diff --git a/Eigen/src/CholmodSupport/CholmodSupport.h b/Eigen/src/CholmodSupport/CholmodSupport.h
index 447a393a1..e5b46c4ca 100644
--- a/Eigen/src/CholmodSupport/CholmodSupport.h
+++ b/Eigen/src/CholmodSupport/CholmodSupport.h
@@ -329,8 +329,10 @@ class CholmodBase : public SparseSolverBase<Derived> {
     cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
     internal::cm_factorize_p<StorageIndex>(&A, m_shiftOffset, 0, 0, m_cholmodFactor, m_cholmod);
 
-    // If the factorization failed, minor is the column at which it did. On success minor == n.
-    this->m_info = (m_cholmodFactor->minor == m_cholmodFactor->n ? Success : NumericalIssue);
+    // If the factorization failed, either the input matrix was zero (so m_cholmodFactor == nullptr), or minor is the
+    // column at which it failed. On success minor == n.
+    this->m_info =
+        (m_cholmodFactor != nullptr && m_cholmodFactor->minor == m_cholmodFactor->n ? Success : NumericalIssue);
     m_factorizationIsOk = true;
   }
 
diff --git a/test/cholmod_support.cpp b/test/cholmod_support.cpp
index 24126a079..066674950 100644
--- a/test/cholmod_support.cpp
+++ b/test/cholmod_support.cpp
@@ -54,6 +54,13 @@ void test_cholmod_ST() {
   check_sparse_spd_determinant(llt_colmajor_upper);
   check_sparse_spd_determinant(ldlt_colmajor_lower);
   check_sparse_spd_determinant(ldlt_colmajor_upper);
+
+  check_sparse_zero_matrix(chol_colmajor_lower);
+  check_sparse_zero_matrix(chol_colmajor_upper);
+  check_sparse_zero_matrix(llt_colmajor_lower);
+  check_sparse_zero_matrix(llt_colmajor_upper);
+  check_sparse_zero_matrix(ldlt_colmajor_lower);
+  check_sparse_zero_matrix(ldlt_colmajor_upper);
 }
 
 template <typename T, int flags, typename IdxType>
diff --git a/test/sparse_solver.h b/test/sparse_solver.h
index e7518e4e5..033df835f 100644
--- a/test/sparse_solver.h
+++ b/test/sparse_solver.h
@@ -484,6 +484,15 @@ void check_sparse_spd_determinant(Solver& solver) {
   }
 }
 
+template <typename Solver>
+void check_sparse_zero_matrix(Solver& solver) {
+  typedef typename Solver::MatrixType Mat;
+
+  Mat A(1, 1);
+  solver.compute(A);
+  VERIFY_IS_EQUAL(solver.info(), NumericalIssue);
+}
+
 template <typename Solver, typename DenseMat>
 Index generate_sparse_square_problem(Solver&, typename Solver::MatrixType& A, DenseMat& dA, int maxSize = 300,
                                      int options = ForceNonZeroDiag) {