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.

Get the latest insights on emerging cyber threats

Attackers are adapting, are you ready? This report explores the latest trends shaping the cybersecurity landscape and what defenders need to know in 2025.

Identity-based attacks: How attackers are bypassing traditional defenses
Zero-day exploitation: The rise of previously unknown vulnerabilities
AI-driven threats: How adversaries are leveraging AI to outmaneuver security controls

Stay ahead of evolving threats with expert analysis from Darktrace. Download the report here.

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

‍

Written by

Adam Potter

Senior Cyber Analyst

Inside the SOC

Written by

Adam Potter

Senior Cyber Analyst

•

October 21, 2026

Tara Gould

Malware Research Lead

•

October 22, 2026

Nathaniel Jones

SVP, Global Threat Intelligence

Watch the NIS2 Webinar

Blog

AI

October 23, 2026

PHP Vulnerabilities, ARTEX and the Growing Role of AI in Cyber Attacks

The disclosure of CVE-2026-109618 and CVE-2026-109619 placed immediate pressure on organizations running PHP. Both vulnerabilities can allow unauthenticated remote code execution, including in products and appliances where PHP is embedded, and updates depend on third-party vendors [1].

Early guidance focused on patching internet-facing systems and monitoring for behavior associated with successful exploitation, including unexpected command execution, Webroot changes and outbound connections from PHP servers.

Darktrace observed widespread scanning across monitored environments involving hundreds of distinct source IP addresses that public reporting has associated with activity targeting the PHP vulnerabilities. The volume of scanning was significantly greater than the evidence available for successful exploitation. For analysts, that distinction is important. Scanning demonstrates interest in exposed infrastructure; establishing compromise requires evidence of subsequent behavior on the targeted system, including command execution, file modification or unexpected outbound communication.

While Darktrace has not observed direct evidence of CVE-2026-109618 or CVE-2026-109619 exploitation, on October 21^st we observed a six-month high in detections consistent with zero-day exploitation activity, representing a 64% increase compared to historic data. This increase has not been confirmed as related to the PHP vulnerabilities. Darktrace’s behavioral approach is designed to detect anomalous activity without relying solely on rules written for a specific exploit. Comparable increases were observed around the Log4j disclosure and other globally significant vulnerability disclosures.

AI-assisted vulnerability research

The PHP disclosure arrives as AI systems have become more capable at vulnerability research [2]. OpenAI launched Daybreak in June 2026, combining GPT-5.5-Cyber, Codex Security and partnerships with security researchers and software maintainers. OpenAI says its models have been applied to discovering and generating patches for vulnerabilities in browsers, network infrastructure, FreeBSD and the Linux kernel. Darktrace joined the OpenAI Daybreak Cyber Partner Program in June to explore how OpenAI's cyber capabilities could be integrated within Darktrace products and services [3][9].

OpenAI reported in August that Codex Security Cloud had analyzed more than 30 million commits across more than 30,000 codebases. According to OpenAI, Cloudflare uses models accessed through Daybreak to investigate customer-authorized code and combines findings with live traffic and security signals to assess whether affected routes are active or receiving suspicious traffic, with proposed mitigations and patches remaining subject to customer review [4][5].

Faster discovery still leaves defenders with the work of locating affected software, testing fixes and completing remediation. The PHP case shows that gap clearly, particularly when vulnerable runtimes are embedded inside other products.

Enterprise agents as an attack surface

Darktrace Signal Labs has also examined how a trusted enterprise agent could be abused after an attacker has already obtained access to an environment. In a controlled simulation, researchers demonstrated that, in that post-compromise scenario, the Claude platform’s memory stores feature could be abused to establish a live C2 channel between an external operator and internal Claude Code agents. The external operator was able to dynamically assign network discovery, credential access, and data exfiltration tasks to the agents via this C2 channel. Detection of the agents’ activities relied on the correlation of process creation and network traffic activity from agent harness processes, alongside behavioral analysis to identify deviations from expected behavior. Darktrace has not claimed it observed this memory-store command-and-control technique in operational attacks [6].

AI-assisted attacks in Japan

Evidence from Japan indicates AI being used for vulnerability scanning and attacks outside controlled research. On 21 October, JPCERT/CC published findings from an investigation into recent unauthorized access incidents affecting organizations in Japan. JPCERT/CC states that it confirmed attackers had used AI to scan for known vulnerabilities and conduct attacks through APIs. According to JPCERT/CC, its examination of attack infrastructure found evidence of Android application analysis, API discovery and testing for weaknesses including server-side request forgery, and the infrastructure also targeted services intended for users outside Japan [7].

JPCERT/CC does not identify ARTEX by name in that publication. The named ARTEX attribution comes from separate investigations, including Microsoft's analysis of Storm-0940.

AI in offensive operations

Microsoft describes ARTEX as an open-source, multi-agent penetration-testing system capable of automating activity with limited human interaction. Microsoft reported that Storm-0940, which it assesses to be a China state-aligned actor active since 2021, used ARTEX against hundreds of organizations, and Microsoft attributed the ConnectWise supply-chain compromise [8].

Microsoft observed ARTEX accelerating scanning, reconnaissance, password spraying and OAuth application abuse. Several ARTEX-driven operations reached privileged cloud access less than three hours after initial targeting. Following the ConnectWise compromise, Storm-0940 attempted to authenticate to more than 2,250 tenants at rates of up to 2,900 attempts per minute [8].

Darktrace Threat Research found activity in its own telemetry involving infrastructure later associated with the campaign. On 13 October, Darktrace recorded failed authentication activity involving 144.172.64[.]128, one of the addresses Microsoft later identified as performing sign-ins and Microsoft Graph activity in ConnectWise customer environments. Darktrace analysis identified 65 failed authentication attempts in around 20 minutes.

*Figure 1: Darktrace Advanced Search showing failed authentication events involving 144.172.64[.]128 on 13 October 2026, (customer-identifying information redacted).*

The telemetry establishes repeated failed authentication from infrastructure later associated with the campaign. It does not establish ARTEX execution or successful compromise. At the time of observation, Microsoft's later attribution was unavailable. Analysts therefore had the behavior itself: repeated failed authentication from the same source over a short period, together with any related identity, application or network activity inside the environment.

Microsoft documented a wider password-spray campaign against 327 accounts across eight organizations between 10 and 14 October. It recorded more than 151,000 failed logons, including more than 111,000 on 11 October, but no successful authentication, token issuance, Graph call or directory change from that campaign. Microsoft also reported that most Storm-0940 targeting was unsuccessful [8].

Where the actor progressed beyond authentication, Microsoft observed service-principal sign-ins followed by Graph and directory operations. Activity included reconnaissance, application credential changes and attempts to modify privileges. Microsoft recommends correlating service-principal sign-ins with Graph activity, directory changes and resource access [8].

Behavior before attribution

The PHP and ARTEX cases begin with different information. PHP defenders knew which software required urgent remediation but initially had limited information about exploitation. Process execution, file modification and outbound communication could still provide evidence of compromise.

The PHP and ARTEX observations also illustrate the difference between volume and impact. Darktrace observed broad scanning around the PHP disclosure, while the ARTEX-associated infrastructure produced concentrated authentication activity. Neither observation independently demonstrates compromise and in each case examining the behavior that follows the initial interaction is the investigative clue.

The Darktrace ARTEX-related observation began with authentication behavior. Microsoft publicly attributed the source infrastructure eight days later. That attribution added context, but it did not change what had originally been recorded in the environment.

AI is now present at several points in this cycle. Daybreak applies models to vulnerability discovery and remediation. Darktrace Signal Labs demonstrated how a trusted enterprise agent could be co-opted in a controlled environment. JPCERT/CC confirmed AI-assisted vulnerability scanning and API attacks in recent incidents. Microsoft documented ARTEX being used by Storm-0940 in active operations [3][6][7][8].

Microsoft's findings also show why scale and impact must be assessed separately. One ARTEX-associated campaign produced more than 151,000 failed logons without successful access, while other operations reached privileged cloud access in less than three hours. Security teams have to distinguish high-volume attempts from activity that progresses through authentication, privilege changes and resource access.

The evidence required to assess these cases remains familiar: authentication records, process execution, application and directory changes, file activity and network communication. AI can increase the rate at which those behaviors occur. Defenders still need to establish their sequence and impact.

Credit to Emma Foulger, Sam Lister, Dylan Evans, Moishe Tajtelbaum

References

[1] NCSC-NL, php2shell vulnerabilities (CVE-2026-109618, CVE-2026-109619), 21 October 2026. https://github.com/NCSC-NL/php2shell

[2] Cyber Security Agency of Singapore, https://www.csa.gov.sg/alerts-and-advisories/alerts/al-2026-151/

[3] OpenAI, Daybreak: Tools for securing every organization in the world, 22 June 2026. https://openai.com/index/daybreak-securing-the-world/

[4] OpenAI Developers, Scaling cyber defenders with Daybreak, 21 August 2026. https://developers.openai.com/blog/scaling-cyber-defenders-with-daybreak

[5] OpenAI, Cloudflare links vulnerability discovery to defense with OpenAI, 21 October 2026. https://openai.com/index/cloudflare-cyber/

[6] Darktrace Signal Labs, Shared Memories as a Covert C2 Channel, draft research supplied for review.

[7] JPCERT/CC, Recent AI-Assisted Cyber Attacks in Japan: Investigating Attack Infrastructure and Techniques, 21 October 2026. https://blogs.jpcert.or.jp/en/2026/10/web_api_attacks.html

[8] Microsoft Security Research and Microsoft Threat Intelligence, AI-driven, large-scale nation-state campaign using ARTEX enables supply chain compromise, 21 October 2026. https://www.microsoft.com/en-us/security/blog/2026/10/21/storm-0940-uses-artex-agentic-ai-connectwise-supply-chain-compromise/

[9] Darktrace, Advancing the Use of Frontier AI in Cybersecurity: Darktrace Joins the OpenAI Daybreak Cyber Partner Program to Explore Defensive AI Integrations, 22 June 2026. https://www.darktrace.com/blog/advancing-the-use-of-frontier-ai-in-cybersecurity-darktrace-joins-the-openai-daybreak-cyber-partner-program-to-explore-defensive-ai-integrations

About the author

Nathaniel Jones

SVP, Global Threat Intelligence

Blog

OT

October 23, 2026

Beyond the Fridge: Exposed Industrial Control Systems

Introduction

In October 2026, hundreds of supermarkets across France were reportedly affected by a cyberattack targeting their refrigeration systems. According to public reports, the attackers gained access to internet-connected controllers and modified their settings, forcing refrigeration units into high and extremely low temperatures and causing significant disruption. Total losses have been reported to reach several million euros.

The incident drew attention to the security of industrial refrigeration systems, particularly older devices with exposed management interfaces and known vulnerabilities.

The exact details of how the attackers gained access have not been confirmed, however it is speculated that the public-facing web server could be accessed with the username “admin” and password being the current date. Researchers from Claroty’s Team82 identified a vulnerability in Danfoss AK-SM 8xxA Series in 2025, “CVE-2025-41450", allowing for administrative access using a time-based “code-of-the-day" for authentication [1].

Default credentials, outdated firmware and publicly accessible administrative interfaces have been an issue for years. And yet these systems continue to appear in internet scans and require little sophistication to gain admin access. A simple search of internet-connected devices shows a range of exposed devices from Programmable Logic Controllers (PLCs) and remote gateways, to, yes, more fridges.

Darktrace malware researchers identified hundreds of IoT and OT devices publicly exposed on the internet, many of which are configured with no authentication, weak credentials, or default credentials. As shown in Figure 1, an exposed Copeland XWEB web interface, used to manage Dixell equipment, including refrigerators, can provide the ability to remotely control connected devices.

‍

Figure 1: Copeland XWEB interface used to control systems including refrigerators and air conditioning.

However, it’s not only fridges; web management interfaces for industrial controls are also publicly accessible, often protected only by weak credentials. Figure 2 shows an example of a publicly exposed WAGO interface. The WAGO management interface is a configuration and administration panel for controllers. Through it, a logged-in user can view device details and diagnostics, manage user accounts and passwords, update firmware, back up or restore the full configuration, set the clock, and manage SD card storage. While it typically doesn’t manage switch outputs or read live process values, someone with access could still disrupt operation by changing network or Modbus settings, loading bad firmware or configurations, or by resetting passwords and enabling insecure services.

‍

‍

The issue extends beyond management interfaces. During our research, we identified publicly accessible web interfaces belonging to PLCs, including Rockwell Automation Allen-Bradley devices. In each case, the risk arises from how the devices have been deployed and configured, not from a flaw in the vendors’ products.

‍

Figure 3: Web interface for Allen-Bradley CompactLogix controller.

‍

Figure 3 shows the web interface of an Allen-Bradley CompactLogix controller. Unlike the previous examples, this interface provides a view into the controller's operation, including running tasks, network connections, memory usage and diagnostic information. Rockwell Automation's CompactLogix controllers are commonly used to automate industrial processes, from manufacturing and packaging lines to water treatment and material handling systems. Depending on their configuration, these controllers can operate motors, pumps, valves and other physical equipment.

Although in this example the interface shown does not provide direct control over the PLC's logic, it exposes information about the model, firmware, network layout, and connections, which is useful reconnaissance for a bigger attack.

The concern is not necessarily that every exposed interface allows an attacker to immediately manipulate industrial processes. However, these devices are accessible from the public internet in the first place, providing information about systems that may be responsible for controlling physical equipment.

The attacks on refrigeration systems in France highlight the consequences of poorly secured industrial devices. As demonstrated throughout this research, publicly accessible management interfaces are not limited to refrigeration controllers but extend to PLCs and other systems used to manage industrial equipment.

Finding these devices requires little effort. Internet scanners make it possible to identify publicly exposed interfaces quickly, and in some cases these interfaces rely on publicly documented default credentials or have no authentication at all. As attackers increasingly use AI tools, such attacks may be identified and carried out faster and at a greater scale.

The consequences of this access depend on the device and the functionality exposed. While some interfaces provide little more than diagnostic information, others allow users to modify configurations, disrupt communications, or change settings that affect physical equipment. In industrial environments, this can result in operational downtime, damaged equipment and financial losses.

Weak passwords, default credentials and exposed administrative interfaces are not new security issues. Yet their continued presence on internet-connected industrial systems demonstrates how easily preventable weaknesses can leave physical operations vulnerable to attack.

Exposed devices often come from third-party suppliers and contractors, who frequently install refrigeration controllers, gateways and PLCs without the organization ever being aware they are connected to the internet. Asset visibility remains an important foundation, but organizations should assume that some unknown assets and services will exist. Effective security therefore also depends on continuous monitoring, anomaly detection, network segmentation and rapid response, so that risky exposure and unusual activity can be identified and addressed before it becomes disruptive.

Darktrace helps security teams gain visibility across IT and OT and respond to risks: https://www.darktrace.com/products/operational-technology.

Copeland, Dixell, WAGO, Rockwell Automation, Allen-Bradley and CompactLogix are trademarks of their respective owners. Their use here is for identification only and does not imply any affiliation with or endorsement by those owners.

References

1. https://claroty.com/team82/research/freeze-the-controller-defrost-the-food-uncovering-vulnerabilities-in-danfoss-refrigeration-controllers

‍

About the author

Tara Gould

Malware Research Lead

Your data. Our AI.

Elevate your network security with Darktrace AI

Get a demo

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)

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

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

How did exploitation occur?

Post-Exploitation Patterns of Activity

Exploit Validation

Initial Payload Retrieval

C2 Communication and Additional Payloads

Reconnaissance and Cryptomining

Conclusion

Get the latest insights on emerging cyber threats

References

Appendices

MITRE ATT&CK Mapping

List of IoCs

Beyond the Fridge: Exposed Industrial Control Systems

PHP Vulnerabilities, ARTEX and the Growing Role of AI in Cyber Attacks

Enjoying the blog?

More in this series

Why Kubernetes Security Needs A Behavioral Approach

CikaBika Bot: Inside a Discord RAT

A Chain Reaction: Blockchain-Hosted Infostealer Campaign Targets Windows and macOS

Blog

AI

October 23, 2026

PHP Vulnerabilities, ARTEX and the Growing Role of AI in Cyber Attacks

AI-assisted vulnerability research

Enterprise agents as an attack surface

AI-assisted attacks in Japan

AI in offensive operations

Behavior before attribution

References

Blog

OT

October 23, 2026

Beyond the Fridge: Exposed Industrial Control Systems

Introduction

References