Recent reports have confirmed that the Acting Director of the Cybersecurity and Infrastructure Security Agency (CISA), Madhu Gottumukkala, uploaded several sensitive “For Official Use Only” (FOUO) documents to a public version of ChatGPT. While the documents were not classified, they contained sensitive contracting information not intended for public release. Although the Director had requested a temporary exception to use the tool, the incident triggered automated security alerts because the data was uploaded to a public platform rather than a protected, agency-approved environment.
This incident highlights a critical “Shadow AI” risk: the tendency for even the most security-conscious professionals to bypass established guardrails for the sake of convenience or productivity.
Bridging the Gap Between Policy and Practice
For many organizations, the disconnect between executive-level goals and day-to-day security compliance is a major vulnerability. We often see leadership teams inadvertently normalize the use of public AI tools without applying the same rigor used for other enterprise systems. Engaging Virtual CISO (vCISO) services can help bridge this gap by establishing governance frameworks that are both practical and inclusive. A vCISO ensures that security policies are not just a set of rules on a shelf, but are integrated into the workflow of every department, including the executive suite.
Technical Guardrails and Visibility
The CISA leak was detected because automated sensors were in place to flag the movement of sensitive data. This underscores the necessity of Security Configuration Audits, particularly concerning Data Loss Prevention (DLP) settings. Many organizations have the right tools but haven’t tuned them to recognize or block the “copy-paste” or “file upload” behaviors associated with public AI interfaces. Regularly auditing these configurations ensures your technical defenses stay ahead of evolving user habits.
Proactive Risk Identification
Understanding where your sensitive data lives and how it moves is the foundation of a strong defense. We recommend conducting a Best Practice Strategic Security Assessment or a targeted Risk Assessment to identify potential exposure points. These assessments look beyond traditional malware to examine how emerging technologies like Generative AI might be creating new, unmonitored pathways for data egress. By identifying these “exception pathways” early, you can provide safer, governed alternatives for your team.
Cultivating a Security-First Culture
Ultimately, security is a human challenge. This incident serves as a perfect case study for your next Security Awareness Training session. It demonstrates that the risk is not just about “bad actors” but about well-intentioned employees making mistakes with new tools. Training should focus on the specific risks of public LLMs, such as how OpenAI may retain and use uploaded data for model training, effectively making your private company data part of the public domain.
Other AI News We’re Tracking
- Malicious AI “Skills”: We are monitoring reports regarding “OpenClaw,” an open-source AI agent system. Recent warnings highlight security risks where malicious “skills” or third-party plugins could be used to exfiltrate data from the environments where these agents are deployed. This represents a shift in supply chain attacks, moving from traditional software libraries to the emerging ecosystem of AI plugins.
- Deepfake Financial Fraud: A recent report from Arup details a staggering $25 million loss due to a deepfake video call where an employee was convinced by “digital clones” of their CFO and colleagues to authorize multiple transfers. This highlights the need for multi-factor authorization processes that go beyond visual or vocal confirmation.
