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"with the agent's credentials." - so you are surprised that agent can respond with private repository details when it has access to it? WoW! anyone and anything with credentials can access it. Github action, Jenkins, me.

"injected" is so fancy word to describe prompting - one thing that LLMs are made to do - respond to a prompt.

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The "surprise" is not that the agent can respond with private repository details, it's that it can receive and act upon prompts issued by someone other than the person running the agent, hence "prompt _injection_".

Or to come back to the SQL injection analogy, no one is surprised that the web app can query the database for password hashes. The surprise is that it can be instructed to do so when loading the next image in a carousel.

Did you read the article?

The attack is not via the prompt the victim types to the AI, but via [text in an issue or PR in the repo] that the victim is unaware about.

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