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-rw-r--r--docs/binaryonly_fuzzing.txt12
1 files changed, 6 insertions, 6 deletions
diff --git a/docs/binaryonly_fuzzing.txt b/docs/binaryonly_fuzzing.txt
index ed654e2a..f370ec74 100644
--- a/docs/binaryonly_fuzzing.txt
+++ b/docs/binaryonly_fuzzing.txt
@@ -43,7 +43,8 @@ insert instructions, which changes addresses in the process space and that
everything still works afterwards. Hence more often than not binaries
crash when they are run.
-The speed decrease is about 25-35%
+The speed decrease is about 15-35%, depending on the optimization options
+used with afl-dyninst.
So if dyninst works, its the best option available. Otherwise it just doesn't
work well.
@@ -55,10 +56,9 @@ INTEL-PT
--------
The big issue with Intel's PT is the small buffer size and the complex
encoding of the debug information collected through PT.
-This makes the decoding very CPU intensive, hence slow and using up twice
-the CPU resources. So to fairly compare Intel PT based afl fuzzers with
-native afl or afl qemu we need to calculate in the higher CPU resources used.
-As a result, the overall speed decrease is about 85-90%
+This makes the decoding very CPU intensive and hence slow.
+As a result, the overall speed decrease is about 70-90% (depending on
+the implementation and other factors)
there are two afl intel-pt implementations:
@@ -67,7 +67,7 @@ there are two afl intel-pt implementations:
2. https://github.com/hunter-ht-2018/ptfuzzer
=> this needs a 4.14 or 4.15 kernel. the "nopti" kernel boot option must
- be used
+ be used. This one is faster than the other.
CORESIGHT