Why ‘Industry-Standard’ Vendors Still Create Hidden Cyber Risk
Key Highlights
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Trusted, widely adopted analytics and monitoring tools can introduce hidden cyber risk as third-party behavior and data collection evolve over time.
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Static vendor risk assessments and point-in-time audits often fail to capture changes that occur after a tool is deployed.
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Attackers increasingly target downstream vendors as an easier path to sensitive data than breaching well-defended enterprises directly.
In late 2025, analytics provider Mixpanel disclosed a security incident in which an unauthorized party accessed its systems and exported a limited set of customer analytics data. Public reporting and customer notifications indicated that the exposed information consisted primarily of metadata such as names, email addresses, browser and device details, referrers and organization or user identifiers rather than passwords, credentials or application data.
The incident affected data associated with services using Mixpanel’s analytics tools including OpenAI and was attributed to a compromise of Mixpanel’s environment rather than the affected customers’ own infrastructure.
The false sense of safety behind trusted tools
At first glance, the Mixpanel incident is troubling but not because OpenAI or other customers failed to take reasonable security precautions. Organizations with mature security programs routinely rely on widely adopted analytics and monitoring tools that meet established industry standards and pass formal vendor reviews. The assumption is that selecting a reputable provider significantly reduces risk.
The issue is that selecting a well-known vendor is not always enough. Even vendors that check every compliance and certification box can introduce new risk over time particularly when security teams rely on third-party evaluation processes that are static shallow or rooted in blind trust.
No one questions why a security-conscious organization would select an industry-standard analytics platform and that is precisely where the risk begins. Widespread adoption can create a false sense of safety making it harder to challenge a vendor’s real-time security posture. If a third-party compromise can occur in the orbit of a highly defended enterprise it raises uncomfortable questions for everyone else operating with fewer resources and less visibility.
What CISOs Should Take Away
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Vendor approval is not the end of risk ownership. Once third-party tools are deployed, changes to scripts, SDKs and data collection can materially alter exposure without triggering a new review.
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Point-in-time assessments miss how risk evolves. Questionnaires and audits validate controls at a moment in time but offer little insight into how vendor behavior shifts months later in production environments.
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Browser-side activity is a growing blind spot. Third-party analytics and monitoring tools embedded in applications can collect and transmit data in ways security teams may not routinely inspect.
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Attackers follow the path of least resistance. Compromising a trusted vendor can provide easier access to valuable metadata than attempting to breach a security-hardened enterprise directly.
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Third-party risk management must be continuous. CISOs should evaluate whether their programs detect meaningful changes in vendor behavior and data flows after deployment, not just at procurement.
The slow drift of third-party exposure
A key lesson from the Mixpanel incident is that vendor risk is not static. Many analytics and monitoring tools rely on third-party JavaScript embedded directly into applications. Initially these scripts may be limited to basic telemetry but over time additional capabilities are often layered in including session replay expanded metadata collection or deeper behavioral tracking.
This gradual expansion is rarely malicious but it is often invisible to customers. Product teams are incentivized to collect more data and add features while security teams may only revisit vendor risk during periodic reviews. The result is a slow drift in data exposure that remains largely unnoticed until a breach occurs.
In the Mixpanel case analytics data collected through customer applications was exported into the vendor’s own environment. Once that environment was compromised attackers were able to access and export the data. The breach did not require compromising the customer’s core infrastructure only the trusted third party embedded within it.
Why vendor risk assessments fall short
The incident also highlights fundamental weaknesses in how organizations assess vendor security. Many vendor risk programs still rely heavily on self-attested questionnaires and point-in-time audits. These assessments are often completed by sales or compliance teams rather than engineers with direct insight into code-level behavior.
Even formal attestations such as SOC 2 reports provide only a snapshot of a vendor’s controls at a specific moment in time. They do not account for what changes months later when new scripts SDKs or data flows are introduced. In an environment where software changes continuously static assessments quickly lose relevance.
At the same time organizations continue to increase spending on internal security controls. Yet many of these investments focus on protecting infrastructure networks and cloud environments while overlooking what third-party code is doing inside the browser.
For attackers this imbalance is attractive. Directly targeting a hardened enterprise is difficult even for sophisticated adversaries. Targeting a downstream vendor with fewer defenses can be far easier and often yields access to valuable contextual data that can be leveraged for phishing social engineering or follow-on attacks.
The broader takeaway is not that organizations should abandon third-party tools but that traditional trust-based models are no longer sufficient. Vendor relationships must be treated as dynamic not fixed and security programs must account for how risk evolves after a tool is deployed. The Mixpanel incident serves as a reminder that widely trusted tools can quietly become sources of exposure when changes occur outside a customer’s field of view.
About the Author

Clarence Chio
CEO and Co-founder, Coverbase
Clarence Chio is the CEO and co-founder of Coverbase. He previously co-founded Unit21, a company focused on applying AI to fraud and anti-money laundering challenges in the financial sector. Chio holds degrees in computer science and artificial intelligence from Stanford University, is the author of "Machine Learning and Security" published by O’Reilly Media, and teaches courses on AI and security at the University of California, Berkeley.
