March 20, 2025

Cyberhaven Supply Chain Attack: Exploiting Browser Extensions

In late 2024, Darktrace detected unusual activity linked to Cyberhaven's Chrome browser extension. Read more about Darktrace’s investigation here.

Written by

Rajendra Rushanth

Cyber Analyst

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

Rajendra Rushanth

Cyber Analyst

woman looking at laptop in the office building

Mar 2025

The evolution of supply chain attacks

Supply chain attacks are becoming increasingly sophisticated. As network defenses improve, threat actors continuously adapt and refine their tactics, techniques, and procedures (TTPs) to achieve their goals. In recent years, this has led to a rise in the exploitation of trusted services and software, including legitimate browser extensions. Exploitation of these extensions can provide adversaries with a stealthy means to infiltrate target networks and access high-value accounts undetected.

A notable example of this trend was the compromise of the Cyberhaven Chrome extension at the end of 2024. This incident appeared to be part of a broader campaign targeting multiple Chrome browser extensions, highlighting the evolving nature of supply chain attacks [1].

What is Cyberhaven?

Cyberhaven, a US-based data security organization, experienced a security breach on December 24, 2024, when a phishing attack reportedly compromised one of their employee's credentials [2]. This allowed attackers to publish a malicious version of the Cyberhaven Chrome extension, which exfiltrated cookies and authenticated sessions from targeted websites. The malicious extension was active from December 25 to December 26 – a time when most businesses and employees were out of office and enjoying the festive period, a fact not lost on threat actors. The attackers, likely a well-organized and financially motivated group, compromised more than 30 additional Chrome extensions, affecting more than 2.6 million users [3]. They used sophisticated phishing techniques to authorize malicious OAuth applications, bypassing traditional security measures and exploiting vulnerabilities in OAuth authorizations. The primary motive appeared to be financial gain, targeting high-value platforms like social media advertising and AI services [4].

In late December 2024, multiple Darktrace customers were compromised via the Cyberhaven Chrome extension; this blog will primarily focus on Darktrace / NETWORK detections from one affected customer.

Darktrace’s coverage of Cyberhaven compromises

On December 26, 2024, Darktrace identified a series of suspicious activities across multiple customer environments, uncovering a structured attack sequence that progressed from initial intrusion to privilege escalation and data exfiltration. The attack was distributed through a malicious update to the Cyberhaven Chrome extension [2]. The malicious update established a foothold in customer environments almost immediately, leading to further anomalies.

As with other Chrome browser extensions, Cyberhaven Chrome extensions were updated automatically with no user interaction required. However, in this instance, the automatic update included a malicious version which was deployed to customer environments. This almost immediately introduced unauthorized activity, allowing attackers to establish a foothold in customer networks. The update allowed attackers to execute their objectives in the background, undetected by traditional security tools that rely on known indicators of compromise (IoCS) rather than identifying anomalies.

While multiple customer devices were seen connecting to cyberhaven[.]io, a legitimate Cyberhaven domain, Darktrace detected persistent beaconing behavior to cyberhavenext[.]pro, which appeared to be attempting to masquerade as another legitimate Cyberhaven domain. Darktrace recognized this activity as unusual, triggering several model alerts in Darktrace / NETWORK to highlight the persistent outbound connections to the suspicious domain.

Further analysis of external connectivity patterns indicated an increase in anomalous HTTP requests alongside this beaconing activity. Multiple open-source intelligence (OSINT) sources also suggest that the cyberhavenext[.]pro endpoint is associated with malicious activities [5].

Figure 1: Darktrace / NETWORK’s detection of beaconing activity to cyberhavenext[.]pro

Analysis using Darktrace’s Advanced Search revealed that some of these connections were directed to the suspicious external IP address 149.28.124[.]84. Further investigation confirmed that the IP correlated with two SSL hostnames, including the malicious cyberhavenext[.]pro, further reinforcing its connection to the attack infrastructure.

Figure 2: Darktrace Advanced Search analysis showing the IP address 149.28.124[.]84 correlating to two SSL hostnames, one of which is cyberhavenext[.]pro.

Between December 23 and December 27, Darktrace observed sustained beaconing-like activity from affected devices on the customer’s network.

Figure 3: Darktrace’s detection of beaconing activities from a customer device to the endpoint 149.28.124[.]84 between December 23 and December 27.

Darktrace observed 27 unique devices connecting to the malicious command-and-control (C2) infrastructure as far back as December 3. While most connections were brief, they represented an entry point for malicious activity. Over a two-day period, two devices transmitted 5.57 GiB of incoming data and 859.37 MiB of outgoing data, generating over 3 million log events across SSL, HTTP, and connection data.

Subsequent analysis identified a significant increase in unauthorized data transfers to the aforementioned 149.28.124[.]84 IP on another customer network, highlighting the potential broader impact of this compromise. The volume and frequency of these transfers suggested that attackers were leveraging automated data collection techniques, further underscoring the sophistication of the attack.

Figure 4: Darktrace’s detection of the likely exfiltration of 859.37 MiB to the endpoint 149.28.124[.]84.

External research suggested that once active, the Cyberhaven extension would begin silently collecting session cookies and authentication tokens, specifically targeting high-value accounts such as Facebook Ads accounts [4]. Darktrace’s analysis of another affected customer noted many HTTP POST connections directed to a specific URI ("ai-cyberhaven"), while GET requests contained varying URIs prefixed with "/php/urlblock?args=AAAh....--redirect." This activity indicated an exfiltration mechanism, consistent with techniques observed in other compromised Chrome extensions. By compromising session cookies, attackers could potentially gain administrative access to connected accounts, further escalating their privileges [4].

Conclusion

This incident highlights the importance of monitoring not just endpoint security, but also cloud and browser-based security solutions, as attackers increasingly target these trusted and oft overlooked vectors.

Ultimately, by focusing on anomaly detection and behavioral analysis rather than static signatures and lists of ‘known bads’, Darktrace was able to successfully detect devices affected by the Cyberhaven Chrome browser extension compromise, by identifying activity that would likely have been considered legitimate and benign by traditional security solutions.

This compromise also serves as a reminder that supply chain attacks are not limited to traditional software vendors. Browser extensions, cloud-based applications, and SaaS services are equally vulnerable, as evidenced by Darktrace's detection of Balada Injector malware exploiting WordPress vulnerabilities to gain unauthorized network access [6]. Therefore, increased targeting of browser-based security tools, and a greater exploitation of OAuth and session hijacking techniques are to be expected. Attackers will undoubtedly refine their methods to infiltrate legitimate vendors and distribute malicious updates through trusted channels. By staying informed, vigilant, and proactive, organizations can mitigate exposure to evolving supply chain threats and safeguard their critical assets from emerging browser-based attack techniques.

Credit to Rajendra Rushanth (Cyber Analyst) Justin Torres (Senior Cyber Analyst) and Ryan Traill (Analyst Content Lead)

[related-resource]

Appendices

Darktrace Model Detections

· Compromise / Beaconing Activity To External Rare (AP: C2 Comms)

· Compromise / Beacon for 4 Days (AP: C2 Comms)

· Compromise / HTTP Beaconing to Rare Destination (AP: C2 Comms)

· Device / Suspicious Domain (AP: C2 Comms, AP: Tooling)

· Compromise / Sustained TCP Beaconing Activity To Rare Endpoint (AP: C2 Comms)

· Anomalous Server Activity / Rare External from Server (AP: C2 Comms)

· Anomalous Connection / Multiple Failed Connections to Rare Endpoint (AP: C2 Comms)

· Anomalous Server Activity / Anomalous External Activity from Critical Network Device (AP: C2 Comms)

· Compromise / Slow Beaconing Activity To External Rare (AP: C2 Comms)

· Compromise / Repeating Connections Over 4 Days (AP: C2 Comms)

· Anomalous Connection / Multiple HTTP POSTs to Rare Hostname (AP: C2 Comms)

· Anomalous Server Activity / Outgoing from Server (AP: C2 Comms)

· Compromise / High Volume of Connections with Beacon Score (AP: C2 Comms)

· Compromise / Large Number of Suspicious Failed Connections (AP: C2 Comms)

· Email Nexus / Connection to Hijacked Correspondent Link

· Compromise / Suspicious TLS Beaconing To Rare External (AP: C2 Comms)

· Compromise / Quick and Regular Windows HTTP Beaconing (AP: C2 Comms)

List of IoCs

IoC - Type - Description + Confidence

cyberhavenext[.]pro - Hostname - Used for C2 communications and data exfiltration (cookies and session tokens)

149.28.124[.]84 - IP - Associated with malicious infrastructure

45.76.225[.]148 - IP - Associated with malicious infrastructure

136.244.115[.]219 - IP - Associated with malicious infrastructure

MITRE ATT&CK Mapping

Tactic – Technique – Sub-Technique

INITIAL ACCESS - T1176 - Browser Extensions

EXECUTION - T1204.002 - Malicious Browser Extensions

PERSISTENCE - T1176 - Browser Extensions

COMMAND AND CONTROL - T1071.001 - Web Protocols

COMMAND AND CONTROL - T1001 - Data Obfuscation

CREDENTIAL ACCESS - T1539 - Steal Web Session Cookie

DISCOVERY - T1518.001 - Security Software Discovery

LATERAL MOVEMENT - T1557.003 - Man-in-the-Browser

EXFILTRATION - T1041 - Exfiltration Over C2 Channel

EXFILTRATION - T1567.002 - Exfiltration to Cloud Storage

IMPACT - T1583.006 - Session Hijacking

References

[1] https://thehackernews.com/2024/12/16-chrome-extensions-hacked-exposing.html

[2] https://www.cyberhaven.com/blog/cyberhavens-chrome-extension-security-incident-and-what-were-doing-about-it

[3] https://www.infosecurity-magazine.com/news/chrome-browser-extensions-hijacked/

[4] https://www.theverge.com/2024/12/28/24330758/chrome-extension-cyberhaven-hijack-phishing-cyberattack-facebook-ads-authentication-theft

[5] https://www.virustotal.com/gui/domain/cyberhavenext.pro

[6] https://darktrace.com/blog/balada-injector-darktraces-investigation-into-the-malware-exploiting-wordpress-vulnerabilities

Get the latest insights on emerging cyber threats

This report explores the latest trends shaping the cybersecurity landscape and what defenders need to know in 2025

Inside the SOC

Written by

Rajendra Rushanth

Cyber Analyst

Senior Product Marketing Manager, Email

Watch the NIS2 Webinar

Blog

Identity

July 7, 2025

Top Eight Threats to SaaS Security and How to Combat Them

login screen for mutli factor authentication

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]

‍

About the author

Carlos Gray

Senior Product Marketing Manager, Email

Blog

July 7, 2025

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

‍

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 Foulger (Global Threat Research Operations Lead), Ryan Traill (Analyst Content Lead)

References and further reading:

Related Darktrace blogs:

‍

*Self-reported by customer, confirmed afterwards.

**Updated January 2024 blog now reflects current findings

About the author

Your data. Our AI.

Elevate your network security with Darktrace AI

Get a demo

Check out this article by Darktrace: Cyberhaven Supply Chain Attack: Exploiting Browser Extensions

Cyberhaven Supply Chain Attack: Exploiting Browser Extensions

The evolution of supply chain attacks

What is Cyberhaven?

Darktrace’s coverage of Cyberhaven compromises

Conclusion

Appendices

Darktrace Model Detections

List of IoCs

MITRE ATT&CK Mapping

References

Get the latest insights on emerging cyber threats

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

Top Eight Threats to SaaS Security and How to Combat Them

Enjoying the blog?

More in this series

Patch and Persist: Darktrace’s Detection of Blind Eagle (APT-C-36)

Customer Case Study: Leading Petrochemical Manufacturer

Tracking CVE-2025-31324: Darktrace’s detection of SAP Netweaver exploitation before and after disclosure

Blog

Identity

July 7, 2025

Top Eight Threats to SaaS Security and How to Combat Them

The latest on the identity security landscape

What is SaaS security?

1. Account Takeover (ATO)

2. Privilege escalation

3. Lateral movement

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

5. OAuth token abuse

6. Insider threats

7. Application Programming Interface (API)-based attacks

8. Business Email Compromise (BEC) via SaaS

Protecting against these SaaS threats

AI-powered SaaS security stays ahead of the threat landscape

Blog

July 7, 2025

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

Detecting threats without relying on CVE disclosure

Below are 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

Autonomous Response

Conclusion

References and further reading:

Related Darktrace blogs: