The Invisible Data Leak

Common web chat AI tools can inadvertently expose sensitive business information. A product marketer’s quick task of drafting content using internal documents can lead to a long journey of that data through remote servers, where it is retained, reviewed, and used for training by AI models. This process can happen even if the user believes the data is gone after closing a tab.

The document details specific ways data leaks occur. These include AI bots remembering inputs, prompt injection vulnerabilities where bots can be tricked into revealing secrets, and inadequate access boundaries for internal data. It also covers the risks of unlocked plain text storage in databases, server-side request forgery, and sensitive data passing through leaky third-party middleware.

Adamiro’s platform addresses these vulnerabilities by cutting off the data retention chain at the source. It uses direct connections to foundation model providers under strict enterprise terms. Data is processed in private memory sessions, never retained for vendor training, and not reviewed by human contractors. Adamiro also employs field-level encryption, strict network filters, and isolates stored data at the organization and account level.

Beyond platform security, teams must practice sound daily security habits. These include keeping raw credentials out of prompt boxes, carefully inspecting imported web content for hidden text, and regularly updating platform connections. Setting team account limits and checking audit logs to ensure permissions match user responsibilities are also crucial steps for maintaining data privacy.

• How web chat AI remembers what you tell it
• Methods to trick AI bots into revealing secrets
• Risks of inadequate access boundaries for internal data
• Vulnerabilities of unlocked plain text in database storage
• How servers can be tricked into scanning internal networks
• Dangers of passing secrets through third-party middleware