No, that doesn't guarantee anything. A density matrix must have non-negative eigenvalues and unit trace. Say you have a matrix $D$ that has been factorized into two matrices:
$$
D = A \otimes B
$$
Then for $D$ to be a density operator, you have to satisfy two conditions:
- $\text{Tr}(D) = \text{Tr}(A) \text{Tr}(B) = 1$
- $D\geq 0$ (or $A \otimes B \geq 0$)
where $D\geq 0$ is shorthand for "$D$ is a positive semidefinite operator". Notice you don't necessarily need $A\geq 0$ and $\text{Tr}(A) = 1$, for instance $A = -2 \mathbb{I}_2$ and $B = -\mathbb{I}_2/8$ would produce a valid density operator if $A$ and $B$ are both qubit operators.
You can slightly refine the above conditions on $A$ and $B$, which might be useful for numerical work. In our setting, $D\geq 0$ implies $D^\dagger = D$, which further implies $A=A^\dagger$ and $B=B^\dagger$. This means $A$ and $B$ are diagonalizable with real eigenvalues. Now, suppose either $A$ or $B$ possess negative eigenvalues. Then the only way to get $D \geq 0$ is either:
- $A\geq 0$ and $B \geq 0$
- $A \leq 0$ and $B \leq 0$
So, conversely, $D$ is not a density matrix if any of the following conditions is true:
- $\text{Tr}(A) \text{Tr}(B) \neq 1$
- Exactly one of the following holds: $A \leq 0$ or $B\leq 0$ (but not both)
Unfortunately, you can't escape the task of testing the negativity of eigenvalues for the component matrices, but these rejection criteria means that sometimes you'll only have to check the smallest eigenvalue of just $A$, instead of $D$.