# API Leakage: 3 Live Keys Found in 27k Prompts

> Source: <https://promptcube3.com/en/threads/2282/>
> Published: 2026-07-23 12:01:47+00:00

# API Leakage: 3 Live Keys Found in 27k Prompts

[ChatGPT](/en/tags/chatgpt/)reveals a worrying trend: sensitive credentials are still leaking into LLM contexts. Out of that dataset, 3 live API keys were discovered sitting in plain text.

This is a classic case of "convenience over security." Developers often paste entire config files or environment snippets into a chat to debug a connection error, forgetting that once that data hits the prompt, it's part of the session history and potentially the model's training telemetry.

To stop this, you need a strict prompt engineering habit of sanitizing inputs. Instead of pasting raw code, use a placeholder pattern.

Here is a simple system prompt I use to force my AI assistants to remind me to scrub data, or to help me generate "safe" versions of my configs for debugging:

```
You are a Security-First Technical Assistant. Whenever I provide a code snippet or configuration file for debugging, your first priority is to identify potential secrets (API keys, passwords, tokens). 

If you detect a potential secret:
1. Alert me immediately at the top of your response.
2. Provide a "Sanitized Version" of my code where all sensitive values are replaced with placeholders like `YOUR_API_KEY_HERE`.
3. Proceed with the technical analysis using the sanitized version.

Example output format:
⚠️ SECURITY ALERT: Potential API Key detected.
---
[Sanitized Code Block]
---
[Technical Analysis]
```

The logic here is simple: by making the AI the "security auditor," you create a feedback loop that trains you to stop pasting raw keys. For anyone building a real-world AI workflow, implementing a pre-processing script that regex-scans for common key patterns (like `sk-`

for OpenAI) before the prompt ever leaves your local environment is the only way to be 100% sure.

[Next Echo: Getting Fable-level Results with Open-Weight Models →](/en/threads/2264/)