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October 02, 2026 - 09:48 AM
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  This highlights a growing situation: LLMs skilled on insecure code may inadvertently generate unsafe outputs. Last month, we printed a submit about Large Language Models (LLMs) instructing developers to hardcode API keys. That received us questioning: why is that this occurring at scale and across different LLMs? A logical starting point: the coaching knowledge itself. While we can’t entry proprietary datasets, many are publicly accessible. Popular LLMs, together with DeepSeek, are trained on Common Crawl, an enormous dataset containing webpage snapshots. Given our expertise finding uncovered secrets and techniques on the general public internet, we suspected that hardcoded credentials may be current in the coaching knowledge, potentially influencing model habits. To check this, we downloaded the December 2024 Common Crawl archive (four hundred terabytes of net information from 2.67 billion net pages) and scanned it with TruffleHog, our open-source secret scanner. Note: We understand that LLM behavior is influenced by a number of elements - coaching knowledge is only one. Our purpose is to spotlight how ceaselessly hardcoded credentials appear in one of many most generally-used LLM training datasets and spark a discussion on securing AI-generated code.
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October 02, 2026 - 09:47 AM
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