One in Four Organizations Are Leaking Secrets Through AI Agent Config Files
A Codacy scan of 34,266 repos found credentials, API keys, and system prompts exposed in AI agent config files at 25% of organizations.
Per a thread blowing up on Reddit's r/artificial, Chinese AI lab MiniMax has released M3, a model that scores 83.5 on BrowseComp — beating Claude Opus 4.7's 79.3 on the web-navigation benchmark that has become a key barometer for agentic performance. The model ships with a live API, a one-million-token context window, and open weights reportedly in the pipeline, a combination that would rank it among the most capable open releases of 2026.
The PostTrainBench picture is more nuanced: M3 lands third there, behind Opus 4.7 and GPT-5.5. But benchmarks are a selective mirror, and for developers building agents that browse the web autonomously, BrowseComp is the number that matters.
Open weights would be the larger story. If MiniMax follows through, enterprise teams will have a genuine frontier alternative they can self-host — cutting off the per-token revenue streams Western labs depend on.
Chinese frontier labs have gone from benchmark chasers to benchmark setters in under two years. Washington is paying attention.
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A Codacy scan of 34,266 repos found credentials, API keys, and system prompts exposed in AI agent config files at 25% of organizations.
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