API Leakage: 3 Live Keys Found in 27k Prompts

A dataset of 27,000 ChatGPT prompts contained 3 live API keys in plain text, according to a report highlighting the security risk of developers pasting sensitive credentials into large language model contexts. The article recommends sanitizing inputs and using a security-focused system prompt to detect secrets before submission.

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/