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April 29, 2025

MFA Under Attack: AiTM Phishing Kits Abusing Legitimate Services

Tycoon 2FA uses AiTM phishing and legitimate services to bypass MFA. Darktrace AI stopped it, read the blog to learn how Self-Learning AI detects sophisticated threats.
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
Alexandra Sentenac
Cyber Analyst
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29
Apr 2025

In late 2024 and early 2025, the Darktrace Security Operations Center (SOC) investigated alerts regarding separate cases of Software-as-a-Service (SaaS) account compromises on two customer environments that presented several similarities, suggesting they were part of a wider phishing campaign.

This campaign was found to leverage the project collaboration and note-taking application, Milanote, and the Tycoon 2FA phishing kit.

Legitimate services abused

As highlighted in Darktrace's 2024 Annual Threat Report [1], threat actors are abusing legitimate services, like Milanote, in their phishing campaigns. By leveraging these trusted platforms and domains, malicious actors can bypass traditional security measures, making their phishing emails appear benign and increasing the likelihood of successful attacks.

Darktrace categorizes these senders and platforms as free content senders. These services allow users to send emails containing custom content (e.g., files) from fully validated, fixed service address belonging to legitimate corporations. Although some of these services permit full body and subject customization by attackers, the structure of these emails is generally consistent, making it challenging to differentiate between legitimate and malicious emails.

What is Tycoon 2FA?

Tycoon 2FA is an Adversary-in-the-Middle (AitM) phishing kit, first seen in August 2023 and distributed via the Phishing-as-a-Service (PhaaS) model [2]. It targets multi-factor authentication (MFA) by intercepting credentials and MFA tokens during authentication on fake Microsoft or Google login pages. The attacker captures session cookies after MFA is completed, allowing them to replay the session and access the user account, even if credentials are reset. The rise in MFA use has increased the popularity of AitM phishing kits like Tycoon 2FA and Mamba 2FA, another AiTM phishing kit investigated by Darktrace.

Initial access via phishing email

At the beginning of 2025, Darktrace observed phishing emails leveraging Milanote being sent to multiple internal recipients in an organization. In this attack, the same email was sent to 19 different users, all of which were held by Darktrace.

The subject line of the emails mentioned both a legitimate internal user of the company, the company name, as well as a Milanote board regarding a “new agreement” in German. It is a common social engineering technique to mention urgent matters, such as unpaid invoices, expired passwords, or awaiting voicemails, in the subject line to prompt immediate action from the user. However, this tactic is now widely covered in phishing awareness training, making users more suspicious of such emails. In this case, while the subject mentioned a “new agreement,” likely raising the recipient’s curiosity, the tone remained professional and not overly alarming. Additionally, the mention of a colleague and the standardized language typical of free content sender emails further helped dispel concerns regarding the email.

These emails were sent by the legitimate address support@milanote[.]com and referenced "Milanote" in the personal field of the header but originated from the freemail address “ahnermatternk.ef.od.13@gmail[.]com”. Darktrace / EMAIL recognized that none of the recipients had previously received a file share email from Milanote, making this sender unfamiliar in the customer's email environment

The emails contained several benign links to legitimate Milanote endpoints (including an unsubscribe link) which were not flagged by Darktrace. However, they also included a malicious link designed to direct recipients to a pre-filled credential harvesting page hosted on Milanote, prompting them to register for an account. Despite not blocking the legitimate Milanote links in the same email, Darktrace locked the malicious link, preventing users from visiting the credential harvester.

Credential harvesting page sent to recipients, as seen in. sandbox environment.
Figure 1: Credential harvesting page sent to recipients, as seen in. sandbox environment.

Around one minute later, one recipient received a legitimate email from Milanote confirming their successful account registration, indicating they had accessed the phishing page. This email had a lower anomaly score and was not flagged by Darktrace / EMAIL because, unlike the first email, it did not contain any suspicious links and was a genuine account registration notification. Similarly, in the malicious Milanote email, only the link leading to the phishing page was blocked, while the benign and legitimate Milanote links remained accessible, demonstrating Darktrace’s precise and targeted actioning.

A legitimate and a malicious Milanote email received by one recipient.
Figure 2: A legitimate and a malicious Milanote email received by one recipient.

Around the same time, Darktrace / NETWORK observed the same user’s device making DNS query for the domain name “lrn.ialeahed[.]com” , which has been flagged as a Tycoon 2FA domain [2], suggesting the use of this phishing platform.

Once the user had entered their details in the credential harvester, it is likely that they were presented a document hosted on Milanote that contained the final payload link – likely hidden behind text instructing users to access a “new agreement” document.

External research indicates that the user was likely directed to a Cloudflare Turnstile challenge meant to reroute unwanted traffic, such as automated security scripts and penetration testing tools [2] [3]. After these checks and other background processes are completed, the user is directed to the final landing page. In this case, it was likely a fake login prompt hosted on the attacker’s server, where the user is asked to authenticate to their account using MFA. By burrowing malicious links and files in this manner, threat actors can evade analysis by traditional security email gateways, effectively bypassing their protection.

Darktrace’s analysis of the structure and word content of the phishing emails resulted in an 82% probability score that the email was malicious, and the email further received a 67% phishing inducement score, representing how closely the structure and word content of the emails compared to typical phishing emails.

All these unusual elements triggered multiple alerts in Darktrace / EMAIL, focusing on two main suspicious aspects: a new, unknown sender with no prior correspondence with the recipients or the environment, and the inclusion of a link to a previously unseen file storage solution.

Milanote phishing email as seen within Darktrace / EMAIL.
Figure 3: Milanote phishing email as seen within Darktrace / EMAIL.

After detecting the fifth email, the “Sender Surge” model alert was triggered in Darktrace / EMAIL due to a significant number of recipients being emailed by this new suspicious sender in a short period. These recipients were from various departments across the customer’s organization, including sales, marketing, purchasing, and production. Darktrace / EMAIL determined that the emails were sent to a highly unusual group of internal recipients, further raising doubts about the business legitimacy.

Darktrace / EMAIL suggested actions to contain the attack by holding all Milanote phishing emails back from recipient’s inboxes, except for the detailed email with locked links. However, autonomous actions were not enabled at the time, allowing the initial email to reach recipients' inboxes, providing a brief window for interaction. Unfortunately, during this window, one recipient clicked on the Milanote payload link, leading to the compromise of their account.

SaaS account takeover

About three minutes after the malicious Milanote email was received, Darktrace / IDENTITY detected an unusual login to the email recipient’s SaaS account. The SaaS actor was observed accessing files from their usual location in Germany, while simultaneously, a 100% rare login occurred from a location in the US that had never been seen in the customer’s environment before. This login was also flagged as suspicious by Microsoft 365, triggering a 'Conditional Access Policy' that required MFA authentication, which was successfully completed.

Tycoon 2FA adnimistration panel login page dated from October 2023 [3].
Figure 4: Tycoon 2FA adnimistration panel login page dated from October 2023 [3].

Despite the successful authentication, Darktrace / IDENTITY recognized that the login from this unusual location, coupled with simultaneous activity in another geographically distant location, were highly suspicious. Darktrace went on to observe MFA-validated logins from three separate US-based IP addresses: 89.185.80[.]19, 5.181.3[.]68, and 38.242.7[.]252. Most of the malicious activity was performed from the latter, which is associated with the Hide My Ass (HMA) VPN network [5].

Darktrace’s detection of the suspicious login from the US while the legitimate user was logged in from Germany.
Figure 5: Darktrace’s detection of the suspicious login from the US while the legitimate user was logged in from Germany.
Darktrace’s detection of the suspicious login following successful MFA authentication.
Figure 6: Darktrace’s detection of the suspicious login following successful MFA authentication.

Following this, the malicious actor accessed the user’s inbox and created a new mailbox rule named “GTH” that deleted any incoming email containing the string “milanote” in the subject line or body. Rules like this are a common technique used by attackers to leverage compromised accounts for launching phishing campaigns and concealing replies to phishing emails that might raise suspicions among legitimate account holders. Using legitimate, albeit compromised, accounts to send additional phishing emails enhances the apparent legitimacy of the malicious emails. This tactic has been reported as being used by Tycoon 2FA attackers [4].

The attacker accessed over 140 emails within the legitimate user’s inbox, including both the inbox and the “Sent Items” folder. Notably, the attacker accessed five emails in the “Sent Items” folder and modified their attachments. These emails were mainly related to invoices, suggesting the threat actor may have been looking to hijack those email threads to send fake invoices or replicate previous invoice emails.

Darktrace’s Cyber AI AnalystTM launched autonomous investigations into the individual events surrounding this suspicious activity. It connected these separate events into a single, broad account takeover incident, providing the customer with a clearer view of the ongoing compromise.

Cyber AI Analyst’s detection of unusual SaaS account activities in a single incident.
Figure 7: Cyber AI Analyst’s detection of unusual SaaS account activities in a single incident.
Cyber AI Analyst investigation of suspicious activities performed by the attacker.
Figure 8: Cyber AI Analyst investigation of suspicious activities performed by the attacker.

Darktrace's response

Within three minutes of the first unusual login alert, Darktrace’s Autonomous Response intervened, disabling the compromised user account for two hours.

As the impacted customer was subscribed to the Managed Threat Detection Service, Darktrace’s SOC team investigated the activity further and promptly alerted the customer’s security team. With the user’s account still disabled by Autonomous Response, the attack was contained, allowing the customer’s security team valuable time to investigate and remediate. Within ten minutes of receiving the alert from Darktrace’s SOC, they reset the user’s password, closed all active SaaS sessions, and deleted the malicious email rule. Darktrace’s SOC further supported the customer through the Security Operations Service Support service by providing information about the data accessed and identifying any other affected users.

Autonomous Response actions carried out by Darktrace / IDENTITY to contain the malicious activity
Figure 9: Autonomous Response actions carried out by Darktrace / IDENTITY to contain the malicious activity.

A wider Milanote phishing campaign?

Around a month before this compromise activity, Darktrace alerted another customer to similar activities involving two compromised user accounts. These accounts created new inbox rules named “GFH” and “GVB” to delete all incoming emails containing the string “milanote” in their subject line and/or body.

The phishing emails that led to the compromise of these user accounts were similar to the ones discussed above. Specifically, these emails were sent via the Milanote platform and referenced a “new agreement” (in Spanish) being shared by a colleague. Additionally, the payload link included in the phishing emails showed the same UserPrincipalName (UPN) attribute (i.e., click?upn=u001.qLX9yCzR), which has been seen in other Milanote phishing emails leveraging Tycoon 2FA reported by OSINT sources [6]. Interestingly, in some cases, the email also referenced a “new agreement” in Portuguese, indicating a global campaign.

Based on the similarities in the rule’s naming convention and action, as well as the similarities in the phishing email subjects, it is likely that these were part of the same campaign leveraging Milanote and Tycoon 2FA to compromise user accounts. Since its introduction, the Tycoon 2FA phishing kit has undergone several enhancements to increase its stealth and obfuscation methods, making it harder for security tools to detect. For example, the latest versions contain special source code to obstruct web page analysis by defenders, prevent users from copying meaningful text from the phishing webpages, and disable the right-click menu to prevent offline analysis [4].

Conclusion

Threat actors are continually employing new methods to bypass security detection tools and measures. As highlighted in this blog, even robust security mechanisms like MFA can be compromised using AitM phishing kits. The misuse of legitimate services such as Milanote for malicious purposes can help attackers evade traditional email security solutions by blurring the distinction between legitimate and malicious content.

This is why security tools based on anomaly detection are crucial for defending against such attacks. However, user awareness is equally important. Delays in processing can impact the speed of response, making it essential for users to be informed about these threats.

[related-resource]

Appendices

References

[1] https://www.darktrace.com/resources/annual-threat-report-2024

[2] https://www.validin.com/blog/tycoon_2fa_analyzing_and_hunting_phishing-as-a-service_domains

[3] https://blog.sekoia.io/tycoon-2fa-an-in-depth-analysis-of-the-latest-version-of-the-aitm-phishing-kit/#h-iocs-amp-technical-details

[4] https://blog.barracuda.com/2025/01/22/threat-spotlight-tycoon-2fa-phishing-kit

[5] https://spur.us/context/38.242.7.252    

[6] https://any.run/report/5ef1ac94e4c6c1dc35579321c206453aea80d414108f9f77abd2e2b03ffbd658/be5351d9-53c0-470b-8708-ee2e29300e70

Indicators of Compromise (IoCs)

IoC         Type      Description + Probability

89.185.80[.]19 - IP Address - Malicious login

5.181.3[.]68 - IP Address -Malicious login

38.242.7[.]252 - IP Address - Malicious login and new email inbox rule creation -  Hide My Ass VPN

lrn.ialeahed[.]com – Hostname - Likely Tycoon 2FA domain

Darktrace Model Detections

Email alerts

Platforms / Free Content Sender + High Sender Surge

Platforms / Free Content Sender + Sender Surge

Platforms / Free Content Sender + Unknown Initiator

Platforms / Free Content Sender

Platforms / Free Content Sender + First Time Recipient

Unusual / New Sender Surge

Unusual / Sender Surge

Antigena Anomaly / High Antigena Anomaly

Association / Unknown Sender

History / New Sender

Link / High Rarity Link to File Storage

Link/ Link To File Storage

Link / Link to File Storage + Unknown Sender

Link / Low Link Association

Platforms / Free Content Sender + First Time Initiator

Platforms / Free Content Sender + Unknown Initiator + Freemail

Platforms / Free Content Sender Link

Unusual / Anomalous Association

Unusual / Unlikely Recipient Association

IDENTITY

SaaS / Access / Unusual External Source for SaaS Credential Use

SaaS / Compromise / Login from Rare High Risk Endpoint

SaaS / Access / M365 High Risk Level Login

SaaS / Compromise / Login From Rare Endpoint While User Is Active

SaaS / Access / MailItemsAccessed from Rare Endpoint

SaaS / Unusual Activity / Multiple Unusual SaaS Activities

SaaS / Unusual Activity / Multiple Unusual External Sources For SaaS Credential

SaaS / Compliance / Anomalous New Email Rule

SaaS / Compromise / Unusual Login and New Email Rule

SaaS / Compromise / SaaS Anomaly Following Anomalous Login

Antigena / SaaS / Antigena Suspicious SaaS Activity Block

Antigena / SaaS / Antigena Enhanced Monitoring from SaaS User Block

Antigena / SaaS / Antigena Unusual Activity Block

Antigena / SaaS / Antigena Suspicious SaaS and Email Activity Block

Cyber AI Analyst Incident

Possible Hijack of Office365 Account

MITRE ATT&CK Mapping

Tactic – Technique

DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS - Cloud Accounts

INITIAL ACCESS - Phishing

CREDENTIAL ACCESS - Steal Web Session Cookie

PERSISTENCE - Account Manipulation

PERSISTENCE - Outlook Rules

RESOURCE DEVELOPMENT - Email Accounts

RESOURCE DEVELOPMENT - Compromise Accounts

Experts breakdown of Identity Security in the Cloud Era

This white paper discusses the current identity threat landscape and how defenders can adopt new tools to better secure their users and data.

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
Alexandra Sentenac
Cyber Analyst

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June 24, 2026

From Click to Command: Behavioral Detection of AppleScript-Led MacOS Intrusions

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Introduction

Darktrace’s Threat Research team is publishing this analysis to help defenders understand an active pattern of macOS tradecraft observed in multiple customer environments. This post summarizes the behaviors observed, how they were assessed, and what defenders can do now.

Across multiple environments, Darktrace observed a consistent MacOS intrusion pattern beginning with ClickFix-style user-assisted “update” execution and transitioning into AppleScript-driven post-compromise activity and sustained outbound signaling.

While individual indicators were low-confidence, the repeated convergence of weak behavioral signals — including HTTP POST beaconing, rare or IP-only destinations, SSL anomalies, and abnormal client characteristics — provided a defensible indication of command-and-control establishment Darktrace detection and response in these cases was driven by behavior over artifacts. In the highest-confidence instances, automated containment disrupted outbound signaling before sustained tasking could occur.

Background

ClickFix-style activity typically relies on user-assisted execution and plausible “update” pretexting, followed by post-execution use of native tools to keep the footprint light. In MacOS environments, AppleScript and other built-in scripting mechanisms enable flexible post-compromise workflows while minimizing stable file-based indicators.

Following execution, affected devices exhibited a consistent behavioral pattern. AppleScript or equivalent native scripting activity was observed initiating follow-on workflows, after which outbound communications began to establish a structured rhythm.

These communications were characterized by repeated HTTP POST requests to low-prevalence or IP-only endpoints, often combined with unusual SSL properties and client identifiers that diverged from baseline device behavior. Individually, these signals were weak. When correlated across time and devices, they formed a pattern consistent with control establishment rather than benign software activity.

In higher-confidence cases, Autonomous Response actions were able to reduce or halt outbound signaling, interrupting the attacker’s ability to maintain control.

Detection Timeline

In representative cases, the sequence unfolded as follows:

Stage 1 – Initial Execution

Initial activity began with suspicious or masqueraded execution on a MacOS endpoint, consistent with ClickFix-style user deception.

Stage 2 – Post-Execution Scripting

This was followed closely by native scripting activity, most commonly AppleScript, indicating the transition into post-execution workflow.

Stage 3 – Outbound Communications

Outbound communications then emerged, initially sporadic but quickly forming a consistent cadence of HTTP POST requests to rare external endpoints.

Stage 4 – Anomaly Convergence

As activity persisted, additional anomalies became visible — unusual SSL characteristics, abnormal user agents, and connections to infrastructure with no prior network prevalence.

Stage 5 – Autonomous Response

In the most mature stages of the activity, automated containment actions disrupted outbound communications on affected devices, limiting the attacker’s ability to continue tasking while investigations progressed.

Darktrace coverage and detections

The following use-case highlights systems likely affected by malicious macOS intrusion activity linked by Microsoft to the Democratic People’s Republic of Korea (DPRK) [1], with indications of suspicious behavior observed between March 1 and May 3, 2026. The activity overlaps with patterns described in recent reporting on DPRK-nexus MacOS intrusions [1], though attribution confidence in this case remains moderate and based on behavioral alignment rather than solely infrastructure linkage.

Analyst confidence emerged through the correlation of multiple weak signals across time and devices. This included model coverage for rare external communications, sustained beaconing patterns, repeated HTTP POSTs, and anomalous client characteristics. Where enabled, Autonomous Response actions disrupted the most active outbound paths to reduce the attacker’s ability to maintain control while Darktrace’s investigation continued.

Notably, this highly anomalous behavior included:

  • Outbound connections to the rare external endpoint, zoom[.]uswebob[.]us associated with IP address, 148.72.73[.]98 [2][3] over port 443
  • Outbound connections to the rare external endpoint, check02id[.]com associated with IP address, 83.136.210[.]180 [4] over port 7365
  • Outbound connections to the rare external endpoints, 104.145.210[.]107 [5] over port 8443 and 83.136.208[.]48 [6] over port 443
  • Outbound connections to the rare external endpoint, 83.136.208[.]246 [7] over port 6783 with observed URI `/api/daemon` and a PowerShell user agent

Darktrace’s detection initially highlighted a desktop device (running MacOS) engaging in anomalous behavior as early as March 12, 2026. Starting on March 12, the source device triggered a ‘Possible Doppelganger Attack’ alert including connectivity to the hostname "zoom[.]uswebob[.]us · 148.72.73[.]98" over port 443 (TCP, HTTPS, H2). This model highlights a device connecting to a location that is rare but masquerades as legitimate software, such as Zoom in this case, a commonly used technique to blend into expected traffic [2] [3].

 Initial connectivity observed to the rare external hostname, zoom[.]uswebob[.]us · 148.72.73[.]98, over port 443.
Figure 1: Initial connectivity observed to the rare external hostname, zoom[.]uswebob[.]us · 148.72.73[.]98, over port 443.

This was followed roughly seven later by a connection to 104.145.210[.]107 over port 8443, during which approximately 250 KiB of data of inbound data and 30 MiB of outbound data was observed, triggering the ‘Unusual Activity / Unusual External Data to New Endpoint’ in Darktrace.

Quickly after this connection, Darktrace’s Autonomous Response intervened, blocking the device’s access to the unusual external location and halting the data exfiltration attempt.

Figure 2: Darktrace’s detection of unusual data exfiltration, shortly followed by an Autonomous Response action to block it.

The device continued to consistently trigger model alerts relating to unusual external connectivity, including 'Posting HTTP to IP Without Hostname', 'Anomalous Connection / Rare External SSL Self-Signed' alerts, until well after 3 PM that day.

Figure 3: Additional external connectivity to new IP without a hostname, including connectivity to 83.136.208[.]246, alongside an anomalous ‘curl/8.7.1’ user agent and ‘/api/daemon’ URI.
Figure 4: Continued external SSL connectivity to IP 83.136.208[.]48, including connectivity to 83.136.208[.]246, alongside an anomalous ‘curl/8.7.1’ user agent and ‘/api/daemon’ URI.
Figure 5: Continued external HTTP connectivity to hostname, check02id[.]com · 83.136.210[.]180, alongside an anomalous ‘Go-http-client/1,1’ user agent.

From March 13 to March 28, the device continued exhibit unusual connectivity to various endpoints (e.g., 83.136.208[.]48, 83.136.208[.]246, check02id[.]com · 83.136.210[.]180), with the 'Multiple HTTP POSTs to Rare Hostname' model consistently triggering.

Windows OS Case

Pivoting over to an additional device, this time running Windows OS, anomalous behavior was also observed between March 30 and April 20. Notably, on March 30, the device was observed making a large number of suspicious external connection attempts to 83.136.208[.]246 over port 6783, all of which failed.

A further indicator was observed on April 1 with PowerShell connectivity to the same rare endpoint (83.136.208[.]246, port 6783), using the URI '/api/daemon' and the user agent 'Mozilla/5.0 (Windows NT; Windows NT 10.0; fr-FR) WindowsPowerShell/5.1.26100.7920'.  Additional alerts included 'New User Agent to IP Without Hostname' and 'Anomalous Github Download', alongside activity involving the same endpoint.

Figure 6 : ‘Anomalous Powershell to Rare External Destination’ and ‘Github Download’ model alerts. This behavior involved connectivity with the endpoints ‘83.136.208[.]246’ and ‘github[.]com’.

The device continued triggering 'Posting HTTP to IP Without Hostname' & 'PowerShell to External Rare' alerts between April 4 and April 20 across multiple related endpoints (i.e., 83.136.208[.]48, 83.136.208[.]246, check02id[.]com · 83.136.210[.]180).

Darktrace’s Autonomous Response capability was able to block suspicious PowerShell attempts to unusual external locations, as shown below in an example from April 20.

Figure 7:  Autonomous Response intervening to block an unusual PowerShell connection to an external destination.

Cyber AI Analyst investigations

In higher-confidence instances, Darktrace’s Cyber AI Analyst investigations helped connect otherwise separate model alerts into a single incident narrative, highlighting the attacker’s progression from post-execution scripting into sustained outbound signaling. This contextual stitching is particularly valuable in macOS scenarios where static artefacts are limited, and behavioral sequencing defines the intrusion.

Cyber AI Analyst investigations highlighted alerts on March 12, including unusual repeated connections and possible SSL command-and-control (C2) to multiple endpoints:

Figure 8: Cyber AI Analyst investigation linking events into a unified incident.

Autonomous Response

In addition to the containment actions detailed earlier, Autonomous Response implemented multiple additional measures to contain suspicious activity throughout the course of this attack. Whenever unusual external connectivity was detected, Darktrace blocked it, closing down potential C2 channels. Likewise, when data exfiltration attempts were identified, these connections were stopped to prevent the potential loss of sensitive data.

Figure 9: Autonomous Response actions implemented by Darktrace in response to suspicious connectivity in mid-March.

Furthermore, in cases where a device was deemed to have carried out a significant number of anomalous activities, Darktrace enforced a “pattern of life” on the device, preventing it from deviating from its expected behavior while allowing legitimate business operations to continue uninterrupted.

Figure 10: Autonomous Response actions implemented by Darktrace in response to suspicious connectivity in April, including the “Enforce Pattern of Life” action.

Conclusion

macOS intrusion tradecraft continues to shift toward native tooling and lightweight control channels designed to evade signature-led controls.

The repeated convergence of rare destinations, POST-based signaling, and anomalous client behavior — observed across time and across devices — provided sufficient evidence to act early and with confidence.

As macOS tradecraft continues to evolve, the defender advantage increasingly lies not in signatures, but in the ability to reason from behavior.

Credit to Justin Torres (Senior Cyber Analyst), Nathaniel Jones (VP, Security & AI Strategy, FCISO)

Edited by Ryan Traill (Content Manager)

Appendices

Darktrace Model Alert Coverage:

/ NETWORK-based model alerts:

·       Anomalous Connection::Multiple HTTP POSTs to Rare Hostname

·       Anomalous Connection::Rare External SSL Self-Signed

·       Anomalous Connection::Powershell to Rare External

·       Anomalous Connection::New User Agent to IP Without Hostname

·       Anomalous Connection::Posting HTTP to IP Without Hostname

·       Compromise::Fast Beaconing to DGA

·       Compromise::Large Number of Suspicious Failed Connections

·       Device::Anomalous Github Download

·       Device::New PowerShell User Agent

·       Unusual Activity::Unusual External Data to New Endpoint

/ NETWORK-based Autonomous Response model alerts:

·       Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block

·       Antigena / Network::Significant Anomaly::Antigena Controlled and Model Breach

·       Antigena / Network::Significant Anomaly::Antigena Breaches Over Time Block

Indicators of Compromise (IoCs)

IP/Hostname:

·       zoom[.]uswebob[.]us · 148.72.73[.]98

·       83.136.208[.]246

·       check02id[.]com · 83.136.210[.]180

·       83.136.208[.]48

·       104.145.210[.]107

URIs:

·       /api/daemon

Destination Port Usage:

·       6783

·       5202

·       443

·       7365

·       8443

ASN:

·       AS400897 PETROSKY

·       AS398256 AS-ULTAHOST

User agents:

·       Mozilla/5.0 (Windows NT; Windows NT 10.0; fr-FR) WindowsPowerShell/5.1.26100.7920

·       Go-http-client/1.1

·       curl/8.7.1

MITRE ATT&CK Mapping

(Technique Name - Tactic - ID - Sub-Technique of)

·       Browser Session Hijacking - COLLECTION - T1185

·       Web Protocols - COMMAND AND CONTROL - T1071.001 - T1071

·       Install Digital Certificate - RESOURCE DEVELOPMENT - T1608.003 - T1608

·       PowerShell - EXECUTION - T1059.001 - T1059

·       Domain Generation Algorithms - COMMAND AND CONTROL - T1568.002 - T1568

·       Non-Standard Port - COMMAND AND CONTROL - T1571

·       Malware - RESOURCE DEVELOPMENT - T1588.001 - T1588

·       Web Service - COMMAND AND CONTROL - T1102

·       Code Repositories - COLLECTION - T1213.003 - T1213

·       Exploitation of Remote Services - LATERAL MOVEMENT - T1210

·       Exfiltration Over C2 Channel - EXFILTRATION - T1041

·       Exfiltration to Cloud Storage - EXFILTRATION - T1567.002 - T1567

References:

[1] https://www.microsoft.com/en-us/security/blog/2026/04/16/dissecting-sapphire-sleets-macos-intrusion-from-lure-to-compromise/

[2] https://radar.securityalliance.org/advisory-on-dprk-unc1069-fake-microsoft-teams-and-zoom-calls/

[3] https://www.virustotal.com/gui/domain/uswebob.us

[4] https://www.virustotal.com/gui/ip-address/83.136.210.180/community

[5] https://www.virustotal.com/gui/ip-address/104.145.210.107/community

[6] https://www.virustotal.com/gui/ip-address/83.136.208.48/community

[7] https://www.virustotal.com/gui/ip-address/83.136.208.246/community

[8] https://www.darktrace.com/blog/applescript-abuse-unpacking-a-macos-phishing-campaign

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About the author
Justin Torres
Cyber Analyst

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June 24, 2026

A New Security Challenge: The Curious Case of Prompt Language Analysis

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Why prompt analysis is emerging as a key AI security challenge

If securing AI has been one of the defining cybersecurity conversations of the past year, prompt analysis is quickly becoming one of its most interesting frontiers.

Security leaders are under pressure to understand how AI is being used across the business. In some organizations, that means governing employee use of chatbots. In others, it means overseeing copilots embedded into SaaS platforms, monitoring coding assistants, or assessing the growing footprint of autonomous agents. However different these use cases may appear on the surface, they share a common factor: humans and machines are usually interacting with enterprise systems through language.  

How prompt language differs from traditional security telemetry

For years, defenders have become used to working with familiar forms of telemetry: email traffic, network connections, API calls, endpoint processes, authentication events. Prompt language is different. It is not simply another log source. It is an expression of intent, instruction, curiosity, urgency, and sometimes manipulation. It reflects the end-goal of a user or agent, but not always with enough surrounding context to interpret the risk correctly.

Why existing security approaches only partially explain prompt risk

A growing number of vendors are approaching the task of securing AI from the angle they know best. Perimeter vendors are extending web or browser controls into AI usage. Identity vendors are emphasizing agent permissions and access governance. Data security and DLP providers are focusing on content inspection and exfiltration risk. All of these perspectives matter, but individually can’t fully explain the problem.

The challenge with securing AI is not just that a new application category has emerged. It is that language has become a new operating layer in the enterprise.

Employees now use prompts to summarize documents, generate code, analyze spreadsheets, query internal knowledge, and trigger multi-step actions through agents. In each case, prompt language acts as the interface between human intent and machine execution. That makes prompts incredibly valuable from a security perspective as they can hint at misuse, policy violations, data exposure, or attempts to circumvent controls. However, they can also be deeply ambiguous when viewed in isolation. That ambiguity is the heart of the issue.

Prompts as behavioral signals, not just text to classify

A prompt by itself tells you what was asked. It does not necessarily tell you whether the request is expected, risky, accidental, or entirely legitimate in context. Two nearly identical prompts can carry very different meanings depending on the role and function of who issued them, what systems they can access, and what actions followed. In other words, prompts are not just text to classify. They are behavioral signals to interpret.

Example: How context changes prompt risk entirely

Consider a common enterprise scenario. An employee is pulled into a new project with an aggressive deadline. Almost overnight, their use of AI tools spikes. They begin prompting more frequently, working across unfamiliar documents, querying new data sources, and interacting with more systems than usual to accelerate delivery. Viewed narrowly, this may look suspicious. Prompt volume increases, file access patterns change, API and SaaS activity rise. From some vantage points, it may resemble insider risk or unmanaged AI usage.

But now add context. Imagine that, earlier that day, the employee received instructions from a senior leader asking them to support a time-sensitive initiative. Their communication history shows that this leader is a legitimate reporting-line superior. Their recent collaboration patterns align with the new project team. Their subsequent activity, while unusual for that individual’s baseline, is consistent with the business task they were assigned.

What initially looked like a risk event may actually be a normal response to business pressure. Without the surrounding context of communication, organizational relationships, and broader behavioral patterns, prompt activity alone could generate more noise than insight.

The reverse is also true. A prompt may appear benign on the surface while the context around it suggests elevated risk. A request that seems routine could originate from a compromised user, a newly connected external agent, a shadow AI workflow, or a user acting outside their normal role. The language itself may not contain anything obviously malicious, but the surrounding conditions may tell a very different story.

What security teams need to analyze prompts effectively

The future of prompt analysis is not just about understanding language. It is about understanding language in context.

To do that well, security teams need more than prompt inspection. They need to understand:

  • Who is issuing the prompt, whether human or agent
  • How that identity normally behaves across the enterprise
  • What systems, data, and workflows are connected to the interaction
  • Which relationships and communications explain the surrounding activity
  • Whether the downstream actions align with expected business behavior

When those layers are absent, prompt analysis can become another isolated control surface: useful in theory, but limited in practice. Security teams may detect unusual wording but miss the operational function behind it, overreact to benign changes in behavior, or miss subtle misuse because the prompt itself did not appear dangerous.

How organizations should think about prompt analysis going forward

Security teams have seen this pattern before. In the cloud, posture without runtime context left important gaps. In identity, access control without behavioral understanding missed misuse that looked legitimate on paper. In data security, content inspection without business context often created friction without resolving risk. AI is exposing the same lesson again: controls are strongest when they are coordinated, not isolated. As organizations work to secure AI and identify gaps across their security operations, prompt analysis will become an increasingly important source of insight, but only as part of a broader strategy.

Prompt analysis will undoubtedly become more common, as prompts are one of the clearest windows into how people and agents are using AI systems. However, what matters most is not simply collecting prompts or filtering dangerous phrases, but being able to place that language inside a wider behavioral and operational picture.

Organizations that already have a broader understanding of how work gets done across the enterprise will be better positioned to make sense of prompt language as this category matures. They will be better able to distinguish urgency from abuse, experimentation from exfiltration, and productive AI adoption from hidden risk.

Figure 1: Darktrace / SECURE AI reconstructs the full sequence of events, showing every user and agent interaction in context, with risky prompts highlighted and categorized, including PII, sensitive data, and other policy violations.

At Darktrace, this is the key lesson emerging from the market: prompt language does matter, but it does not stand alone. It is most valuable when treated as a new behavioral input that can enrich understanding across the enterprise, not as a self-contained source of truth.

Why prompts become less useful when analyzed in isolation

The curious case of prompt language analysis, then, is this: the more important prompts become, the less useful they are in a vacuum.

The real opportunity is not just to see what was asked. It is to understand why it was asked, what it meant in that moment, and what happened next.

For a deeper look at how organizations are approaching this challenge from the strengths of prompt analysis to its limitations in isolation see Prompt Security in Enterprise AI: Strengths, Weaknesses, and Common Approaches, which expands on the role prompt-level controls play within a broader, context-driven security strategy.

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About the author
Nabil Zoldjalali
VP, Field CISO
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