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November 3, 2022

Uncover New Malicious Email Payloads in Google Translate

Discover how threat actors are concealing malicious email payloads within Google Translate domains. Learn how Darktrace responds to these attacks effectively.
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
Rachel Resnekov
Cyber Analyst
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03
Nov 2022

Darktrace recently detected a new technique used by threat actors to deliver malicious email payloads. The malicious link was observed hidden within a legitimate domain, namely Google Translate services. To understand its abusive capabilities, it is important to first understand a benign case of how these links are created.  

Google often provides a ‘Translate this page’ option for sites written in a different language to the default browser language.

Figure 1: A google search result for an international company E.g ‘Crédit Agricole’ gives the option to translate the page from French to English.
Figure 2: When clicked, the browser displays a link with a translate[.]goog domain, and the original domain, credit-agricole[.]fr, becomes the link’s subdomain.

When this feature is exploited by threat actors it can be particularly dangerous, as legacy security products that rely on ‘known’ or ‘safe’ domain-based detection are likely to register these emails as safe and provide no protective actions. If a recipient were to click on the malicious link, they could risk losing their credentials or even compromising their machine. 

 In contrast, Darktrace/Email has been able to consistently identify and action emails from such campaigns. This blog will discuss one of these events.

The Campaign 

The apparent motive in this attack was to harvest credentials and/or deploy malware on the recipient’s device. Credential harvesting can lead to the sale of credentials on the dark web, or the attacker may choose to leverage those credentials in subsequent attacks. Both harvesting credentials and deploying malware have severe potential ramifications, including but not limited to sensitive company data leaks and financial loss. 

During this attack, the threat actor sent similar emails to a group of recipients in a short space of time. The recipients were not normally associated with each other and Darktrace swiftly identified them as unsolicited bulk mail. The new technique that was leveraged included using Google’s translate services to share malicious links using legitimate seeming domains. The malicious host was visible within the subdomain ‘636416-selcdn-ru[.]translate[.]goog’.  

When clicked, the link displays a google translate page stating, “Can’t translate this page”. There is then a hyperlink, “Go to original page”, that brings the user to the malicious host- 636416[.]selcdn[.]ru. Finally, the host displays a fake webmail portal login. If a user engages, the attacker can harvest their credentials to either sell or use in subsequent attacks.

Figure 3- The Google Translate page that is displayed once clicking on the full link within the email. The hyperlink at the bottom of the image is where the user is redirected by clicking “Go to original page”. It is there that the fake webmail portal login is then displayed. 

Darktrace Coverage 

As the malicious emails contained links to ‘safe’ Google Translate domains, most email security products would not characterize the links as suspicious. However, Darktrace/Email levies hundreds of metrics to identify whether emails belong in a recipient’s inbox. In this case Darktrace highlighted anomalies including rare subdomains, links containing unknown redirects, emails from spoofed freemail accounts and senders that had sent a relatively large number of emails within a short time frame. Furthermore, the attacker had never sent any previous emails to the organization prior to this email campaign. 

On top of providing visibility, the RESPOND function of Darktrace/Email took action autonomously and instantaneously without any human confirmation required. These actions included locking links and holding malicious emails. 

Figure 4- Darktrace/Email overview tab shows the Anomaly Indicators section as well as the History, Association, and Validation information of this sender.

Figure 5 - The Darktrace RESPOND/Email model tab displays all models that triggered on the email and the associated actions. The most severe delivery action supersedes the others, so here the email was held. 

Concluding Thoughts 

Threat actors are continuously updating the way they deliver malicious payloads within emails. While this particular email campaign utilized Google Translate domains to hide malicious links, subsequent attacks may well be seen leveraging other legitimate domains. Companies are only as strong as their weakest link; a single compromised internal email account can be used to send phishing emails to internal recipients, collect sensitive company information, inject malware onto the device, and more. Security tools must evolve to focus on anomalies within the email, rather than relying on rules or signatures of previously seen attacks. Furthermore, email tools must be able to autonomously respond as soon as the malicious emails enter the company’s environment. Only with these precautions will the risks associated with malicious emails be mitigated. 

Thanks to Steven Haworth and Steven Sosa for their contributions.

Appendices 

Relevant Darktrace Model Detections

·      Association / Anomalous Association

·      Association / New Sender

·      Association / Unknown Sender

·      Association / Unlikely Recipient Association

·      High Antigena Anomaly [part of the RESPOND functionality]

·      Link / Low Link Association

·      Link / Low Link Association and Unknown Sender

·      Link / New Correspondent Classified Link

·      Link / New Unknown Redirect

·      Link / Open Redirect

·      Link / Visually Prominent Link

·      Spam / Unsolicited Bulk Mail

·      Spoof / Spoofed Freemail

·      Unusual / New Sender Wide Distribution

·      Unusual / Sender Surge

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
Rachel Resnekov
Cyber Analyst

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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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