Minimax algorithm for tic tac toe doesnt give optimal solution - c++

Question

I am writing 3D tic tac toe game using minimax algorithm with alpha beta pruning, but the algorithm doesnt give optimal solution, it goes and chooses next possible solution from winning states, not taking into concern what is on the board, meaning it wont block my moves.
This is the code:
`
int Game::miniMax(char marker, int depth, int alpha, int beta){
// Initialize best move
bestMove = std::make_tuple(-1, -1, -1);
// If we hit a terminal state (leaf node), return the best score and move
if (isBoardFull() || getBoardState('O')!=0 || depth>5)
return getBoardState('O');
auto allowedMoves = getAllowedMoves();
for (int i = 0; i < allowedMoves.size(); i++){
auto move = allowedMoves[i];
board[std::get<0>(move)][std::get<1>(move)][std::get<2>(move)] = marker;
// Maximizing player's turn
if (marker == 'O'){
int bestScore = INT32_MIN;
int score = miniMax('X', depth + 1, alpha, beta);
// Get the best scoring move
if (bestScore <= score){
bestScore = score - depth * 10;
bestMove = move;
// Check if this branch's best move is worse than the best
// option of a previously search branch. If it is, skip it
alpha = std::max(alpha, bestScore);
board[std::get<0>(move)][std::get<1>(move)][std::get<2>(move)] = '-';
if (beta <= alpha){
break;
}
}
} // Minimizing opponent's turn
else{
int bestScore = INT32_MAX;
int score = miniMax('O', depth + 1, alpha, beta);
if (bestScore >= score){
bestScore = score + depth * 10;
bestMove = move;
// Check if this branch's best move is worse than the best
// option of a previously search branch. If it is, skip it
beta = std::min(beta, bestScore);
board[std::get<0>(move)][std::get<1>(move)][std::get<2>(move)] = '-';
if (beta <= alpha){
break;
}
}
}
board[std::get<0>(move)][std::get<1>(move)][std::get<2>(move)] = '-'; // Undo move
}
if(marker== 'O')
return INT32_MIN;
else
return INT32_MAX;
}
`
What do I need to change to make it work?
I tried other ways to implement minimax, but it doesnt give optimal, or any, solution.
The limit on depth is because it is too slow for bigger depths, but still not giving solution, also increasing the value of the constant that multiplies the depth in the score part is only slowing the program