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March 7, 2025

Darktrace's Early Detection of the Latest Ivanti Exploits

In January 2025, Ivanti disclosed two critical vulnerabilities affecting their products. Darktrace detected exploitation of these vulnerabilities as early as December 2024.
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
Hugh Turnbull
Cyber Analyst
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07
Mar 2025

As reported in Darktrace’s 2024 Annual Threat Report, the exploitation of Common Vulnerabilities and Exposures (CVEs) in edge infrastructure has consistently been a significant concern across the threat landscape, with internet-facing assets remaining highly attractive to various threat actors.

Back in January 2024, the Darktrace Threat Research team investigated a surge of malicious activity from zero-day vulnerabilities such as those at the time on Ivanti Connect Secure (CS) and Ivanti Policy Secure (PS) appliances. These vulnerabilities were disclosed by Ivanti in January 2024 as CVE-2023-46805 (Authentication bypass vulnerability) and CVE-2024-21887 (Command injection vulnerability), where these two together allowed for unauthenticated, remote code execution (RCE) on vulnerable Ivanti systems.

What are the latest vulnerabilities in Ivanti products?

In early January 2025, two new vulnerabilities were disclosed in Ivanti CS and PS, as well as their Zero Trust Access (ZTA) gateway products.

  • CVE-2025-0282: A stack-based buffer overflow vulnerability. Successful exploitation could lead to unauthenticated remote code execution, allowing attackers to execute arbitrary code on the affected system [1]
  • CVE-2025-0283: When combined with CVE-2025-0282, this vulnerability could allow a local authenticated attacker to escalate privileges, gaining higher-level access on the affected system [1]

Ivanti also released a statement noting they are currently not aware of any exploitation of CVE-2025-0283 at the time of disclosure [1].

Darktrace coverage of Ivanti

The Darktrace Threat Research team investigated the new Ivanti vulnerabilities across their customer base and discovered suspicious activity on two customer networks. Indicators of Compromise (IoCs) potentially indicative of successful exploitation of CVE-2025-0282 were identified as early as December 2024, 11 days before they had been publicly disclosed by Ivanti.

Case 1: December 2024

Authentication with a Privileged Credential

Darktrace initially detected suspicious activity connected with the exploitation of CVE-2025-0282 on December 29, 2024, when a customer device was observed logging into the network via SMB using the credential “svc_negbackups”, before authenticating with the credential “svc_negba” via RDP.

This likely represented a threat actor attempting to identify vulnerabilities within the system or application and escalate their privileges from a basic user account to a more privileged one. Darktrace / NETWORK recognized that the credential “svc_negbackups” was new for this device and therefore deemed it suspicious.

Darktrace / NETWORK’s detection of the unusual use of a new credential.
Figure 1: Darktrace / NETWORK’s detection of the unusual use of a new credential.

Likely Malicious File Download

Shortly after authentication with the privileged credential, Darktrace observed the device performing an SMB write to the C$ share, where a likely malicious executable file, ‘DeElevate64.exe’ was detected. While this is a legitimate Windows file, it can be abused by malicious actors for Dynamic-Link Library (DLL) sideloading, where malicious files are transferred onto other devices before executing malware. There have been external reports indicating that threat actors have utilized this technique when exploiting the Ivanti vulnerabilities [2].

Darktrace’s detection the SMB write of the likely malicious file ‘DeElevate64.exe’ on December 29, 2024.
Figure 2: Darktrace’s detection the SMB write of the likely malicious file ‘DeElevate64.exe’ on December 29, 2024.

Shortly after, a high volume of SMB login failures using the credential “svc_counteract-ext” was observed, suggesting potential brute forcing activity. The suspicious nature of this activity triggered an Enhanced Monitoring model alert that was escalated to Darktrace’s Security Operations Center (SOC) for further investigation and prompt notification, as the customer was subscribed to the Security Operations Support service.  Enhanced Monitoring are high-fidelity models detect activities that are more likely to be indicative of compromise

Suspicious Scanning and Internal Reconnaissance

Darktrace then went on to observe the device carrying out network scanning activity as well as anomalous ITaskScheduler activity. Threat actors can exploit the task scheduler to facilitate the initial or recurring execution of malicious code by a trusted system process, often with elevated permissions. The same device was also seen carrying out uncommon WMI activity.

Darktrace’s detection of a suspicious network scan from the compromised device.
Figure 3: Darktrace’s detection of a suspicious network scan from the compromised device.

Further information on the suspicious scanning activity retrieved by Cyber AI Analyst, including total number of connections and ports scanned.
Figure 4: Further information on the suspicious scanning activity retrieved by Cyber AI Analyst, including total number of connections and ports scanned.
Darktrace’s detection of a significant spike in WMI activity represented by DCE_RPC protocol request increases at the time, with little to no activity observed one week either side.
Figure 5: Darktrace’s detection of a significant spike in WMI activity represented by DCE_RPC protocol request increases at the time, with little to no activity observed one week either side.

Case 2: January 2025

Suspicious File Downloads

On January 13, 2025, Darktrace began to observe activity related to the exploitation of CVE-2025-0282  on the network of another customer, with one in particular device attempting to download likely malicious files.

Firstly, Darktrace observed the device making a GET request for the file “DeElevator64.dll” hosted on the IP 104.238.130[.]185. The device proceeded to download another file, this time “‘DeElevate64.exe”. from the same IP. This was followed by the download of “DeElevator64.dll”, similar to the case observed in December 2024. External reporting indicates that this DLL has been used by actors exploiting CVE-2025-0282 to sideload backdoor into infected systems [2]

Darktrace’s detection of the download of the suspicious file “DeElevator64.dll” on January 13, 2025.
Figure 6: Darktrace’s detection of the download of the suspicious file “DeElevator64.dll” on January 13, 2025.

Suspicious Internal Activity

Just like the previous case, on January 15, the same device was observed making numerous internal connections consistent with network scanning activity, as well as DCE-RPC requests.

Just a few minutes later, Darktrace again detected the use of a new administrative credential, observing the following details:

  • domain=REDACTED hostname=DESKTOP-1JIMIV3 auth_successful=T result=success ntlm_version=2 .

The hostname observed by Darktrace, “DESKTOP-1JIMIV3,” has also been identified by other external vendors and was associated with a remote computer name seen accessing compromised accounts [2].

Darktrace also observed the device performing an SMB write of an additional file, “to.bat,” which may have represented another malicious file loaded from the DLL files that the device had downloaded earlier. It is possible this represented the threat actor attempting to deploy a remote scheduled task.

Darktrace’s detection of SMB Write of the suspicious file “to.bat”.
Figure 7: Darktrace’s detection of SMB Write of the suspicious file “to.bat”.

Further investigation revealed that the device was likely a Veeam server, with its MAC address indicating it was a VMware device. It also appeared that the Veeam server was capturing activities referenced from the hostname DESKTOP-1JIMIV3. This may be analogous to the remote computer name reported by external researchers as accessing accounts [2]. However, this activity might also suggest that while the same threat actor and tools could be involved, they may be targeting a different vulnerability in this instance.

Autonomous Response

In this case, the customer had Darktrace’s Autonomous Response capability enabled on their network. As a result, Darktrace was able to contain the compromise and shut down any ongoing suspicious connectivity by blocking internal connections and enforcing a “pattern of life” on the affected device. This action allows a device to make its usual connections while blocking any that deviate from expected behavior. These mitigative actions by Darktrace ensured that the compromise was promptly halted, preventing any further damage to the customer’s environment.

Darktrace's Autonomous Response capability actively mitigating the suspicious internal connectivity.
Figure 8: Darktrace's Autonomous Response capability actively mitigating the suspicious internal connectivity.

Conclusion

If the previous blog in January 2024 was a stark reminder of the threat posed by malicious actors exploiting Internet-facing assets, the recent activities surrounding CVE-2025-0282 and CVE-2025-0283 emphasize this even further.

Based on the telemetry available to Darktrace, a wide range of malicious activities were identified, including the malicious use of administrative credentials, the download of suspicious files, and network scanning in the cases investigated .

These activities included the download of suspicious files such as “DeElevate64.exe” and “DeElevator64.dll” potentially used by attackers to sideload backdoors into infected systems. The suspicious hostname DESKTOP-1JIMIV3 was also observed and appears to be associated with a remote computer name seen accessing compromised accounts. These activities are far from exhaustive, and many more will undoubtedly be uncovered as threat actors evolve.

Fortunately, Darktrace was able to swiftly detect and respond to suspicious network activity linked to the latest Ivanti vulnerabilities, sometimes even before these vulnerabilities were publicly disclosed.

Credit to: Nahisha Nobregas, Senior Cyber Analyst, Emma Foulger, Principle Cyber Analyst, Ryan Trail, Analyst Content Lead and the Darktrace Threat Research Team

Appendices

Darktrace Model Detections

Case 1

·      Anomalous Connection / Unusual Admin SMB Session

·      Anomalous File / EXE from Rare External Location

·      Anomalous File / Internal / Unusual SMB Script Write

·      Anomalous File / Multiple EXE from Rare External Locations

·      Anomalous File / Script from Rare External Location

·      Compliance / SMB Drive Write

·      Device / Multiple Lateral Movement Model Alerts

·      Device / Network Range Scan

·      Device / Network Scan

·      Device / New or Uncommon WMI Activity

·      Device / RDP Scan

·      Device / Suspicious Network Scan Activity

·      Device / Suspicious SMB Scanning Activity

·      User / New Admin Credentials on Client

·      User / New Admin Credentials on Server 

Case 2

·      Anomalous Connection / Unusual Admin SMB Session

·      Anomalous Connection / Unusual Admin RDP Session

·      Compliance / SMB Drive Write

·      Device / Multiple Lateral Movement Model Alerts

·      Device / SMB Lateral Movement

·      Device / Possible SMB/NTLM Brute Force

·      Device / Suspicious SMB Scanning Activity

·      Device / Network Scan

·      Device / RDP Scan

·      Device / Large Number of Model Alerts

·      Device / Anomalous ITaskScheduler Activity

·      Device / Suspicious Network Scan Activity

·      Device / New or Uncommon WMI Activity

List of IoCs Possible IoCs:

·      DeElevator64.dll

·      deelevator64.dll

·      DeElevate64.exe

·      deelevator64.dll

·      deelevate64.exe

·      to.bat

Mid-high confidence IoCs:

-       104.238.130[.]185

-       http://104.238.130[.]185/DeElevate64.exe

-       http://104.238.130[.]185/DeElevator64.dll

-       DESKTOP-1JIMIV3

References:

1.     https://www.ivanti.com/blog/security-update-ivanti-connect-secure-policy-secure-and-neurons-for-zta-gateways

2.     https://unit42.paloaltonetworks.com/threat-brief-ivanti-cve-2025-0282-cve-2025-0283/

3.     https://www.proofpoint.com/uk/blog/identity-threat-defense/privilege-escalation-attack#:~:text=In%20this%20approach%2C%20attackers%20exploit,handing%20over%20their%20login%20credentials

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
Hugh Turnbull
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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About the author
Dr. Tim Bazalgette
Chief AI Officer, Darktrace

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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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About the author
Parvatha Ananthakannan
Cyber Analyst
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