We prove new hardness results for fundamental lattice problems under the Exponential Time Hypothesis (ETH). Building on a recent breakthrough by Bitansky et al. [BHIRW24], who gave a polynomial-time reduction from $\mathsf{3SAT}$ to the (gap) $\mathsf{MAXLIN}$ problem-a class of CSPs with linear equations over finite fields-we derive ETH-hardness for several lattice problems. First, we show that for any $p \in [1, \infty)$, there exists an explicit constant $γ> 1$ such that $\mathsf{CVP}_{p,γ}$ (the $\ell_p$-norm approximate Closest Vector Problem) does not admit a $2^{o(n)}$-time algorithm unless ETH is false. Our reduction is deterministic and proceeds via a direct reduction from (gap) $\mathsf{MAXLIN}$ to $\mathsf{CVP}_{p,γ}$. Next, we prove a randomized ETH-hardness result for $\mathsf{SVP}_{p,γ}$ (the $\ell_p$-norm approximate Shortest Vector Problem) for all $p > 2$. This result relies on a novel property of the integer lattice $\mathbb{Z}^n$ in the $\ell_p$ norm and a randomized reduction from $\mathsf{CVP}_{p,γ}$ to $\mathsf{SVP}_{p,γ'}$. Finally, we improve over prior reductions from $\mathsf{3SAT}$ to $\mathsf{BDD}_{p, α}$ (the Bounded Distance Decoding problem), yielding better ETH-hardness results for $\mathsf{BDD}_{p, α}$ for any $p \in [1, \infty)$ and $α> α_p^{\ddagger}$, where $α_p^{\ddagger}$ is an explicit threshold depending on $p$. We additionally observe that prior work implies ETH hardness for the gap minimum distance problem ($γ$-$\mathsf{MDP}$) in codes.