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How Darktrace’s Cyber AI Analyst accelerates reporting incidents to the US federal government

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12
Apr 2022
12
Apr 2022
This blog explains how Darktrace helps defenders abide by US federal laws on reporting cyber security incidents, featuring a real-world example of a ransomware attack investigated by Cyber AI Analyst.

On March 15, 2022, President Biden signed the Cyber Incident Reporting for Critical Infrastructure Act into law, included as part of the Congressional Omnibus Appropriations bill. The law requires critical infrastructure owners and operators to quickly notify the Cyber and Infrastructure Security Agency (CISA) of ransomware payments and significant cyber-attacks.

The Cyber Incident Reporting for Critical Infrastructure Act creates two new reporting requirements:

  1. an obligation to report certain cyber incidents to DHS CISA within 72 hours
  2. an obligation to report ransomware payments within 24 hours

Supporting the new law, Darktrace AI accelerates the cyber incident reporting process. Specifically, Darktrace’s Cyber AI Analyst understands the connections among disparate security incidents with supervised machine learning and autonomously writes incident reports in human-readable language using natural language processing (NLP). These Darktrace incident reports allow human analysts to send reports to CISA quickly and efficiently.

In the below real-world attack case study, we demonstrate how Cyber AI Analyst facilitates seamless reporting for critical infrastructure organizations that fall victim to ransomware and malicious data exfiltration. The AI technology, trained on human analyst behavior, replicates investigations at machine speed and scale, surfacing relevant details in minutes and allowing security teams to understand what happened precisely and share this information with the relevant authorities.

The below threat investigation details a significant threat find on a step by step level in technical detail to demonstrate the power and speed of Cyber AI Analyst.

Cyber AI Analyst’s incident report

When ransomware struck this organization, Cyber AI Analyst was invaluable, autonomously investigating the full scope of the incident and generating a natural language summary that clearly showed the progression of the attack.

Figure 1: Cyber AI Analyst reveals the full scope of the attack

In the aftermath of this attack, Darktrace’s technology also offered analyst assistance in mapping out the timeline of the attack and identifying what files were compromised, helping the security team identify anomalous activity related to the ransomware attack.

Figure 2: Cyber AI Analyst showing the stages of the attack chain undergone by the compromised device

With Darktrace AI’s insights, the team easily identified the timeline of the attack, affected devices, credentials used, file shares accessed, files exfiltrated, and malicious endpoints contacted, enabling the customer to disclose the scale of the attack and notify necessary parties.

This example demonstrates how Cyber AI Analyst empowers critical infrastructure owners and operators to swiftly report major cyber-attacks to the federal government. Considering that 72 hours is the reporting period is for significant incidents — and 24 hours for ransomware payments — Cyber AI Analyst is no longer a nice-to-have but a must-have for critical infrastructure.

Attack breakdown: Ransomware and data exfiltration

Cyber AI Analyst delivered the most critical information in an easy-to-read report — with no human touch involved — as shown in the incident report above. We will now break down the attack further to demonstrate how Darktrace’s Self-Learning AI understood the unusual activity throughout the attack lifecycle.

In this double extortion ransomware, attackers exfiltrated data over 22 days. The detections made by Darktrace’s Self-Learning AI, and the parallel investigation by Cyber AI Analyst, were used to map the attack chain and identify how and what data had been exfiltrated and encrypted.

The attack consisted of three general groups of events:

  • Unencrypted FTP (File Transfer Protocol) data exfiltration to rare malicious external endpoint in Bulgaria (May 9 07:23:46 UTC – May 21 03:06:46 UTC)
  • Ransomware encryption of files in network file shares (May 25 01:00:27 UTC – May 30 07:09:53 UTC)
  • Encrypted SSH (Secure Shell) data exfiltration to rare malicious external endpoint (May 29 16:43:37 UTC – May 30 13:23:59 UTC)
Figure 3: Timeline of the attack alongside Darktrace model breaches

First, uploads of internal data to a rare external endpoint in Bulgaria were observed within the networks. The exfiltration was preceded by SMB reads of internal file shares before approximately 450GB of data was exfiltrated via FTP.

Darktrace’s AI identified this threatening activity on its own, and the organization was quickly able to pinpoint what data had been exfiltrated, including files camouflaged by markings such as ‘Talent Acquisition’ and ‘Engineering and Construction,’ and legal and financial documents — suggesting that these were documents of an extremely sensitive nature.

Figure 4: Screenshots showing two model breaches relating to external uploads over FTP
Figure 5: Screenshot showing SMB reads from a file share before FTP upload

Model breaches:

  • Anomalous Connection / Unusual Incoming Data Volume
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Compromise / Ransomware / Suspicious SMB Activity
  • Compromise / Ransomware / SMB Reads then Writes with Additional Extensions
  • Unusual Activity / Anomalous SMB Move & Write
  • Unusual Activity / High Volume Server Data Transfer
  • Unusual Activity / Sustained Anomalous SMB Activity
  • Device / SMB Lateral Movement

Four days following this observed activity, Darktrace’s AI detected the deployment of ransomware when multiple compromised devices began making anomalous SMB connections to file shares that they do not typically access, reading and writing similar volumes to the SMB file shares, as well as writing additional extensions to files over SMB. The file extension comprised a random string of letters and was likely to be unique to this target.

Using Darktrace, the customer obtained a full list of files that had been encrypted. The list included apparent financial records in an ‘Accounts’ file share.

Figure 6: Model breach showing additional extension written to file during ransomware encryption

Model breaches:

  • Anomalous Connection / Unusual Incoming Data Volume
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Compromise / Ransomware / Suspicious SMB Activity
  • Compromise / Ransomware / SMB Reads then Writes with Additional Extensions
  • Unusual Activity / Anomalous SMB Move & Write
  • Unusual Activity / High Volume Server Data Transfer
  • Unusual Activity / Sustained Anomalous SMB Activity
  • Device / SMB Lateral Movement

Simultaneously, uploads of internal data to a rare external endpoint were observed within the network. The uploads were all performed using encrypted SSH/SFTP. In total, approximately 3.5GB of data was exfiltrated this way.

Despite the attacker using an encrypted channel to exfiltrate this data, Darktrace detected anomalous SMB file transfers prior to the external upload, indicating which files were exfiltrated. Here, Darktrace’s ability to go ‘back in time’ proved invaluable in helping analysts determine which files had been exfiltrated, although they were exfiltrated via an encrypted means.

Figure 7: Model breaches showing anomalous SMB activity before upload over SSH

Model breaches:

  • Anomalous Server Activity / Outgoing from Server
  • Compliance / SSH to Rare External Destination
  • Unusual Activity / Enhanced Unusual External Data Transfer
  • Device / Anomalous SMB Followed By Multiple Model Breaches
  • Device / Large Number of Model Breaches
  • Anomalous Connection / Uncommon 1 GiB Outbound
  • Anomalous Connection / Data Sent to Rare Domain
  • Anomalous Connection / Data Sent To New External Device

How did the attack bypass the rest of the security stack?

Existing administrative credentials were used to escalate privileges within the network and perform malicious activity.

Had Darktrace Antigena been active, it would have actioned a targeted, autonomous response to contain the activity in its early stages. Antigena would have enforced the ‘pattern of life’ on the devices involved in anomalous SMB activity — containing activity such as reading from file shares that are not normally connected, appending extensions to files and blocking outgoing connections to rare external endpoints.

However, in this case, Antigena was not set up to take action – it was configured in Human Confirmation mode. The incident was clearly alerted on by Darktrace, and appeared as a top priority item in the security team’s workflow. However, the security team was not monitoring Darktrace’s user interface, and in the absence of any action taken by other tools, the attack was allowed to progress, and the organization was obligated to disclose the details of the incident.

Streamlining the reporting process

In the modern threat landscape, leaning on AI to stop fast-moving and sophisticated attacks at machine speed and scale is critical. As this attack shows, the technology also helps organizations fulfill reporting requirements in the aftermath of an attack.

New legislation requires timely disclosure; with many traditional approaches to security, organizations do not have the capacity to surface the full details after an attack. On top of this, collating these details can take days or weeks. This is why Darktrace is no longer a nice-to-have but a must-have for critical infrastructure organizations, which are now required to report significant incidents swiftly.

Darktrace’s AI detects malicious activity as it happens and empowers customers to quickly understand the timeline of a compromise, as well as files accessed and exfiltrated by an attacker. This not only prepares organizations to resist the most sophisticated attacks, but also accelerates and radically simplifies the process of reporting the data breach.

Security teams should not have to confront disclosure processes on their own. Attacks happen fast, and their aftermaths are messy – retrospective investigation of lost data can be a futile effort with traditional approaches. With Darktrace, security teams can meet disruptive and sudden attacks with precise and nimble means of uncovering data, as well as detection and mitigation of risk. And, should the need arise, rapid and accurate reporting of events is laid out on a silver platter by the AI.

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.
AUTHOR
ABOUT ThE AUTHOR
Justin Fier
SVP, Red Team Operations

Justin is one of the US’s leading cyber intelligence experts, and holds the position of SVP, Red Team Operations at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years’ experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.

Sally Kenyon Grant
VP, Darktrace Federal

Sally Kenyon Grant is Vice President of Federal at Darktrace, working with the US Department of Defense, the Intelligence Community and Federal Civilian Agencies.

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Inside the SOC

Connecting the Dots: Darktrace’s Detection of the Exploitation of the ConnectWise ScreenConnect Vulnerabilities

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10
May 2024

Introduction

Across an ever changing cyber landscape, it is common place for threat actors to actively identify and exploit newly discovered vulnerabilities within commonly utilized services and applications. While attackers are likely to prioritize developing exploits for the more severe and global Common Vulnerabilities and Exposures (CVEs), they typically have the most success exploiting known vulnerabilities within the first couple years of disclosure to the public.

Addressing these vulnerabilities in a timely manner reduces the effectiveness of known vulnerabilities, decreasing the pace of malicious actor operations and forcing pursuit of more costly and time-consuming methods, such as zero-day related exploits or attacking software supply chain operations. While actors also develop tools to exploit other vulnerabilities, developing exploits for critical and publicly known vulnerabilities gives actors impactful tools at a low cost they are able to use for quite some time.

Between January and March 2024, the Darktrace Threat Research team investigated one such example that involved indicators of compromise (IoCs) suggesting the exploitation of vulnerabilities in ConnectWise’s remote monitoring and management (RMM) software ScreenConnect.

What are the ConnectWise ScreenConnect vulnerabilities?

CVE-2024-1708 is an authentication bypass vulnerability in ScreenConnect 23.9.7 (and all earlier versions) that, if exploited, would enable an attacker to execute remote code or directly impact confidential information or critical systems. This exploit would pave the way for a second ScreenConnect vunerability, CVE-2024-1709, which allows attackers to directly access confidential information or critical systems [1].

ConnectWise released a patch and automatically updated cloud versions of ScreenConnect 23.9.9, while urging security temas to update on-premise versions immediately [3].

If exploited in conjunction, these vulnerabilities could allow a malicious actor to create new administrative accounts on publicly exposed instances by evading existing security measures. This, in turn, could enable attackers to assume an administrative role and disable security tools, create backdoors, and disrupt RMM processes. Access to an organization’s environment in this manner poses serious risk, potentially leading to significant consequences such as deploying ransomware, as seen in various incidents involving the exploitation of ScreenConnect [2]

Darktrace Coverage of ConnectWise Exploitation

Darktrace’s anomaly-based detection was able to identify evidence of exploitation related to CVE-2024-1708 and CVE-2024-1709 across two distinct timelines; these detections included connectivity with endpoints that were later confirmed to be malicious by multiple open-source intelligence (OSINT) vendors. The activity observed by Darktrace suggests that threat actors were actively exploiting these vulnerabilities across multiple customer environments.

In the cases observed across the Darktrace fleet, Darktrace DETECT™ and Darktrace RESPOND™ were able to work in tandem to pre-emptively identify and contain network compromises from the onset. While Darktrace RESPOND was enabled in most customer environments affected by the ScreenConnect vulnerabilities, in the majority of cases it was configured in Human Confirmation mode. Whilst in Human Confirmation mode, RESPOND will provide recommended actions to mitigate ongoing attacks, but these actions require manual approval from human security teams.

When enabled in autonomous response mode, Darktrace RESPOND will take action automatically, shutting down suspicious activity as soon as it is detected without the need for human intervention. This is the ideal end state for RESPOND as actions can be taken at machine speed, without any delays waiting for user approval.

Looking within the patterns of activity observed by Darktrace , the typical  attack timeline included:

Darktrace observed devices on affected customer networks performing activity indicative of ConnectWise ScreenConnect usage, for example connections over 80 and 8041, connections to screenconnect[.]com, and the use of the user agent “LabTech Agent”. OSINT research suggests that this user agent is an older name for ConnectWise Automate [5] which also includes ScreenConnect as standard [6].

Darktrace DETECT model alert highlighting the use of a remote management tool, namely “screenconnect[.]com”.
Figure 1: Darktrace DETECT model alert highlighting the use of a remote management tool, namely “screenconnect[.]com”.

This activity was typically followed by anomalous connections to the external IP address 108.61.210[.]72 using URIs of the form “/MyUserName_DEVICEHOSTNAME”, as well as additional connections to another external, IP 185.62.58[.]132. Both of these external locations have since been reported as potentially malicious [14], with 185.62.58[.]132 in particular linked to ScreenConnect post-exploitation activity [2].

Figure 2: Darktrace DETECT model alert highlighting the unusual connection to 185.62.58[.]132 via port 8041.
Figure 2: Darktrace DETECT model alert highlighting the unusual connection to 185.62.58[.]132 via port 8041.
Figure 3: Darktrace DETECT model alert highlighting connections to 108.61.210[.]72 using a new user agent and the “/MyUserName_DEVICEHOSTNAME” URI.
Figure 3: Darktrace DETECT model alert highlighting connections to 108.61.210[.]72 using a new user agent and the “/MyUserName_DEVICEHOSTNAME” URI.

Same Exploit, Different Tactics?  

While the majority of instances of ConnectWise ScreenConnect exploitation observed by Darktrace followed the above pattern of activity, Darktrace was able to identify some deviations from this.

In one customer environment, Darktrace’s detection of post-exploitation activity began with the same indicators of ScreenConnect usage, including connections to screenconnect[.]com via port 8041, followed by connections to unusual domains flagged as malicious by OSINT, in this case 116.0.56[.]101 [16] [17]. However, on this deployment Darktrace also observed threat actors downloading a suspicious AnyDesk installer from the endpoint with the URI “hxxp[:]//116.0.56[.]101[:]9191/images/Distribution.exe”.

Figure 4: Darktrace DETECT model alert highlighting the download of an unusual executable file from 116.0.56[.]101.
Figure 4: Darktrace DETECT model alert highlighting the download of an unusual executable file from 116.0.56[.]101.

Further investigation by Darktrace’s Threat Research team revealed that this endpoint was associated with threat actors exploiting CVE-2024-1708 and CVE-2024-1709 [1]. Darktrace was additionally able to identify that, despite the customer being based in the United Kingdom, the file downloaded came from Pakistan. Darktrace recognized that this represented a deviation from the device’s expected pattern of activity and promptly alerted for it, bringing it to the attention of the customer.

Figure 5: External Sites Summary within the Darktrace UI pinpointing the geographic locations of external endpoints, in this case highlighting a file download from Pakistan.
Figure 5: External Sites Summary within the Darktrace UI pinpointing the geographic locations of external endpoints, in this case highlighting a file download from Pakistan.

Darktrace’s Autonomous Response

In this instance, the customer had Darktrace enabled in autonomous response mode and the post-exploitation activity was swiftly contained, preventing the attack from escalating.

As soon as the suspicious AnyDesk download was detected, Darktrace RESPOND applied targeted measures to prevent additional malicious activity. This included blocking connections to 116.0.56[.]101 and “*.56.101”, along with blocking all outgoing traffic from the device. Furthermore, RESPOND enforced a “pattern of life” on the device, restricting its activity to its learned behavior, allowing connections that are considered normal, but blocking any unusual deviations.

Figure 6: Darktrace RESPOND enforcing a “pattern of life” on the offending device after detecting the suspicious AnyDesk download.
Figure 6: Darktrace RESPOND enforcing a “pattern of life” on the offending device after detecting the suspicious AnyDesk download.
Figure 7: Darktrace RESPOND blocking connections to the suspicious endpoint 116.0.56[.]101 and “*.56.101” following the download of the suspicious AnyDesk installer.
Figure 7: Darktrace RESPOND blocking connections to the suspicious endpoint 116.0.56[.]101 and “*.56.101” following the download of the suspicious AnyDesk installer.

The customer was later able to use RESPOND to manually quarantine the offending device, ensuring that all incoming and outgoing traffic to or from the device was prohibited, thus preventing ay further malicious communication or lateral movement attempts.

Figure 8: The actions applied by Darktrace RESPOND in response to the post-exploitation activity related to the ScreenConnect vulnerabilities, including the manually applied “Quarantine device” action.

Conclusion

In the observed cases of the ConnectWise ScreenConnect vulnerabilities being exploited across the Darktrace fleet, Darktrace was able to pre-emptively identify and contain network compromises from the onset, offering vital protection against disruptive cyber-attacks.

While much of the post-exploitation activity observed by Darktrace remained the same across different customer environments, important deviations were also identified suggesting that threat actors may be adapting their tactics, techniques and procedures (TTPs) from campaign to campaign.

While new vulnerabilities will inevitably surface and threat actors will continually look for novel ways to evolve their methods, Darktrace’s Self-Learning AI and behavioral analysis offers organizations full visibility over new or unknown threats. Rather than relying on existing threat intelligence or static lists of “known bads”, Darktrace is able to detect emerging activity based on anomaly and respond to it without latency, safeguarding customer environments whilst causing minimal disruption to business operations.

Credit: Emma Foulger, Principal Cyber Analyst for their contribution to this blog.

Appendices

Darktrace Model Coverage

DETECT Models

Compromise / Agent Beacon (Medium Period)

Compromise / Agent Beacon (Long Period)

Anomalous File / EXE from Rare External Location

Device / New PowerShell User Agent

Anomalous Connection / Powershell to Rare External

Anomalous Connection / New User Agent to IP Without Hostname

User / New Admin Credentials on Client

Device / New User Agent

Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

Anomalous Server Activity / Anomalous External Activity from Critical Network Device

Compromise / Suspicious Request Data

Compliance / Remote Management Tool On Server

Anomalous File / Anomalous Octet Stream (No User Agent)

RESPOND Models

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

Antigena / Network::External Threat::Antigena File then New Outbound Block

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

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

Antigena / Network::Significant Anomaly::Antigena Controlled and Model Breach

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

Antigena / Network / External Threat / Antigena Suspicious File Pattern of Life Block

Antigena / Network / Insider Threat / Antigena Unusual Privileged User Activities Pattern of Life Block

List of IoCs

IoC - Type - Description + Confidence

185.62.58[.]132 – IP- IP linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

108.61.210[.]72- IP - IP linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

116.0.56[.]101    - IP - IP linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

/MyUserName_ DEVICEHOSTNAME – URI - URI linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

/images/Distribution.exe – URI - URI linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

24780657328783ef50ae0964b23288e68841a421 - SHA1 Filehash - Filehash linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

a21768190f3b9feae33aaef660cb7a83 - MD5 Filehash - Filehash linked with threat actors exploiting CVE-2024-1708 and CVE-2024-17091

MITRE ATT&CK Mapping

Technique – Tactic – ID - Sub-technique of

Web Protocols - COMMAND AND CONTROL - T1071.001 - T1071

Web Services      - RESOURCE DEVELOPMENT - T1583.006 - T1583

Drive-by Compromise - INITIAL ACCESS - T1189 – NA

Ingress Tool Transfer   - COMMAND AND CONTROL - T1105 - NA

Malware - RESOURCE DEVELOPMENT - T1588.001- T1588

Exploitation of Remote Services - LATERAL MOVEMENT - T1210 – NA

PowerShell – EXECUTION - T1059.001 - T1059

Pass the Hash      - DEFENSE EVASION, LATERAL MOVEMENT     - T1550.002 - T1550

Valid Accounts - DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS - T1078 – NA

Man in the Browser – COLLECTION - T1185     - NA

Exploit Public-Facing Application - INITIAL ACCESS - T1190         - NA

Exfiltration Over C2 Channel – EXFILTRATION - T1041 – NA

IP Addresses – RECONNAISSANCE - T1590.005 - T1590

Remote Access Software - COMMAND AND CONTROL - T1219 – NA

Lateral Tool Transfer - LATERAL MOVEMENT - T1570 – NA

Application Layer Protocol - COMMAND AND CONTROL - T1071 – NA

References:

[1] https://unit42.paloaltonetworks.com/connectwise-threat-brief-cve-2024-1708-cve-2024-1709/  

[2] https://www.huntress.com/blog/slashandgrab-screen-connect-post-exploitation-in-the-wild-cve-2024-1709-cve-2024-1708    

[3] https://www.huntress.com/blog/a-catastrophe-for-control-understanding-the-screenconnect-authentication-bypass

[4] https://www.speedguide.net/port.php?port=8041  

[5] https://www.connectwise.com/company/announcements/labtech-now-connectwise-automate

[6] https://www.connectwise.com/solutions/software-for-internal-it/automate

[7] https://www.securityweek.com/slashandgrab-screenconnect-vulnerability-widely-exploited-for-malware-delivery/

[8] https://arcticwolf.com/resources/blog/cve-2024-1709-cve-2024-1708-follow-up-active-exploitation-and-pocs-observed-for-critical-screenconnect-vulnerabilities/https://success.trendmicro.com/dcx/s/solution/000296805?language=en_US&sfdcIFrameOrigin=null

[9] https://www.connectwise.com/company/trust/security-bulletins/connectwise-screenconnect-23.9.8

[10] https://socradar.io/critical-vulnerabilities-in-connectwise-screenconnect-postgresql-jdbc-and-vmware-eap-cve-2024-1597-cve-2024-22245/

[11] https://www.trendmicro.com/en_us/research/24/b/threat-actor-groups-including-black-basta-are-exploiting-recent-.html

[12] https://otx.alienvault.com/indicator/ip/185.62.58.132

[13] https://www.virustotal.com/gui/ip-address/185.62.58.132/community

[14] https://www.virustotal.com/gui/ip-address/108.61.210.72/community

[15] https://otx.alienvault.com/indicator/ip/108.61.210.72

[16] https://www.virustotal.com/gui/ip-address/116.0.56[.]101/community

[17] https://otx.alienvault.com/indicator/ip/116.0.56[.]101

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About the author
Justin Torres
Cyber Analyst

Blog

Email

How Empowering End Users can Improve Your Email Security and Decrease the Burden on the SOC

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08
May 2024

Why do we pay attention to the end user?

Every email security solution filters inbound mail, then typically hands over false positives and false negatives to the security team for manual triage. A crucial problem with this lifecycle is that it ignores the inevitability of end users being at the front line of any organization. Employees may receive point in time security awareness training, but it is rarely engaging or contextualized to their reality. While an employee may report a suspicious-looking email to the security team, they will rarely get to understand the outcome or impact of that decision. This means that the quality of reporting never improves, so the burden on the security team of triaging these emails – of which 90% are falsely reported – persists and grows with the business over time.

At Darktrace, we recognize that employees will always be on the front line of email security. That’s why we aim to improve end-user reporting from the ground up, reducing the overall number of emails needing triage and saving security team resource.

How does Darktrace improve the quality of end-user reporting?

Darktrace prioritizes improving users’ security awareness to increase the quality of end-user reporting from day one. We train users and optimize their experience, which in turn provides better detection. 

That starts with training and security awareness. Traditionally, organizations oblige employees to attend point-in-time training sessions which interrupt their daily work schedules. With Darktrace/Email, if a message contains some potentially suspicious markers but is most likely safe, Darktrace takes a specific action to neutralize the risky components and presents it to the user with a simple narrative explaining why certain elements have been held back. The user can then decide whether to report this email to the security team. 

AI shares its analysis in context and in real time at the moment a user is questioning an email
Figure 1: AI shares its analysis in context and in real time at the moment a user is questioning an email

The AI narrative gives the user context for why their specific email may carry risk, putting their security awareness training into practice. This creates an element of trust with the security solution, rather than viewing it as outside of daily workflows. Users may also receive a daily or weekly digest of their held emails and make a decision on whether to release or report them.  

Whatever the user’s existing workflow is for reporting emails, Darktrace/Email can integrate with it and improve its quality. Our add-in for Outlook gives users a fully optimized experience, allowing them to engage with the narratives for each email, as well as non-productive mail management. However, if teams want to integrate Darktrace into an existing workflow, it can analyze emails reported to an internal SOC mailbox, the native email provider’s 'Report Phish’ button, or the ‘Knowbe4’ button.

By empowering the user with contextual feedback on each unique email, we foster employee engagement and elevate both reporting quality and security awareness. In fact, 60% fewer benign emails are reported because of the extra context supplied by Darktrace to end users. The eventual report is then fed back to the detection algorithm, improving future decision-making.  

Reducing the amount of emails that reach the SOC

Out of the higher-quality emails that do end up being reported by users, the next step is to reduce the amount of emails that reach the SOC.   

Once a user reports an email, Darktrace will independently determine if the mail should be automatically remediated based on second level triage. Darktrace/Email’s Mailbox Security Assistant automates secondary triage by combining additional behavioral signals and the most advanced link analysis engine we have ever built. It detects 70% more sophisticated malicious phishing links by looking at an additional twenty times more context than at the primary analysis stage, revealing the hidden intent within interactive and dynamic webpages. This directly alleviates the burden of manual triage for security analysts.

Following this secondary triage the emails that are deemed worthy of security team attention are then passed over, resulting in a lower quantity and higher quality of emails for SOC manual triage.

Centralizing and speeding analysis for investigations

For those emails that are received by the SOC, Darktrace also helps to improve triage time for manual remediation.  

AI-generated narratives and automated remediation actions empower teams to fast-track manual triage and remediation, while still providing security analysts with the necessary depth. With live inbox view, security teams gain access to a centralized platform that combines intuitive search capabilities, Cyber AI Analyst reports, and mobile application access. With all security workflows consolidated within a unified interface, users can analyze and take remediation actions without the need to navigate multiple tools, such as e-discovery platforms – eliminating console hopping and accelerating incident response.

Our customers tell us that our AI allows them to go in-depth quickly for investigations, versus other solutions that only provide a high-level view.

Cyber AI Analyst provides a simple language narrative for each reported email, allowing teams to quickly understand why it may be suspicious
Figure 2: Cyber AI Analyst provides a simple language narrative for each reported email, allowing teams to quickly understand why it may be suspicious

Conclusion

Unlike our competitors, we believe that improving the quality of users’ experience is not only a nice-to-have, but a fundamental means for improving security. Any modern solution should consider end users as a key source of information as well as an opportunity for defense. Darktrace does both – optimizing the user experience as well as our AI learning from the user to augment detection.  

The benefits of empowering users are ultimately felt by the security team, who benefit from improved detection, a reduction in manual triage of benign emails, and faster investigation workflows.

Augmented end user reporting is just one of a range of features new to Darktrace/Email. Check out the latest Innovations to Darktrace/Email in our recent blog.

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About the author
Carlos Gray
Product Manager
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