• The evidence comes from what developers actually hit, not lab experiments: 1.1M posts across 29 subreddits, narrowed to 446 posts about security and privacy in AI-first IDEs, with 6,000+ comments coded into a taxonomy.
• The headline finding is that most reported problems trace to system-level design choices in the IDE itself, like what user data it can reach and which actions it takes unchecked, rather than to the underlying model. Swapping models will not fix them.
• Developers defend themselves with external measures rather than the tool's own controls: sandboxing the code and manually reviewing what the agent does. That workaround pattern is itself the study's measure of how little they trust these IDEs.

• LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
• sandbox — An isolated environment where AI-generated code or agent actions run without being able to touch anything real.
• AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.

The agentic IDE holding your credentials and source is itself a vulnerability surface.

• articleUsing LLMs to Secure Source CodeEugene Yan
• postLLMs still produce bugs, but those bugs are different than what they used to be.Boris Cherny
• articleDeepsecBenchMalte Ubl

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