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Cloud

Illuminer les environnements de cloud AWS avec Darktrace Cyber AI

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21
May 2020
21
May 2020
This blog post explains how enterprise-wide and real-time analysis enables self-learning AI to uniquely detect and investigate threats in AWS environments at an early stage.

Cloud platforms transform the way we build digital infrastructure, allowing us to create incredibly innovative environments for business – but often, it’s at the cost of visibility and control.

With complex hybrid and multi-cloud infrastructures becoming an essential part of increasingly diverse digital estates, the journey to the cloud has fundamentally reshaped the traditional paradigm of the network perimeter, while expanding the attack surface at an alarming rate. Meanwhile, traditional security controls still only offer point solutions that rely on retrospective rules and threat signatures and fail to stop novel and advanced attacks.

To shoulder the weight of shared responsibility for cloud security, organizations require the approach offered by Darktrace DETECT & RESPOND. With Self-Learning AI, DETECT continuously learns what normal ‘patterns of life’ look like for every user, device, virtual machine, and container across an organization. By actively developing a bespoke understanding of ‘self,’ the DETECT can identify the subtle anomalies that point to an advanced attack, without any pre-defined assumptions of ‘good’ or ‘bad' and RESPOND can autonomously interfere to stop emerging threats without disrupting business operations.

As more and more businesses turn to AWS to leverage the benefits of cloud infrastructure, gaining visibility and security for AWS-hosted data and applications is absolutely crucial. The advent of AWS VPC traffic mirroring has allowed Darktrace to shine a light on blind spots in our customers’ AWS environments, ensuring that our Cyber AI security platform can stop any type of threat that emerges. With the AI-powered security securing your AWS environment, you can embrace all the benefits of the cloud with confidence.

Self-learning Cyber AI with granular, real-time visibility

VPC traffic mirroring gives our Self-Learning AI access to granular packet data, allowing DETECT to extract hundreds of features from the raw data and build rich behavioral models for our customers’ AWS cloud environments. This real-time visibility to the underlying fabric of AWS environments provided by VPC traffic mirroring helps Darktrace Cyber AI learn ‘on the job,’ continuously adapting as your business evolves. Darktrace provides the only security solution that learns in real time, a critical feature given the speed and scale of development in the cloud.

Unified control: Correlating patterns across infrastructure

Taking a fundamentally unique approach, DETECT actively correlates activity across AWS and beyond – whether your digital ecosystem includes other cloud environments, SaaS applications, or any range of on- and off-premise infrastructure. From a threat detection perspective, this is crucial, as security events detected in one part of an organization are often part of a broader security incident. This ensures that threats in the cloud are not siloed from monitoring of the rest of the infrastructure, nor are the implications for cloud security ignored when intrusions occur elsewhere in the network.

Neutralizing sophisticated and novel attacks

Legacy security controls miss novel and advanced attacks targeting cloud infrastructure. With VPC traffic mirroring supporting Darktrace Cyber AI’s understanding of an organization’s AWS environment, any slight changes from normal behavior that may indicate a potential threat can be detected immediately. This allows the DETECT to catch the full range of cloud-based attacks, from zero-day malware, to stealthy insider threats.

“Darktrace represents a new frontier in AI-based cyber defense. Our team now has complete real-time coverage across our SaaS applications and cloud containers.”

— CIO, City of Las Vegas

How it works: Using VPC traffic mirroring to analyze AWS traffic

For customers leveraging AWS within an IaaS model, Darktrace uses VPC traffic mirroring to collect metadata from mirrored VPC packets in a Darktrace probe known as a ‘vSensor’. The vSensor captures real-time traffic and selectively forwards relevant metadata to a Darktrace cloud instance or on-premise probe. From here, DETECT correlates VPC traffic with cloud, email, network, and SaaS traffic across a customer’s hybrid and multi-cloud infrastructure for analysis.

By utilizing VPC traffic mirroring in this way, the Immune System can perform deep packet inspection on traffic in the customer’s AWS cloud environment, up to and including the application layer. Hundreds of features are extracted from the raw data, ranging from high-level metrics of data flow quantities, to peer relationship meta-data, to specific application layer events. These features allow Darktrace Cyber AI to build rich behavioral models that let it understand normal patterns of life for the organization and detect malicious activity. It is important that Darktrace is able to construct these metrics from the raw data rather than relying on flow logs alone, as flow logs don't provide the required level of granularity or real-time events within connections.

For non-Nitro AWS instances, we deploy lightweight agents known as ‘OS-Sensors’ that feed relevant traffic to a local vSensor and, in turn, to a Darktrace cloud instance or on-premise probe. Once configured, OS-Sensors can easily be scaled as new instances are spun up. Darktrace also offers a specialized OS-Sensor that provides coverage in containerized systems like Docker and Kubernetes.

Richer context with AWS CloudTrail logs

In addition to analyzing data with VPC traffic mirroring, the DETECT also monitors management and data events within AWS. It does so via HTTP requests for logfiles generated by AWS CloudTrail, which monitors events from all AWS services, including:

  • EC2
  • IAM
  • S3
  • VPC
  • Lambda

Different event types produced via CloudTrail are organized by Darktrace into categories based on the action type and the AWS services that generate it. These different categories show up as metrics in the DETECT user interface, the Threat Visualizer. This information is used to provide even richer context in connection with mirrored traffic in VPCs, as well as all cloud, network, email, and SaaS traffic across a customer’s entire digital environment.

Darktrace deployment scenarios for AWS customers

For IaaS environments, Darktrace deploys a vSensor in each cloud environment. Within AWS environments, the vSensor captures real-time traffic with AWS VPC traffic mirroring. The receiving vSensor processes the data and feeds it back to the cloud-based Darktrace instance. AWS customers additionally have the option of deploying a ‘Darktrace Security Module’ to monitor IaaS management and data events at the API level, such as logins, editing virtual servers, or creating new access credentials.

Figure 1: A cloud-only deployment scenario — Darktrace manages a master cloud probe which receives traffic from sensors and connectors in IaaS and/or SaaS environments.

For hybrid IaaS deployments, Darktrace will similarly deploy vSensors, and OS-Sensors as appropriate. Cloud traffic and event data from AWS and any other cloud environments is then fed to a Darktrace probe in the cloud or on-premise network. For the latter scenario, Darktrace will deploy a physical appliance that ingests real-time network traffic via a SPAN port or network tap, allowing it to correlate patterns across the entire digital ecosystem.

Figure 2: A hybrid cloud deployment scenario, with multi-cloud infrastructure across AWS, Azure and GCP

For hybrid SaaS deployments, Darktrace will deploy provider-specific Darktrace Security Modules on either a physical or cloud-based Darktrace probe, in addition to any other relevant vSensors and OS-Sensors in place. SaaS data is then analyzed and correlated with traffic and user behaviors across AWS, other cloud environments, and any on- and off- premise cyber-physical infrastructure.

Figure 3: A hybrid SaaS deployment scenario

Defense against the full range of threats in the cloud

With the deep insight and powerful reaction capabilities of Cyber AI, Darktrace DETECT & RESPOND are the only proven technologies to stop the full range of cyber-threats in the cloud, including:

  • Critical misconfigurations
  • Insider threat
  • Compromised credentials
  • Novel and advanced malware
  • Password brute-force attacks
  • Data exfiltration
  • Lateral movement
  • Man-in-the-middle attacks
  • Crypto-jacking
  • Violations of policy

Case Studies

Crypto mining malware inadvertently installed

Darktrace detected a mistake from a junior DevOps engineer in a multinational organization with workloads across AWS and Azure and leveraging containerized systems like Docker and Kubernetes. The engineer accidentally downloaded an update that included a crypto miner, which led to an infection across multiple cloud production systems.

After the initial infection, the malware started beaconing out to an external command and control server, which was immediately picked up by Darktrace. With the external connection established and the attack mission instructions delivered, the crypto malware infection was then able to rapidly spread across the organization’s expansive cloud infrastructure at machine speed, infecting 20 cloud servers in under 15 seconds.

Extensive visibility into the organization’s AWS environment via VPC traffic mirroring was a key factor allowing Darktrace Cyber AI to identify the scale of the attack. With the dynamic and unified view across the company’s sprawling hybrid and multi-cloud infrastructure provided by Darktrace, the company’s security team was able to contain the attack within minutes, rather than hours or days. Even though the attack moved at machine speed, by leveraging solutions like VPC traffic mirroring to continuously analyze behavior in the cloud, Darktrace caught the threat at an early enough stage – well before the costs could start to mount.

Developer misuse of AWS cloud infrastructure

At an insurance group, a DevOps Engineer was attempting to build a parallel back-up infrastructure within AWS to replicate the organization’s data center production systems. The technical implementation was perfect, and the back-up systems were created – however, the cost of running the system would have been several million dollars per year.

The DevOps Engineer was unaware of the costs associated with the project and kept management in the dark. The cloud infrastructure was launched, and the costs started rising. Yet with real-time access to the company’s AWS environment provided by VPC traffic mirroring, Darktrace’s Cyber AI was immediately alerted to this unusual behavior, allowing the security team to take preventative action immediately.

With Darktrace Cyber AI, embrace the benefits of AWS

As organizations increasingly turn to the cloud and the threat surface continues to expand, security teams need self-learning AI on their side to gain the strongest insights, illuminate every blind spot, and stop all attacks.

By providing an enterprise-wide Cyber AI platform, Darktrace helps teams overcome the traditional security challenge of manually piecing together incidents across disparate corners of an organization. The unified visibility and control offered by Darktrace PREVENT, DETECTRESPOND, & HEAL reduces the complexity and dashboard fatigue that many teams continue to struggle with, while the system’s multi-dimensional insight enhances its decision-making and threat confidence. Darktrace further augments this process with the Immune System’s AI Analyst capability, which takes the additional step of automatically investigating threats detected by Darktrace and producing concise, AI-generated reports that communicate the full scope of an incident.

With the granular, real-time visibility of VPC traffic mirroring Darktrace, you can be certain your AWS cloud environments are always protected.

DANS LE SOC
Darktrace sont des experts de classe mondiale en matière de renseignement sur les menaces, de chasse aux menaces et de réponse aux incidents. Ils fournissent une assistance SOC 24 heures sur 24 et 7 jours sur 7 à des milliers de clients Darktrace dans le monde entier. Inside the SOC est exclusivement rédigé par ces experts et fournit une analyse des cyberincidents et des tendances en matière de menaces, basée sur une expérience réelle sur le terrain.
AUTEUR
à propos de l'auteur
Andrew Tsonchev
VP of Technology

Andrew is a technical expert on cyber security and advises Darktrace’s strategic customers on advanced threat defense, AI and autonomous response. He has a background in threat analysis and research, and holds a first-class degree in physics from Oxford University and a first-class degree in philosophy from King’s College London. His comments on cyber security and the threat to critical national infrastructure have been reported in international media, including CNBC and the BBC World.

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A l'intérieur du SOC

Sliver C2: How Darktrace Provided a Sliver of Hope in the Face of an Emerging C2 Framework

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17
Apr 2024

Offensive Security Tools

As organizations globally seek to for ways to bolster their digital defenses and safeguard their networks against ever-changing cyber threats, security teams are increasingly adopting offensive security tools to simulate cyber-attacks and assess the security posture of their networks. These legitimate tools, however, can sometimes be exploited by real threat actors and used as genuine actor vectors.

What is Sliver C2?

Sliver C2 is a legitimate open-source command-and-control (C2) framework that was released in 2020 by the security organization Bishop Fox. Silver C2 was originally intended for security teams and penetration testers to perform security tests on their digital environments [1] [2] [5]. In recent years, however, the Sliver C2 framework has become a popular alternative to Cobalt Strike and Metasploit for many attackers and Advanced Persistence Threat (APT) groups who adopt this C2 framework for unsolicited and ill-intentioned activities.

The use of Sliver C2 has been observed in conjunction with various strains of Rust-based malware, such as KrustyLoader, to provide backdoors enabling lines of communication between attackers and their malicious C2 severs [6]. It is unsurprising, then, that it has also been leveraged to exploit zero-day vulnerabilities, including critical vulnerabilities in the Ivanti Connect Secure and Policy Secure services.

In early 2024, Darktrace observed the malicious use of Sliver C2 during an investigation into post-exploitation activity on customer networks affected by the Ivanti vulnerabilities. Fortunately for affected customers, Darktrace DETECT™ was able to recognize the suspicious network-based connectivity that emerged alongside Sliver C2 usage and promptly brought it to the attention of customer security teams for remediation.

How does Silver C2 work?

Given its open-source nature, the Sliver C2 framework is extremely easy to access and download and is designed to support multiple operating systems (OS), including MacOS, Windows, and Linux [4].

Sliver C2 generates implants (aptly referred to as ‘slivers’) that operate on a client-server architecture [1]. An implant contains malicious code used to remotely control a targeted device [5]. Once a ‘sliver’ is deployed on a compromised device, a line of communication is established between the target device and the central C2 server. These connections can then be managed over Mutual TLS (mTLS), WireGuard, HTTP(S), or DNS [1] [4]. Sliver C2 has a wide-range of features, which include dynamic code generation, compile-time obfuscation, multiplayer-mode, staged and stageless payloads, procedurally generated C2 over HTTP(S) and DNS canary blue team detection [4].

Why Do Attackers Use Sliver C2?

Amidst the multitude of reasons why malicious actors opt for Sliver C2 over its counterparts, one stands out: its relative obscurity. This lack of widespread recognition means that security teams may overlook the threat, failing to actively search for it within their networks [3] [5].

Although the presence of Sliver C2 activity could be representative of authorized and expected penetration testing behavior, it could also be indicative of a threat actor attempting to communicate with its malicious infrastructure, so it is crucial for organizations and their security teams to identify such activity at the earliest possible stage.

Darktrace’s Coverage of Sliver C2 Activity

Darktrace’s anomaly-based approach to threat detection means that it does not explicitly attempt to attribute or distinguish between specific C2 infrastructures. Despite this, Darktrace was able to connect Sliver C2 usage to phases of an ongoing attack chain related to the exploitation of zero-day vulnerabilities in Ivanti Connect Secure VPN appliances in January 2024.

Around the time that the zero-day Ivanti vulnerabilities were disclosed, Darktrace detected an internal server on one customer network deviating from its expected pattern of activity. The device was observed making regular connections to endpoints associated with Pulse Secure Cloud Licensing, indicating it was an Ivanti server. It was observed connecting to a string of anomalous hostnames, including ‘cmjk3d071amc01fu9e10ae5rt9jaatj6b.oast[.]live’ and ‘cmjft14b13vpn5vf9i90xdu6akt5k3pnx.oast[.]pro’, via HTTP using the user agent ‘curl/7.19.7 (i686-redhat-linux-gnu) libcurl/7.63.0 OpenSSL/1.0.2n zlib/1.2.7’.

Darktrace further identified that the URI requested during these connections was ‘/’ and the top-level domains (TLDs) of the endpoints in question were known Out-of-band Application Security Testing (OAST) server provider domains, namely ‘oast[.]live’ and ‘oast[.]pro’. OAST is a testing method that is used to verify the security posture of an application by testing it for vulnerabilities from outside of the network [7]. This activity triggered the DETECT model ‘Compromise / Possible Tunnelling to Bin Services’, which breaches when a device is observed sending DNS requests for, or connecting to, ‘request bin’ services. Malicious actors often abuse such services to tunnel data via DNS or HTTP requests. In this specific incident, only two connections were observed, and the total volume of data transferred was relatively low (2,302 bytes transferred externally). It is likely that the connections to OAST servers represented malicious actors testing whether target devices were vulnerable to the Ivanti exploits.

The device proceeded to make several SSL connections to the IP address 103.13.28[.]40, using the destination port 53, which is typically reserved for DNS requests. Darktrace recognized that this activity was unusual as the offending device had never previously been observed using port 53 for SSL connections.

Model Breach Event Log displaying the ‘Application Protocol on Uncommon Port’ DETECT model breaching in response to the unusual use of port 53.
Figure 1: Model Breach Event Log displaying the ‘Application Protocol on Uncommon Port’ DETECT model breaching in response to the unusual use of port 53.

Figure 2: Model Breach Event Log displaying details pertaining to the ‘Application Protocol on Uncommon Port’ DETECT model breach, including the 100% rarity of the port usage.
Figure 2: Model Breach Event Log displaying details pertaining to the ‘Application Protocol on Uncommon Port’ DETECT model breach, including the 100% rarity of the port usage.

Further investigation into the suspicious IP address revealed that it had been flagged as malicious by multiple open-source intelligence (OSINT) vendors [8]. In addition, OSINT sources also identified that the JARM fingerprint of the service running on this IP and port (00000000000000000043d43d00043de2a97eabb398317329f027c66e4c1b01) was linked to the Sliver C2 framework and the mTLS protocol it is known to use [4] [5].

An Additional Example of Darktrace’s Detection of Sliver C2

However, it was not just during the January 2024 exploitation of Ivanti services that Darktrace observed cases of Sliver C2 usages across its customer base.  In March 2023, for example, Darktrace detected devices on multiple customer accounts making beaconing connections to malicious endpoints linked to Sliver C2 infrastructure, including 18.234.7[.]23 [10] [11] [12] [13].

Darktrace identified that the observed connections to this endpoint contained the unusual URI ‘/NIS-[REDACTED]’ which contained 125 characters, including numbers, lower and upper case letters, and special characters like “_”, “/”, and “-“, as well as various other URIs which suggested attempted data exfiltration:

‘/upload/api.html?c=[REDACTED] &fp=[REDACTED]’

  • ‘/samples.html?mx=[REDACTED] &s=[REDACTED]’
  • ‘/actions/samples.html?l=[REDACTED] &tc=[REDACTED]’
  • ‘/api.html?gf=[REDACTED] &x=[REDACTED]’
  • ‘/samples.html?c=[REDACTED] &zo=[REDACTED]’

This anomalous external connectivity was carried out through multiple destination ports, including the key ports 443 and 8888.

Darktrace additionally observed devices on affected customer networks performing TLS beaconing to the IP address 44.202.135[.]229 with the JA3 hash 19e29534fd49dd27d09234e639c4057e. According to OSINT sources, this JA3 hash is associated with the Golang TLS cipher suites in which the Sliver framework is developed [14].

Conclusion

Despite its relative novelty in the threat landscape and its lesser-known status compared to other C2 frameworks, Darktrace has demonstrated its ability effectively detect malicious use of Sliver C2 across numerous customer environments. This included instances where attackers exploited vulnerabilities in the Ivanti Connect Secure and Policy Secure services.

While human security teams may lack awareness of this framework, and traditional rules and signatured-based security tools might not be fully equipped and updated to detect Sliver C2 activity, Darktrace’s Self Learning AI understands its customer networks, users, and devices. As such, Darktrace is adept at identifying subtle deviations in device behavior that could indicate network compromise, including connections to new or unusual external locations, regardless of whether attackers use established or novel C2 frameworks, providing organizations with a sliver of hope in an ever-evolving threat landscape.

Credit to Natalia Sánchez Rocafort, Cyber Security Analyst, Paul Jennings, Principal Analyst Consultant

Appendices

DETECT Model Coverage

  • Compromise / Repeating Connections Over 4 Days
  • Anomalous Connection / Application Protocol on Uncommon Port
  • Anomalous Server Activity / Server Activity on New Non-Standard Port
  • Compromis / Activité soutenue de balisage TCP vers un endpoint rare.
  • Compromise / Quick and Regular Windows HTTP Beaconing
  • Compromise / High Volume of Connections with Beacon Score
  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Compromise / Slow Beaconing Activity To External Rare
  • Compromise / HTTP Beaconing to Rare Destination
  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Large Number of Suspicious Failed Connections
  • Compromise / SSL or HTTP Beacon
  • Compromise / Possible Malware HTTP Comms
  • Compromise / Possible Tunnelling to Bin Services
  • Anomalous Connection / Low and Slow Exfiltration to IP
  • Device / New User Agent
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Numeric File Download
  • Anomalous Connection / Powershell to Rare External
  • Anomalous Server Activity / New Internet Facing System

List of Indicators of Compromise (IoCs)

18.234.7[.]23 - Destination IP - Likely C2 Server

103.13.28[.]40 - Destination IP - Likely C2 Server

44.202.135[.]229 - Destination IP - Likely C2 Server

References

[1] https://bishopfox.com/tools/sliver

[2] https://vk9-sec.com/how-to-set-up-use-c2-sliver/

[3] https://www.scmagazine.com/brief/sliver-c2-framework-gaining-traction-among-threat-actors

[4] https://github[.]com/BishopFox/sliver

[5] https://www.cybereason.com/blog/sliver-c2-leveraged-by-many-threat-actors

[6] https://securityaffairs.com/158393/malware/ivanti-connect-secure-vpn-deliver-krustyloader.html

[7] https://www.xenonstack.com/insights/out-of-band-application-security-testing

[8] https://www.virustotal.com/gui/ip-address/103.13.28.40/detection

[9] https://threatfox.abuse.ch/browse.php?search=ioc%3A107.174.78.227

[10] https://threatfox.abuse.ch/ioc/1074576/

[11] https://threatfox.abuse.ch/ioc/1093887/

[12] https://threatfox.abuse.ch/ioc/846889/

[13] https://threatfox.abuse.ch/ioc/1093889/

[14] https://github.com/projectdiscovery/nuclei/issues/3330

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About the author
Natalia Sánchez Rocafort
Cyber Security Analyst

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Email

Looking Beyond Secure Email Gateways with the Latest Innovations to Darktrace/Email

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09
Apr 2024

Organizations Should Demand More from their Email Security

In response to a more intricate threat landscape, organizations should view email security as a critical component of their defense-in-depth strategy, rather than defending the inbox alone with a traditional Secure Email Gateway (SEG). Organizations need more than a traditional gateway – that doubles, instead of replaces, the capabilities provided by native security vendor – and require an equally granular degree of analysis across all messaging, including inbound, outbound, and lateral mail, plus Teams messages.  

Darktrace/Email is the industry’s most advanced cloud email security, powered by Self-Learning AI. It combines AI techniques to exceed the accuracy and efficiency of leading security solutions, and is the only security built to elevate, not duplicate, native email security.  

With its largest update ever, Darktrace/Email introduces the following innovations, finally allowing security teams to look beyond secure email gateways with autonomous AI:

  • AI-augmented data loss prevention to stop the entire spectrum of outbound mail threats
  • an easy way to deploy DMARC quickly with AI
  • major enhancements to streamline SOC workflows and increase the detection of sophisticated phishing links
  • expansion of Darktrace’s leading AI prevention to lateral mail, account compromise and Microsoft Teams

What’s New with Darktrace/Email  

Data Loss Prevention  

Block the entire spectrum of outbound mail threats with advanced data loss prevention that builds on tags in native email to stop unknown, accidental, and malicious data loss

Darktrace understands normal at individual user, group and organization level with a proven AI that detects abnormal user behavior and dynamic content changes. Using this understanding, Darktrace/Email actions outbound emails to stop unknown, accidental and malicious data loss.  

Traditional DLP solutions only take into account classified data, which relies on the manual input of labelling each data piece, or creating rules to catch pattern matches that try to stop data of certain types leaving the organization. But in today’s world of constantly changing data, regular expression and fingerprinting detection are no longer enough.

  • Human error – Because it understands normal for every user, Darktrace/Email can recognize cases of misdirected emails. Even if the data is correctly labelled or insensitive, Darktrace recognizes when the context in which it is being sent could be a case of data loss and warns the user.  
  • Unclassified data – Whereas traditional DLP solutions can only take action on classified data, Darktrace analyzes the range of data that is either pending labels or can’t be labeled with typical capabilities due to its understanding of the content and context of every email.  
  • Insider threat – If a malicious actor has compromised an account, data exfiltration may still be attempted on encrypted, intellectual property, or other forms of unlabelled data to avoid detection. Darktrace analyses user behaviour to catch cases of unusual data exfiltration from individual accounts.

And classification efforts already in place aren’t wasted – Darktrace/Email extends Microsoft Purview policies and sensitivity labels to avoid duplicate workflows for the security team, combining the best of both approaches to ensure organizations maintain control and visibility over their data.

End User and Security Workflows

Achieve more than 60% improvement in the quality of end-user phishing reports and detection of sophisticated malicious weblinks1

Darktrace/Email improves end-user reporting from the ground up to save security team resource. Employees will always be on the front line of email security – while other solutions assume that end-user reporting is automatically of poor quality, Darktrace prioritizes improving users’ security awareness to increase the quality of end-user reporting from day one.  

Users are empowered to assess and report suspicious activity with contextual banners and Cyber AI Analyst generated narratives for potentially suspicious emails, resulting in 60% fewer benign emails reported.  

Out of the higher-quality emails that end up being reported, the next step is to reduce the amount of emails that reach the SOC. Darktrace/Email’s Mailbox Security Assistant automates their triage with secondary analysis combining additional behavioral signals – using x20 more metrics than previously – with advanced link analysis to detect 70% more sophisticated malicious phishing links.2 This directly alleviates the burden of manual triage for security analysts.

For the emails that are received by the SOC, Darktrace/Email uses automation to reduce time spent investigating per incident. 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. Analysts can take remediation actions from within Darktrace/Email, eliminating console hopping and accelerating incident response.

Darktrace takes a user-focused and business-centric approach to email security, in contrast to the attack-centric rules and signatures approach of secure email gateways

Microsoft Teams

Detect threats within your Teams environment such as account compromise, phishing, malware and data loss

Around 83% of Fortune 500 companies rely on Microsoft Office products and services, particularly Teams and SharePoint.3

Darktrace now leverages the same behavioral AI techniques for Microsoft customers across 365 and Teams, allowing organizations to detect threats and signals of account compromise within their Teams environment including social engineering, malware and data loss.  

The primary use case for Microsoft Teams protection is as a potential entry vector. While messaging has traditionally been internal only, as organizations open up it is becoming an entry vector which needs to be treated with the same level of caution as email. That’s why we’re bringing our proven AI approach to Microsoft Teams, that understands the user behind the message.  

Anomalous messaging behavior is also a highly relevant indicator of whether a user has been compromised. Unlike other solutions that analyze Microsoft Teams content which focus on payloads, Darktrace goes beyond basic link and sandbox analysis and looks at actual user behavior from both a content and context perspective. This linguistic understanding isn’t bound by the requirement to match a signature to a malicious payload, rather it looks at the context in which the message has been delivered. From this analysis, Darktrace can spot the early symptoms of account compromise such as early-stage social engineering before a payload is delivered.

Lateral Mail Analysis

Detect and respond to internal mailflow with multi-layered AI to prevent account takeover, lateral phishing and data leaks

The industry’s most robust account takeover protection now prevents lateral mail account compromise. Darktrace has always looked at internal mail to inform inbound and outbound decisions, but will now elevate suspicious lateral mail behaviour using the same AI techniques for inbound, outbound and Teams analysis.

Darktrace integrates signals from across the entire mailflow and communication patterns to determine symptoms of account compromise, now including lateral mailflow

Unlike other solutions which only analyze payloads, Darktrace analyzes a whole range of signals to catch lateral movement before a payload is delivered. Contributing yet another layer to the AI behavioral profile for each user, security teams can now use signals from lateral mail to spot the early symptoms of account takeover and take autonomous actions to prevent further compromise.

DMARC

Gain in-depth visibility and control of 3rd parties using your domain with an industry-first AI-assisted DMARC

Darktrace has created the easiest path to brand protection and compliance with the new Darktrace/DMARC. This new capability continuously stops spoofing and phishing from the enterprise domain, while automatically enhancing email security and reducing the attack surface.

Darktrace/DMARC helps to upskill businesses by providing step by step guidance and automated record suggestions provide a clear, efficient road to enforcement. It allows organizations to quickly achieve compliance with requirements from Google, Yahoo, and others, to ensure that their emails are reaching mailboxes.  

Meanwhile, Darktrace/DMARC helps to reduce the overall attack surface by providing visibility over shadow-IT and third-party vendors sending on behalf of an organization’s brand, while informing recipients when emails from their domains are sent from un-authenticated DMARC source.

Darktrace/DMARC integrates with the wider Darktrace product platform, sharing insights to help further secure your business across Email Attack Path and Attack Surface management.

Conclusion

To learn more about the new innovations to Darktrace/Email download the solution brief here.

All of the new updates to Darktrace/Email sit within the new Darktrace ActiveAI Security Platform, creating a feedback loop between email security and the rest of the digital estate for better protection. Click to read more about the Darktrace ActiveAI Security Platform or to hear about the latest innovations to Darktrace/OT, the most comprehensive prevention, detection, and response solution purpose built for critical infrastructures.  

Learn about the intersection of cyber and AI by downloading the State of AI Cyber Security 2024 report to discover global findings that may surprise you, insights from security leaders, and recommendations for addressing today’s top challenges that you may face, too.

References

[1] Internal Darktrace Research

[2] Internal Darktrace Research

[3] Essential Microsoft Office Statistics in 2024

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About the author
Carlos Gray
Product Manager
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