears in around 80% of cloud and application environments, making this a high‑leverage breach [1].

The attack chain was simple yet effective:

  • A compromised maintainer account enabled legitimate‑looking malicious releases.
  • The poisoned dependency executed Remote Access Trojans (RATs) across Linux, macOS and Windows systems.
  • The malware beaconed to a remote command-and-control (C2) server every 60 seconds in a loop, awaiting further instructions.
  • The installer self‑cleaned by deleting malicious artifacts.

All of this matters because a single maintainer compromise was enough to project attacker access into thousands of trusted production environments without exploiting a single vulnerability.

A view from Darktrace

Multiple cases linked with the Axios compromise were identified across Darktrace’s customer base in March 2026, across both Darktrace / NETWORK and Darktrace / CLOUD deployments.

In one Darktrace / CLOUD deployment, an Azure Cloud Asset was observed establishing new external HTTP connectivity to the IP 142.11.206[.]73 on port 8000. Darktrace deemed this activity as highly anomalous for the device based on several factors, including the rarity of the endpoint across the network and the unusual combination of protocol and port for this asset. As a result, the triggering the "Anomalous Connection / Application Protocol on Uncommon Port" model was triggered in Darktrace / CLOUD. Detection was driven by environmental context rather than a known indicator at the time. Subsequent reporting later classified the destination as malicious in relation to the Axios supply‑chain compromise, reinforcing the gap that often exists between initial attacker activity and the availability of actionable intelligence. [5]

Additionally, shortly before this C2 connection, the device was observed communicating with various endpoints associated with the NPM package manager, further reinforcing the association with this attack.

Darktrace’s detection of the unusual external connection to 142.11[.]206[.]73 via port 8000.  
Figure 1: Darktrace’s detection of the unusual external connection to 142.11[.]206[.]73 via port 8000.  

Within Axios cases observed within Darktrace / NETWORK customer environments, activity generally focused on the use of newly observed cURL user agents in outbound connections to the C2 URL sfrclak[.]com/6202033, alongside the download of malicious files.

In other cases, Darktrace / NETWORK customers with Microsoft Defender for Endpoint integration received alerts flagging newly observed system executables and process launches associated with C2 communication.

A Security Integration Alert from Microsoft Defender for Endpoint associated with the Axios supply chain attack.
Figure 2: A Security Integration Alert from Microsoft Defender for Endpoint associated with the Axios supply chain attack.

2. Why Trivy bypassed security tooling trust

Between late February and March 22, 2026, the threat group TeamPCP leveraged credentials from a previous incident to insert malicious artifacts across Trivy’s distribution ecosystem, including its CI automation, release binaries, Visual Studio Code extensions, and Docker container images [2].

While public reporting has emphasized GitHub Actions, Darktrace telemetry highlights attacker execution within CI/CD runner environments, including ephemeral build runners. These execution contexts are typically granted broad trust and limited visibility, allowing malicious activity within build automation to blend into expected operational workflows, regardless of provider.

This was a coordinated multi‑phase attack:

  • 75 of 76  of trivy-action tags and all setup‑trivy tags were force‑pushed to deliver a malicious payload.
  • A malicious binary (v0.69.4) was distributed across all major distribution channels.
  • Developer machines were compromised, receiving a persistent backdoor and a self-propagating worm.
  • Secrets were exfiltrated at scale, including SSH keys, Kuberenetes tokens, database passwords, and cloud credentials across Amazon Web Service (AWS), Azure, and Google Cloud Platform (GCP).

Within Darktrace’s customer base, an AWS EC2 instance monitored by Darktrace / CLOUD  appeared to have been impacted by the Trivy attack. On March 19, the device was seen connecting to the attacker-controlled C2 server scan[.]aquasecurtiy[.]org (45.148.10[.]212), triggering the model 'Anomalous Server Activity / Outgoing from Server’ in Darktrace / CLOUD.

Despite this limited historical context, Darktrace assessed this activity as suspicious due to the rarity of the destination endpoint across the wider deployment. This resulted in the triggering of a model alert and the generation of a Cyber AI Analyst incident to further analyze and correlate the attack activity.

TeamPCP’s continued abused of GitHub Actions against security and IT tooling has also been observed more recently in Darktrace’s customer base. On April 22, an AWS asset was seen connecting to the C2 endpoint audit.checkmarx[.]cx (94.154.172[.]43). The timing of this activity suggests a potential link to a malicious Bitwarden package distributed by the threat actor, which was only available for a short timeframe on April 22. [4][3]

Figure 3: A model alert flagging unusual external connectivity from the AWS asset, as seen in Darktrace / CLOUD .

While the Trivy activity originated within build automation, the underlying failure mode mirrors later intrusions observed via management tooling. In both cases, attackers leveraged platforms designed for scale and trust to execute actions that blended into normal operational noise until downstream effects became visible.

Quest KACE: Legacy Risk, Real Impact

The Quest KACE System Management Appliance (SMA) incident reinforces that software risk is not confined to development pipelines alone. High‑trust infrastructure and management platforms are increasingly leveraged by adversaries when left unpatched or exposed to the internet.

Throughout March 2026, attackers exploited CVE 2025-32975 to authentication on outdated, internet-facing KACE appliances, gaining administrative control and pushing remote payloads into enterprise environments. Organizations still running pre-patch versions effectively handed adversaries a turnkey foothold, reaffirming a simple strategic truth: legacy management systems are now part of the supply-chain threat surface, and treating them as “low-risk utilities” is no longer defensible [3].

Within the Darktrace customer base, a potential case was identified in mid-March involving an internet-facing server that exhibited the use of a new user agent alongside unusual file downloads and unexpected external connectivity. Darktrace identified the device downloading file downloads from "216.126.225[.]156/x", "216.126.225[.]156/ct.py" and "216.126.225[.]156/n", using the user agents, "curl/8.5.0" & "Python-urllib/3.9".

The timeframe and IoCs observed point towards likely exploitation of CVE‑2025‑32975. As with earlier incidents, the activity became visible through deviations in expected system behavior rather than through advance knowledge of exploitation or attacker infrastructure. The delay between observed exploitation and its addition to the Known Exploited Vulnerabilities (KEV) catalogue underscores a recurring failure: retrospective validation cannot keep pace with adversaries operating at automation speed.

The strategic pattern: Ecosystem‑scale adversaries

The Axios and Trivy compromises are not anomalies; they are signals of a structural shift in the threat landscape. In this post-trust era, the compromise of a single maintainer, repository token, or CI/CD tag can produce large-scale blast radiuses with downstream victims numbering in the thousands. Attackers are no longer just exploiting vulnerabilities; they are exploiting infrastructure privileges, developer trust relationships, and automated build systems that the industry has generally under secured.

Supply‑chain compromise should now be treated as an assumed breach scenario, not a specialized threat class, particularly across build, integration, and management infrastructure. Organizations must operate under the assumption that compromise will occur within trusted software and automation layers, not solely at the network edge or user endpoint. Defenders should therefore expect compromise to emerge from trusted automation layers before it is labelled, validated, or widely understood.

The future of supply‑chain defense lies in continuous behavioral visibility, autonomous detection across developer and build environments, and real‑time anomaly identification.

As AI increasingly shapes software development and security operations, defenders must assume adversaries will also operate with AI in the loop. The defensive edge will come not from predicting specific compromises, but from continuously interrogating behavior across environments humans can no longer feasibly monitor at scale.

Credit to Nathaniel Jones (VP, Security & AI Strategy, FCISCO), Emma Foulger (Global Threat Research Operations Lead), Justin Torres (Senior Cyber Analyst), Tara Gould (Malware Research Lead)

Edited by Ryan Traill (Content Manager)

Appendices

References:

1)         https://www.infosecurity-magazine.com/news/hackers-hijack-axios-npm-package/

2)         https://thehackernews.com/2026/03/trivy-hack-spreads-infostealer-via.html

3)         https://thehackernews.com/2026/03/hackers-exploit-cve-2025-32975-cvss-100.html

4)         https://www.endorlabs.com/learn/shai-hulud-the-third-coming----inside-the-bitwarden-cli-2026-4-0-supply-chain-attack

5)         https://socket.dev/blog/axios-npm-package-compromised?trk=public_post_comment-text

IoCs

- 142.11.206[.]73 – IP Address – Axios supply chain C2

- sfrclak[.]com – Hostname – Axios supply chain C2

- hxxp://sfrclak[.]com:8000/6202033 - URI – Axios supply chain payload

- 45.148.10[.]212 – IP Address – Trivy supply chain C2

- scan.aquasecurtiy[.]org – Hostname - Trivy supply chain C2

- 94.154.172[.]43 – IP Address - Checkmarx/Bitwarden supply chain C2

- audit.checkmarx[.]cx – Hostname - Checkmarx/Bitwarder supply chain C2

- 216.126.225[.]156 – IP Address – Quest KACE exploitation C2

- 216.126.225[.]156/32 - URI – Possible Quest KACE exploitation payload

- 216.126.225[.]156/ct.py - URI - Possible Quest KACE exploitation payload

- 216.126.225[.]156/n - URI - Possible Quest KACE exploitation payload

- 216.126.225[.]156/x - URI - Possible Quest KACE exploitation payload

- e1ec76a0e1f48901566d53828c34b5dc – MD5 - Possible Quest KACE exploitation payload

- d3beab2e2252a13d5689e9911c2b2b2fc3a41086 – SHA1 - Possible Quest KACE exploitation payload

- ab6677fcbbb1ff4a22cc3e7355e1c36768ba30bbf5cce36f4ec7ae99f850e6c5 – SHA256 - Possible Quest KACE exploitation payload

- 83b7a106a5e810a1781e62b278909396 – MD5 - Possible Quest KACE exploitation payload

- deb4b5841eea43cb8c5777ee33ee09bf294a670d – SHA1 - Possible Quest KACE exploitation payload

- b1b2f1e36dcaa36bc587fda1ddc3cbb8e04c3df5f1e3f1341c9d2ec0b0b0ffaf – SHA256 - Possible Quest KACE exploitation payload

Darktrace Model Detections

Anomalous Connection / Application Protocol on Uncommon Port

Anomalous Server Activity / Outgoing from Server

Anomalous Connection / New User Agent to IP Without Hostname

Anomalous File / EXE from Rare External Location

Anomalous File / Script from Rare External Location

Anomalous Server Activity / New User Agent from Internet Facing System

Anomalous Server Activity / Rare External from Server

Antigena / Network / External Threat / Antigena Suspicious File Block

Antigena / Network / External Threat / Antigena Suspicious File Pattern of Life Block

Device / New User Agent

Device / Internet Facing Device with High Priority Alert

Anomalous File / New User Agent Followed By Numeric File Download

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About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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May 5, 2026

How email-delivered prompt injection attacks can target enterprise AI – and why it matters

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What are email-delivered prompt injection attacks?

As organizations rapidly adopt AI assistants to improve productivity, a new class of cyber risk is emerging alongside them: email-delivered AI prompt injection. Unlike traditional attacks that target software vulnerabilities or rely on social engineering, this is the act of embedding malicious or manipulative instructions into content that an AI system will process as part of its normal workflow. Because modern AI tools are designed to ingest and reason over large volumes of data, including emails, documents, and chat histories, they can unintentionally treat hidden attacker-controlled text as legitimate input.  

At Darktrace, our analysis has shown an increase of 90% in the number of customer deployments showing signals associated with potential prompt injection attempts since we began monitoring for this type of activity in late 2025. While it is not always possible to definitively attribute each instance, internal scoring systems designed to identify characteristics consistent with prompt injection have recorded a growing number of high-confidence matches. The upward trend suggests that attackers are actively experimenting with these techniques.

Recent examples of prompt injection attacks

Two early examples of this evolving threat are HashJack and ShadowLeak, which illustrate prompt injection in practice.

HashJack is a novel prompt injection technique discovered in November 2025 that exploits AI-powered web browsers and agentic AI browser assistants. By hiding malicious instructions within the URL fragment (after the # symbol) of a legitimate, trusted website, attackers can trick AI web assistants into performing malicious actions – potentially inserting phishing links, fake contact details, or misleading guidance directly into what appears to be a trusted AI-generated output.

ShadowLeak is a prompt injection method to exfiltrate PII identified in September 2025. This was a flaw in ChatGPT (now patched by OpenAI) which worked via an agent connected to email. If attackers sent the target an email containing a hidden prompt, the agent was tricked into leaking sensitive information to the attacker with no user action or visible UI.

What’s the risk of email-delivered prompt injection attacks?

Enterprise AI assistants often have complete visibility across emails, documents, and internal platforms. This means an attacker does not need to compromise credentials or move laterally through an environment. If successful, they can influence the AI to retrieve relevant information seamlessly, without the labor of compromise and privilege escalation.

The first risk is data exfiltration. In a prompt injection scenario, malicious instructions may be embedded within an ordinary email. As in the ShadowLeak attack, when AI processes that content as part of a legitimate task, it may interpret the hidden text as an instruction. This could result in the AI disclosing sensitive data, summarizing confidential communications, or exposing internal context that would otherwise require significant effort to obtain.

The second risk is agentic workflow poisoning. As AI systems take on more active roles, prompt injection can influence how they behave over time. An attacker could embed instructions that persist across interactions, such as causing the AI to include malicious links in responses or redirect users to untrusted resources. In this way, the attacker inserts themselves into the workflow, effectively acting as a man-in-the-middle within the AI system.

Why can’t other solutions catch email-delivered prompt injection attacks?

AI prompt injection challenges many of the assumptions that traditional email security is built on. It does not fit the usual patterns of phishing, where the goal is to trick a user into clicking a link or opening an attachment.  

Most security solutions are designed to detect signals associated with user engagement: suspicious links, unusual attachments, or social engineering cues. Prompt injection avoids these indicators entirely, meaning there are fewer obvious red flags.

In this case, the intention is actually the opposite of user solicitation. The objective is simply for the email to be delivered and remain in the inbox, appearing benign and unremarkable. The malicious element is not something the recipient is expected to engage with, or even notice.

Detection is further complicated by the nature of the prompts themselves. Unlike known malware signatures or consistent phishing patterns, injected prompts can vary widely in structure and wording. This makes simple pattern-matching approaches, such as regex, unreliable. A broad rule set risks generating large numbers of false positives, while a narrow one is unlikely to capture the diversity of possible injections.

How does Darktrace catch these types of attacks?

The Darktrace approach to email security more generally is to look beyond individual indicators and assess context, which also applies here.  

For example, our prompt density score identifies clusters of prompt-like language within an email rather than just single occurrences. Instead of treating the presence of a phrase as a blocking signal, the focus is on whether there is an unusual concentration of these patterns in a way that suggests injection. Additional weighting can be applied where there are signs of obfuscation. For example, text that is hidden from the user – such as white font or font size zero – but still readable by AI systems can indicate an attempt to conceal malicious prompts.

This is combined with broader behavioral signals. The same communication context used to detect other threats remains relevant, such as whether the content is unusual for the recipient or deviates from normal patterns.

Ask your email provider about email-delivered AI prompt injection

Prompt injection targets not just employees, but the AI systems they rely on, so security approaches need to account for both.

Though there are clear indications of emerging activity, it remains to be seen how popular prompt injection will be with attackers going forward. Still, considering the potential impact of this attack type, it’s worth checking if this risk has been considered by your email security provider.

Questions to ask your email security provider

  • What safeguards are in place to prevent emails from influencing AI‑driven workflows over time?
  • How do you assess email content that’s benign for a human reader, but may carry hidden instructions intended for AI systems?
  • If an email contains no links, no attachments, and no social engineering cues, what signals would your platform use to identify malicious intent?

Visit the Darktrace / EMAIL product hub to discover how we detect and respond to advanced communication threats.  

Learn more about securing AI in your enterprise.

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About the author
Kiri Addison
Senior Director of Product
Your data. Our AI.
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