It took some digging but I found the answers in an old email thread. The paper linked there is archived here.
$$E_{\mu}(x,\lambda,z) = \max \Big\{ \frac{\| \nabla f(x) + \nabla c(x)\lambda + z \|_\infty}{s_d}, \|c(x)\|_\infty,\frac{\| \text{Diag}(x)\text{Diag(z)}e-\mu e\|_\infty}{s_c} \Big\}$$
Is the the overall NLP error. Dual infeasibility is calculated by $$\| \nabla f(x) + \nabla c(x)\lambda + z \|_\infty$$
The scalings $s_d$, $s_c$ are explained in the paper on page four. A $s_d$ value of around $50$ would explain your observation, such a value is allowed to occur. For the meaning of these in the constraint satisfaction case just think $\nabla f(x) = 0$.
I haven't confirmed numerically if this always holds, so let me know if you have issues. Then someone would have to dive into the code of IpOpt to find the true answer.