If the private exponent $d$ has very low Hamming weight, it will be easy to break the scheme.
Suppose that $d$ has weight $w$, and is $m$ bits wide. @Antimony already explained how to break it in $m \choose w$ time. I'll show how to break it even faster, using a birthday-style technique. My algorithm takes about $2.5 \sqrt{w} {m/2 \choose w/2}$ time, which is quite a bit faster. For instance, if $d$ is a 1024-bit exponent with Hamming weight 10, then @Antimony's method will take about $2^{78}$ steps of computation, whereas my method will take about $2^{41}$ steps of computation.
Start by writing $d=d'+d''$, where $d'$ has its low $m/2$ bits all zero, and $d''$ has its high $m/2$ bits all zero. We'll hope that both $d'$ and $d''$ have Hamming weight $w/2$ (this happens with probability about ${w \choose w/2}/2^w$, which is fairly large; I'll describe later how to remove this requirement).
Pick a random value $x$, and let $y=x^e$. Note that
$$y^d = x.$$
It follows that
$$y^{d'} = x/y^{d''}.$$
My algorithm will iterative over all possible values of $d'$, and store the corresponding value of $y^{d'}$ in a hash table. Then, it will iterate over all possible values of $d''$, and look up $x/y^{d''}$ in the hash table. If it finds a match in the hashtable, then it has found both $d$ and $d''$, and thus recovered the private exponent $d=d'+d''$.
The running time is $m/2 \choose w/2$ steps to populate the hashtable, and another $m/2 \choose w/2$ steps to look up entries, for a total running time of $2 {m/2 \choose w/2}$.
What's the success probability? This succeeds if half of the 1-bits of $d$ fall in its high $m/2$ bits, and half fall in the low $m/2$ bits. This happens with probability ${w \choose w/2}/2^w$, so this algorithm succeeds in recovering $d$ with probability about ${w \choose w/2}/2^w$. Using Stirling's formula, the success probability is about $1/\sqrt{\pi w/2}$.
What if the algorithm doesn't succeed? Well, then we try it again, but with a different way of splitting the $m$ bit positions into two sets. Above, I described it as a split with one set containing the high $m/2$ bits and the other set containing the low $m/2$ bits. However, we can generalize the algorithm and apply it, given any way of partitioning the $m$ bit positions into two sets, each of size $m/2$. Each such partition has about a $1/\sqrt{\pi w/2}$ probability of revealing $d$, so we can repeatedly try many random partitions, and after about $\sqrt{\pi w/2}$ trials, we expect to find one that reveals $d$. Thus, the total running time is $2 \sqrt{\pi w/2} {m/2 \choose w/2} \approx 2.5 \sqrt{w} {m/2 \choose w/2}$.