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Date: Thu, 26 May 2016 13:37:09 -0700
From: Thomas Garnier <thgarnie@...gle.com>
To: Christoph Lameter <cl@...ux.com>,
Pekka Enberg <penberg@...nel.org>,
David Rientjes <rientjes@...gle.com>,
Joonsoo Kim <iamjoonsoo.kim@....com>,
Andrew Morton <akpm@...ux-foundation.org>,
"Paul E . McKenney" <paulmck@...ux.vnet.ibm.com>,
Pranith Kumar <bobby.prani@...il.com>,
David Howells <dhowells@...hat.com>,
Tejun Heo <tj@...nel.org>,
Johannes Weiner <hannes@...xchg.org>,
David Woodhouse <David.Woodhouse@...el.com>,
Thomas Garnier <thgarnie@...gle.com>,
Petr Mladek <pmladek@...e.com>,
Kees Cook <keescook@...omium.org>
Cc: linux-mm@...ck.org,
linux-kernel@...r.kernel.org,
gthelen@...gle.com,
kernel-hardening@...ts.openwall.com
Subject: [PATCH v1 0/2] mm: SLUB Freelist randomization
This is PATCH v1 for the SLUB Freelist randomization. The patch is now based
on the Linux master branch (as the based SLAB patch was merged).
Changes since RFC v2:
- Redone slab_test testing to decide best entropy approach on new page
creation.
- Moved to use get_random_int as best approach to still use hardware
randomization when available but lower cost when not available.
- Update SLAB implementation to use get_random_long and get_random_int
on refactoring.
- Updated testing that highlight 3-4% impact on slab_test for direct
testing on non-smp, 100000 iterations.
- Updated commit messages based on feedback.
- Use unsigned int* for random_seq for both SLUB & SLAB.
***Background:
This proposal follows the previous SLAB Freelist patch submitted to next.
It resuses parts of previous implementation and keep a similar approach.
The kernel heap allocators are using a sequential freelist making their
allocation predictable. This predictability makes kernel heap overflow
easier to exploit. An attacker can careful prepare the kernel heap to
control the following chunk overflowed.
For example these attacks exploit the predictability of the heap:
- Linux Kernel CAN SLUB overflow (https://goo.gl/oMNWkU)
- Exploiting Linux Kernel Heap corruptions (http://goo.gl/EXLn95)
***Problems that needed solving:
- Randomize the Freelist (singled linked) used in the SLUB allocator.
- Ensure good performance to encourage usage.
- Get best entropy in early boot stage.
***Parts:
- 01/02 Reorganize the SLAB Freelist randomization to share elements
with the SLUB implementation.
- 02/02 The SLUB Freelist randomization implementation. Similar approach
than the SLAB but tailored to the singled freelist used in SLUB.
***Performance data:
slab_test impact is between 3% to 4% on average for 100000 attemps
wihout smp. It is a very focused testing, kernbench show the overall
impact on the system is way lower.
Before:
Single thread testing
=====================
1. Kmalloc: Repeatedly allocate then free test
100000 times kmalloc(8) -> 49 cycles kfree -> 77 cycles
100000 times kmalloc(16) -> 51 cycles kfree -> 79 cycles
100000 times kmalloc(32) -> 53 cycles kfree -> 83 cycles
100000 times kmalloc(64) -> 62 cycles kfree -> 90 cycles
100000 times kmalloc(128) -> 81 cycles kfree -> 97 cycles
100000 times kmalloc(256) -> 98 cycles kfree -> 121 cycles
100000 times kmalloc(512) -> 95 cycles kfree -> 122 cycles
100000 times kmalloc(1024) -> 96 cycles kfree -> 126 cycles
100000 times kmalloc(2048) -> 115 cycles kfree -> 140 cycles
100000 times kmalloc(4096) -> 149 cycles kfree -> 171 cycles
2. Kmalloc: alloc/free test
100000 times kmalloc(8)/kfree -> 70 cycles
100000 times kmalloc(16)/kfree -> 70 cycles
100000 times kmalloc(32)/kfree -> 70 cycles
100000 times kmalloc(64)/kfree -> 70 cycles
100000 times kmalloc(128)/kfree -> 70 cycles
100000 times kmalloc(256)/kfree -> 69 cycles
100000 times kmalloc(512)/kfree -> 70 cycles
100000 times kmalloc(1024)/kfree -> 73 cycles
100000 times kmalloc(2048)/kfree -> 72 cycles
100000 times kmalloc(4096)/kfree -> 71 cycles
After:
Single thread testing
=====================
1. Kmalloc: Repeatedly allocate then free test
100000 times kmalloc(8) -> 57 cycles kfree -> 78 cycles
100000 times kmalloc(16) -> 61 cycles kfree -> 81 cycles
100000 times kmalloc(32) -> 76 cycles kfree -> 93 cycles
100000 times kmalloc(64) -> 83 cycles kfree -> 94 cycles
100000 times kmalloc(128) -> 106 cycles kfree -> 107 cycles
100000 times kmalloc(256) -> 118 cycles kfree -> 117 cycles
100000 times kmalloc(512) -> 114 cycles kfree -> 116 cycles
100000 times kmalloc(1024) -> 115 cycles kfree -> 118 cycles
100000 times kmalloc(2048) -> 147 cycles kfree -> 131 cycles
100000 times kmalloc(4096) -> 214 cycles kfree -> 161 cycles
2. Kmalloc: alloc/free test
100000 times kmalloc(8)/kfree -> 66 cycles
100000 times kmalloc(16)/kfree -> 66 cycles
100000 times kmalloc(32)/kfree -> 66 cycles
100000 times kmalloc(64)/kfree -> 66 cycles
100000 times kmalloc(128)/kfree -> 65 cycles
100000 times kmalloc(256)/kfree -> 67 cycles
100000 times kmalloc(512)/kfree -> 67 cycles
100000 times kmalloc(1024)/kfree -> 64 cycles
100000 times kmalloc(2048)/kfree -> 67 cycles
100000 times kmalloc(4096)/kfree -> 67 cycles
Kernbench, before:
Average Optimal load -j 12 Run (std deviation):
Elapsed Time 101.873 (1.16069)
User Time 1045.22 (1.60447)
System Time 88.969 (0.559195)
Percent CPU 1112.9 (13.8279)
Context Switches 189140 (2282.15)
Sleeps 99008.6 (768.091)
After:
Average Optimal load -j 12 Run (std deviation):
Elapsed Time 102.47 (0.562732)
User Time 1045.3 (1.34263)
System Time 88.311 (0.342554)
Percent CPU 1105.8 (6.49444)
Context Switches 189081 (2355.78)
Sleeps 99231.5 (800.358)
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