We prove that the closest vector problem with preprocessing (CVPP) is NP-hard to approximate within any factor less than sqrt{5/3}. More specifically, we show that there exists a reduction from an NP-hard problem to the approximate closest vector problem such that the lattice depends only on the size of the original problem, and the specific instance is encoded solely in the target vector. It follows that there are lattices for which the closest vector problem cannot be approximated within factors gamma < sqrt{5/3} in polynomial time, no matter how the lattice is represented, unless NP is equal to P (or NP is contained in P/poly, in case of nonuniform sequences of lattices). The result easily extends to any L_p norm, for p >= 1, showing that CVPP in the L_p norm is hard to approximate within any factor gamma < {5/3}^{1/p}. As an intermediate step, we establish analogous results for the nearest codeword problem with preprocessing (NCPP), proving that for any finite field GF(q), NCPP over GF(q) is NP-hard to approximate within any factor less than 5/3.