(01/07/17) WARNING: this documentation is out of date (but will be updated soon). In particular, the results presented here are not the latest one obtained with scat and may be different from the recent papers.
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Some results obtained with scat
In a few words, scat
is a python
/C++
tool for reverse-engineering on
binaries in a single execution. It embeds several analysis, such as arity
detection, undertype recovery, etc. The philosophy is to perform each analysis
in one lightweight intrumented execution of a given binary (plus possible
offline analysis). Because scat
works on a single execution, it can only
recover parts of the binary that are actually executed: scat
is not a tool for
exhaustive analysis, it is a tool to analyze what we see.
For now, scat
targets x86_64
binaries on Linux using the System V
ABI.
However, scat
is an implementation of a more general approach that can be
extended to other architectures and/or ABI. This approach is described in a PhD
thesis that will be available online soon.
Originally, scat
was a tool to recover high-level information about functions embedded in an executable
using dynamic analysis. In particular, scat
aimed to recover:
Now, we've made scat
more generic, and it handles several reverse-engineering
functionalities:
- allocator retrieving
- (WIP) simplified use-after-free detection
It is also easy to add your own pintools to scat
to perform your own analysis.
The following sections provide information about each feature of scat
.
scat
embeds an analyzer to retrieve arity of functions.
By arity, we mean two things: first the number of parameters that a function
takes, and second if a function returns a value or not.
scat
infers a simplified notion of type. We indeed consider only three
possible ones: INT
, ADDR
and FLOAT
.
We consider that they represent three different classes of variables that
make sense semantically.
For instance, the size of an integer (char
, short
, int
, long int
)
and weither it is signed or not
does not make a significant difference semantically.
We also introduce a notion of coupling between functions. Intuitively, two functions are coupled if they
interact during the execution. scat
is also able tor recover couples of functions from one execution.
Let's take an example, with four functions (among others) embedded in a binary: alloc
, realloc
, free
and strlen
.
From an execution, we follow the values returned by those four functions, and see if they are given as a parameter to another
function.
Figure 1 - Data flow between functions
In Figure 1, an arrow from A
to B
means that one value returned by A
was given as a parameter to B
.
From this observation, what we want is to invert the information. It means that instead of knowing where the
output goes, we want to know from where parameters come from. So for each function, we compute the proportion
of times a parameter is a value returned by a particular function.
In Figure 2, we see that 70% of the parameters of free
come directly from an output of alloc
. Therefore, in this example
(meaning regarding this execution), alloc
and free
are coupled with a coupling coefficient of 0.7. In the same way, realloc
and alloc
are coupled with a coefficient of 1.
Finding functions coupled with a high coefficient can have different interests.
For example, two functions that are always coupled with a high coefficient are malloc
and free
, or
more generally the allocating and the liberating functions of an allocator. Therefore, the notion
of coupling can be the first step to retrieve custom allocators embedded in binaries (for security purposes,
such as use-after-free detection).
scat > launch couple ./pgm/bin/mupdf-x11 ./testfile.pdf
[*] Launching couple inference on ./pgm/bin/mupdf-x11
[*] /usr/bin/pin/pin -t ./bin/obj-intel64/couple.so -o ./log/mupdf-x11_couple_1452528857.log -i ./log/mupdf-x11_type_1452528848.log -- ./pgm/bin/mupdf-x11 ./testfile.pdf
[*] Inference results logged in ./log/mupdf-x11_couple_1452528857.log
scat > display mupdf-x11 couple
...
(jsV_toobject, newproperty[2]) -- 0.986
(jsV_toobject, insert[2]) -- 0.976
(jsV_toobject, jsV_newobject[3]) -- 0.924
(jsV_toobject, jsV_setproperty[2]) -- 0.986
(jsV_toobject, js_pushobject[2]) -- 0.926
(jsV_toobject, jsR_defproperty[2]) -- 0.986
(jsU_bsearch, fz_new_pixmap_with_data[2]) -- 0.998
(jsU_bsearch, fz_new_pixmap[2]) -- 0.998
(jsU_bsearch, jsP_newnode[4]) -- 0.82
Information about inference
| Last inference: 1970-01-01 01:00:11
| Total number of couples: 899
| Unique left/right-side: 83/244
Memory management in a binary can be handled by a standard allocator (e.g. the libc
allocator)
or by a custom one. For many security and safety analysis focused on memory, the knowledge of
the allocator is a requirement. scat
implements an allocator detection that aim retrieve the two main functions
(ALLOC
, FREE
) of the interface of the main allocator used by a program.
(WIP) We are also currently working on retrieving a third function that is often defined by an allocator: REALLOC
.
scat
uses pin
to instrument dynamically an execution of the program.
This instrumentation aims to be scalable. Some analysis are performed on-the-fly, whereas
others are a two-step process: an online step during which data is collected, and an offline step
to conclude.
scat
performs heuristic-based analysis, meaning that from a theoretical point of view, we cannot ensure
the soundness nor the completeness of the results. However, experiments (see relevant section)
show that these heuristics are well-suited for our purposes.
For details about the heuristics, please refer to our papers.
The goal of scat
is not to recover information about every function embedded on the binary, but
to demonstrate the relevance of our heuristics in a lightweight way. For this reason, scat
only
requires on execution for each of the three steps (arity, type and couple).
Pros. The inference is very lightweight.
Cons. Only functions that are executed at least one can be infered.
Here are presented some results obtained with scat
on several open-source libraries.
First, note that each result is a consequence of one single execution with standard inputs.
Second, the accuracy was obtained by comparison between results given by scat
and the
source code of the binary under inference. This comparison is also performed automatically by scat
if the source
code can be provided (see commands parsedata
and accuracy
in the relevant section.
- #function is the number of functions detected during the one execution we ran.
- accuracy is the percentage of functions (that we detect) for which the arity we infered is consistant with the source code.
midori | grep | mupdf | emacs | |
---|---|---|---|---|
#function | 4094 | 51 | 526 | 591 |
accuracy (%) | 95.8 | 95.6 | 98.7 | 92.4 |
- #function is the number of functions detected during the one execution we ran.
- accuracy is the percentage of functions (that we detect) for which the type of each parameter we infered is consistant with the source code.
midori | grep | mupdf | emacs | |
---|---|---|---|---|
#function | 4094 | 51 | 526 | 591 |
accuracy (%) | 96.2 | 100 | 92.5 | 90.4 |
- #function is the number of functions detected during the one execution we ran.
- T0 is the time of execution with no instrumentation.
- T1 is the time of execution with arity inference.
- T2 is the time of execution with type inference.
grep | tar | a2ps | |
---|---|---|---|
size (KB) | 188 | 346 | 360 |
#function | 46 | 101 | 127 |
T0 (s) | 0.80 | 0.99 | 0.80 |
T1 (s) | 1.70 | 2.64 | 31.6 |
T2 (s) | 1.06 | 1.79 | 13.2 |
scat
requires python 2.7 and is not compatible with python 3.- You need to have
Pin
installed on your computer (official website). - If you want to test the results of inference (see relative section), you also need to have
libclang1-3.4
installed.
$LOCAL_DIR
represents the path to where you want to download scat
.
- Clone this repository:
git clone https://github.com/Frky/scat.git $LOCAL_DIR
- (optional) Create a virtualenv for
scat
:virtualenv ~/.venv/scat && source ~/.venv/scat/bin/activate
- Install required python libraries:
pip install -r requirements.txt
The configuration of scat
is set in a yaml file, namely ./config/config.yaml
. You
can edit this file in order to fit with your own configuration. Main points are:
pin -> bin
: set the path to thePin
executable. Typical value for this is/usr/bin/pin/pin
or/usr/bin/pin/intel64/bin/pinbin
. Required forscat
to work correctly.pin -> path
: set the path to thePin
main directory. May be different from the path to the executable. Typical value for this is/usr/bin/pin/
. Required forscat
to work correctly.log -> path
: set the path to the log directory.
If you use an esoteric linux distribution (e.g. ArchLinux), it may not be supported by Pin
explicitly.
If so, you can add the command line argument -ifeellucky
to Pin
by setting the entry pin -> cli-options
in the configuration file.
If you're linux distribution uses a recent gcc version, you may encounter this kind of errors when trying to compile the pintool.
To fix this, you can add the gcc flags -fabi-version=2 -D_GLIBCXX_USE_CXX11_ABI=0
by setting the entry pin -> compile-flags
in the configuration file.
pin:
path: /usr/bin/pin
bin: /usr/bin/pin/pin
cli-options: -ifeellucky
pintool:
arity:
src: ./src/pintool/arity.cpp
obj: ./bin/obj-intel64/arity.so
type:
src: ./src/pintool/type.cpp
obj: ./bin/obj-intel64/type.so
prev_step: arity
couple:
src: ./src/pintool/couple.cpp
obj: ./bin/obj-intel64/couple.so
alloc:
src: ./src/pintool/alloc.cpp
obj: ./bin/obj-intel64/alloc.so
res:
path: ./res
log:
path: ./log
clang:
lib-path: /usr/lib/x86_64-linux-gnu/libclang.so.1
data-path: ./data/
Run scat
(from your virtualenv): ./scat.py
. You are now in th scat
shell, where you can launch inference
on different binaries and display results.
Before being able to launch any inference, you must compile pintools with the command make:
- make [-f] [-d] [-t] [pintools...]
where:
- -f --force -B : Force compilation even if already up to date
- -d --debug : Compile in debug mode
- -t --trace : Compile in trace mode (Warning: very verbose ! Mostly useful when debugging segfault)
Note: This actually use the os command make under the hood, thus tools will only be compiled after changes.
scat > make
[*] Compiling pintool: arity ...
[*] => Done !
[*] Compiling pintool: type ...
[*] => Up to date !
To perform an inference driven by a pintool, use launch
followed by the name of the inference (relatively to the configuration file).
Examples:
launch arity $PGM
: launch arity inference on$PGM
, where$PGM
is an executable and its arguments if any.launch type $PGM
: launch type inference on$PGM
. Note that it requires that arity inference was previously run on the same program.launch couple $PGM
: launch couple inference on$PGM
. Note that it requires that type inference was previously run on the same program.
scat > launch arity grep -r "def" ./src
[*] Launching arity inference on grep
[*] /usr/bin/pin/pin -t ./bin/obj-intel64/arity.so -o ./log/grep_arity_1451915233.log -- grep -r "def" ./
[*] Inference results logged in ./log/grep_arity_1451915233.log
scat > launch type grep -R "def" ./
[*] Launching type inference on grep
[*] /usr/bin/pin/pin -t ./bin/obj-intel64/type.so -o ./log/grep_type_1451915649.log -i ./log/grep_arity_1451915233.log -- grep -R "def" ./
[*] Inference results logged in ./log/grep_type_1451915649.log
display $PGM $INF
: show the results of the last inference$INF
on the program$PGM
.$INF
can be eitherarity
,type
orcouple
.
scat > display grep arity
('rpl_fcntl', 3, 0, 0, 1) [grep@0x421446]
('reset', 2, 0, 0, 1) [grep@0x40353b]
('safe_hasher', 2, 0, 0, 1) [grep@0x416c17]
('hash_delete', 2, 0, 0, 1) [grep@0x417ff4]
('dup_safer', 1, 0, 0, 1) [grep@0x421420]
('set_binary_mode', 2, 0, 0, 1) [grep@0x415585]
('kwsexec', 4, 0, 0, 1) [grep@0x413fd2]
...
Information about inference
| Last inference: 2016-07-19 15:06:15
| Total functions infered: 123
scat > display grep type
addr fts_alloc(addr, addr, int);
void pr_sgr_start_if(int);
int kwsexec(addr, addr, int, addr);
void setbit(int, addr);
void print_sep(int);
addr strcmp(addr, addr);
int tr(int, int);
int EGexecute(addr, int, addr, int);
int undossify_input(addr, int);
addr _dl_fixup(int, int);
...
Information about inference
| Last inference: 2016-07-21 14:53:05
| Total functions infered: 38
In order to check the accuracy of inference, some metadata (mainly functions prototypes) needs to be retrieved beforehand for comparison. scat use two sources to retrieve these metadata :
- Debug info stored in the binary using the dwarf debug format
- Source code info using clang library for parsing
These two methods are more complementary than interchangeable as they both retrieve informations that the other does not.
Pitfall: For the accuracy command to work properly, the program has to be compiled in debug mode (For two reasons : to ensure all functions name are available and for the debug informations retrieval to work).
-
parsedata $BIN [$SRCPATH]
: launch retrieval of informations on given binary.$BIN
can either be the program for which the inference has been run or one of its libraries$SRCPATH
(optional) path of the source code of the program
scat > parsedata ./pgm/bin/glibc-obj/libc.so.6
scat > parsedata ./pgm/bin/grep ./pgm/src/grep/
Note: results are stored in ./data/
as python pickled files.
accuracy $PGM $INF
: compare meta-informations with results of inference$INF
(arity
ortype
) on the program$PGM
.
scat > accuracy grep arity
!! Missing data for libpcre.so.1
Information about inference
| Last inference: 2016-07-19 15:06:15
- Total functions infered: 123
Ignored
| Without name: 26
| Variadic: 3
| Pseudo-Functions: 1
- Not in binary/source: 0
Accuracy of inference
| Arity Ok/Total tested: 87/93
| Return Ok/Total tested: 91/93
| Ratio arity: 93.55%
- Ratio return: 97.85%
mismatch $PGM $INF
:$INF
(arity
) on the program$PGM
.
scat > mismatch grep arity
!! Missing data for libpcre.so.1
Information about inference
| Last inference: 2016-07-19 15:06:15
- Total functions infered: 123
[libc.so.6@0xb3cc0] __getdents64 (int, char *, int) -> long
Arity : Expected 3 got 2
[grep@0x405527] grepfile (int, const char*, _Bool, _Bool) -> _Bool
Return : Expected 1 got 0
[libc.so.6@0xdb8c0] do_fcntl (int, int, void*) -> int
Arity : Expected 3 got 2
[libc.so.6@0x11ea40] _dl_mcount_wrapper_check (void*) -> void
Arity : Expected 1 got 0
[ld-linux-x86-64.so.2@0x8f70] check_match (regmatch_t *, int, const char *, const char *, const char *) -> int
Arity : Expected 5 got 9
[libc.so.6@0xdb560] __write (int, void*, int) -> int
Arity : Expected 3 got 0
[libc.so.6@0x771b0] malloc_consolidate (mstate) -> void
Return : Expected 0 got 1
[libc.so.6@0x242f0] __gconv_transform_ascii_internal (__gconv_step*, __gconv_step_data*, const unsigned char**, const unsigned char*, unsigned char**, size_t*, int, int) -> int
Arity : Expected 8 got 7
To add your own pintool, simply add an entry to the configuration file (typically congig/config.yaml
). For example, let's say you want to add
a pintool named nopcounter
to count the number of NOP
instructions.
Here is what you should add to your configuration file:
pin:
path: /usr/bin/pin
bin: /usr/bin/pin/pin
cli-options: -ifeellucky
pintool:
arity:
src: ./src/pintool/arity.cpp
obj: ./bin/obj-intel64/arity.so
type:
src: ./src/pintool/type.cpp
obj: ./bin/obj-intel64/type.so
prev_step: arity
couple:
src: ./src/pintool/couple.cpp
obj: ./bin/obj-intel64/couple.so
alloc:
src: ./src/pintool/alloc.cpp
obj: ./bin/obj-intel64/alloc.so
+ nopcounter:
+ src: $SRC_DIR/nopcounter.cpp
+ obj: $OBJ_DIR/nopcounter.so
res:
path: ./res
log:
path: ./log
clang:
lib-path: /usr/lib/x86_64-linux-gnu/libclang.so.1
data-path: ./data/
where:
$SRC_DIR
is the path to the source file ofnopcount
$OBJ_DIR
is the path to the compiled shared library ofnopcount
And that's it. You don't need to actually compile your pintool, compilation will be handled by scat
.
From now on, you can use the command launch nopcount $PGM
within scat
(be sure you ran make nopcount
in scat
before
to compile it).
checkconfig
: check if the configuration file is consistant, and in particular ifPin
is found and executablemake
: compile pintools (optional: the pintool to compile, e.g.make arity
- if not specified, compile all)launch $INF $PGM $ARGS
where$PGM
is the program to analyze (full path),$ARGS
are its argumentslaunch arity $PGM $ARGS
: infer arity of functionslaunch type $PGM $ARGS
: infer type (ADDR
,INT
orFLOAT
) of parameterslaunch couple $PGM $ARGS
: collect data to infer couples (then, seecouple
)launch memalloc $PGM $ARGS
: collect data to infer allocators (then, seememcomb
)- example:
launch arity pgm/bin/mupdf-x11 test/input/poc.pdf
display $PGM $INF
where$PGM
is the program previously analyzed (basename only)display $PGM arity
: show the arity of functions (results of the last analysis)display $PGM type
: show the undertyped prototypes (results of the last analysis)- example:
display mupdf-x11 arity
parsedata $PGM $SRC
: parse the source files in directory$SRC
for program$PGM
- example:
parsedata pgm/bin/mupdf-x11 pgm/src/mupdf-x11/
- example:
accuracy $PGM $INF
where$PGM
is the program previously analyzed (basename only) - requiresparsedata
accuracy $PGM arity
: display the accuracy of arity inferenceaccuracy $PGM type
: display the accuracy of type (ADDR
,INT
,FLOAT
) inference- example:
accuracy mupdf-x11 arity
mismatch $PGM $INF
where$PGM
is the program previously analyzed (basename only) - requiresparsedata
mismatch $PGM arity
: show the functions whose accuracy was retrieved wronglymismatch $PGM type
: show the functions whose parameters were wrongly typed- example:
mismatch mupdf-x11 arity
test $CONFIG
: (wip) test for arity and type on several programs specified in the configuration file (outputs the average accuracy for arity and type)
scat
comes with several limitations. Some of them are relative to the approach, but we will detail here only
the ones relative to incomplete or mis-implementation.
For now, scat
is not capable of performing inference on object-oriented programs. The reason of this is that scat
relies on
the calling convention, and specificities introduced by object-oriented programs (and in particular this call convention)
have not been studied yet.
As mentioned previously, scat
relies on the knowledge of the calling convention. The approach proposed can be easily adapted to
any calling convention. However, the work has only been done for x86-64 System V AMD64
calling convention. Therefore, only this kind
of binaries can be analysed for now.