June 25, 2024

Following up on our Conversation: Detecting & Containing a LinkedIn Phishing Attack with Darktrace

Darktrace/Email detected a phishing attack that had originated from LinkedIn, where the attacker impersonated a well known construction company to conduct a credential harvesting attack on the target. Darktrace’s ActiveAI Security Platform played a critical role in investigating the activity and initiating real-time responses that were outside the physical capability of human security teams.

Written by

Nicole Wong

Cyber Security 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

Nicole Wong

Cyber Security Analyst

Jun 2024

Note: Real organization, domain and user names have been modified and replaced with fictitious names to maintain anonymity.

Social media cyber-attacks

Social media is a known breeding ground for cyber criminals to easily connect with a near limitless number of people and leverage the wealth of personal information shared on these platforms to defraud the general public. Analysis suggests even the most tech savvy ‘digital natives’ are vulnerable to impersonation scams over social media, as criminals weaponize brands and trends, using the promise of greater returns to induce sensitive information sharing or fraudulent payments [1].

LinkedIn phishing

As the usage of a particular social media platform increases, cyber criminals will find ways to exploit the increasing user base, and this trend has been observed with the rise in LinkedIn scams in recent years [2]. LinkedIn is the dominant professional networking site, with a forecasted 84.1million users by 2027 [3]. This platform is data-driven, so users are encouraged to share information publicly, including personal life updates, to boost visibility and increase job prospects [4] [5]. While this helps legitimate recruiters to gain a good understanding of the user, an attacker could also leverage the same personal content to increase the sophistication and success of their social engineering attempts.

Darktrace detection of LinkedIn phishing

Darktrace detected a Software-as-a-Service (SaaS) compromise affecting a construction company, where the attack vector originated from LinkedIn (outside the monitoring of corporate security tools), but then pivoted to corporate email where a credential harvesting payload was delivered, providing the attacker with credentials to access a corporate file storage platform.

Because LinkedIn accounts are typically linked to an individual’s personal email and are most commonly accessed via the mobile application [6] on personal devices that are not monitored by security teams, it can represent an effective initial access point for attackers looking to establish an initial relationship with their target. Moreover, user behaviors to ignore unsolicited emails from new or unknown contacts are less frequently carried over to platforms like LinkedIn, where interactions with ‘weak ties’ as opposed to ‘strong ties’ are a better predictor of job mobility [7]. Had this attack been allowed to continue, the threat actor could have leveraged access to further information from the compromised business cloud account to compromise other high value accounts, exfiltrate sensitive data, or defraud the organization.

LinkedIn phishing attack details

Reconnaissance

The initial reconnaissance and social engineering occurred on LinkedIn and was thus outside the purview of corporate security tools, Darktrace included.

However, the email domain “hausconstruction[.]com” used by the attacker in subsequent communications appears to be a spoofed domain impersonating a legitimate construction company “haus[.]com”, suggesting the attacker may have also impersonated an employee of this construction company on LinkedIn. In addition to spoofing the domain, the attacker seemingly went further to register “hausconstruction.com” on a commercial web hosting platform. This is a technique used frequently not just to increase apparent legitimacy, but also to bypass traditional security tools since newly registered domains will have no prior threat intelligence, making them more likely to evade signature and rules-based detections [8]. In this instance, open-source intelligence (OSINT) sources report that the domain was created several months earlier, suggesting this may have been part of a targeted attack on construction companies.

Initial Intrusion

It was likely that during the correspondence over LinkedIn, the target user was solicited into following up over email regarding a prospective construction project, using their corporate email account. In a probable attempt to establish a precedent of bi-directional correspondence so that subsequent malicious emails would not be flagged by traditional security tools, the attacker did not initially include suspicious links, attachments or use solicitous or inducive language within their initial emails.

Figure 1: Example of bi-directional email correspondence between the target and the attacker impersonating a legitimate employee of the construction company haus.com.

Figure 2: Cyber AI Analyst investigation into one of the initial emails the target received from the attacker.

To accomplish the next stage of their attack, the attacker shared a link, hidden behind the inducing text “VIEW ALL FILES”, to a malicious file using the Hightail cloud storage service. This is also a common method employed by attackers to evade detection, as this method of file sharing does not involve attachments that can be scanned by traditional security tools, and legitimate cloud storage services are less likely to be blocked.

OSINT analysis on the malicious link link shows the file hosted on Hightail was a HTML file with the associated message “Following up on our LinkedIn conversation”. Further analysis suggests the file contained obfuscated Javascript that, once opened, would automatically redirect the user to a malicious domain impersonating a legitimate Microsoft login page for credential harvesting purposes.

Figure 3: The malicious HTML file containing obfuscated Javascript, where the highlighted string references the malicious credential harvesting domain.

Screenshot of fraudulent Microsoft Sign In page hosted on the malicous credential harvesting domain. — Figure 4: Screenshot of fraudulent Microsoft Sign In page hosted on the malicious credential harvesting domain.

Although there was prior email correspondence with the attacker, this email was not automatically deemed safe by Darktrace and was further analyzed for unusual properties and unusual communications for the recipient and the recipient’s peer group.

Darktrace determined that:

It was unusual for this file storage solution to be referenced in communications to the user and the wider network
Textual properties of the email body suggested a high level of inducement from the sender, with a high level of focus on the phishing link.
The full link contained suspicious properties suggesting it is high risk.

Figure 5: Darktrace’s analysis of the phishing email, presenting key information about the unusual characteristics of this email, information on highlighted content, and an overview of actions that were initially applied.

Based on these anomalies, Darktrace initially moved the phishing email to the junk folder and locked the link, preventing the user from directly accessing the malicious file hosted on Hightail. However, the customer’s security team released the email, likely upon end-user request, allowing the target user to access the file and ultimately enter their credentials into that credential harvesting domain.

Figure 6: Darktrace alerts triggered by the malicious phishing email and the corresponding Autonomous Response actions.

Lateral Movement

Correspondence between the attacker and target continued for two days after the credential harvesting payload was delivered. Five days later, Darktrace detected an unusual login using multi-factor authentication (MFA) from a rare external IP and ASN that coincided with Darktrace/Email logs showing access to the credential harvesting link.

This attempt to bypass MFA, known as an Office365 Shell WCSS attack, was likely achieved by inducing the target to enter their credentials and legitimate MFA token into the fake Microsoft login page. This was then relayed to Microsoft by the attacker and used to obtain a legitimate session. The attacker then reused the legitimate token to log into Exchange Online from a different IP and registered their own device for MFA.

Figure 7: Screenshot within Darktrace/Email of the phishing email that was released by the security team, showing the recipient clicked the link to file storage where the malicious payload was stored.

‍

Figure 8: Event Log showing a malicious login and MFA bypass at 17:57:16, shortly after the link was clicked. Highlighted in green is activity from the legitimate user prior to the malicious login, using Edge. Highlighted in orange and red is the malicious activity using Chrome.

The IP addresses used by the attacker appear to be part of anonymization infrastructure, but are not associated with any known indicators of compromise (IoCs) that signature-based detections would identify [9] [10].

In addition to logins being observed within half an hour of each other from multiple geographically impossible locations (San Francisco and Phoenix), the unexpected usage of Chrome browser, compared to Edge browser previously used, provided Darktrace with further evidence that this activity was unlikely to originate from the legitimate user. Although the user was a salesperson who frequently travelled for their role, Darktrace’s Self-Learning AI understood that the multiple logins from these locations was highly unusual at the user and group level, and coupled with the subsequent unexpected account modification, was a likely indicator of account compromise.

Accomplish mission

Although the email had been manually released by the security team, allowing the attack to propagate, additional layers of defense were triggered as Darktrace's Autonomous Response initiated “Disable User” actions upon detection of the multiple unusual logins and the unauthorized registration of security information.

However, the customer had configured Autonomous Response to require human confirmation, therefore no actions were taken until the security team manually approved them over two hours later. In that time, access to mail items and other SharePoint files from the unusual IP address was detected, suggesting a potential loss of confidentiality to business data.

Figure 9: Advanced Search query showing several FilePreviewed and MailItemsAccessed events from either the IPs used by the attacker, or using the software Chrome. Note some of the activity originated from Microsoft IPs which may be whitelisted by traditional security tools.

However, it appears that the attacker was able to maintain access to the compromised account, as login and mail access events from 199.231.85[.]153 continued to be observed until the afternoon of the next day.

Conclusion

This incident demonstrates the necessity of AI to security teams, with Darktrace’s ActiveAI Security Platform detecting a sophisticated phishing attack where human judgement fell short and initiated a real-time response when security teams could not physically respond as fast.

Security teams are very familiar with social engineering and impersonation attempts, but these attacks remain highly prevalent due to the widespread adoption of technologies that enable these techniques to be deployed with great sophistication and ease. In particular, the popularity of information-rich platforms like LinkedIn that are geared towards connecting with unknown people make it an attractive initial access point for malicious attackers.

In the second half of 2023 alone, over 200 thousand fake profiles were reported by members on LinkedIn [11]. Fake profiles can be highly sophisticated, use professional images, contain compelling descriptions, reference legitimate company listings and present believable credentials.

It is unrealistic to expect end users to defend themselves against such sophisticated impersonation attempts. Moreover, it is extremely difficult for human defenders to recognize every fraudulent interaction amidst a sea of fake profiles. Instead, defenders should leverage AI, which can conduct autonomous investigations without human biases and limitations. AI-driven security can ensure successful detection of fraudulent or malicious activity by learning what real users and devices look like and identifying deviations from their learned behaviors that may indicate an emerging threat.

Appendices

Darktrace Model Detections

DETECT/ Apps

SaaS / Compromise / SaaS Anomaly Following Anomalous Login

SaaS / Compromise / Unusual Login and Account Update

SaaS / Unusual Activity / Multiple Unusual External Sources For SaaS Credential

SaaS / Access / Unusual External Source for SaaS Credential Use

SaaS / Compliance / M365 Security Information Modified

‍

RESPOND/ Apps

Antigena / SaaS / Antigena Suspicious SaaS Activity Block

Antigena / SaaS / Antigena Unusual Activity Block

DETECT & RESPOND/ Email

· Link / High Risk Link + Low Sender Association

· Link / New Correspondent Classified Link

· Link / Watched Link Type

· Antigena Anomaly

· Association / Unknown Sender

· History / New Sender

· Link / Link to File Storage

· Link / Link to File Storage + Unknown Sender

· Link / Low Link Association

List of IoCs

· 142.252.106[.]251 - IP - Possible malicious IP used by attacker during cloud account compromise

· 199.231.85[.]153 – IP - Probable malicious IP used by attacker during cloud account compromise

· vukoqo.hebakyon[.]com – Endpoint - Credential harvesting endpoint

MITRE ATT&CK Mapping

· Resource Development - T1586 - Compromise Accounts

· Resource Development - T1598.003 – Spearphishing Link

· Persistence - T1078.004 - Cloud Accounts

· Persistence - T1556.006 - Modify Authentication Process: Multi-Factor Authentication

· Reconnaissance - T1593.001 – Social Media

· Reconnaissance - T1598 – Phishing for Information

· Reconnaissance - T1589.001 – Credentials

· Reconnaissance - T1591.002 – Business Relationships

· Collection - T1111 – Multifactor Authentication Interception

· Collection - T1539 – Steal Web Session Cookie

· Lateral Movement - T1021.007 – Cloud Services

· Lateral Movement - T1213.002 - Sharepoint

References

[1] Jessica Barker, Hacked: The secrets behind cyber attacks, (London: Kogan Page, 2024), p. 130-146.

[2] https://www.bitdefender.co.uk/blog/hotforsecurity/5-linkedin-scams-and-how-to-avoid-them/

[3] https://www.washingtonpost.com/technology/2023/08/31/linkedin-personal-posts/

[4] https://www.forbes.com/sites/joshbersin/2012/05/21/facebook-vs-linkedin-whats-the-difference/

[5] https://thelinkedblog.com/2022/3-reasons-why-you-should-make-your-profile-public-1248/

[6] https://www.linkedin.com/pulse/50-linkedin-statistics-every-professional-should-ti9ue

[7] https://www.nytimes.com/2022/09/24/business/linkedin-social-experiments.html

[8] https://darktrace.com/blog/the-domain-game-how-email-attackers-are-buying-their-way-into-inboxes

[9] https://spur.us/context/142.252.106[.]251

[10] https://spur.us/context/199.231.85[.]153

[11]https://www.statista.com/statistics/1328849/linkedin-number-of-fake-accounts-detected-and-removed

Written by

Nicole Wong

Cyber Security Analyst

Inside the SOC

Written by

Nicole Wong

Cyber Security Analyst

VP, Security & AI Strategy, Field CISO

Watch the NIS2 Webinar

Blog

Network

April 2, 2026

How Chinese-Nexus Cyber Operations Have Evolved – And What It Means For Cyber Risk and Resilience

Cybersecurity has traditionally organized risk around incidents, breaches, campaigns, and threat groups. Those elements still matter—but if we fixate on individual incidents, we risk missing the shaping of the entire ecosystem. Nation‑state–aligned operators are increasingly using cyber operations to establish long-term strategic leverage, not just to execute isolated attacks or short‑term objectives.

Our latest research, Crimson Echo, shifts the lens accordingly. Instead of dissecting campaigns, malware families, or actor labels as discrete events, the threat research team analyzed Chinese‑nexus activity as a continuum of behaviors over time. That broader view reveals how these operators position themselves within environments: quietly, patiently, and persistently—often preparing the ground long before any recognizable “incident” occurs.

How Chinese-nexus cyber threats have changed over time

Chinese-nexus cyber activity has evolved in four phases over the past two decades. This ranges from early, high-volume operations in the 1990s and early 2000s to more structured, strategically-aligned activity in the 2010s, and now toward highly adaptive, identity-centric intrusions.

Today’s phase is defined by scale, operational restraint, and persistence. Attackers are establishing access, evaluating its strategic value, and maintaining it over time. This reflects a broader shift: cyber operations are increasingly integrated into long-term economic and geopolitical strategies. Access to digital environments, specifically those tied to critical national infrastructure, supply chains, and advanced technology, has become a form of strategic leverage for the long-term.

How Darktrace analysts took a behavioral approach to a complex problem

One of the challenges in analyzing nation-state cyber activity is attribution. Traditional approaches often rely on tracking specific threat groups, malware families, or infrastructure. But these change constantly, and in the case of Chinese-nexus operations, they often overlap.

Crimson Echo is the result of a retrospective analysis of three years of anomalous activity observed across the Darktrace fleet between July 2022 and September 2025. Using behavioral detection, threat hunting, open-source intelligence, and a structured attribution framework (the Darktrace Cybersecurity Attribution Framework), the team identified dozens of medium- to high-confidence cases and analyzed them for recurring operational patterns.

This long-horizon, behavior-centric approach allows Darktrace to identify consistent patterns in how intrusions unfold, reinforcing that behavioral patterns that matter.

What the data shows

Several clear trends emerged from the analysis:

Targeting is concentrated in strategically important sectors. Across the dataset, 88% of intrusions occurred in organizations classified as critical infrastructure, including transportation, critical manufacturing, telecommunications, government, healthcare, and Information Technology (IT) services.
Strategically important Western economies are a primary focus. The US alone accounted for 22.5% of observed cases, and when combined with major European economies including Germany, Italy, Spain and the UK, over half of all intrusions (55%) were concentrated in these regions.
Nearly 63% of intrusions of intrusions began with the exploitation of internet-facing systems, reinforcing the continued risk posed by externally exposed infrastructure.

Two models of cyber operations

Across the dataset, Chinese-nexus activity followed two operational models.

The first is best described as “smash and grab.” These are short-horizon intrusions optimized for speed. Attackers move quickly – often exfiltrating data within 48 hours – and prioritize scale over stealth. The median duration of these compromises is around 10 days. It’s clear they are willing to risk detection for short-term gain.

The second is “low and slow.” These operations were less prevalent in the dataset, but potentially more consequential. Here, attackers prioritize persistence, establishing durable access through identity systems and legitimate administrative tools, so they can maintain access undetected for months or even years. In one notable case, the actor had fully compromised the environment and established persistence, only to resurface in the environment more than 600 days after. The operational pause underscores both the depth of the intrusion and the actor’s long‑term strategic intent. This suggests that cyber access is a strategic asset to preserve and leverage over time, and we observed these attacks most often inin sectors of the high strategic importance.

It’s important to note that the same operational ecosystem can employ both models concurrently, selecting the appropriate model based on target value, urgency, intended access. The observation of a “smash and grab” model should not be solely interpreted as a failure of tradecraft, but instead an operational choice likely aligned with objectives. Where “low and slow” operations are optimized for patience, smash and grab is optimized for speed; both seemingly are deliberate operational choices, not necessarily indicators of capability.

Rethinking cyber risk

For many organizations, cyber risk is still framed as a series of discrete events. Something happens, it is detected and contained, and the organization moves on. But persistent access, particularly in deeply interconnected environments that span cloud, identity-based SaaS and agentic systems, and complex supply chain networks, creates a major ongoing exposure risk. Even in the absence of disruption or data theft, that access can provide insight into operations, dependencies, and strategic decision-making. Cyber risk increasingly resembles long-term competitive intelligence.

This has impact beyond the Security Operations Center. Organizations need to shift how they think about governance, visibility, and resilience, and treat cyber exposure as a structural business risk instead of an incident response challenge.

What comes next

The goal of this research is to provide a clearer understanding of how these operations work, so defenders can recognize them earlier and respond more effectively. That includes shifting from tracking indicators to understanding behaviors, treating identity providers as critical infrastructure risks, expanding supplier oversight, investing in rapid containment capabilities, and more.

Learn more about the findings of Darktrace’s latest research, Crimson Echo: Understanding Chinese-nexus Cyber Operations Through Behavioral Analysis, by downloading the full report and summaries for business leaders, CISOs, and SOC analysts here.

About the author

Nathaniel Jones

VP, Security & AI Strategy, Field CISO

Blog

Proactive Security

April 1, 2026

AI-powered security for a rapidly growing grocery enterprise

Protecting a complex, fast-growing retail organization

For this multi-banner grocery holding organization, cybersecurity is considered an essential business enabler, protecting operations, growth, and customer trust. The organization’s lean IT team manages a highly distributed environment spanning corporate offices, 100+ stores, distribution centers and thousands of endpoints, users, and third-party connections.

Mergers and acquisitions fueled rapid growth, but they also introduced escalating complexity that constrained visibility into users, endpoints, and security risks inherited across acquired environments.

Closing critical visibility gaps with limited resources

Enterprise-wide visibility is a top priority for the organization, says the Vice President of Information Technology. “We needed insights beyond the perimeter into how users and devices were behaving across the organization.”

A security breach that occurred before the current IT leadership joined the company reinforced the urgency and elevated cybersecurity to an executive-level priority with a focus on protecting customer trust. The goal was to build a multi-layered security model that could deliver autonomous, enterprise-wide protection without adding headcount.

Managing cyber risk in M&A

Mergers and acquisitions are central to the grocery holding company’s growth strategy. But each transaction introduces new cyber risk, including inherited network architectures, inconsistent tooling, excessive privileges, and remnants of prior security incidents that were never fully remediated.

“Our M&A targets range from small chains with a single IT person and limited cyber tools to large chains with more developed IT teams, toolsets and instrumentation,” explains the VP of IT. “We needed a fast, repeatable, and reliable way to assess cyber risk before transactions closed.”

AI-driven security built for scale, speed, and resilience

Rather than layering additional point tools onto an already complex environment, the retailer adopted the Darktrace ActiveAI Security Platform™ in 2020 as part of a broader modernization effort to improve resilience, close visibility gaps, and establish a security foundation that could scale with growth.

“Darktrace’s AI-driven approach provided the ideal solution to these challenges,” shares the VP of IT. “It has empowered our organization to maintain a robust security strategy, ensuring the protection of our network and the smooth operation of our business.”

Enterprise-wide visibility into traffic

By monitoring both north-south and east-west traffic and applying Self-Learning AI, Darktrace develops a dynamic understanding of how users and devices normally behave across locations, roles, and systems.

“Modeling normal behavior across the environment enables us to quickly spot behavior that doesn’t fit. Even subtle changes that could signal a threat but appear legitimate at first glance,” explains the VP of IT.

Real-time threat containment, 24/7

Adopting autonomous response has created operational breathing room for the security team, says the company’s Cybersecurity Engineer.

“Early on, we enabled full Darktrace autonomous mode and we continue to do so today,” shares the IT Security Architect. “Allowing the technology to act first gives us the time we need to investigate incidents during business hours without putting the business at risk.”

Unified, actionable view of security ecosystem

The grocery retailer integrated Darktrace with its existing security ecosystem of firewalls, vulnerability management tools, and endpoint detection and response, and the VP of IT described the adoption process as “exceptionally smooth.”

The team can correlate enterprise-wide security data for a unified and actionable picture of all activity and risk. Using this “single pane of glass” approach, the retailer trains Level 1 and Level 2 operations staff to assist with investigations and user follow-ups, effectively extending the reach of the security function without expanding headcount.

From reactive defense to security at scale

With Darktrace delivering continuous visibility, autonomous containment, and integrated security workflows, the organization has strengthened its cybersecurity posture while improving operational efficiency. The result is a security model that not only reduces risk, but also supports growth, resilience, and informed decision-making at the business level.

Faster detection, faster resolution

With autonomous detection and response, the retailer can immediately contain risk while analysts investigate and validate activity. With this approach, the company can maintain continuous protection even outside business hours and reduce the chance of lateral spread across systems or locations.

Enterprise-grade protection with a lean team

From cloud environments to clients to SaaS collaboration tools, Darktrace provides holistic autonomous AI defense, processing petabytes of the organization’s network traffic and investigating millions of individual events that could be indicative of a wider incident.

Today, Darktrace autonomously conducts the majority of all investigations on behalf of the IT team, escalating only a tiny fraction for analyst review. The impact has been profound, freeing analysts from endless alerts and hours of triage so they can focus on more valuable, proactive, and gratifying work.

“From an operational perspective, Darktrace gives us time back,” says the Cybersecurity Engineer. More importantly, says the VP of IT, “it gives us peace of mind that we’re protected even if we’re not actively monitoring every alert.”

A strategic input for M&A decision-making

One of the most strategic outcomes has been the role of cybersecurity on M&A. 90 days prior to closing a transaction, the security team uses Darktrace alongside other tools to perform a cyber risk assessment of the potential acquisition. “Our approach with Darktrace has consistently identified gaps and exposed risks,” says the VP of IT, including:

Remnants of previous incidents that were never fully remediated
Network configurations with direct internet exposure
Excessive administrative privileges in Active Directory or on critical hosts

While security findings may not alter deal timelines, the VP of IT says they can have enormous business implications. “With early visibility into these risks, we can reduce exposure to inherited cyber threats, strengthen our position during negotiations, and establish clear remediation requirements.”

A security strategy built to evolve with the business

As the holding group expands its cloud footprint, it will extend Darktrace protections into Azure, applying the same AI-driven visibility and autonomous response to cloud workloads. The VP of IT says Darktrace's evolving capabilities will be instrumental in addressing the organization’s future cybersecurity needs and ability to adapt to the dynamic nature of cloud security.

“With Darktrace’s AI-driven approach, we have moved beyond reactive defense, establishing a resilient security foundation for confident expansion and modernization.”

‍

About the author

Your data. Our AI.

Elevate your network security with Darktrace AI

Get a demo

Check out this article by Darktrace: Following up on our Conversation: Detecting & Containing a LinkedIn Phishing Attack with Darktrace

Following up on our Conversation: Detecting & Containing a LinkedIn Phishing Attack with Darktrace

Social media cyber-attacks

LinkedIn phishing

Darktrace detection of LinkedIn phishing

LinkedIn phishing attack details

Reconnaissance

Initial Intrusion

Lateral Movement

Accomplish mission

Conclusion

Appendices

Darktrace Model Detections

List of IoCs

MITRE ATT&CK Mapping

References

Phantom Footprints: Tracking GhostSocks Malware

How Chinese-Nexus Cyber Operations Have Evolved – And What It Means For Cyber Risk and Resilience

Enjoying the blog?

More in this series

Darktrace Unites Human Behavior and Threat Detection Across Email, Slack, Teams, and Zoom

Why Organizations are Moving to Label-free, Behavioral DLP for Outbound Email

Beyond MFA: Detecting Adversary-in-the-Middle Attacks and Phishing with Darktrace

Blog

Network

April 2, 2026

How Chinese-Nexus Cyber Operations Have Evolved – And What It Means For Cyber Risk and Resilience

How Chinese-nexus cyber threats have changed over time

How Darktrace analysts took a behavioral approach to a complex problem

What the data shows

Two models of cyber operations

Rethinking cyber risk

What comes next

Blog

Proactive Security

April 1, 2026

AI-powered security for a rapidly growing grocery enterprise

Protecting a complex, fast-growing retail organization

Closing critical visibility gaps with limited resources

Managing cyber risk in M&A

AI-driven security built for scale, speed, and resilience

Enterprise-wide visibility into traffic

Real-time threat containment, 24/7

Unified, actionable view of security ecosystem

From reactive defense to security at scale

Faster detection, faster resolution

Enterprise-grade protection with a lean team

A strategic input for M&A decision-making

A security strategy built to evolve with the business