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March 20, 2025

Cyberhaven Supply Chain Attack: Exploiting Browser Extensions

In late 2024, Darktrace detected unusual activity linked to Cyberhaven's Chrome browser extension. Read more about Darktrace’s investigation here.
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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
Rushanth Ramanathan
Cyber Analyst
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20
Mar 2025

The evolution of supply chain attacks

Supply chain attacks are becoming increasingly sophisticated. As network defenses improve, threat actors continuously adapt and refine their tactics, techniques, and procedures (TTPs) to achieve their goals. In recent years, this has led to a rise in the exploitation of trusted services and software, including legitimate browser extensions. Exploitation of these extensions can provide adversaries with a stealthy means to infiltrate target networks and access high-value accounts undetected.

A notable example of this trend was the compromise of the Cyberhaven Chrome extension at the end of 2024. This incident appeared to be part of a broader campaign targeting multiple Chrome browser extensions, highlighting the evolving nature of supply chain attacks [1].

What is Cyberhaven?

Cyberhaven, a US-based data security organization, experienced a security breach on December 24, 2024, when a phishing attack reportedly compromised one of their employee's credentials [2]. This allowed attackers to publish a malicious version of the Cyberhaven Chrome extension, which exfiltrated cookies and authenticated sessions from targeted websites. The malicious extension was active from December 25 to December 26 – a time when most businesses and employees were out of office and enjoying the festive period, a fact not lost on threat actors. The attackers, likely a well-organized and financially motivated group, compromised more than 30 additional Chrome extensions, affecting more than 2.6 million users [3]. They used sophisticated phishing techniques to authorize malicious OAuth applications, bypassing traditional security measures and exploiting vulnerabilities in OAuth authorizations. The primary motive appeared to be financial gain, targeting high-value platforms like social media advertising and AI services [4].

In late December 2024, multiple Darktrace customers were compromised via the Cyberhaven Chrome extension; this blog will primarily focus on Darktrace / NETWORK detections from one affected customer.

Darktrace’s coverage of Cyberhaven compromises

On December 26, 2024, Darktrace identified a series of suspicious activities across multiple customer environments, uncovering a structured attack sequence that progressed from initial intrusion to privilege escalation and data exfiltration. The attack was distributed through a malicious update to the Cyberhaven Chrome extension [2]. The malicious update established a foothold in customer environments almost immediately, leading to further anomalies.

As with other Chrome browser extensions, Cyberhaven Chrome extensions were updated automatically with no user interaction required. However, in this instance, the automatic update included a malicious version which was deployed to customer environments. This almost immediately introduced unauthorized activity, allowing attackers to establish a foothold in customer networks. The update allowed attackers to execute their objectives in the background, undetected by traditional security tools that rely on known indicators of compromise (IoCS) rather than identifying anomalies.

While multiple customer devices were seen connecting to cyberhaven[.]io, a legitimate Cyberhaven domain, Darktrace detected persistent beaconing behavior to cyberhavenext[.]pro, which appeared to be attempting to masquerade as another legitimate Cyberhaven domain. Darktrace recognized this activity as unusual, triggering several model alerts in Darktrace / NETWORK to highlight the persistent outbound connections to the suspicious domain.

Further analysis of external connectivity patterns indicated  an increase in anomalous HTTP requests alongside this beaconing activity. Multiple open-source intelligence (OSINT) sources also suggest that the cyberhavenext[.]pro endpoint is associated with malicious activities [5].

Darktrace / NETWORK’s detection of beaconing activity to cyberhavenext[.]pro
Figure 1: Darktrace / NETWORK’s detection of beaconing activity to cyberhavenext[.]pro

Analysis using Darktrace’s Advanced Search revealed that some of these connections were directed to the suspicious external IP address 149.28.124[.]84. Further investigation confirmed that the IP correlated with two SSL hostnames, including the malicious cyberhavenext[.]pro, further reinforcing its connection to the attack infrastructure.

Darktrace Advanced Search analysis showing the IP address 149.28.124[.]84 correlating to two SSL hostnames, one of which is cyberhavenext[.]pro.
Figure 2: Darktrace Advanced Search analysis showing the IP address 149.28.124[.]84 correlating to two SSL hostnames, one of which is cyberhavenext[.]pro.

Between December 23 and December 27, Darktrace observed sustained beaconing-like activity from affected devices on the customer’s network.

Darktrace’s detection of beaconing activities from a customer device to the endpoint 149.28.124[.]84 between December 23 and December 27.
Figure 3: Darktrace’s detection of beaconing activities from a customer device to the endpoint 149.28.124[.]84 between December 23 and December 27.

Darktrace observed 27 unique devices connecting to the malicious command-and-control (C2) infrastructure as far back as December 3. While most connections were brief, they represented an entry point for malicious activity. Over a two-day period, two devices transmitted 5.57 GiB of incoming data and 859.37 MiB of outgoing data, generating over 3 million log events across SSL, HTTP, and connection data.

Subsequent analysis identified a significant increase in unauthorized data transfers to the aforementioned 149.28.124[.]84 IP on another customer network, highlighting the potential broader impact of this compromise. The volume and frequency of these transfers suggested that attackers were leveraging automated data collection techniques, further underscoring the sophistication of the attack.

Darktrace’s detection of the likely exfiltration of 859.37 MiB to the endpoint 149.28.124[.]84.
Figure 4: Darktrace’s detection of the likely exfiltration of 859.37 MiB to the endpoint 149.28.124[.]84.

External research suggested that once active, the Cyberhaven extension would begin silently collecting session cookies and authentication tokens, specifically targeting high-value accounts such as Facebook Ads accounts [4]. Darktrace’s analysis of another affected customer noted many HTTP POST connections directed to a specific URI ("ai-cyberhaven"), while GET requests contained varying URIs prefixed with "/php/urlblock?args=AAAh....--redirect." This activity indicated an exfiltration mechanism, consistent with techniques observed in other compromised Chrome extensions. By compromising session cookies, attackers could potentially gain administrative access to connected accounts, further escalating their privileges [4].

Conclusion

This incident highlights the importance of monitoring not just endpoint security, but also cloud and browser-based security solutions, as attackers increasingly target these trusted and oft overlooked vectors.

Ultimately, by focusing on anomaly detection and behavioral analysis rather than static signatures and lists of ‘known bads’, Darktrace was able to successfully detect devices affected by the Cyberhaven Chrome browser extension compromise, by identifying activity that would likely have been considered legitimate and benign by traditional security solutions.

This compromise also serves as a reminder that supply chain attacks are not limited to traditional software vendors. Browser extensions, cloud-based applications, and SaaS services are equally vulnerable, as evidenced by Darktrace's detection of Balada Injector malware exploiting WordPress vulnerabilities to gain unauthorized network access [6]. Therefore, increased targeting of browser-based security tools, and a greater exploitation of OAuth and session hijacking techniques are to be expected. Attackers will undoubtedly refine their methods to infiltrate legitimate vendors and distribute malicious updates through trusted channels. By staying informed, vigilant, and proactive, organizations can mitigate exposure to evolving supply chain threats and safeguard their critical assets from emerging browser-based attack techniques.

Credit to Rajendra Rushanth (Cyber Analyst) Justin Torres (Senior Cyber Analyst) and Ryan Traill (Analyst Content Lead)

[related-resource]

Appendices

Darktrace Model Detections

·       Compromise / Beaconing Activity To External Rare (AP: C2 Comms)

·       Compromise / Beacon for 4 Days (AP: C2 Comms)

·       Compromise / HTTP Beaconing to Rare Destination (AP: C2 Comms)

·       Device / Suspicious Domain (AP: C2 Comms, AP: Tooling)

·       Compromise / Sustained TCP Beaconing Activity To Rare Endpoint (AP: C2 Comms)

·       Anomalous Server Activity / Rare External from Server (AP: C2 Comms)

·       Anomalous Connection / Multiple Failed Connections to Rare Endpoint (AP: C2 Comms)

·       Anomalous Server Activity / Anomalous External Activity from Critical Network Device (AP: C2 Comms)

·       Compromise / Slow Beaconing Activity To External Rare (AP: C2 Comms)

·       Compromise / Repeating Connections Over 4 Days (AP: C2 Comms)

·       Anomalous Connection / Multiple HTTP POSTs to Rare Hostname (AP: C2 Comms)

·       Anomalous Server Activity / Outgoing from Server (AP: C2 Comms)

·       Compromise / High Volume of Connections with Beacon Score (AP: C2 Comms)

·       Compromise / Large Number of Suspicious Failed Connections (AP: C2 Comms)

·       Email Nexus / Connection to Hijacked Correspondent Link

·       Compromise / Suspicious TLS Beaconing To Rare External (AP: C2 Comms)

·       Compromise / Quick and Regular Windows HTTP Beaconing (AP: C2 Comms)

List of IoCs

IoC - Type - Description + Confidence

cyberhavenext[.]pro - Hostname - Used for C2 communications and data exfiltration (cookies and session tokens)

149.28.124[.]84 - IP - Associated with malicious infrastructure

45.76.225[.]148 - IP - Associated with malicious infrastructure

136.244.115[.]219 - IP - Associated with malicious infrastructure

MITRE ATT&CK Mapping

Tactic – Technique – Sub-Technique

INITIAL ACCESS - T1176 - Browser Extensions

EXECUTION - T1204.002 - Malicious Browser Extensions

PERSISTENCE - T1176 - Browser Extensions

COMMAND AND CONTROL - T1071.001 - Web Protocols

COMMAND AND CONTROL - T1001 - Data Obfuscation

CREDENTIAL ACCESS - T1539 - Steal Web Session Cookie

DISCOVERY - T1518.001 - Security Software Discovery

LATERAL MOVEMENT - T1557.003 - Man-in-the-Browser

EXFILTRATION - T1041 - Exfiltration Over C2 Channel

EXFILTRATION - T1567.002 - Exfiltration to Cloud Storage

IMPACT - T1583.006 - Session Hijacking

References

[1] https://thehackernews.com/2024/12/16-chrome-extensions-hacked-exposing.html

[2] https://www.cyberhaven.com/blog/cyberhavens-chrome-extension-security-incident-and-what-were-doing-about-it

[3] https://www.infosecurity-magazine.com/news/chrome-browser-extensions-hijacked/

[4] https://www.theverge.com/2024/12/28/24330758/chrome-extension-cyberhaven-hijack-phishing-cyberattack-facebook-ads-authentication-theft

[5] https://www.virustotal.com/gui/domain/cyberhavenext.pro

[6] https://darktrace.com/blog/balada-injector-darktraces-investigation-into-the-malware-exploiting-wordpress-vulnerabilities

Get the latest insights on emerging cyber threats

This report explores the latest trends shaping the cybersecurity landscape and what defenders need to know in 2025

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
Rushanth Ramanathan
Cyber Analyst

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September 3, 2026

Darktrace Advances Incident Investigation and AI-Agent Security with OpenAI Daybreak Models

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Earlier this year, Darktrace joined OpenAI’s Daybreak Defense Network to explore how their cyber capabilities can be integrated within Darktrace products and services to transform how security teams move from signal to action.

At the heart of this work is Darktrace's behavioral understanding of customer environments and identification of complex security incidents, combined with OpenAI models that can add context to help explain why an incident matters and its potential impact on the business. By bringing these capabilities into defensive workflows security teams already use, the goal is to give defenders not just greater visibility, but the context and guidance they need to act with confidence.

Since joining the program, we've been working with OpenAI to explore how these capabilities can address specific security challenges for defenders.

The problem we're solving

Attackers continue to change how they operate, including by using AI to increase the speed and scale of some techniques. Security teams are already managing a large volume of alerts, and the question isn't just what's happening, but how it could affect the organization. Even when an incident is fully investigated and correlated, technical severity alone doesn't tell a security team how much it actually matters to the business. That same challenge extends to internal AI adoption. As organizations adopt more AI systems and agents, security teams need visibility into their behavior, access and activity, along with the broader business context needed to identify and investigate potential risk.

Darktrace's Adaptive AI™ builds a detailed, organization-specific picture of what's normal for each environment, and uses that picture to investigate threats and identify complex security activity across domains. OpenAI's models can build on Darktrace's correlated, technically prioritized incidents by adding context that can help defenders understand what may be at stake.

What we're building

Our work is focused on two areas: supporting security investigation and response, and helping defenders identify risky behavior across enterprise AI systems and agents.

The first aligns Darktrace's behavioral understanding with OpenAI models to support  security investigation and prioritization. Darktrace's Adaptive AI continuously learns the unique patterns of normal behavior within each customer it protects, creating a deep, organization-specific understanding of its digital estate. When unusual activity emerges, OpenAI's models can draw on that context to help analysts investigate the incident, understand its significance and assess potential business consequences — reducing the need to manually assemble context from fragmented signals.

Second, we are exploring how these capabilities can support AI-agent and runtime security through Darktrace / SECURE AI™. OpenAI’s Daybreak models can build on the detections and visibility Darktrace / SECURE AI provides, connecting signals across a customer's environment and help defenders identify potentially risky behavior involving AI systems and agents. Activity that might appear isolated can instead be connected with related signals, helping defenders investigate the broader context and determine appropriate remediation.

Darktrace brings deep cybersecurity expertise, an evolving understanding of each customer's environment, and AI-driven identification of threats across the digital estate. Through the Daybreak Defense Network, Darktrace is exploring how OpenAI models can augment those capabilities in defensive security workflows — supporting incident investigation and response and improving visibility into AI-agent and runtime risk.

These capabilities are still in development, and we're excited to continue building on this work.

To learn more about how Darktrace continues to innovate to meet today's most pressing security challenges, register for our upcoming launch broadcast here.

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September 3, 2026

Botnet Behind the Camera: Mirai Katana Activity on a Video Recording Device

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Key takeaways

  • Darktrace identified a camera device infected with the Mirai/Katana botnet in a sports-sector customer environment, showing how exposed IoT devices can become active participants in wider attack chains.
  • The compromise involved suspicious Wget behavior, file downloads from rare external IPs, unusual incoming HTTP connections to video recorder management interfaces, and large outbound data transfers to infrastructure associated with botnet activity.
  • The incident highlights the importance of extending visibility and response beyond traditional endpoints, as unmanaged or overlooked connected devices can be exploited for command-and-control, malware delivery, and data exfiltration.

Mirai and the Katana variant

Mirai is a botnet that first emerged in August 2016 and is well known for launching large-scale distributed-denial-of-service (DDoS) attacks, typically targeting exposed Internet of Things (IoT) devices. It identifies vulnerable IoT devices ,often by abusing default credentials or exposed services, and recruiting them into a remotely controlled botnet that can be used in DDoS campaigns [1].

Katana, one of the many variants that arose after Mirai’s source code was released publicly, was first observed in late 2020 and has been seen using more advanced capabilities, including custom command-and-control (C2), persistence mechanisms, and DDoS functionality [2].

In March 2026, research from the Nokia Deepfield Emergency Response Team (ERT) identified Katana as a Mirai-derived DDoS botnet targeting Android-based TV set-top boxes through exposed Android Debug Bridge (ADB) access.  Observed capabilities included custom C2, runtime domain rotation, multiple DDoS methods, and an on-device compiled kernel rootkit used for persistence and stealth [3].

Darktrace’s detection of Mirai Botnet activity on a camera device

In early 2026, Darktrace identified a Network/Digital Video Recorder (NVR/DVR) on the network of a sports-sector customer that had been infected with the Mirai Katana botnet and subsequently used to exfiltrate data from the customer’s environment. Seemingly related follow-up activity was observed on the same device several months later.

In both instances, the Darktrace Security Operations Centre (SOC) alerted the customer as part of the Managed Threat Detection (MTD) service. However, as Darktrace’s Autonomous Response capability was not fully enabled on the affected device, Darktrace was unable to proactively block the suspicious activity or prevent the compromise from continuing and recurring.

The initial compromise appears to have occurred when the affected device was seen using Wget to download Linux-based Executable and Linkable Format (ELF) files from a rare external IP, 195.177.94[.]105, which had not previously been observed in the customer’s network. Further analysis downloaded file hashes identified files related to the Mirai botnet.

Figure 1: Darktrace’s Real-Time AI Analyst investigation into the unusual outbound connection where the ELF files were downloaded.

Within a few hours, Darktrace detected the device uploading close to 3GB of data to another external IP, 50.7.49[.]4:3017 (ASN AS30058 FDCSERVERS), suggesting that the activity was likely routed via a virtual private server (VPS) hosted by FDC Servers [2]. Attackers often abuse VPS infrastructure from legitimate cloud providers to blend in with legitimate traffic and evade IP reputation and geolocation-based detections.

Figure 2:  Darktrace’s detection of the unusual data upload activity by the affected camera device.

Darktrace continued to observe similar data transfers to multiple rare endpoints  including 171.225.223[.]53, 95.161.128[.]62, 61.7.209[.]88, 95.161.128[.]62, which have been linked to Mirai by open-source intelligence (OSINT).

Figure 3: Darktrace’s detection of spikes in unusual external data transfer activity from the camera device.

Exploitation continued

Several months later, Darktrace identified the same exfiltration pattern on the device again, this time with stronger indications of associations with Mirai Katana botnet infection.

The device received incoming HTTP connections from 129.121.114[.]124, an external IP known to be associated with the Katana botnet IP [3]. The connections targeted the ‘/dvr/cmd’ path using the root username and user agent Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/42.0.2311.135 Safari/537.36 Edge/12.246.

The ‘/dvr/cmd’ path appears to be associated with the affected device’s web management functionality. This API endpoint has historically been targeted by Mirai and other IoT botnets through the exploitation of critical command injection vulnerabilities and automated botnet exploitation [4].

Figure 4: Darktrace’s  detection of HTTP connectivity from the external IP associated with Mirai Katana Botnet.

A few days later, Darktrace observed the Wget utility being used to download ELF files, including “/lil”,  from the IP 129.121.114[.]124. OSINT reporting has since associated this IP address with the Mirai Katana botnet. Notably, the IP observed earlier in the year, 195.177.94[.]105, had also hosted a file named “lil”, indicating a link between the observed activity.

Over the following days, the device received a sudden spike in connections from multiple rare external endpoints, suggesting a possible successful brute force attack. Darktrace also observed the device exfiltrating just under 4GB of data to another Mirai-associated IP address,  66.92.198[.]194, over ports 3344, 954922, and 80. Finally, the device was seen uploading data to the Mirai botnet IP 5.175.249[.]53 over port138 and exhibited an increase in UDP connections to 34.18.28[.]10 over port 9068.

Following both file download events, Darktrace identified spikes in external data transfers and connection attempts to rare destinations. While Darktrace’s Threat Research team could not confirm with high confidence that this to activity was directly associated with Mirai, it may indicate that Mirai Katana includes data exfiltration functionality.

Darktrace’s threat researchers also identified an internet-facing NTP server belonging to a separate customer receiving incoming connection attempts from the same initially observed IP, 195.177.94[.]105,over the port 123. This suggests that Mirai Katana may not exclusively target IoT devices.

Conclusion

This case demonstrates how threat actors can exploit overlooked IoT and OT devices to support broader malicious objectives. Here, a camera device infected with a botnet was used to exfiltrate data from the customer's environment, showing how peripheral assets can become active participants in an attack chain.

This case also reinforces a challenge many organizations face today: extending security visibility beyond traditional endpoints and servers. Cameras, sensors, and other connected devices often operate with limited monitoring and may fall outside established security processes, despite maintaining network connectivity and access to potentially sensitive environments. This is particularly relevant in the sports sector, where growing reliance on connected cameras, smart stadium technologies, and other IoT devices continues to expand the attack surface, as highlighted in Darktrace's Sports Sector Threat Report.

As botnets like Kata and Mirai continue to evolve, defenders need visibility across unmanaged IoT and edge devices, as well as security solutions that can recognize subtle deviations in device behavior that may indicate an emerging compromise.

Credit to Parvatha Ananthakannan (Cyber Analyst), Signe Zaharka (Principal Analyst)

Edited by Ryan Traill (Content Manager)

Appendices

Darktrace Model Detections

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Multiple EXE from Rare External Locations

·      Device / Initial Attack Chain Activity

·      Unusual Activity / Unusual External Data to New Endpoint

·      Anomalous Connection / Data Sent to Rare Domain

·      Unusual Activity / Enhanced Unusual External Data Transfer

·      Anomalous Connection / Uncommon 1 GiB Outbound

·      Device / Significant UDP Increase

·      Anomalous Connection / Low and Slow Exfiltration to IP

·      Compromise / Large Number of Suspicious Failed Connections

·      Compromise / Large Number of Suspicious Successful Connections

·      Unusual Activity / Unusual External Activity

·      Compliance / SSH to Rare External Destination

·      Unusual Activity / Unusual DNS

·      Device / External Network Scan

·      Device / Suspicious DNS Activity

·      Device / Large Number of Model Alerts

List of Indicators of Compromise (IoCs)

Indicator of Compromise Type Description
195.177.94[.]105 IP C2 endpoint
50.7.49[.]4:30171 IP Possible C2 endpoint
129.121.114[.]124 IP C2 endpoint
hxxp://195.177.94[.]105/n3 URL Likely C2 endpoint
hxxp://195.177.94[.]105/n2 URL Likely C2 endpoint
hxxp://129.121.114[.]124/lil URL Likely C2 endpoint
hxxp://129.121.114[.]124/HHn URL Possible C2 endpoint
hxxp://129.121.114[.]124/JFc URL Possible C2 endpoint
hxxp://129.121.114[.]124/jum URL Likely C2 endpoint
hxxp://129.121.114[.]124/OaSf URL Likely C2 endpoint
hxxp://129.121.114[.]124/OPWg URL Possible C2 endpoint
hxxp://129.121.114[.]124/vHwK URL Possible C2 endpoint
hxxp://129.121.114[.]124/VLv URL Possible C2 endpoint
hxxp://129.121.114[.]124/WbJ URL Possible C2 endpoint
hxxp://129.121.114[.]124/zkR URL Possible C2 endpoint
Ab17883ae4c3bc6afa18c439166eeeb4b03186e3093d984e3a95f573e0fcb7d8 SHA-256 Mirai payload
3d587e809dac49d34a3f717e072fd0aebe5e71db63333e45c81577d6b4266f87 SHA-256 Mirai payload
Bf6e81733a7e209d3dce80d15bf3c5d300752d961fae6b45d90c9bbe7f8c89a2 SHA-256 Possible payload
f25488303813ab1ec0eaa71562938601aac185e8aaf93adb84522557f7cf4dd6 SHA-256 Possible payload
0cb4ff6b71f4423184bfa35c34e9090297637208b0e30205d4b224e56abde2ef SHA-256 Possible payload
19c24cbeaf06b2e7697083f33a85521a9315105c784691bde7420fde4cc69410 SHA-256 Likely Mirai payload
1e74f734fff8df91f4f7172d0de10c421eca78aeb800e8a48e16bc5dbde5d20e SHA-256 Possible payload
6e71f7763d1f29d5712106ebb122e281c32787540aa2342b0fe5351d585d18d7 SHA-256 Possible payload
71f4ff7cdb6d6a7d2673c543c5d2535093afbd707b20a5b9ddf735466c1105c1 SHA-256 Possible payload
76db7ee73ebf15e48a3cb24a074d92248671ef2c6ed3bc3e708377341fb7674d SHA-256 Possible payload
da87a65f7beb438e61f0b61964fed8aa305a380f569042f84c55eca8fa7929b8 SHA-256 Possible payload
e15809eb6ba66477175270d62cfa53e4bf278595f69938708c81c4bc457930fe SHA-256 Mirai payload

MITRE ATT&CK Mapping

Tactic Technique ID Technique / Sub-technique
Initial Access T1659 Content Injection
T1189 Drive-by Compromise
Exfiltration T1041 Exfiltration Over C2 Channel
T1048.003 Exfiltration Over Unencrypted Non-C2 Protocol
Command and Control T1105 Ingress Tool Transfer
T1095 Non-Application Layer Protocol
T1571 Non-Standard Port
Reconnaissance T1595.001 Scanning IP Blocks
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Parvatha Ananthakannan
Cyber Analyst
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