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December 7, 2017

Darktrace: Investigating Widespread Trojan Infections

Discover how Darktrace expedites the investigation of widespread Trojan infections, enhancing cybersecurity and response times.
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
Max Heinemeyer
Global Field CISO
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07
Dec 2017

This blog post outlines how Darktrace helps security operations centre (SOC) teams become more efficient by drastically cutting down the time needed to investigate incidents. This is illustrated by an example encountered in a recent Proof of Value where over 350 client devices had been infected by a stealthy banking trojan.

Identifying and investigating a compromise of this size would usually take a SOC team several hours if not days using disparate traditional security tools. Employing Darktrace, the most important questions were answered within 90 minutes. The main reason for this is that Darktrace provides full visibility and context into network activity for all devices monitored on a single, unified platform.

Alert fatigue & the cyber security skill gap

Getting cyber security right is difficult and time-consuming. Complexity is one of the main challenges the cyber security community is facing. These days, networks are only vaguely defined with digital supply chains, outsourcing, the push into the cloud and the advent of micro-virtualisation like Docker. The amount of data stored, devices connected to internal networks, connections made by devices and the heterogeneity in IT adds to this complexity. Managing it is difficult at best and securing it with traditional tools can be a daunting task.

Our industry is struggling with what has been labelled the ‘cyber security skill gap’. The demand for skilled, experienced security practitioners consistently outstrips supply. SOC teams struggle to find the right people for the job and to keep their analysts motivated in the face of a rapidly evolving threat landscape. Alert fatigue and burnout are common symptoms for SOC analysts working long hours and graveyard shifts.

Investigation methodology

Any incident responder will always begin by asking some high-level questions concerning the incident under investigation – regardless of it being an adware infection, a banking trojan, ransomware, an active intrusion or any other form of cyber security incident.

The most important questions usually are:

  • How did the infection occur? (To prevent the same initial infection vector in the future)
  • What behavior is the infected device exhibiting? (To understand the threat and the risk of the infection)
  • What Indicators of Compromise (IoC) are seen? (To update other security tools and to use for further investigation)
  • Are other devices infected as well? (To assess the extent of the infection)

We did a recent Proof of Value with an IT service provider in EMEA. Darktrace entered an environment which had already succumbed to a widespread compromise – over 350 client devices had been infected with banking trojans. Let’s walk through how we identified, triaged and investigated this infection using Darktrace.

Identifying the incident

Darktrace came into the environment after the initial infection had taken place already. Darktrace instantly identified several devices exhibiting unexpected HTTP beaconing to unusual, rare external IP addresses. The devices made HTTP POST requests without prior GET requests along other suspicious behavior. Darktrace created several high-severity alerts for this, e.g. ‘Compromise / Suspicious HTTP Beacons to Dotted Quad’ and ‘Compromise / Possible Malware HTTP Comms’:

Figure 1: Example Darktrace alert.

Triaging the incident

Darktrace then provides context around this alert - e.g. the external IP the beaconing was made to, the internal device including the associated user, and the suspicious behavior:

Figure 2: Detection context and C2 IP.

A quick investigation of the external IP reveals that it is a recently discovered command and control (C2) IP address for the Dridex banking trojan.

Drilling deeper into this, Darktrace provides PCAPs for every connection seen. A PCAP for the C2 connection above confirms this incident as active, successful, encoded beaconing to a malicious C2 IP:

Figure 3: PCAP and encoded HTTP POSTs.

Investigating the incident

At this stage, we want to further examine the behavior of the infected device around the time of the incident. Darktrace provides full visibility into past activity, including all network connection made by any device - regardless of whether the incident occurred on the device or not.

We attend to all external connections made by the infected device around the time of the incident and immediately identify more suspicious C2 communication:

Figure 4: More device behavior; further C2 IPs.

By now we have identified 6 different C2 IP addresses.

We can use Darktrace’s ‘External Sites Summary’ to view all devices that have connected to a specific IP or domain in the recent past. Doing this for the initial C2 IP yields the following result (excerpt):

Figure 5: External Sites Summary; further infections.

We immediately identify 5 additional devices that made successful connections to the C2 IP address. In fact, the list above is abridged as we actually saw over 350 devices connecting to this and other C2 IP addresses. Notably, all observed devices appear to have a similar naming structure - this will become important in the next part of the analysis.

At this point we have answered all but the first question: ‘How did the infection occur?’

Darktrace started monitoring the network after the initial infection occurred and spread. Further research into the C2 IP addresses shows that they are associated with the Emotet trojan. This sophisticated malware often precedes banking trojan (e.g. Dridex) infections and is spread via phishing. We can thus assume that phishing was a likely initial infection vector.

How then did the infection manage to spread to so many devices?

Surely not all users clicked on suspicious phishing emails? Recent versions of Emotet have limited lateral movement capabilities. They mainly propagate via SMB brute forcing - trying administrative accounts and hard-coded password lists. The naming convention on the infected devices is very similar - this could indicate a similar build-process and setup of the devices. If a vulnerability - such as an administrative account with a weak password - existed on one of the devices, it might be present in all of the devices with a similar build.

Using Darktrace, the security team has now a solid understanding of the nature and size of the infection, the IoCs available to update firewalls and other preventive security controls and outstanding remediation-activities.

What would this investigation look like with traditional tools, not using Darktrace?

Detecting these covert banking trojans in the first place, let alone triaging them fully, can be a difficult challenge in itself. Current banking Trojan strains such as Dridex, Fedeo or Vawtrak keep updating the malware with new C2 addresses to avoid blacklisting. Initial detection could be at any stage of the attack lifecycle – likely it will be in the latter stages though, when considerable damage has already been done.

An analyst will have to log into various security devices to get close to the same level of visibility provided in Darktrace – web proxy logs, anti-virus logs, running PCAPs on infected hosts, SIEM logs. Having to switch between all those disparate security tools is not time-efficient and produces a fragmentary picture of what actually transpired.

Conclusion

A working hypothesis is that a single device was initially infected via phishing, allowing Emotet to spread to over 350 internal devices via SMB brute forcing. It took no longer than 90 minutes to come from an initial detection of the incident to this conclusion, which forms the basis for an actionable report.

The last thing a SOC needs is yet another tool producing a profusion of alerts. Using Darktrace’s machine learning and unrivalled network visibility, you can focus on the small set of relevant alerts and rapidly investigate those incidents according to their severity and priority.

Darktrace can reduce costs even if you bring in a third-party incident response team. You will be able to significantly speed up their ongoing investigation if they have access to Darktrace. Third-party incident response teams are expensive – their daily rates ranging between £2,000 and £3,000 per day. Cutting their work down from days to hours will result in cost and efforts saved.

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
Max Heinemeyer
Global Field CISO

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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.

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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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