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When exploiting memory vulnerabilities, "heap spraying" is a common
technique targeting those related to dynamic memory allocation (i.e. the
"heap"), and it plays an important role in a successful exploitation.
Basically, it is to overwrite the memory area of vulnerable object by
triggering allocation in other subsystems or modules and therefore
getting a reference to the targeted memory location. It's usable on
various types of vulnerablity including use after free (UAF), heap out-
of-bound write and etc.
There are (at least) two reasons why the heap can be sprayed: 1) generic
slab caches are shared among different subsystems and modules, and
2) dedicated slab caches could be merged with the generic ones.
Currently these two factors cannot be prevented at a low cost: the first
one is a widely used memory allocation mechanism, and shutting down slab
merging completely via `slub_nomerge` would be overkill.
To efficiently prevent heap spraying, we propose the following approach:
to create multiple copies of generic slab caches that will never be
merged, and random one of them will be used at allocation. The random
selection is based on the address of code that calls `kmalloc()`, which
means it is static at runtime (rather than dynamically determined at
each time of allocation, which could be bypassed by repeatedly spraying
in brute force). In other words, the randomness of cache selection will
be with respect to the code address rather than time, i.e. allocations
in different code paths would most likely pick different caches,
although kmalloc() at each place would use the same cache copy whenever
it is executed. In this way, the vulnerable object and memory allocated
in other subsystems and modules will (most probably) be on different
slab caches, which prevents the object from being sprayed.
Meanwhile, the static random selection is further enhanced with a
per-boot random seed, which prevents the attacker from finding a usable
kmalloc that happens to pick the same cache with the vulnerable
subsystem/module by analyzing the open source code. In other words, with
the per-boot seed, the random selection is static during each time the
system starts and runs, but not across different system startups.
The overhead of performance has been tested on a 40-core x86 server by
comparing the results of `perf bench all` between the kernels with and
without this patch based on the latest linux-next kernel, which shows
minor difference. A subset of benchmarks are listed below:
sched/ sched/ syscall/ mem/ mem/
messaging pipe basic memcpy memset
(sec) (sec) (sec) (GB/sec) (GB/sec)
control1 0.019 5.459 0.733 15.258789 51.398026
control2 0.019 5.439 0.730 16.009221 48.828125
control3 0.019 5.282 0.735 16.009221 48.828125
control_avg 0.019 5.393 0.733 15.759077 49.684759
experiment1 0.019 5.374 0.741 15.500992 46.502976
experiment2 0.019 5.440 0.746 16.276042 51.398026
experiment3 0.019 5.242 0.752 15.258789 51.398026
experiment_avg 0.019 5.352 0.746 15.678608 49.766343
The overhead of memory usage was measured by executing `free` after boot
on a QEMU VM with 1GB total memory, and as expected, it's positively
correlated with # of cache copies:
control 4 copies 8 copies 16 copies
total 969.8M 968.2M 968.2M 968.2M
used 20.0M 21.9M 24.1M 26.7M
free 936.9M 933.6M 931.4M 928.6M
available 932.2M 928.8M 926.6M 923.9M
Co-developed-by: Xiu Jianfeng <xiujianfeng@huawei.com>
Signed-off-by: Xiu Jianfeng <xiujianfeng@huawei.com>
Signed-off-by: GONG, Ruiqi <gongruiqi@huaweicloud.com>
Reviewed-by: Kees Cook <keescook@chromium.org>
Reviewed-by: Hyeonggon Yoo <42.hyeyoo@gmail.com>
Acked-by: Dennis Zhou <dennis@kernel.org> # percpu
Signed-off-by: Vlastimil Babka <vbabka@suse.cz>
3c61529405