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Securing the Cloud Starts By Understanding It

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01
Nov 2023
01
Nov 2023
Many cloud security vendors purport to offer 'response' - but what do they really mean? What does meaningful response to cloud-related cyber-threats look like, and how is this achieved? This blog reveals all.

Widespread use of the cloud continues to transform business, while cyber security solutions race to keep up. Today’s multi-cloud environments introduce complexity and gaps in visibility that open doors for attackers. Given the dynamic nature of the cloud, these blind spots are constantly changing. And given its scalability, simple mistakes like a minor misconfiguration can lead to disproportionately large security incidents.

Enterprises can no longer afford to rely on disparate tools and static, point-in-time views of risk. The cloud is inherently complex, and security tools shouldn’t aim to simplify that complexity, but instead harness it, using its scale and intricacy to its advantage.

In a world where the cloud is highly customizable and every cloud is different, a one-size-fits-all approach to cloud security fails to adapt to the nuances of an individual environment. This blog explores how harnessing AI that learns and understands the unique organization can give security teams the visibility, understanding, and real-time detection and response needed to secure the cloud.

Security hinges on action

Typically, cloud security tends to fall into one of two camps:

  • Agentless approaches used by most Cloud Security Posture Management (CSPM) vendors that promise quick and easy installation with minimal disruption of operations, and
  • Agent-based approaches that offer finer granularity but may mean a lengthy, time-consuming, and expensive set-up process.

Both approaches have inherent drawbacks. Agentless solutions typically don’t give security teams the real-time awareness needed to detect emerging threats – be that a malicious insider, a zero-day exploit, or something else. On the other hand, agent-based solutions provide limited reach and scalability, usually being deployed in an area of the cloud the security team already knew posed a risk, offering no new insight and leaving blind spots untouched.

So cloud security today seems to be stuck in a dilemma. And another issue for both methods is that these products may be able to alert analysts when something goes wrong, but lack the ability to mount a genuine response. Even newer solutions claiming to provide automated response are usually referring to automating the process of sending alerts and opening tickets.

Rapid response is the holy grail

The same attributes that make the cloud so useful and attractive to organizations – speed, agility, availability, and scale – hold a symmetrical appeal for attackers. When cyber-attacks in the cloud unfold rapidly, it’s not enough to simply open a ticket and wait for somebody on the other end to pick it up. (If anything, having to field too many tickets can actually bog down triage and investigation, and delay rather than hasten response.) The ultimate test for useful response comes down to whether or not the security team is willing to use it. Response capabilities that never get turned on, with security teams fearful of disruption, miss the point entirely.

Effective response requires an understanding of when and how to respond, as well as having the cloud-native mechanisms to carry out the action. We can break this down into three steps:

Step 1: Beyond Visibility: Real-Time Understanding

Today’s static cloud security solutions provide snapshots of your environment prior to integration and installation. Static insights help validate and set up controls before deployment, but the real risks related to cloud migration appear later.

To drive the right response, your security solution must deliver a real-time, holistic view of your organization’s cloud environment, not just a generic sense of what the environment looks like.

Understanding risk related to the cloud requires more than just visibility. It requires understanding the various patterns of behavior across the environment, and knowing the nuances in how applications and workloads are architected. Who has access to what? Which virtual machines typically connect with each other? Is this container behaving as expected? Is this new Lambda function expected?

Darktrace/Cloud uses Self-Learning AI to see and understand your unique organization at the cloud network, architectural, and management layers. The ability of AI to recognize patterns across vast quantities of data puts it in a unique position to give security teams genuine insight into what’s happening in their cloud environment right now.

Each deployment and specific use of AI is different (based on your unique environment) but always includes an architectural view of your cloud footprint that aligns security and DevOps teams throughout the deployment lifecycle.  

One beta customer reported deploying Darktrace/Cloud was:

like flipping on a light switch in a dark room."

Step 2: Detection must apply context

With a true understanding of exactly what’s ‘normal’ in your cloud – which users are connecting to what resources, who has access to specific workloads, groups, overlaps, and privileges — the solution progresses toward response by teaching itself to spot what isn’t so normal.

A static snapshot of your cloud security posture can surface unpatched vulnerabilities and problematic misconfigurations, but the insight ends there. Cloud security solutions based on static views and point-in-time visibility can’t connect the dots to deliver the end-goal: the ability to spot real-time threats.

Darktrace/Cloud delivers meaningful insight into vulnerabilities and misconfigurations, but its real-time understanding also enables detection of emerging threats. And combining with other Darktrace modules like Darktrace/Network and Darktrace/Email, it enriches these findings with business context to find and shut down emerging threats in seconds. This business-wide context to understand your cloud footprint and how it interacts with your on-premises infrastructure, endpoints, and applications

Step 3: Response must be truly autonomous

By understanding your unique cloud footprint within the context of your own business, Darktrace/Cloud uniquely detects when something unusual is occurring that requires a response right now.

The use of AI to understand your environment enables a truly autonomous and precise cloud-native response. The platform can take targeted action to stop only the threatening behaviors as they appear, without disrupting regular business operations.

Because the platform understands your complete cloud architecture, it also knows what cloud-native mechanisms are at its disposal to initiate a real response. Automated real-time responses include cloud-native actions like detaching EC2 instances and applying security groups to contain risky assets.

See it in action

Darktrace is offering 30-day free trials of Darktrace/Cloud that combine easy install with unprecedented understanding of multi-cloud environments. Click here to register your interest and experience the benefits first-hand.

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
Nabil Zoldjalali
VP, Technology Innovation

Based in Toronto, Nabil develops innovative ways to continuously realize the Darktrace technology vision, working closely with Darktrace’s Research & Development team. He advises strategic Fortune 500 customers across North America on advanced threat detection, Self-Learning AI, and Autonomous Response. Nabil is a frequent speaker at leading industry conferences across North America, including Microsoft Ignite, Black Hat, and the World AI Forum. He holds a Bachelor’s degree in Electrical and Electronic Engineering from McGill University and is an advisory board member of the EC Council.

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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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