The most reliable way to stop sensitive data from reaching AI tools is real-time inspection of what's being typed or uploaded, before it leaves the device — combined with a clear, written AI usage policy so employees know what's expected.
Approach 1: Block AI sites outright
Blocking ChatGPT, Claude, and Gemini at the firewall or DNS level stops the leak, but also stops legitimate use — and employees find workarounds (personal devices, phone hotspots, mobile apps) that are harder to see than if you'd left it open with monitoring.
Approach 2: Policy and training alone
A written policy sets expectations, but doesn't stop a mistake in the moment — someone debugging under time pressure pastes a config file without thinking about what's in it. Training reduces the rate, but doesn't eliminate it.
Approach 3: Network-level monitoring
Routing traffic through a proxy to log or inspect it gives visibility, but if the proxy only logs after the fact, the data has already left. And if the proxy is cloud-hosted, the prompt content passes through a third party to get inspected.
Approach 4: Real-time, on-device inspection
Inspecting the prompt on the device, before it's sent, means a sensitive value can be blocked or redacted before it ever leaves — not logged after the fact. This is the approach SafePrompt takes: detection runs locally, and the actual sensitive value is stripped out before anything is written to a log anywhere. See how it works.
A practical combination
- Deploy an agent that inspects prompts locally and blocks or redacts known-sensitive patterns by default.
- Add custom rules for anything specific to your business (codenames, customer lists, internal domains).
- Keep AI tools accessible rather than blocked — the goal is safe use, not no use.
- Review the activity log periodically to catch patterns worth addressing with training.
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