December 9, 2024

Darktrace’s view on Operation Lunar Peek: Exploitation of Palo Alto firewall devices (CVE 2024-0012 and 2024-9474)

Darktrace’s Threat Research team investigated a major campaign exploiting vulnerabilities in Palo Alto firewall devices (CVE 2024-0012 and 2024-9474). Learn about the spike in post-exploitation activities and understand the need for anomaly-based detection to stay ahead of evolving threats.

Written by

Adam Potter

Senior Cyber Analyst

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

Adam Potter

Senior Cyber Analyst

Dec 2024

Introduction: Spike in exploitation and post-exploitation activity affecting Palo Alto firewall devices

As the first line of defense for many organizations, perimeter devices such as firewalls are frequently targeted by threat actors. If compromised, these devices can serve as the initial point of entry to the network, providing access to vulnerable internal resources. This pattern of malicious behavior has become readily apparent within the Darktrace customer base. In 2024, Darktrace Threat Research analysts identified and investigated at least two major campaigns targeting internet-exposed perimeter devices. These included the exploitation of PAN-OS firewall exploitation via CVE 2024-3400 and FortiManager appliances via CVE 2024-47575.

More recently, at the end of November, Darktrace analysts observed a spike in exploitation and post-exploitation activity affecting, once again, Palo Alto firewall devices in the days following the disclosure of the CVE 2024-0012 and CVE-2024-9474 vulnerabilities.

Threat Research analysts had already been investigating potential exploitation of the firewalls’ management interface after Palo Alto published a security advisory (PAN-SA-2024-0015) on November 8. Subsequent analysis of data from Darktrace’s Security Operations Center (SOC) and external research uncovered multiple cases of Palo Alto firewalls being targeted via the likely exploitation of these vulnerabilities since November 13, through the end of the month. Although this spike in anomalous behavior may not be attributable to a single malicious actor, Darktrace Threat Research identified a clear increase in PAN-OS exploitation across the customer base by threat actors likely utilizing the recently disclosed vulnerabilities, resulting in broad patterns of post-exploitation activity.

How did exploitation occur?

CVE 2024-0012 is an authentication bypass vulnerability affecting unpatched versions of Palo Alto Networks Next-Generation Firewalls. The vulnerability resides in the management interface application on the firewalls specifically, which is written in PHP. When attempting to access highly privileged scripts, users are typically redirected to a login page. However, this can be bypassed by supplying an HTTP request where a Palo Alto related authentication header can be set to “off”. Users can supply this header value to the Nginx reverse proxy server fronting the application which will then send it without any prior processing [1].

CVE-2024-9474 is a privilege escalation vulnerability that allows a PAN-OS administrator with access to the management web interface to execute root-level commands, granting full control over the affected device [2]. When combined, these vulnerabilities enable unauthenticated adversaries to execute arbitrary commands on the firewall with root privileges.

Post-Exploitation Patterns of Activity

Darktrace Threat Research analysts examined potential indicators of PAN-OS software exploitation via CVE 2024-0012 and CVE-2024-9474 during November 2024. The investigation identified three main groupings of post-exploitation activity:

Exploit validation and initial payload retrieval
Command and control (C2) connectivity, potentially featuring further binary downloads
Potential reconnaissance and cryptomining activity

Exploit Validation

Across multiple investigated customers, Darktrace analysts identified likely vulnerable PAN-OS devices conducting external network connectivity to bin services. Specifically, several hosts performed DNS queries for, and HTTP requests to Out-of-Band Application Security Testing (OAST) domains, such as csv2im6eq58ujueonqs0iyq7dqpak311i.oast[.]pro. These endpoints are commonly used by network administrators to harden defenses, but they are increasingly used by threat actors to verify successful exploitation of targeted devices and assess their potential for further compromise. Although connectivity involving OAST domains were prevalent across investigated incidents, this activity was not necessarily the first indicator observed. In some cases, device behavior involving OAST domains also occurred shortly after an initial payload was downloaded.

Figure 1: Darktrace model alert logs detailing the HTTP request to an OAST domain immediately following PAN-OS device compromise.

Initial Payload Retrieval

Following successful exploitation, affected devices commonly performed behaviors indicative of initial payload download, likely in response to incoming remote command execution. Typically, the affected PAN-OS host would utilize the command line utilities curl and Wget, seen via use of user agents curl/7.61.1 and Wget/1.19.5 (linux-gnu), respectively.

In some cases, the use of these command line utilities by the infected devices was considered new behavior. Given the nature of the user agents, interaction with the host shell suggests remote command execution to achieve the outgoing payload requests.

While additional binaries and scripts were retrieved in later stages of the post-exploitation activity in some cases, this set of behaviors and payloads likely represent initial persistence and execution mechanisms that will enable additional functionality later in the kill chain. During the investigation, Darktrace analysts noted the prevalence of shell script payload requests. Devices analyzed would frequently make HTTP requests over the usual destination port 80 using the command line URL utility (curl), as seen in the user-agent field.

The observed URIs often featured requests for text files, such as “1.txt”, or shell scripts such as “y.sh”. Although packet capture (PCAP) samples were unavailable for review, external researchers have noted that the IP address hosting such “1.txt” files (46.8.226[.]75) serves malicious PHP payloads. When examining the contents of the “y.sh” shell script, Darktrace analysts noticed the execution of bash commands to upload a PHP-written web shell on the affected server.

Figure 2: PCAP showing the client request and server response associated with the download of the y.sh script from 45.76.141[.]166. The body content of the HTTP response highlights a shebang command to run subsequent code as bash script. The content is base64 encoded and details PHP script for what appears to be a webshell that will likely be written to the firewall device.

While not all investigated cases saw initial shell script retrieval, affected systems would commonly make an external HTTP connection, almost always via Wget, for the Executable and Linkable Format (ELF) file “/palofd” from the rare external IP 38.180.147[.]18.

Such requests were frequently made without prior hostname lookups, suggesting that the process or script initiating the requests already contained the external IP address. Analysts noticed a consistent SHA1 hash present for all identified instances of “/palofd” downloads (90f6890fa94b25fbf4d5c49f1ea354a023e06510). Multiple open-source intelligence (OSINT) vendors have associated this hash sample with Spectre RAT, a remote access trojan with capabilities including remote command execution, payload delivery, process manipulation, file transfers, and data theft [3][4].

Figure 3: Advanced Search log metrics highlighting details of the “/palofd” file download over HTTP.

Several targeted customer devices were observed initiating TLS/SSL connections to rare external IPs with self-signed TLS certificates following exploitation. Model data from across the Darktrace fleet indicated some overlap in JA3 fingerprints utilized by affected PAN-OS devices engaging in the suspicious TLS activity. Although JA3 hashes alone cannot be used for process attribution, this evidence suggests some correlation of source process across instances of PAN-OS exploitation.

These TLS/SSL sessions were typically established without the specification of a Server Name Indication (SNI) within the TLS extensions. The SNI extension prevents servers from supplying an incorrect certificate to the requesting client when multiple sites are hosted on the same IP. SSL connectivity without SNI specification suggests a potentially malicious running process as most software establishing TLS sessions typically supply this information during the handshake. Although the encrypted nature of the connection prevented further analysis of the payload packets, external sources note that JavaScript content is transmitted during these sessions, serving as initial payloads for the Sliver C2 platform using Wget [5].

C2 Communication and Additional Payloads

Following validation and preliminary post-compromise actions, examined hosts would commonly initiate varying forms of C2 connectivity. During this time, devices were frequently detected making further payload downloads, likely in response to directives set within C2 communications.

Palo Alto firewalls likely exploited via the newly disclosed CVEs would commonly utilize the Sliver C2 platform for external communication. Sliver’s functionality allows for different styles and formatting for communication. An open-source alternative to Cobalt Strike, this framework has been increasingly popular among threat actors, enabling the generation of dynamic payloads (“slivers”) for multiple platforms, including Windows, MacOS, Linux.

These payloads allow operators to establish persistence, spawn new shells, and exfiltrate data. URI patterns and PCAPs analysis yielded evidence of both English word type encoding within Sliverand Gzip formatting.

For example, multiple devices contacted the Sliver-linked IP address 77.221.158[.]154 using HTTP to retrieve Gzip files. The URIs present for these requests follow known Sliver Gzip formatted communication patterns [6]. Investigations yielded evidence of both English word encoding within Sliver, identified through PCAP analysis, and Gzip formatting.

Figure 4: Sample of URIs observed in Advanced Searchhighlighting HTTP requests to 77.221.158[.]154 for Gzip content suggest of Sliver communication.

Figure 5: PCAP showing English word encoding for Sliver communication observed during post-exploitation C2 activity.

External connectivity during this phase also featured TCP connection attempts over uncommon ports for common application protocols. For both Sliver and non-Sliver related IP addresses, devices utilized destination ports such as 8089, 3939, 8880, 8084, and 9999 for the HTTP protocol. The use of uncommon destination ports may represent attempts to avoid detection of connectivity to rare external endpoints. Moreover, some external beaconing within included URIs referencing the likely IP of the affected device. Such behavior can suggest the registration of compromised devices with command servers.

Targeted devices also proceeded to download additional payloads from rare external endpoints as beaconing/C2 activity was ongoing. For example, the newly registered domain repositorylinux[.]org (IP: 103.217.145[.]112) received numerous HTTP GET requests from investigated devices throughout the investigation period for script files including “linux.sh” and “cron.sh”. Young domains, especially those that present as similar to known code repositories, tend to host harmful content. Packet captures of the cron.sh file reveal commands within the HTTP body content involving crontab operations, likely to schedule future downloads. Some hosts that engaged in connectivity to the fake repository domain were later seen conducting crypto-mining connections, potentially highlighting the download of miner applications from the domain.

Additional payloads observed during this time largely featured variations of shell scripts, PHP content, and/or executables. Typically, shell scripts direct the device to retrieve additional content from external servers or repositories or contain potential configuration details for subsequent binaries to run on the device. For example, the “service.sh” retrieves a tar-compressed archive, a configuration JSON file as well as a file with the name “solr” from GitHub, potentially associated with the Apache Solr tool used for enterprise search. These could be used for further enumeration of the host and/or the network environment. PHP scripts observed may involve similar web shell functionality and were retrieved from both rare external IPs identified as well by external researchers [7]. Darktrace also detected the download of octet-stream data occurring mid-compromise from an Amazon Web Services (AWS) S3 bucket. Although no outside research confirmed the functionality, additional executable downloads for files such as “/initd”(IP: 178.215.224[.]246) and “/x6” (IP: 223.165.4[.]175) may relate to tool ingress, further Trojan/backdoor functionality, or cryptocurrency mining.

Figure 7: PCAP specifying the HTTP response headers and body content for the service.sh file request. The body content shown includes variable declarations for URLs that will eventually be called by the device shell via bash command.

Reconnaissance and Cryptomining

Darktrace analysts also noticed additional elements of kill chain operations from affected devices after periods of initial exploit activity. Several devices initiated TCP connections to endpoints affiliated with cryptomining pools such as us[.]zephyr[.]herominers[.]com and xmrig[.]com. Connectivity to these domains indicates likely successful installation of mining software during earlier stages of post-compromise activity. In a small number of instances, Darktrace observed reconnaissance and lateral movement within the time range of PAN-OS exploitation. Firewalls conducted large numbers of internal connectivity attempts across several critical ports related to privileged protocols, including SMB and SSH. Darktrace detected anonymous NTLM login attempts and new usage of potential PAN-related credentials. These behaviors likely constitute attempts at lateral movement to adjacent devices to further extend network compromise impact.

Figure 8: Model alert connection logs detailing the uncommon failed NTLM logins using an anonymous user account following PAN-OS exploitation.

Conclusion

Darktrace Threat Research and SOC analysts increasingly detect spikes in malicious activity on internet-facing devices in the days following the publication of new vulnerabilities. The latest iteration of this trend highlighted how threat actors quickly exploited Palo Alto firewall using authentication bypass and remote command execution vulnerabilities to enable device compromise. A review of the post-exploitation activity during these events reveals consistent patterns of perimeter device exploitation, but also some distinct variations.

Prior campaigns targeting perimeter devices featured activity largely confined to the exfiltration of configuration data and some initial payload retrieval. Within the current campaign, analysts identified a broader scope post-compromise activity consisting not only of payloads downloads but also extensive C2 activity, reconnaissance, and coin mining operations. While the use of command line tools like curl featured prominently in prior investigations, devices were seen retrieving a generally wider array of payloads during the latest round of activity. The use of the Sliver C2 platform further differentiates the latest round of PAN-OS compromises, with evidence of Sliver activity in about half of the investigated cases.

Several of the endpoints contacted by the infected firewall devices did not have any OSINT associated with them at the time of the attack. However, these indicators were noted as unusual for the devices according to Darktrace based on normal network traffic patterns. This reality further highlights the need for anomaly-based detection that does not rely necessarily on known indicators of compromise (IoCs) associated with CVE exploitation for detection. Darktrace’s experience in 2024 of multiple rounds of perimeter device exploitation may foreshadow future increases in these types of comprise operations.

Credit to Adam Potter (Senior Cyber Analyst), Alexandra Sentenac (Senior Cyber Analyst), Emma Foulger (Principal Cyber Analyst) and the Darktrace Threat Research team.

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References

[1]: https://labs.watchtowr.com/pots-and-pans-aka-an-sslvpn-palo-alto-pan-os-cve-2024-0012-and-cve-2024-9474/

[2]: https://security.paloaltonetworks.com/CVE-2024-9474

[3]: https://threatfox.abuse[.]ch/ioc/1346254/

[4]:https://www.virustotal.com/gui/file/4911396d80baff80826b96d6ea7e54758847c93fdbcd3b86b00946cfd7d1145b/detection

[5]: https://arcticwolf.com/resources/blog/arctic-wolf-observes-threat-campaign-targeting-palo-alto-networks-firewall-devices/

[6] https://www.immersivelabs.com/blog/detecting-and-decrypting-sliver-c2-a-threat-hunters-guide

[7] https://arcticwolf.com/resources/blog/arctic-wolf-observes-threat-campaign-targeting-palo-alto-networks-firewall-devices/

Appendices

Darktrace Model Alerts

Anomalous Connection / Anomalous SSL without SNI to New External

Anomalous Connection / Application Protocol on Uncommon Port

Anomalous Connection / Multiple Failed Connections to Rare Endpoint

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

Anomalous Connection / New User Agent to IP Without Hostname

Anomalous Connection / Posting HTTP to IP Without Hostname

Anomalous Connection / Rare External SSL Self-Signed

Anomalous File / EXE from Rare External Location

Anomalous File / Incoming ELF File

Anomalous File / Mismatched MIME Type From Rare Endpoint

Anomalous File / Multiple EXE from Rare External Locations

Anomalous File / New User Agent Followed By Numeric File Download

Anomalous File / Script from Rare External Location

Anomalous File / Zip or Gzip from Rare External Location

Anomalous Server Activity / Rare External from Server

Compromise / Agent Beacon (Long Period)

Compromise / Agent Beacon (Medium Period)

Compromise / Agent Beacon to New Endpoint

Compromise / Beacon for 4 Days

Compromise / Beacon to Young Endpoint

Compromise / Beaconing Activity To External Rare

Compromise / High Priority Tunnelling to Bin Services

Compromise / High Volume of Connections with Beacon Score

Compromise / HTTP Beaconing to New IP

Compromise / HTTP Beaconing to Rare Destination

Compromise / Large Number of Suspicious Failed Connections

Compromise / Large Number of Suspicious Successful Connections

Compromise / Slow Beaconing Activity To External Rare

Compromise / SSL Beaconing to Rare Destination

Compromise / Suspicious Beaconing Behavior

Compromise / Suspicious File and C2

Compromise / Suspicious HTTP and Anomalous Activity

Compromise / Suspicious TLS Beaconing To Rare External

Compromise / Sustained SSL or HTTP Increase

Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

Device / Initial Attack Chain Activity

Device / New User Agent

MITRE ATT&CK Mapping

Tactic – Technique

INITIAL ACCESS – Exploit Public-Facing Application

RESOURCE DEVELOPMENT – Malware

EXECUTION – Scheduled Task/Job (Cron)

EXECUTION – Unix Shell

PERSISTENCE – Web Shell

DEFENSE EVASION – Masquerading (Masquerade File Type)

DEFENSE EVASION - Deobfuscate/Decode Files or Information

CREDENTIAL ACCESS – Brute Force

DISCOVERY – Remote System Discovery

COMMAND AND CONTROL – Ingress Tool Transfer

COMMAND AND CONTROL – Application Layer Protocol (Web Protocols)

COMMAND AND CONTROL – Encrypted Channel

COMMAND AND CONTROL – Non-Standard Port

COMMAND AND CONTROL – Data Obfuscation

IMPACT – Resource Hijacking (Compute)

List of IoCs

IoC – Type – Description

sys.traceroute[.]vip – Hostname - C2 Endpoint
77.221.158[.]154 – IP - C2 Endpoint
185.174.137[.]26 – IP - C2 Endpoint
93.113.25[.]46 – IP - C2 Endpoint
104.131.69[.]106 – IP - C2 Endpoint
95.164.5[.]41 – IP - C2 Endpoint
bristol-beacon-assets.s3.amazonaws[.]com – Hostname - Payload Server
img.dxyjg[.]com – Hostname - Payload Server
38.180.147[.]18 – IP - Payload Server
143.198.1[.]178 – IP - Payload Server
185.208.156[.]46 – IP - Payload Server
185.196.9[.]154 – IP - Payload Server
46.8.226[.]75 – IP - Payload Server
223.165.4[.]175 – IP - Payload Server
188.166.244[.]81 – IP - Payload Server
bristol-beaconassets.s3[.]amazonaws[.]com/Y5bHaYxvd84sw – URL - Payload
img[.]dxyjg[.]com/KjQfcPNzMrgV – URL - Payload
38.180.147[.]18/palofd – URL - Payload
90f6890fa94b25fbf4d5c49f1ea354a023e06510 – SHA1 - Associated to file /palofd
143.198.1[.]178/7Z0THCJ – URL - Payload
8d82ccdb21425cf27b5feb47d9b7fb0c0454a9ca – SHA1 - Associated to file /7Z0THCJ
fefd0f93dcd6215d9b8c80606327f5d3a8c89712 – SHA1 - Associated to file /7Z0THCJ
e5464f14556f6e1dd88b11d6b212999dd9aee1b1 – SHA1 - Associated to file /7Z0THCJ
143.198.1[.]178/o4VWvQ5pxICPm – URL - Payload
185.208.156[.]46/lUuL095knXd62DdR6umDig – URL - Payload
185.196.9[.]154/ykKDzZ5o0AUSfkrzU5BY4w – URL - Payload
46.8.226[.]75/1.txt – URL - Payload
223.165.4[.]175/x6 – URL - Payload
45.76.141[.]166/y.sh – URL - Payload
repositorylinux[.]org/linux.sh – URL - Payload
repositorylinux[.]org/cron.sh – URL - Payload

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Written by

Adam Potter

Senior Cyber Analyst

Inside the SOC

Written by

Adam Potter

Senior Cyber Analyst

Product Marketing Manager, OT Security & Compliance

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Blog

Email

September 30, 2025

Out of Character: Detecting Vendor Compromise and Trusted Relationship Abuse with Darktrace

What is Vendor Email Compromise?

Vendor Email Compromise (VEC) refers to an attack where actors breach a third-party provider to exploit their access, relationships, or systems for malicious purposes. The initially compromised entities are often the target’s existing partners, though this can extend to any organization or individual the target is likely to trust.

It sits at the intersection of supply chain attacks and business email compromise (BEC), blending technical exploitation with trust-based deception. Attackers often infiltrate existing conversations, leveraging AI to mimic tone and avoid common spelling and grammar pitfalls. Malicious content is typically hosted on otherwise reputable file sharing platforms, meaning any shared links initially seem harmless.

While techniques to achieve initial access may have evolved, the goals remain familiar. Threat actors harvest credentials, launch subsequent phishing campaigns, attempt to redirect invoice payments for financial gain, and exfiltrate sensitive corporate data.

Why traditional defenses fall short

These subtle and sophisticated email attacks pose unique challenges for defenders. Few busy people would treat an ongoing conversation with a trusted contact with the same level of suspicion as an email from the CEO requesting ‘URGENT ASSISTANCE!’ Unfortunately, many traditional secure email gateways (SEGs) struggle with this too. Detecting an out-of-character email, when it does not obviously appear out of character, is a complex challenge. It’s hardly surprising, then, that 83% of organizations have experienced a security incident involving third-party vendors [1].

This article explores how Darktrace detected four different vendor compromise campaigns for a single customer, within a two-week period in 2025. Darktrace / EMAIL successfully identified the subtle indicators that these seemingly benign emails from trusted senders were, in fact, malicious. Due to the configuration of Darktrace / EMAIL in this customer’s environment, it was unable to take action against the malicious emails. However, if fully enabled to take Autonomous Response, it would have held all offending emails identified.

How does Darktrace detect vendor compromise?

The answer lies at the core of how Darktrace operates: anomaly detection. Rather than relying on known malicious rules or signatures, Darktrace learns what ‘normal’ looks like for an environment, then looks for anomalies across a wide range of metrics. Despite the resourcefulness of the threat actors involved in this case, Darktrace identified many anomalies across these campaigns.

Different campaigns, common traits

A wide variety of approaches was observed. Individuals, shared mailboxes and external contractors were all targeted. Two emails originated from compromised current vendors, while two came from unknown compromised organizations - one in an associated industry. The sender organizations were either familiar or, at the very least, professional in appearance, with no unusual alphanumeric strings or suspicious top-level domains (TLDs). Subject line, such as “New Approved Statement From [REDACTED]” and “[REDACTED] - Proposal Document” appeared unremarkable and were not designed to provoke heightened emotions like typical social engineering or BEC attempts.

All emails had been given a Microsoft Spam Confidence Level of 1, indicating Microsoft did not consider them to be spam or malicious [2]. They also passed authentication checks (including SPF, and in some cases DKIM and DMARC), meaning they appeared to originate from an authentic source for the sender domain and had not been tampered with in transit.

All observed phishing emails contained a link hosted on a legitimate and commonly used file-sharing site. These sites were often convincingly themed, frequently featuring the name of a trusted vendor either on the page or within the URL, to appear authentic and avoid raising suspicion. However, these links served only as the initial step in a more complex, multi-stage phishing process.

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Figure 1: A legitimate file sharing site used in phishing emails to host a secondary malicious link.

Figure 2: Another example of a legitimate file sharing endpoint sent in a phishing email and used to host a malicious link.

If followed, the recipient would be redirected, sometimes via CAPTCHA, to fake Microsoft login pages designed to capturing credentials, namely http://pub-ac94c05b39aa4f75ad1df88d384932b8.r2[.]dev/offline[.]html and https://s3.us-east-1.amazonaws[.]com/s3cure0line-0365cql0.19db86c3-b2b9-44cc-b339-36da233a3be2ml0qin/s3cccql0.19db86c3-b2b9-44cc-b339-36da233a3be2%26l0qn[.]html#.

The latter made use of homoglyphs to deceive the user, with a link referencing ‘s3cure0line’, rather than ‘secureonline’. Post-incident investigation using open-source intelligence (OSINT) confirmed that the domains were linked to malicious phishing endpoints [3] [4].

Figure 3: Fake Microsoft login page designed to harvest credentials.

Figure 4: Phishing kit with likely AI-generated image, designed to harvest user credentials. The URL uses ‘s3cure0line’ instead of ‘secureonline’, a subtle misspelling intended to deceive users.

Darktrace Anomaly Detection

Some senders were unknown to the network, with no previous outbound or inbound emails. Some had sent the email to multiple undisclosed recipients using BCC, an unusual behavior for a new sender.

Where the sender organization was an existing vendor, Darktrace recognized out-of-character behavior, in this case it was the first time a link to a particular file-sharing site had been shared. Often the links themselves exhibited anomalies, either being unusually prominent or hidden altogether - masked by text or a clickable image.

Crucially, Darktrace / EMAIL is able to identify malicious links at the time of processing the emails, without needing to visit the URLs or analyze the destination endpoints, meaning even the most convincing phishing pages cannot evade detection – meaning even the most convincing phishing emails cannot evade detection. This sets it apart from many competitors who rely on crawling the endpoints present in emails. This, among other things, risks disruption to user experience, such as unsubscribing them from emails, for instance.

Darktrace was also able to determine that the malicious emails originated from a compromised mailbox, using a series of behavioral and contextual metrics to make the identification. Upon analysis of the emails, Darktrace autonomously assigned several contextual tags to highlight their concerning elements, indicating that the messages contained phishing links, were likely sent from a compromised account, and originated from a known correspondent exhibiting out-of-character behavior.

A summary of the anomalous email, confirming that it contained a highly suspicious link. — Figure 5: Tags assigned to offending emails by Darktrace / EMAIL.

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Figure 6: A summary of the anomalous email, confirming that it contained a highly suspicious link.

Out-of-character behavior caught in real-time

In another customer environment around the same time Darktrace / EMAIL detected multiple emails with carefully crafted, contextually appropriate subject lines sent from an established correspondent being sent to 30 different recipients. In many cases, the attacker hijacked existing threads and inserted their malicious emails into an ongoing conversation in an effort to blend in and avoid detection. As in the previous, the attacker leveraged a well-known service, this time ClickFunnels, to host a document containing another malicious link. Once again, they were assigned a Microsoft Spam Confidence Level of 1, indicating that they were not considered malicious.

Figure 7: The legitimate ClickFunnels page used to host a malicious phishing link.

This time, however, the customer had Darktrace / EMAIL fully enabled to take Autonomous Response against suspicious emails. As a result, when Darktrace detected the out-of-character behavior, specifically, the sharing of a link to a previously unused file-sharing domain, and identified the likely malicious intent of the message, it held the email, preventing it from reaching recipients’ inboxes and effectively shutting down the attack.

Figure 8: Darktrace / EMAIL’s detection of malicious emails inserted into an existing thread.*

*To preserve anonymity, all real customer names, email addresses, and other identifying details have been redacted and replaced with fictitious placeholders.

Legitimate messages in the conversation were assigned an Anomaly Score of 0, while the newly inserted malicious emails identified and were flagged with the maximum score of 100.

Key takeaways for defenders

Phishing remains big business, and as the landscape evolves, today’s campaigns often look very different from earlier versions. As with network-based attacks, threat actors are increasingly leveraging legitimate tools and exploiting trusted relationships to carry out their malicious goals, often staying under the radar of security teams and traditional email defenses.

As attackers continue to exploit trusted relationships between organizations and their third-party associates, security teams must remain vigilant to unexpected or suspicious email activity. Protecting the digital estate requires an email solution capable of identifying malicious characteristics, even when they originate from otherwise trusted senders.

Credit to Jennifer Beckett (Cyber Analyst), Patrick Anjos (Senior Cyber Analyst), Ryan Traill (Analyst Content Lead), Kiri Addison (Director of Product)

Appendices

IoC - Type - Description + Confidence

- http://pub-ac94c05b39aa4f75ad1df88d384932b8.r2[.]dev/offline[.]html#p – fake Microsoft login page

- https://s3.us-east-1.amazonaws[.]com/s3cure0line-0365cql0.19db86c3-b2b9-44cc-b339-36da233a3be2ml0qin/s3cccql0.19db86c3-b2b9-44cc-b339-36da233a3be2%26l0qn[.]html# - link to domain used in homoglyph attack

MITRE ATT&CK Mapping

Tactic – Technique – Sub-Technique

Initial Access - Phishing – (T1566)

References

1. https://gitnux.org/third-party-risk-statistics/

2. https://learn.microsoft.com/en-us/defender-office-365/anti-spam-spam-confidence-level-scl-about

3. https://www.virustotal.com/gui/url/5df9aae8f78445a590f674d7b64c69630c1473c294ce5337d73732c03ab7fca2/detection

4. https://www.virustotal.com/gui/url/695d0d173d1bd4755eb79952704e3f2f2b87d1a08e2ec660b98a4cc65f6b2577/details

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About the author

Jennifer Beckett

Cyber Analyst

Blog

OT

October 1, 2025

Announcing Unified OT Security with Dedicated OT Workflows, Segmentation-Aware Risk Insights, and Next-Gen Endpoint Visibility for Industrial Teams

The challenge of convergence without clarity

Convergence is no longer a roadmap idea, it is the daily reality for industrial security teams. As Information Technology (IT) and Operational Technology (OT) environments merge, the line between a cyber incident and an operational disruption grows increasingly hard to define. A misconfigured firewall rule can lead to downtime. A protocol misuse might look like a glitch. And when a pump stalls but nothing appears in the Security Operations Center (SOC) dashboard, teams are left asking: is this operational or is this a threat?

The lack of shared context slows down response, creates friction between SOC analysts and plant engineers, and leaves organizations vulnerable at exactly the points where IT and OT converge. Defenders need more than alerts, they need clarity that both sides can trust.

The breakthrough with Darktrace / OT

This latest Darktrace / OT release was built to deliver exactly that. It introduces shared context between Security, IT, and OT operations, helping reduce friction and close the security gaps at the intersection of these domains.

With a dedicated dashboard built for operations teams, extended visibility into endpoints for new forms of detection and CVE collection, expanded protocol coverage, and smarter risk modeling aligned to segmentation policies, teams can now operate from a shared source of truth. These enhancements are not just incremental upgrades, they are foundational improvements designed to bring clarity, efficiency, and trust to converged environments.

A dashboard built for OT engineers

The new Operational Overview provides OT engineers with a workspace designed for them, not for SOC analysts. It brings asset management, risk insights and operational alerts into one place. Engineers can now see activity like firmware changes, controller reprograms or the sudden appearance of a new workstation on the network, providing a tailored view for critical insights and productivity gains without navigating IT-centric workflows. Each device view is now enriched with cross-linked intelligence, make, model, firmware version and the roles inferred by Self-Learning AI, making it easier to understand how each asset behaves, what function it serves, and where it fits within the broader industrial process. By suppressing IT-centric noise, the dashboard highlights only the anomalies that matter to operations, accelerating triage, enabling smoother IT/OT collaboration, and reducing time to root cause without jumping between tools.

This is usability with purpose, a view that matches OT workflows and accelerates response.

Figure 1: The Operational Overview provides an intuitive dashboard summarizing all OT Assets, Alerts, and Risk.

Full-spectrum coverage across endpoints, sensors and protocols

The release also extends visibility into areas that have traditionally been blind spots. Engineering workstations, Human-Machine Interfaces (HMIs), contractor laptops and field devices are often the entry points for attackers, yet the hardest to monitor.

Darktrace introduces Network Endpoint eXtended Telemetry (NEXT) for OT, a lightweight collector built for segmented and resource-constrained environments. NEXT for OT uses Endpoint sensors to capture localized network, and now process-level telemetry, placing it in context alongside other network and asset data to:

Identify vulnerabilities and OS data, which is leveraged by OT Risk Management for risk scoring and patching prioritization, removing the need for third-party CVE collection.

Surface novel threats using Self-Learning AI that standalone Endpoint Detection and Response (EDR) would miss.

Extend Cyber AI Analyst investigations through to the endpoint root cause.

NEXT is part of our existing cSensor endpoint agent, can be deployed standalone or alongside existing EDR tools, and allows capabilities to be enabled or disabled depending on factors such as security or OT team objectives and resource utilization.

Figure 2: Darktrace / OT delivers CVE patch priority insights by combining threat intelligence with extended network and endpoint telemetry

The family of Darktrace Endpoint sensors also receive a boost in deployment flexibility, with on-prem server-based setups, as well as a Windows driver tailored for zero-trust and high-security environments.

Protocol coverage has been extended where it matters most. Darktrace now performs protocol analysis of a wider range of GE and Mitsubishi protocols, giving operators real-time visibility into commands and state changes on Programmable Logic Controllers (PLCs), robots and controllers. Backed by Self-Learning AI, this inspection does more than parse traffic, it understands what normal looks like and flags deviations that signal risk.

Integrated risk and governance workflows

Security data is only valuable when it drives action. Darktrace / OT delivers risk insights that go beyond patching, helping teams take meaningful steps even when remediation isn't possible. Risk is assessed not just by CVE presence, but by how network segmentation, firewall policies, and attack path logic neutralize or contain real-world exposure. This approach empowers defenders to deprioritize low-impact vulnerabilities and focus effort where risk truly exists. Building on the foundation introduced in release 6.3, such as KEV enrichment, endpoint OS data, and exploit mapping, this release introduces new integrations that bring Darktrace / OT intelligence directly into governance workflows.

Fortinet FortiGate firewall ingestion feeds segmentation rules into attack path modeling, revealing real exposure when policies fail and closing feeds into patching prioritization based on a policy to CVE exposure assessment.

ServiceNow Configuration Management Database (CMDB) sync ensures asset intelligence stays current across governance platforms, eliminating manual inventory work.

Risk modeling has also been made more operationally relevant. Scores are now contextualized by exploitability, asset criticality, firewall policy, and segmentation posture. Patch recommendations are modeled in terms of safety, uptime and compliance rather than just Common Vulnerability Scoring System (CVSS) numbers. And importantly, risk is prioritized across the Purdue Model, giving defenders visibility into whether vulnerabilities remain isolated to IT or extend into OT-critical layers.

Figure 3: Attack Path Modeling based on NetFlow and network topology reveals high risk points of IT/OT convergence.

The real-world impact for defenders

In today’s environments, attackers move fluidly between IT and OT. Without unified visibility and shared context, incidents cascade faster than teams can respond.

With this release, Darktrace / OT changes that reality. The Operational Overview gives Engineers a dashboard they can use daily, tailored to their workflows. SOC analysts can seamlessly investigate telemetry across endpoints, sensors and protocols that were once blind spots. Operators gain transparency into PLCs and controllers. Governance teams benefit from automated integrations with platforms like Fortinet and ServiceNow. And all stakeholders work from risk models that reflect what truly matters: safety, uptime and compliance.

This release is not about creating more alerts. It is about providing more clarity. By unifying context across IT and OT, Darktrace / OT enables defenders to see more, understand more and act faster.

Because in environments where safety and uptime are non-negotiable, clarity is what matters most.

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About the author

Pallavi Singh

Product Marketing Manager, OT Security & Compliance

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Check out this article by Darktrace: Darktrace’s view on Operation Lunar Peek: Exploitation of Palo Alto firewall devices (CVE 2024-0012 and 2024-9474)

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List of IoCs

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Join us for our live event where we will discuss these product innovations in greater detail