To make things concrete, take a simple linear model:
$$E[y \vert x_1, x_2] = \alpha + \beta_1 x_1 +\beta_2 x_2$$
In a one-sided hypothesis test, like $\beta_1 \ge k$ vs. $\beta_1 \lt k$, the confidence interval for $\beta_1$ is unbounded on one side: $[a,+\infty)$ rather than $[a,b]$ (or bounded by the limit of the sample space on one side, like $[a,1]$ with a binary outcome).
If you are interested in the compound null like $\beta_1 \ne 0$ and $\beta_2 \ne 0$, the confidence region now looks like an ellipse.
What does that region look like if you have a one-sided confidence interval for the nulls $\beta_1 \ge k$ and $\beta_2 \le m$?
How does that change if only one of the two hypotheses is one-sided?