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Moving Beyond XDR to Achieve True Cyber Resilience with Darktrace ActiveAI Security Platform

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09
Apr 2024
09
Apr 2024
Announcing the new Darktrace ActiveAI Security Platform designed to transform security operations. This approach gives security teams unprecedented visibility across any area where Darktrace is deployed, including cloud, email, network, endpoints, and operational technology (OT).

Evolving Threats Need Comprehensive Security

Attacker innovations have drastically increased the velocity, sophistication, and success of cyber security attacks, as seen with multi-domain and multi-stage attacks that are now widely used in adversary methodology.

When it comes to defense, traditional cyber security point solutions cannot keep up. They have a depth of intelligence in a specific domain but rely on existing attack data to detect threats. This allows the known to be stopped, but the uncertainty in identifying unknown threats creates an alert deluge. Security teams are then required to build processes to triage alerts, and manually combine data through APIs, integrations and rules – just to correlate incidents across multiple IT domains.

Traditional eXtended Detection and Response (XDR) rose to aid security teams, and while they are able to stitch together suspicious events from network, endpoint, and cloud, they still lack adequate domain coverage in areas such as email – where the majority of initial infection occurs – require human validation, prioritization, and triage, and ultimately remain reactive in nature.

Security teams are at a breaking point, with too many alerts, too little time, and fragmented support from a bloated vendor stack. Simply put, most organizations lack the human resources needed to maintain cyber resilience.

Introducing the Darktrace ActiveAI Security Platform

Darktrace ActiveAI Security was designed to transform security operations to a proactive state. Its AI trains on an organization’s specific business and IT information, learning the day-to-day normal operations, not yesterday's threat intelligence.

This approach gives security teams unprecedented visibility across any area where Darktrace is deployed, including cloud, email, network, endpoints, identities, and operational technology (OT). With this understanding of the business, the AI can detect and respond to known and unknown threats with precision, even those threats never seen before.

Darktrace’s proactive and incident response tools help your team get ahead of security gaps and potential process risk by understanding your internal and external threat surfaces and identifying where preparedness can be improved.

A unique and patented investigative AI, called Cyber AI Analyst, operates across the platform to augment human teams with automation and efficiency gains, performing continuous investigations of prevalent alerts to redefine the SecOps workflow and help security analysts arrive at decisions quickly.  An extensive range of services aid customer resources in getting the most out of the Darktrace ActiveAI Security Platform.

Figure 1: Powered by a self-learning AI that understands your unique business, the Darktrace ActiveAI Security Platform provides coverage across the entire enterprise. Cyber AI Analyst, our investigative AI, investigates relevant alerts helping human security teams triage and prioritize all relevant alerts, even those from 3rd party security tools, to transform security operations.

Security operations and the incident lifecycle

SOC teams have three general areas of focus, and each can be supported by Darktrace ActiveAI Security

1. The benefits of being proactive

Darktrace ActiveAI Security helps teams become proactive by identifying and closing gaps before they are exploited. This reduces the impact and cost of attacks.  

The platform achieves this by looking at each organization to understand potential human and machine entry points for an attacker. In an upcoming update, our technology will also include firewall rule analysis for more precise attack path modeling.

The AI considers its findings with local business and IT context to identify the most risky and impactful devices, identities, and vulnerabilities, so teams can prioritize what to patch first.

Additionally, Darktrace ActiveAI Security boosts proactivity with incident readiness, supporting each organization’s people, processes, and technology with training simulations, dynamic playbooks, and readiness reports.

2. Complete visibility of known and novel threats

Darktrace ActiveAI Security Platform drives efficiencies during the active incident phase, saving time and effort while providing comprehensive and tailored protection. It applies context from enterprise data, ingested from both native sources (email, cloud, operational technology, endpoints, identity, applications, and networks) and external sources (third-party security tools and intelligence) to detect known, novel, and unknown threats.

Other security vendors aggregate and generalize data across their customers, treating threat detection with a big data approach. They extract intelligence, write new rules and signatures, and train their supervised machine running in the cloud. Only after that do they distribute new detections based on the changes in the threat landscape. That leaves a window of opportunity for attackers. For example, when Log4J struck, most vendors needed precious time to catch up and defend against it

Contrast that to Darktrace’s approach to detection. Our AI continuously trains on each organization’s unique business data, allowing it to function beyond known attacks in the threat landscape. Therefore, our AI can defend organizations even against attacks that have never been seen before because it focuses on each customer’s data instead of trying to win this big data problem.

While our AI has always been able to surface threats without needing to decrypt traffic, because it can surface anomalies in the characteristics of the overall communication, an upcoming update will soon make decryption possible for deeper forensic analysis.

This also leads to massive efficiency wins. For example, self-regulation and detection accuracy. If our AI keeps seeing certain types of anomalies in an environment, and if those are part of a legitimate business process, the AI will autonomously start lowering the alert severity, therefore reducing the burden on security teams to fine-tune detection and alerting.

3. AI-led investigation and response

Darktrace ActiveAI Security Platform helps teams triage, investigate, and respond to accelerate response time and reduce disruption.

Traditional security stacks use a lot of raw data combined with threat intelligence, like rules and signatures and supervised detections. The results are then put together and presented to the human team, who still needs to triage, understand, and investigate the situation.

Darktrace customers natively ingest raw data, apply anomaly detection and business learning, then build chains of generic anomalies which could include threat intelligence of third-party alerts. Those are then continuously investigated by our Cyber AI Analyst and put forward for human verification and actioning of next steps if they are deemed critical. This simplifies the triage process to save investigation time.

An upcoming feature for the Cyber AI Analyst allows teams to customize how it investigates each threat type, such as configuring what type of hypotheses are being run – giving teams more control. The result is a complete transformation of the triage process, where every relevant alert is investigated for the security team, those critical are prioritized for action, others await secondary investigation, or allow analysts to proactively review security gaps to stop future attacks of the same attack paths.

Last but not least, we help drive efficiencies by automating threat response with behavioral containment. That means our AI can identify and stop unusual behavior that indicates a threat while still allowing normal benign business activity to continue, all without the security team’s having to predefine every conceivable reaction.

Conclusion

Darktrace ActiveAI Security is a native, holistic, AI-driven platform built on over ten years of AI research. It helps security teams shift to more a productive mode, finding known and unknown attacks and transforming the SOC to drive efficiency gains. It does this across the whole incident lifecycle to lower risk, reduce time spent on active incidents, and drive return on investment.

For more information on the Darktrace Platform, download the solution brief here.

Join over 9,000 customers who have started their journey to the Darktrace ActiveAI Security Platform by selecting one of our leading cybersecurity solutions in Email Security, Network Detection and Response, Cloud Native Application Protection, and OT Security.

Discover more about our ever-strengthening platform with the upcoming changes coming to Darktrace/Email and Darktrace/OT.

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.

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.
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Mitchell Bezzina
VP, Product and Solutions Marketing
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The Price of Admission: Countering Stolen Credentials with Darktrace

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03
Jun 2024

Using leaked credentials to gain unauthorized access

Dark web marketplaces selling sensitive data have increased accessibility for malicious actors, similar to Ransomware-as-a-Service (RaaS), lowering the barrier to entry usually associated with malicious activity. By utilizing leaked credentials, malicious actors can easily gain unauthorized access to accounts and systems which they can leverage to carry out malicious activities like data exfiltration or malware deployment.

Usage of leaked credentials by malicious actors is a persistent concern for both organizations and security providers. Google Cloud’s ‘H1 2024 Threat Horizons Report’ details that initial access seen in 2.9% of cloud compromises observed on Google Cloud resulted from leaked credential usage [1], with the ‘IBM X-Force Threat Intelligence Index 2024’ reporting 71% year-on-year increase in cyber-attacks which utilize stolen or compromised credentials [2].

Darktrace coverage of leaked credentials

In early 2024, one Darktrace customer was compromised by a malicious actor after their internal credentials had been leaked on the dark web. Subsequent attack phases were detected by Darktrace/Network and the customer was alerted to the suspicious activity via the Proactive Threat Notification (PTN) service, following an investigation by Darktrace’s Security Operation Center (SOC).

Darktrace detected a device on the network of a customer in the US carrying out a string of anomalous activity indicative of network compromise. The device was observed using a new service account to authenticate to a Virtual Private Network (VPN) server, before proceeding to perform a range of suspicious activity including internal reconnaissance and lateral movement.

Malicious actors seemingly gained access to a previously unused service account for which they were able to set up multi-factor authentication (MFA) to access the VPN. As this MFA setup was made possible by the configuration of the customer’s managed service provider (MSP), the initial access phase of the attack fell outside of Darktrace’s purview.

Unfortunately for the customer in this case, Darktrace RESPOND™ was not enabled on the network at the time of the attack. Had RESPOND been active, it would have been able to autonomously act against the malicious activity by disabling users, strategically blocking suspicious connections and limiting devices to their expected patterns of activity.

Attack timeline of leaked credentials spotted by darktrace

Network Scanning Activity

On February 22, 2024, Darktrace detected the affected device performing activity indicative of network scanning, namely initiating connections on multiple ports, including ports 80, 161 389 and 445, to other internal devices. While many of these internal connection attempts were unsuccessful, some successful connections were observed.

Devices on a network can gather information about other internal devices by performing network scanning activity. Defensive scanning can be used to support network security, allowing internal security teams to discover vulnerabilities and potential entry points that require their attention, however attackers are also able to take advantage of such information, such as open ports and services available on internal devices, with offensive scanning.

Brute Force Login Attempts

Darktrace proceeded to identify the malicious actor attempting to access a previously unused service account for which they were able to successfully establish MFA to access the organization’s VPN. As the customer’s third-party MSP had been configured to allow all users to login to the organization’s VPN using MFA, this login was successful. Moreover, the service account had never previously been used and MFA and never been established, allowing the attacker to leverage it for their own nefarious means.

Darktrace/Network identified the attacker attempting to authenticate over the Kerberos protocol using a total of 30 different usernames, of which two were observed successfully authenticating. There was a total of 6 successful Kerberos logins identified from two different credentials.  Darktrace also observed over 100 successful NTLM attempts from the same device for multiple usernames including “Administrator” and “mail”. These credentials were later confirmed by the customer to have been stolen and leaked on the dark web.

Advanced Search query results showing the usernames that successfully authenticated via NTLM.
Figure 1: Advanced Search query results showing the usernames that successfully authenticated via NTLM.

Even though MFA requirements had been satisfied when the threat actor accessed the organization’s VPN, Darktrace recognized that this activity represented a deviation from its previously learned behavior.

Malicious actors frequently attempt to gain unauthorized access to accounts and internal systems by performing login attempts using multiple possible usernames and passwords. This type of brute-force activity is typically accomplished using computational power via the use of software or scripts to attempt different username/password combinations until one is successful.

By purchasing stolen credentials from dark web marketplaces, attackers are able to significantly increase the success rate of brute-force attacks and, if they do gain access, they can easily act on their objectives, be that exfiltrating sensitive data or moving through their target networks to further the compromise.

Share Enumeration

Around 30 minutes after the initial network scanning activity, the compromised device was observed performing SMB enumeration using one of the aforementioned accounts. Darktrace understood that this activity was suspicious as the device had never previously been used to perform SMB activity and had not been tagged as a security device.

Darktrace/Network identifying the suspicious SMB enumeration performed by the compromised device.
Figure 2: Darktrace/Network identifying the suspicious SMB enumeration performed by the compromised device.

Such enumeration can be used by malicious actors to gain insights into the structures and configurations of a target device, view permissions associated with shared resources, and also view general identifying information about the system.

Darktrace further identified that the device connected to the named pipe “srvsvc”. By enumerating over srvsvc, a threat actor is able to request a list of all available SMB shares on a destination device, enabling further data gathering as part of network reconnaissance. Srvsvc also provides access to remote procedure call (RPC) for various services on a destination device.

At this stage, a Darktrace/Network Enhanced Monitoring model was triggered for lateral movement activity taking place on the customer’s network. As this particular customer was subscribed to the PTN service, the Enhanced Monitoring model alert was promptly triaged and investigated by the Darktrace SOC. The customer was alerted to the emerging activity and given full details of the incident and the SOC team’s investigation.

Attack and Reconnaissance Tool Usage

A few minutes later, Darktrace observed the device making a connection with a user agent associated with the Nmap network scanning tool, “Mozilla/5.0 (compatible; Nmap Scripting Engine; https://nmap.org/book/nse[.]html)”. While these tools are often used legitimately by an organization’s security team, they can also be used maliciously by attackers to exploit vulnerabilities that attackers may have unearthed during earlier reconnaissance activity.

As such services are often seen as normal network traffic, attackers can often use them to bypass traditional security measures. Darktrace’s Self-Learning AI, however, was able to recognize that the affected device was not a security device and therefore not expected to carry out such activity, even if it was using a legitimate Nmap service.

Darktrace/Network identifying the compromised device using the Nmap scanning tool.
Figure 3: Darktrace/Network identifying the compromised device using the Nmap scanning tool.

Further Lateral Movement

Following this suspicious Nmap usage, Darktrace observed a range of additional anomalous SMB activity from the aforementioned compromised account. The affected device attempted to establish almost 900 SMB sessions, as well as performing 65 unusual file reads from 29 different internal devices and over 300 file deletes for the file “delete.me” from over 100 devices using multiple paths, including ADMIN$, C$, print$.

Darktrace also observed the device making several DCE-RPC connections associated with Active Directory Domain enumeration, including DRSCrackNames and DRSGetNCChanges; a total of more than 1000 successful DCE-RPC connection were observed to a domain controller.

As this customer did not have Darktrace/Network's autonomous response deployed on their network, the above detailed lateral movement and network reconnaissance activity was allowed to progress unfettered, until Darktrace’s SOC alerted the customer’s security team to take urgent action. The customer also received follow-up support through Darktrace’s Ask the Expert (ATE) service, allowing them to contact the analyst team directly for further details and support on the incident.

Thanks to this early detection, the customer was able to quickly identify and disable affected user accounts, effectively halting the attack and preventing further escalation.

Conclusions

Given the increasing trend of ransomware attackers exfiltrating sensitive data for double extortion and the rise of information stealers, stolen credentials are commonplace across dark web marketplaces. Malicious actors can exploit these leaked credentials to drastically lower the barrier to entry associated with brute-forcing access to their target networks.

While implementing well-configured MFA and enforcing regular password changes can help protect organizations, these measures alone may not be enough to fully negate the advantage attackers gain with stolen credentials.

In this instance, an attacker used leaked credentials to compromise an unused service account, allowing them to establish MFA and access the customer’s VPN. While this tactic may have allowed the attacker to evade human security teams and traditional security tools, Darktrace’s AI detected the unusual use of the account, indicating a potential compromise despite the organization’s MFA requirements being met. This underscores the importance of adopting an intelligent decision maker, like Darktrace, that is able to identify and respond to anomalies beyond standard protective measures.

Credit to Charlotte Thompson, Cyber Security Analyst, Ryan Traill, Threat Content Lead

Appendices

Darktrace DETECT Model Coverage

-       Device / Suspicious SMB Scanning Activity (Model Alert)

-       Device / ICMP Address Scan (Model Alert)

-       Device / Network Scan (Model Alert)

-       Device / Suspicious LDAP Search Operation (Model Alert)

-       User / Kerberos Username Brute Force (Model Alert)

-       Device / Large Number of Model Breaches (Model Alert)

-       Anomalous Connection / SMB Enumeration (Model Alert)

-       Device / Multiple Lateral Movement Model Breaches (Enhanced Monitoring Model Alert)

-       Device / Possible SMB/NTLM Reconnaissance (Model Alert)

-       Anomalous Connection / Possible Share Enumeration Activity (Model Alert)

-       Device / Attack and Recon Tools (Model Alert)

MITRE ATT&CK Mapping

Tactic – Technique - Code

INITIAL ACCESS - Hardware Additions     -T1200

DISCOVERY - Network Service Scanning -T1046

DISCOVERY - Remote System Discovery - T1018

DISCOVERY - Domain Trust Discovery      - T1482

DISCOVERY - File and Directory Discovery - T1083

DISCOVERY - Network Share Discovery - T1135

RECONNAISSANCE - Scanning IP Blocks - T1595.001

RECONNAISSANCE - Vulnerability Scanning - T1595.002

RECONNAISSANCE - Client Configurations - T1592.004

RECONNAISSANCE - IP Addresses - T1590.005

CREDENTIAL ACCESS - Brute Force - T1110

LATERAL MOVEMENT - Exploitation of Remote Services -T1210

References

  1. 2024 Google Cloud Threat Horizons Report
    https://services.google.com/fh/files/misc/threat_horizons_report_h12024.pdf
  2. IBM X-Force Threat Intelligence Index 2024
    https://www.ibm.com/reports/threat-intelligence
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About the author
Charlotte Thompson
Cyber Analyst

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Exploring the Benefits and Risks of Third-Party Data Solutions

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03
Jun 2024

Why do companies allow third parties to handle their data?

Companies seek out third parties to handle their data for operational efficiency.

The scale and cost of maintaining in-house infrastructure can be outsourced to third parties who specialize in data management or in certain business functions.

Third parties who handle an organization’s data can range from large public cloud providers such as Azure or AWS, to boutique companies who handle specific business functions such as telemarketing, payment systems, or webpage hosting.

The operational efficiencies gained through third-party data management can be summarized by three key benefits:

  • Global accessibility: Third-party data storage enables data access across the globe, allowing businesses to access data from anywhere.
  • Enhanced collaboration: Third-party data storage allows for file sharing, real-time editing, and integration with other applications and services enhancing a business’s collaboration efforts.
  • Reliability and uptime: Reputable third-party storage providers offer high reliability and uptime guarantees, ensuring that data is available whenever needed. They typically have robust disaster recovery and backup systems in place to prevent data loss.

Given these benefits, it is no surprise that businesses are using these services to expand their operations and scale efforts with the need of a growing business. This strategic move not only optimizes resource allocation but also enhances operational agility, enabling businesses to adapt swiftly to evolving data demands and maintain a competitive edge in a dynamic market.

Security risks of entrusted data to third-party vendors

Entrusting data to third parties can expose businesses to supply chain risks and increase the risk of data breaches and unauthorized access. A business has less control over its data and becomes dependent on the third party's policies, practices, and uptime. Many third-party vendors are the target of hackers who specialize in monetizing sensitive data and exploiting gray areas around who is responsible for securing the data.

Thus, businesses are vulnerable when they entrust sensitive data to third-party platforms, which often lack transparency about data usage and security. The platforms, chosen mainly for cost, efficiency, and user experience, are frequent targets for cyber criminals, hacktivists, and opportunistic lone hackers looking for sensitive data accidentally exposed due to misconfigurations or poor data management policies.

Consumers are putting pressure on businesses to improve cybersecurity when handling their personal data. Businesses who suffer a data breach face a high level of scrutiny from customers, investors, the media, and governments, even when the data breach is the result of a third party’s being hacked. For example, Uber made headlines in 2022 for a data breach which was the result of a compromised vendor who had access to data regarding Uber’s employees.

Similarly, the UK’s Ministry of Defence was the victim of a data breach earlier this year when hackers targeted a third party payroll system used by the government department.

Why do cyber-criminals target third parties?

Cyber-criminals can potentially gain access to multiple networks when targeting a third-party storage provider. A successful attack could give attackers access to the networks and systems of all its clients, amplifying the impact of a single breach.

For example, when Illuminate Education was the target of a cyber-attack, the data of 23 US School Districts was stolen via its student-tracking software. It included student data from the country's two largest school systems - New York City Public Schools and Los Angeles Unified School District.

Common third-party security risks

When collaborating with third parties, organizations should be aware of the most common types of security risks posed to their cybersecurity.

  • Software supply chain attacks: Software supply chain attacks occur when cyber criminals infiltrate and compromise software products or updates at any point in the development or distribution process. This allows attackers to insert malicious code into legitimate software, which then gets distributed to users through trusted channels.
  • Human error: Human error in cybersecurity refers to mistakes made by individuals that lead to security breaches or vulnerabilities. These errors can result from lack of awareness, insufficient training, negligence, or simple mistakes.
  • Privileged access misuse: Privileged access misuse involves the inappropriate or unauthorized use of elevated access rights by individuals within an organization. This can include intentionally malicious actions or unintentional misuse of administrative privileges.

What to look for in a security solution when using third parties to store or manage data

Understanding the security posture of a third party is important when partnering with it and entrusting it with your organization’s data. Understanding how basic cyber hygiene policies are implemented is a good place to start, such as data retention policies, use of encryption for data in storage, and how identity and access are managed.

In some circumstances, it is important to understand who is responsible for the data’s security. For example, when using public cloud infrastructure, it is generally the responsibility of the data owner to manage how the data is accessed and stored.

In that situation, an organization needs to ensure it has solutions in place which gives it full visibility of that third-party environment, and which can proactively identify misconfigurations and detect and respond to suspicious activity in real time.

Benefits of using AI tools to aid in managing sensitive data

According to research performed by IBM, organizations with extensive use of security AI and automation identified and contained a data breach 108 days faster in 2023 than organizations that did not use AI for cybersecurity. (1) This figure is only likely to improve as companies mature in their adoption of AI for cyber security and can be a key indicator in the security posture of a third-party vendor.

Example of third-party security incidents

Sumo data breach

Sumo, an Australian energy and internet provider, suffered a data breach which they became aware of on May 13th, 2024. Further investigation into the cyber incident has found that “the personal details of approximately 40,000 customers were compromised, including approximately 3,000 Australian passport numbers.” (2)

While none of Sumo’s systems were allegedly accessed or affected and the third-party application also worked as designed (3), the incident was blamed on an unnamed third party. The breach may have been the result of a misconfiguration or human error.

This incident underscores the importance of not only selecting third-party providers with robust security measures but also continuously monitoring and assessing their security practices.

How Darktrace helps monitor third-party data usage

Darktrace/Cloud uses Self-Learning AI to provide complete cyber resilience for multi-cloud environments.

Benefits of Darktrace/Cloud:

Architectural awareness: Gives users an understanding of their cloud footprint, including real-time visibility into cloud assets, architectures, users and permissions. Combines asset enumeration, modeled architectures, and flow log analysis. Cost insights give a better understanding of resource allocation, helping teams contextualize resources.

Cloud-native detection and response: AI understands ‘normal’ for your unique business and stops cyber-threats with autonomous response. Near-real-time response goes beyond simple email alerts or opening a ticket; and includes cloud-native actions like detaching EC2 instances and applying security groups to contain risky assets.

Cloud protection and compliance: Identify compliance issues and potential misconfigurations with attack path modeling and prioritized remediation steps. Darktrace’s attack surface management (ASM) adds a critical external view of your organization, highlighting vulnerabilities most impactful to your specific situation and revealing shadow IT.

Learn more about securing cloud environments by reading: The CISO’s Guide to Cloud Security here.

References

1.    https://www.ibm.com/reports/data-breach

2.    https://www.passports.gov.au/news/sumo-data-breach

3.    https://www.smh.com.au/technology/sumo-slammed-by-data-breach-as-energy-and-internet-customers-have-details-leaked-20240515-p5jdwp.html

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About the author
Oakley Cox
Analyst Technical Director, APAC
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