Blog
/
/
April 17, 2024

Cerber Ransomware: Dissecting the three heads

Cerber ransomware's Linux variant is actively exploiting CVE-2023-22518 in Confluence servers. It uses three UPX-packed C++ payloads: a primary stager, a log checker for environment assessment, and an encryptor that renames files with a .L0CK3D extension.
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
Nate Bill
Threat Researcher
Default blog image
17
Apr 2024

Introduction: Cerber ransomware

Researchers at Cado Security Labs (now part of Darktrace) received reports of the Cerber ransomware being deployed onto servers running the Confluence application via the CVE-2023-22518 exploit. [1] There is a large amount of coverage on the Windows variant, however there is very little about the Linux variant. This blog will discuss an analysis of the Linux variant. 

Cerber emerged and was at the peak of its activity around 2016, and has since only occasional campaigns, most recently targeting the aforementioned Confluence vulnerability. It consists of three highly obfuscated C++ payloads, compiled as a 64-bit Executable and Linkable Format (ELF, the format for executable binary files on Linux) and packed with UPX. UPX is a very common packer used by many threat actors. It allows the actual program code to be stored encoded in the binary, and at runtime extracted into memory and executed (“unpacked”). This is done to prevent software from scanning the payload and detecting the malware.

Pure C++ payloads are becoming less common on Linux, with many threat actors now employing newer programming languages such as Rust or Go. [2] This is likely due to the Cerber payload first being released almost 8 years ago. While it will have certainly received updates, the language and tooling choices are likely to have stuck around for the lifetime of the payload.

Initial access

Cado researchers observed instances of the Cerber ransomware being deployed after a threat actor leveraged CVE-2023-22518 in order to gain access to vulnerable instances of Confluence [3]. It is an improper authorization vulnerability that allows an attacker to reset the Confluence application and create a new administrator account using an unprotected configuration restore endpoint used by the setup wizard.

[19/Mar/2024:15:57:24 +0000] - http-nio-8090-exec-10 13.40.171.234 POST /json/setup-restore.action?synchronous=true HTTP/1.1 302 81796ms - - python-requests/2.31.0 
[19/Mar/2024:15:57:24 +0000] - http-nio-8090-exec-3 13.40.171.234 GET /json/setup-restore-progress.action?taskId= HTTP/1.1 200 108ms 283 - python-requests/2.31.0 

Once an administrator account is created, it can be used to gain code execution by uploading & installing a malicious module via the admin panel. In this case, the Effluence web shell plugin is directly uploaded and installed, which provides a web UI for executing arbitrary commands on the host.

Web Shell recreation
Figure 1: Recreation of installing a web shell on a Confluence instance

The threat actor uses this web shell to download and run the primary Cerber payload. In a default install, the Confluence application is executed as the “confluence” user, a low privilege user. As such, the data the ransomware is able to encrypt is limited to files owned by the confluence user. It will of course succeed in encrypting the datastore for the Confluence application, which can store important information. If it was running as a higher privilege user, it would be able to encrypt more files, as it will attempt to encrypt all files on the system.

Primary payload

Summary of payload:

  • Written in C++, highly obfuscated, and packed with UPX
  • Serves as a stager for further payloads
  • Uses a C2 server at 45[.]145[.]6[.]112 to download and unpack further payloads
  • Deletes itself off disk upon execution

The primary payload is packed with UPX, just like the other payloads. Its main purpose is to set up the environment and grab further payloads in order to run.

Upon execution it unpacks itself and tries to create a file at /var/lock/0init-ld.lo. It is speculated that this was meant to serve as a lock file and prevent duplicate execution of the ransomware, however if the lock file already exists the result is discarded, and execution continues as normal anyway. 

It then connects to the (now defunct) C2 server at 45[.]145[.]6[.]112 and pulls down the secondary payload, a log checker, known internally as agttydck. It does this by doing a simple GET /agttydcki64 request to the server using HTTP and writing the payload body out to /tmp/agttydck.bat. It then executes it with /tmp and ck.log passed as arguments. The execution of the payload is detailed in the next section.

Once the secondary payload has finished executing, the primary payload checks if the log file at /tmp/ck.log it wrote exists. If it does, it then proceeds to delete itself and agttydcki64 from the disk. As it is still running in memory, it then downloads the encryptor payload, known internally as agttydcb, and drops it at /tmp/agttydcb.bat. The packing on this payload is more complex. The file command reports it as a DOS executable and the bat extension would imply this as well. However, it does not have the correct magic bytes, and the high entropy of the file suggests that it is potentially encoded or encrypted. Indeed, the primary payload reads it in and then writes out a decoded ELF file back using the same stream, overwriting the content. It is unclear the exact mechanism used to decode agttydcb. The primary payload then executes the decoded agttydcb, the behavior of which is documented in a later section.

2283  openat(AT_FDCWD, "/tmp/agttydcb.bat", O_RDWR) = 4 
2283  read(4, "\353[\254R\333\372\22,\1\251\f\235 'A>\234\33\25E3g\335\0252\344vBg\177\356\321"..., 450560) = 450560 
2283  lseek(4, 0, SEEK_SET)             = 0 
2283  write(4, "\177ELF\2\1\1\0\0\0\0\0\0\0\0\0\2\0>\0\1\0\0\0X\334F\0\0\0\0\0"..., 450560) = 450560 
2283  close(4)                          = 0 

Truncated strace output for the decoding process

Log check payload - agttydck

Summary of payload:

  • Written in C++, highly obfuscated, and packed with UPX
  • Tries to write the phrase “success” to a given file passed in arguments
  • Likely a check for sandboxing, or to check the permission level of the malware on the system

The log checker payload, agttydck, likely serves as a permission checker. It is a very simple payload and was easy to analyze statically despite the obfuscation. Like the other payloads, it is UPX packed.

When run, it concatenates each argument passed to it and delimits with forward slashes in order to obtain a full path. In this case, it is passed /tmp and ck.log, which becomes /tmp/ck.log. It then tries to open this file in write mode, and if it succeeds writes the word “success” and returns 0. If it does not succeed, it returns 1.

cleaned-up routine
Figure 2: Cleaned-up routine that writes out the success phrase

The purpose of this check isn’t exactly clear. It could be to check if the tmp directory is writable and that it can write, which may be a check for if the system is too locked down for the encryptor to work. Given the check is run in a process separate to the primary payload, it could also be an attempt to detect sandboxes that may not handle files correctly, resulting in the primary payload not being told about the file created by the child.

Encryptor - agttydck

Summary of payload:

  • Written in C++, highly obfuscated, and packed with UPX
  • Writes log file /tmp/log.0 on start and /tmp/log.1 on completion, likely for debugging
  • Walks the root directory looking for directories it can encrypt
  • Writes a ransom note to each directory
  • Overwrites all files in directory with their encrypted content and adds a .L0CK3D extension

The encryptor, agttydcb, achieves the goal of the ransomware, which is to encrypt files on the filesystem. Like the other payloads, it is UPX packed and written with heavily obfuscated C++. Upon launch, it deletes itself off disk so as to not leave any artefacts. It then creates a file at /tmp/log.0, but with no content. As it creates a second file at /tmp/log.1 (also with no content) after encryption finishes, it is possible these were debug markers that the attacker mistakenly left in.

The encryptor then spawns a new thread to do the actual encryption. The payload attempts to write a ransom note at /<directory>/read-me3.txt. If it succeeds, it will walk all files in the directory and attempt to encrypt them. If it fails, it moves on to the next directory. The encryptor chooses to pick which directories to encrypt by walking the root file system. For example, it will try to encrypt /usr, and then /var, etc.

Cerber ransom note
Figure 3: Ransom note left by Cerber

When it has identified a file to encrypt, it opens a read-write file stream to the file and reads in the entire file. It is then encrypted in memory before it seeks to the start of the stream and writes the encrypted data, overwriting the file content, and rendering the file fully encrypted. It then renames the file to have the .L0CK3D extension. Rewriting the same file instead of making a new file and deleting the old one is useful on Linux as directories may be set to append only, preventing the outright deletion of files. Rewriting the file may also rewrite the data on the underlying storage, making recovery with advanced forensics also impossible.

2290  openat(AT_FDCWD, "/home/ubuntu/example", O_RDWR) = 6 
2290  read(6, "file content"..., 3691) = 3691 
2290  write(6, "\241\253\270'\10\365?\2\300\304\275=\30B\34\230\254\357\317\242\337UD\266\362\\\210\215\245!\255f"
..., 3691) = 3691 
2290  close(6)                          = 0 
2290  rename("/home/ubuntu/example", "/home/ubuntu/example.L0CK3D") = 0 

Truncated strace of the encryption process

Once this finishes, it tries to delete itself again (which fails as it already deleted itself) and creates /tmp/log.1. It then gracefully exits. Despite the ransom note claiming the files were exfiltrated, Cado researchers did not observe any behavior that showed this.

Conclusion

Cerber is a relatively sophisticated, albeit aging, ransomware payload. While the use of the Confluence vulnerability allows it to compromise a large amount of likely high value systems, often the data it is able to encrypt will be limited to just the confluence data and in well configured systems this will be backed up. This greatly limits the efficacy of the ransomware in extracting money from victims, as there is much less incentive to pay up.

IoCs

The payloads are packed with UPX so will match against existing UPX Yara rules.

Hashes (sha256)

cerber_primary 4ed46b98d047f5ed26553c6f4fded7209933ca9632b998d265870e3557a5cdfe

agttydcb 1849bc76e4f9f09fc6c88d5de1a7cb304f9bc9d338f5a823b7431694457345bd

agttydck ce51278578b1a24c0fc5f8a739265e88f6f8b32632cf31bf7c142571eb22e243

IPs

C2 (Defunct) 45[.]145[.]6[.]112

References

  1. https://confluence.atlassian.com/security/cve-2023-22518-improper-authorization-vulnerability-in-confluence-data-center-and-server-1311473907.html
  1. https://www.proofpoint.com/uk/threat-reference/cerber-ransomware  
  1. https://nvd.nist.gov/vuln/detail/CVE-2023-22518

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
Nate Bill
Threat Researcher

More in this series

No items found.

Blog

/

Network

/

July 28, 2026

Hiding in Plain Sight: Uncovering a Multi-Stage Ransomware Attack Through Behavioral Detection

ransomware attackDefault blog imageDefault blog image

Why ransomware has changed

Ransomware attacks have continued to increase globally, with 698 incidents reported in May 2026, representing a 48% rise compared to 472 incidents in May 2025 [1]. At the same time, the ransomware landscape is evolving. Several major ransomware groups, including LockBit [2], have been disrupted by successful joint law enforcement operations, resulting in a shift away from a small number of dominant actors towards a more fragmented and distributed ecosystem. This is increasingly composed of smaller groups who play a specialized role in the attack, such as initial access brokers, affiliates or developers.

As a result, ransomware tactics, techniques, and procedures (TTPs) are becoming more diverse and less predictable. On top of this, adversaries are leveraging native tools and legitimate penetration testing frameworks to evade detection. Anomaly-based detection is therefore critical to identify pre-ransomware activity, rather than relying on signatures associated with a handful of well-known ransomware groups.

As these attacks often unfold over several days, there is a critical window for defenders to act. In this context, behavioral-based detection plays a vital role in identifying suspicious pre-ransomware activity, and enabling early intervention before encryption or exfiltration occurs.

Inside a modern ransomware intrusion

In early 2026, Darktrace detected activity within a customer’s environment related to a multi-stage ransomware intrusion from the initial compromise. This activity does not appear to be attributable to a specific ransomware group, and no known ransomware payload was observed until the final stage.

The attack aligns with a broader industry trend in which compromised virtual private network (VPN) credentials are used as an entry point, followed by rapid internal reconnaissance and lateral movement using legitimate administrative tools. This growing preference for native tools and legitimate frameworks in cyber-attacks illustrates that it is increasingly unreliable to depend solely on traditional indicators of compromise such as known malware signatures or exploit detection.

The intrusion also involved the use of Sliver, an open-source adversary emulation framework, which is increasingly observed in real-world attacks. Originally designed for penetration testing and red teaming, Sliver has gained traction among threat actors as a stealthier alternative to more heavily signatured frameworks such as Cobalt Strike. As a legitimate framework, its use further complicates detection for security tools that rely on known malicious signatures.

Darktrace’s detection of a ransomware event in a customer’s environment

The initial compromise appears to have occurred via compromised credentials used over the VPN shortly before, or at the onset of the first indicators of suspicious activity. While it remains unclear as to how or when the threat actors gained access to these credentials, the use of initial access brokers (IABs) is a common feature of modern ransomware operations. This suggests that access to the environment may have been established several days or weeks beforehand.

The intrusion unfolded over three days, presenting multiple opportunities for early detection and intervention before ransomware deployment. The attack progressed through a compressed but structured sequence: initial access and reconnaissance were completed within hours, followed by privilege escalation and lateral movement the next day, and culminating in data exfiltration and encryption shortly thereafter. Throughout each stage, distinct behavioral anomalies emerged across the network providing clear indicators of malicious activity well before the ransomware was deployed.

While Darktrace’s Autonomous Response capability was enabled within the customer’s environment, it was not fully configured across the impacted devices, allowing the attack to progress to ransomware deployment. Had Autonomous Response been fully deployed across the affected systems, it could have taken targeted action against the earliest stages of malicious activity, potentially disrupting the intrusion before it escalated.

Figure 1: Timeline of the attack progression.

Day 1: Reconnaissance and privilege escalation

The threat actor gained access via compromised VPN credentials and initiated internal reconnaissance. Darktrace detected anomalous scanning behavior, including unusual port scanning activity and widespread network enumeration.

Specifically, Darktrace detected a high volume of east-west scanning activity across a broad range of ports, with TCP connections targeting ports 21, 80, 445, 4899 and 8080. Associated URIs suggested the use of Nmap, a widely used penetration testing tool. This highlights how attackers often leverage legitimate penetration testing tools for malicious reconnaissance, enabling them to blend into normal network activity and evade traditional signature-based detection methods.

Figure 2: Darktrace's detection of a sharp increase in anomalous internal connections, triggering multiple high-severity model alerts associated with reconnaissance activity.

Several devices were observed using administrative credentials to carry out privileged actions in a manner that was highly anomalous for the environment. This activity was accompanied by behavior consistent with SMB authentication scanning, suggesting efforts to identify and access additional systems. As the activity intensified, an increasing number of devices became involved, signalling lateral movement and further spread across the network.

Darktrace also identified privilege escalation through active directory (AD) replication abuse, specifically via the drsuapi::DRSGetNCChanges function. This technique allows an attacker with sufficient privileges to request directory replication data from a domain controller (DC), enabling them to extract credentials, including password hashes, without directly interacting with user accounts. Commonly associated with ‘DCSync’ attacks, this technique is frequently used to obtain highly privileged credentials and enable further escalation within an environment.

Figure 3: Darktrace’s detection of anomalous AD replication activity indicative of privilege escalation.

This activity was seen alongside the use of the now obsolete SMBv1, repeated NTLM authentication attempts using multiple variations of ‘Administrator’ credentials, reverse DNS scanning, and large-scale network scanning. Darktrace observed widespread use of SMBv1 across the customer’s environment, exposing a significant security weakness. As a legacy protocol with well-documented weaknesses, SMBv1 can be exploited to facilitate lateral movement, allowing the attackers to expand their access following initial compromise.

Day 3: Lateral Movement, Command & Control, and Exfiltration

Two days later, the attacker escalated privileges and expanded their foothold using living-off-the-land (LOTL) techniques such as PSExec, WMI, and RDP. Concurrently, Darktrace identified command-and-control (C2)-style communications consistent with the Sliver framework, alongside rare outbound connections to cloud infrastructure indicating potential data exfiltration. The volume and severity of observed activity increased as attack behavior intensified.

The device was observed conducting extensive lateral movement, leveraging LOTL techniques to evade detection. Activity included WMI execution (e.g. ExecQuery), DCE-RPC activity, SMB sessions and file writes, most of which were successful, as well as the deployment of PSEXESVC.exe via ADMIN$ shares and prolonged RDP sessions. Darktrace identified this behavior as highly anomalous for the environment. Such activity is commonly associated with the transfer of attacker tooling, remote command execution, and the establishment of persistent access across compromised systems.  

Figure 4: Darktrace’s detection of a spike in RPC binding events indicative of potential lateral movement.

On the same day, Darktrace detected C2-style SSL communications originating from multiple internal devices to rare external endpoints. These connections exhibited anomalous characteristics, including invalid SSL certificates and repeated connection patterns resembling beaconing. Analysis of the observed JA3 fingerprint further linked the activity to Sliver, the adversary simulation framework referenced earlier, as the hash has previously been associated with Sliver-related infrastructure [3]. The use of this framework reflects a broader trend of attackers repurposing legitimate offensive security tools for stealthy C2 communications. Connections to 137[.]220[.]59[.]55 (ASN AS20473 AS-VULTR) indicated that the communications were likely routed via a virtual private server (VPS) hosted by Vultr. Attackers often utilize VPS infrastructure from legitimate cloud providers like Vultr to obscure their true origin, blend into benign traffic, and evade IP-based detection mechanisms [4].

Figure 5: Darktrace’s Cyber AI Analyst detection of two linked unusual connections to Vultr infrastructure.

Darktrace also observed a device initiating SSL connections to safedata.s3[.]wasabisys[.]com, an endpoint associated with Wasabi cloud storage. Darktrace recognized that neither the destination nor the associated IP address had previously been observed within the environment.  More than 200 MB of data was subsequently uploaded externally to endpoints sharing the same JA3 client hash, indicating a sustained transfer session and potential data exfiltration to third-party storage. The apparent exfiltration prior to encryption is consistent with a double-extortion ransomware strategy.

Figure 6: Darktrace’s Cyber AI Analyst detection of more than 30 rare outbound connections to a Wasabi cloud storage endpoint, indicative of potential data exfiltration

Day 4: Encryption

The attack culminated in ransomware deployment, marking the transition from suspicious network activity to a business-impacting incident. Using SMB-based propagation, the threat actor encrypted thousands of files across the network, affecting multiple systems and disrupting normal operations. Throughout the encryption event, the legacy SMBv1 protocol was used extensively across multiple internal systems, resulting in a significant increase in newly encrypted files.

Figure 7: Darktrace’s detection of abnormal spikes in SMB activity and associated model alerts, indicative of ransomware encryption and propagation.

Darktrace’s Cyber AI Analyst automatically investigated and correlated the encryption activity and related events into a single incident narrative, providing the customer with real-time visibility into the attack while significantly reducing investigation time.

Figure 8: Darktrace’s Cyber AI Analyst’s investigation into the encryption activity. AI Analyst incident detailing example encryption activity in real time. Related events are automatically correlated and summarized into a clear narrative, reducing investigation time.

Defender action recommendations

What Could Have Stopped the Attack Earlier?

Although the attack ultimately resulted in ransomware deployment, there were multiple opportunities to detect, contain, and disrupt the intrusion before encryption occurred. The following actions could have significantly reduced the overall impact:

Detect and investigate indicators of reconnaissance and lateral movement

  • Unusual scanning
  • Active Directory replication anomalies consistent with DCSync activity
  • Anomalous use of native tools and processes indicative of LOTL attacks
  • Unusual use of common reconnaissance tools such as Nmap and NetScan

Contain compromised credentials and affected devices

  • Disable and reset compromised VPN credentials
  • Isolate devices performing anomalous scanning and lateral movement activity

Block suspicious external communications and data exfiltration

  • Use anomaly-based detection to detect and block repeated outbound connections to rare external infrastructure
  • Prevent data exfiltration to unauthorized cloud storage services such as Wasabi

Conclusion

The incident highlights the importance of anomaly-based detection, particularly against attacks that primarily use native or legitimate tools to evade traditional security measures. Darktrace identified suspicious activity from the first day of the compromise, providing multiple opportunities to disrupt the intrusion before it progressed to lateral movement and data exfiltration.

In this instance, detection was not the limiting factor; response time was. Prompt investigation and containment of devices exhibiting anomalous behavior could have prevented lateral movement, data exfiltration, and ultimately ransomware deployment.

As adversaries increasingly prioritize stealth over custom malware, relying instead on legitimate tools, valid credentials, and trusted infrastructure, traditional signature-based detection becomes less effective. Identifying subtle behavioral deviations early remains critical to disrupting attacks before they escalate into full-scale ransomware incidents.

Credit to Alexandra Evzona (Cyber Analyst), Priya Thapa (Senior Cyber Analyst)
Edited by Ryan Traill (Content Manager)

Appendices

References

[1] https://industrialcyber.co/ransomware/check-point-reports-ransomware-attacks-jump-48-year-over-year-despite-decline-in-overall-cyberattack-activity/

[2] https://www.europol.europa.eu/media-press/newsroom/news/law-enforcement-disrupt-worlds-biggest-ransomware-operation

[3] https://fieldeffect.com/blog/field-effect-mitigates-not-so-simplehelp-exploits-enabling-deployment-of-backdoors

[4] https://www.darktrace.com/blog/from-vps-to-phishing-how-darktrace-uncovered-saas-hijacks-through-virtual-infrastructure-abuse

Indicators of Compromise (IoCs)

IP Addresses

  • 137[.]220[.]59[.]55 – Potential C2 infrastructure (Vultr AS20473)
  • 38[.]27[.]106[.]123 – Wasabi cloud storage endpoint associated with potential data exfiltration
  • 38[.]27[.]106[.]128 – Wasabi cloud storage endpoint associated with potential data exfiltration
  • 38[.]27[.]106[.]117 – Wasabi cloud storage endpoint associated with potential data exfiltration

Domains

  • safedata[.]s3[.]wasabisys[.]com – Potential data exfiltration endpoint
  • *.wasabisys[.]com – Associated Wasabi cloud storage infrastructure

JA3 Fingerprint

  • d6828e30ab66774a91a96ae93be4ae4c – Associated with the Sliver adversary emulation framework

Files

  • Delete[.]me – File observed during reconnaissance activity, commonly associated with NetScan

Darktrace Model Coverage

·       Anomalous Connection / Active Remote Desktop Tunnel

·       Anomalous Connection / Anomalous Remote Registry Service Control

·       Anomalous Connection / Multiple Failed Windows UDP

·       Anomalous Connection / New or Uncommon Service Control

·       Anomalous Connection / New or Uncommon Service Enumeration

·       Anomalous Connection / New User Agent to IP Without Hostname

·       Anomalous Connection / SMB Enumeration

·       Anomalous Connection / Suspicious Activity On High Risk Device

·       Anomalous Connection / Suspicious Read Write Ratio

·       Anomalous Connection / Sustained MIME Type Conversion

·       Anomalous Connection / Uncommon 1 GiB Outbound

·       Anomalous Connection / Unusual Admin RDP Session

·       Anomalous Connection / Unusual Admin SMB Session

·       Anomalous Connection / Unusual SMB Version 1 Connectivity

·       Anomalous File / EXE from Rare External Location

·       Anomalous File / Internal / Additional Extension Appended to SMB File

·       Anomalous Server Activity / Outgoing from Server

·       Compromise / Beaconing Activity To External Rare

·       Compromise / Ransomware / Possible Ransom Note Read

·       Compromise / Ransomware / Ransom or Offensive Words Written to SMB

·       Compromise / Ransomware / Suspicious SMB Activity

·       Device / Anonymous NTLM Logins

·       Device / Attack and Recon Tools

·       Device / Initial Attack Chain Activity

·       Device / Large Number of Model Alerts

·       Device / Long Agent Connection to New Endpoint

·       Device / Multiple Lateral Movement Model Alerts

·       Device / Network Scan

·       Device / New or Uncommon SMB Named Pipe

·       Device / New or Unusual Remote Command Execution

·       Device / New User Agent

·       Device / Possible RPC Lateral Movement

·       Device / Possible SMB/NTLM Brute Force

·       Device / RDP Scan

·       Device / SMB Lateral Movement

·       Device / SMB Session Brute Force (Non-Admin)

·       Device / SMB Version 1 Access Failures

·       Device / Suspicious File Delete Activity

·       Device / Suspicious Network Scan Activity

·       Device / Unusual SMB Error Detected

·       Device / Unusual SMB To Critical Resource

·       Device / Unusual Winreg Operation

·       Unusual Activity / Multiple Failed Internal Connections

·       Unusual Activity / Possible RPC Recon Activity

·       Unusual Activity / Sustained Anomalous SMB Activity

·       Unusual Activity / Unusual External Data to New Endpoint

·       Unusual Activity / Unusual External Data Transfer

·       Unusual Activity / Unusual File Storage Data Transfer

·       Unusual Activity / Unusual Large Internal Transfer

·       User / New Admin Credentials on Client

·       User / NTLM Login from Unauthenticated Device

Autonomous Response Model Alerts

·       Antigena / Network / External Threat / Antigena Ransomware Block

·       Antigena / Network / External Threat / Antigena Suspicious File Block

·       Antigena / Network / Insider Threat / Antigena Active Threat SMB Write Block

·       Antigena / Network / Insider Threat / Antigena Internal Anomalous File Activity

·       Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

·       Antigena / Network / Insider Threat / Antigena Network Scan Block

·       Antigena / Network / Insider Threat / Antigena Unusual Privileged User Activities Block

·       Antigena / Network / Manual / Quarantine Device

·       Antigena / Network / Significant Anomaly / Antigena Alerts Over Time Block

·       Antigena / Network / Significant Anomaly / Antigena Controlled and Model Alert

·       Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block

·       Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block 100

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

MITRE ATT&CK MAPPING

Command and control - Protocol Tunneling - T1572

Command and control – Web Protocols – T1071.001

Credential Access- Exploitation for Credential Access- T1212

Credential Access- Password Guessing- T1110

Discovery- File and Directory Discovery- T1083

Discovery- Network Service Discovery- T1046

Discovery- Network Share Discovery- T1135

Discovery- Remote System Discovery- T1018

Exfiltration- Exfiltration Over C2 Channel- T1041

Exfiltration- Exfiltration to Cloud Storage- T1567

Impact- Data Encrypted for Impact- T1486

Impact- Data Encrypted for Impact- T1486

Impact- Service Stop - T1489

Initial Access- Public-Facing Application- T1190

Lateral Movement- Exploitation of Remote Services- T1210

Lateral Movement- Remote Desktop Protocol- T1021

Lateral Movement- SMB/Windows Admin Shares- T1021

Lateral Movement- Taint Shared Content- T1080

Persistence- Modify Registry- T1112

Privilege Escalation- Exploitation for Privilege Escalation- T0890

Privilege Escalation- Valid Accounts- T1078

Reconnaissance- Scanning IP Blocks- T1595

Reconnaissance- Vulnerability Scanning- T1595

Resource Development- Malware- T1588

Stealth- File Deletion- T1070

Continue reading
About the author
Alexandra Evzona
Cyber Analyst

Blog

/

Email

/

July 24, 2026

Darktrace / EMAIL Expands Behavioral Defense Across Email and Collaboration Workflows

Default blog imageDefault blog image

Email and collaboration tools do more than carry messages. They are where organizations approve payments, share sensitive data, reset credentials, and make thousands of everyday decisions. Increasingly, they are interfaces through which humans direct AI agents in their daily activity. Email, Slack and Teams are high volume, rich with sensitive data, and an easy place to hide malicious activity.

The opportunity isn’t lost on bad actors. Darktrace / EMAIL detected more than 32 million high-confidence phishing emails globally in 2025, and 70% of those messages passed DMARC authentication.  Phishing is increasingly difficult to detect and familiar trust signals alone are not enough. People and security teams need to understand how a message fits the normal behavior of the sender, recipient, and organization. They also need to correlate activity across platforms to spot threats that span multiple channels.

To effectively secure against today’s evolved threats, security teams need to act at two levels: they need to help each employee make a safer decision ‘in the moment’, and they need to understand the wider patterns that may expose the business to risk.

Darktrace is introducing four new capabilities in Darktrace / EMAIL to address both challenges. The new features explain suspicious content more clearly to end users, strengthen the capabilities of Darktrace / Adaptive Human Defense with richer guidance, let organizations define their own patterns for detecting sensitive data in messages, and give security teams a process-level view of risk across email and collaboration workflows.

Darktrace / EMAIL Inbox Analysis highlights risky content within your emails

A warning is more useful when it explains what the user should look at. To help do that, we’ve expanded Darktrace / EMAIL’s Inbox Analysis Add-In to highlight potentially dangerous content within the body of emails that Darktrace / EMAIL flags as potentially suspicious or high risk.  

The add-in can highlight language designed to create urgency, financial references, requests for payment, suspicious links, and content that is unusual for the sender. Each highlighted element includes a pop up that explains why it may be suspicious. Instead of asking an employee to accept a verdict without context, the analysis helps them examine the message and make a more informed decision.

Enhanced Just-In-Time Training Banners in Darktrace / Adaptive Human Defense

Enhanced Just-In-Time Training Banners build on the same principle. The banners now include a contextual header, actionable advice, and specific detection context. This gives employees more useful guidance at the point of risk without adding unnecessary information or cognitive load.

Together, the capabilities help turn a warning into a short learning moment. Employees can see what looks unusual, understand what action to take, and build their judgment.

Custom Sensitive Data Detection in Darktrace / EMAIL - Data Loss Prevention

Sensitive data is different for every business. Standard categories such as payment card details or government identifiers matter, but organizations also have their own customer codes, project names, research formats, account structures, and internal identifiers.

Custom Sensitive Data Detection in Darktrace / EMAIL - Data Loss Prevention allows administrators to write custom expressions for the data their organization needs to protect. Matched content can trigger existing model actions and data loss prevention (DLP) workflows, extending Darktrace's DLP capabilities.

This extends data loss detection beyond a fixed library of common data types. Security teams can apply controls to information that is sensitive in the context of their own organization and adapt those controls as the business changes.

Introducing Email and Collaboration Workflow Risk Posture Dashboards

Some of the most important risks are not isolated events. They are repeated ways of working that create an opening for error, misuse, or attack. For example, a payment request may be one suspicious message, but a recurring approval workflow that relies on weak verification is a business process risk.

The new Email and Collaboration Workflow Risk Posture Dashboard analyzes email and collaboration data across Email, Microsoft Teams, Slack and Zoom to provide a process-level view of risk in the organization. These may include financial authorization workflows, sensitive data sharing patterns, and activity that could expose credentials.

The dashboard brings these patterns into a view and provides actionable recommendations. This helps security teams determine where to investigate or strengthen controls, where ownership needs to be clarified, and where the business may need to change a risky process. It gives CISOs a clearer view of how human and communication risk is embedded in everyday operations, not only where individual alerts occur.

Behavior connects the individual decision to the wider risk

These capabilities build on Darktrace’s unique behavioral approach to security. We use Adaptive AI to learn how people and AI normally behave within an organization, creating the context needed to recognize when activity changes.

Within the Darktrace Behavioral Defense Platform, Darktrace / EMAIL helps protect people against phishing, account takeover, data exfiltration, and human risk across email and collaboration tools. The new capabilities extend that protection in both directions. They give employees clearer context for the decision in front of them, while giving security leaders a broader view of the workflows and behavior that create risk across the organization.

The result is not simply more alerts. It is a better understanding of why something is risky, what action to take, and where the organization can reduce risk before a familiar process becomes an easy route for an attacker.

[related-resource]

Continue reading
About the author
Carlos Gray
Senior Product Marketing Manager, Email
Your data. Our AI.
Elevate your network security with Darktrace AI