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April 9, 2024

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

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).
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Mitchell Bezzina
VP, Product and Solutions Marketing
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09
Apr 2024

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.
Written by
Mitchell Bezzina
VP, Product and Solutions Marketing

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Identity

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July 3, 2025

Top Eight Threats to SaaS Security and How to Combat Them

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The latest on the identity security landscape

Following the mass adoption of remote and hybrid working patterns, more critical data than ever resides in cloud applications – from Salesforce and Google Workspace, to Box, Dropbox, and Microsoft 365.

On average, a single organization uses 130 different Software-as-a-Service (SaaS) applications, and 45% of organizations reported experiencing a cybersecurity incident through a SaaS application in the last year.

As SaaS applications look set to remain an integral part of the digital estate, organizations are being forced to rethink how they protect their users and data in this area.

What is SaaS security?

SaaS security is the protection of cloud applications. It includes securing the apps themselves as well as the user identities that engage with them.

Below are the top eight threats that target SaaS security and user identities.

1.  Account Takeover (ATO)

Attackers gain unauthorized access to a user’s SaaS or cloud account by stealing credentials through phishing, brute-force attacks, or credential stuffing. Once inside, they can exfiltrate data, send malicious emails, or escalate privileges to maintain persistent access.

2. Privilege escalation

Cybercriminals exploit misconfigurations, weak access controls, or vulnerabilities to increase their access privileges within a SaaS or cloud environment. Gaining admin or superuser rights allows attackers to disable security settings, create new accounts, or move laterally across the organization.

3. Lateral movement

Once inside a network or SaaS platform, attackers move between accounts, applications, and cloud workloads to expand their foot- hold. Compromised OAuth tokens, session hijacking, or exploited API connections can enable adversaries to escalate access and exfiltrate sensitive data.

4. Multi-Factor Authentication (MFA) bypass and session hijacking

Threat actors bypass MFA through SIM swapping, push bombing, or exploiting session cookies. By stealing an active authentication session, they can access SaaS environments without needing the original credentials or MFA approval.

5. OAuth token abuse

Attackers exploit OAuth authentication mechanisms by stealing or abusing tokens that grant persistent access to SaaS applications. This allows them to maintain access even if the original user resets their password, making detection and mitigation difficult.

6. Insider threats

Malicious or negligent insiders misuse their legitimate access to SaaS applications or cloud platforms to leak data, alter configurations, or assist external attackers. Over-provisioned accounts and poor access control policies make it easier for insiders to exploit SaaS environments.

7. Application Programming Interface (API)-based attacks

SaaS applications rely on APIs for integration and automation, but attackers exploit insecure endpoints, excessive permissions, and unmonitored API calls to gain unauthorized access. API abuse can lead to data exfiltration, privilege escalation, and service disruption.

8. Business Email Compromise (BEC) via SaaS

Adversaries compromise SaaS-based email platforms (e.g., Microsoft 365 and Google Workspace) to send phishing emails, conduct invoice fraud, or steal sensitive communications. BEC attacks often involve financial fraud or data theft by impersonating executives or suppliers.

BEC heavily uses social engineering techniques, tailoring messages for a specific audience and context. And with the growing use of generative AI by threat actors, BEC is becoming even harder to detect. By adding ingenuity and machine speed, generative AI tools give threat actors the ability to create more personalized, targeted, and convincing attacks at scale.

Protecting against these SaaS threats

Traditionally, security leaders relied on tools that were focused on the attack, reliant on threat intelligence, and confined to a single area of the digital estate.

However, these tools have limitations, and often prove inadequate for contemporary situations, environments, and threats. For example, they may lack advanced threat detection, have limited visibility and scope, and struggle to integrate with other tools and infrastructure, especially cloud platforms.

AI-powered SaaS security stays ahead of the threat landscape

New, more effective approaches involve AI-powered defense solutions that understand the digital business, reveal subtle deviations that indicate cyber-threats, and action autonomous, targeted responses.

[related-resource]

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About the author
Carlos Gray
Senior Product Marketing Manager, Email

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July 2, 2025

Pre-CVE Threat Detection: 10 Examples Identifying Malicious Activity Prior to Public Disclosure of a Vulnerability

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Vulnerabilities are weaknesses in a system that can be exploited by malicious actors to gain unauthorized access or to disrupt normal operations. Common Vulnerabilities and Exposures (or CVEs) are a list of publicly disclosed cybersecurity vulnerabilities that can be tracked and mitigated by the security community.

When a vulnerability is discovered, the standard practice is to report it to the vendor or the responsible organization, allowing them to develop and distribute a patch or fix before the details are made public. This is known as responsible disclosure.

With a record-breaking 40,000 CVEs reported for 2024 and a predicted higher number for 2025 by the Forum for Incident Response and Security Teams (FIRST) [1], anomaly-detection is essential for identifying these potential risks. The gap between exploitation of a zero-day and disclosure of the vulnerability can sometimes be considerable, and retroactively attempting to identify successful exploitation on your network can be challenging, particularly if taking a signature-based approach.

Detecting threats without relying on CVE disclosure

Abnormal behaviors in networks or systems, such as unusual login patterns or data transfers, can indicate attempted cyber-attacks, insider threats, or compromised systems. Since Darktrace does not rely on rules or signatures, it can detect malicious activity that is anomalous even without full context of the specific device or asset in question.

For example, during the Fortinet exploitation late last year, the Darktrace Threat Research team were investigating a different Fortinet vulnerability, namely CVE 2024-23113, for exploitation when Mandiant released a security advisory around CVE 2024-47575, which aligned closely with Darktrace’s findings.

Retrospective analysis like this is used by Darktrace’s threat researchers to better understand detections across the threat landscape and to add additional context.

Below are ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

Trends in pre-cve exploitation

Often, the disclosure of an exploited vulnerability can be off the back of an incident response investigation related to a compromise by an advanced threat actor using a zero-day. Once the vulnerability is registered and publicly disclosed as having been exploited, it can kick off a race between the attacker and defender: attack vs patch.

Nation-state actors, highly skilled with significant resources, are known to use a range of capabilities to achieve their target, including zero-day use. Often, pre-CVE activity is “low and slow”, last for months with high operational security. After CVE disclosure, the barriers to entry lower, allowing less skilled and less resourced attackers, like some ransomware gangs, to exploit the vulnerability and cause harm. This is why two distinct types of activity are often seen: pre and post disclosure of an exploited vulnerability.

Darktrace saw this consistent story line play out during several of the Fortinet and PAN OS threat actor campaigns highlighted above last year, where nation-state actors were seen exploiting vulnerabilities first, followed by ransomware gangs impacting organizations [2].

The same applies with the recent SAP Netweaver exploitations being tied to a China based threat actor earlier this spring with subsequent ransomware incidents being observed [3].

Autonomous Response

Anomaly-based detection offers the benefit of identifying malicious activity even before a CVE is disclosed; however, security teams still need to quickly contain and isolate the activity.

For example, during the Ivanti chaining exploitation in the early part of 2025, a customer had Darktrace’s Autonomous Response capability enabled on their network. As a result, Darktrace was able to contain the compromise and shut down any ongoing suspicious connectivity by blocking internal connections and enforcing a “pattern of life” on the affected device.

This pre-CVE detection and response by Darktrace occurred 11 days before any public disclosure, demonstrating the value of an anomaly-based approach.

In some cases, customers have even reported that Darktrace stopped malicious exploitation of devices several days before a public disclosure of a vulnerability.

For example, During the ConnectWise exploitation, a customer informed the team that Darktrace had detected malicious software being installed via remote access. Upon further investigation, four servers were found to be impacted, while Autonomous Response had blocked outbound connections and enforced patterns of life on impacted devices.

Conclusion

By continuously analyzing behavioral patterns, systems can spot unusual activities and patterns from users, systems, and networks to detect anomalies that could signify a security breach.

Through ongoing monitoring and learning from these behaviors, anomaly-based security systems can detect threats that traditional signature-based solutions might miss, while also providing detailed insights into threat tactics, techniques, and procedures (TTPs). This type of behavioral intelligence supports pre-CVE detection, allows for a more adaptive security posture, and enables systems to evolve with the ever-changing threat landscape.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO), Emma Fougler (Global Threat Research Operations Lead), Ryan Traill (Analyst Content Lead)

References and further reading:

  1. https://www.first.org/blog/20250607-Vulnerability-Forecast-for-2025
  2. https://cloud.google.com/blog/topics/threat-intelligence/fortimanager-zero-day-exploitation-cve-2024-47575
  3. https://thehackernews.com/2025/05/china-linked-hackers-exploit-sap-and.html

Related Darktrace blogs:

*Self-reported by customer, confirmed afterwards.

**Updated January 2024 blog now reflects current findings

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