Automated Whitebox Fuzz Testing

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Automated Whitebox Fuzz Testing Patrice Godefroid (Microsoft Research) Michael Y. Levin (Microsoft Center for Software Excellence) David Molnar (UC-Berkeley,

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Automated Whitebox Fuzz Testing. Patrice Godefroid (Microsoft Research) ‏ Michael Y. Levin (Microsoft Center for Software Excellence) ‏ David Molnar (UC-Berkeley, visiting MSR). Fuzz Testing. An effective technique for finding - PowerPoint PPT Presentation

Transcript of Automated Whitebox Fuzz Testing

Page 1: Automated Whitebox  Fuzz Testing

Automated Whitebox Fuzz Testing

Patrice Godefroid (Microsoft Research)Michael Y. Levin (Microsoft Center for

Software Excellence)David Molnar (UC-Berkeley, visiting MSR)

Page 2: Automated Whitebox  Fuzz Testing

Fuzz Testing

• An effective technique for finding security vulnerabilities in software• Apply invalid, unexpected, or random data to the inputs of a program.• If the program fails(crashing, access violation

exception), the defects can be noted.

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Vulnerability Finding Today

• One Security bug can bring $500-$100,000 on the open market

• Good bug finders make $180-$250/hr consulting• Few companies can find good people, many don’t even

realize this is possible.• Still largely a black art

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Whitebox Fuzzing• This paper present an alternative whitebox fuzz testing approach

inspired by recent advances in symbolic execution and dynamic test generation– Run the code with some initial well-formed input

– Collect constraints on input with symbolic execution

– Generate new constraints (by negating constraints one by one)

– Solve constraints with constraint solver

– Synthesize new inputs

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Dynamic Test Generationvoid top(char input[4]) { int cnt = 0; if (input[0] == ‘b’) cnt++; if (input[1] == ‘a’) cnt++; if (input[2] == ‘d’) cnt++; if (input[3] == ‘!’) cnt++; if (cnt >= 3) crash();}

input = “good”

• Running the program with random values for the 4 input bytes is unlikely to discovery the error: a probability of about

• Traditional fuzz testing is difficult to generate input values that will drive program through all its possible execution paths.

301/ 2

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Depth-First Search

void top(char input[4]) { int cnt = 0; if (input[0] == ‘b’) cnt++; if (input[1] == ‘a’) cnt++; if (input[2] == ‘d’) cnt++; if (input[3] == ‘!’) cnt++; if (cnt >= 3) crash();}

I0 != ‘b’I1 != ‘a’I2 != ‘d’I3 != ‘!’good

I0 != ‘b’

I1 != ‘a’

I2 != ‘d’

I3 != ‘!’

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Depth-First Search

goo!good

void top(char input[4]) { int cnt = 0; if (input[0] == ‘b’) cnt++; if (input[1] == ‘a’) cnt++; if (input[2] == ‘d’) cnt++; if (input[3] == ‘!’) cnt++; if (cnt >= 3) crash();}

I0 != ‘b’I1 != ‘a’I2 != ‘d’I3 == ‘!’

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Practical limitation

godd

void top(char input[4]) { int cnt = 0; if (input[0] == ‘b’) cnt++; if (input[1] == ‘a’) cnt++; if (input[2] == ‘d’) cnt++; if (input[3] == ‘!’) cnt++; if (cnt >= 3) crash();}

I0 != ‘b’I1 != ‘a’I2 == ‘d’I3 != ‘!’good

Every time only one constraint is expanded, low efficiency!

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Generational SearchKey Idea: One Trace, Many Tests

goo!

godd

gaod

bood

“Generation 1” test cases

good

void top(char input[4]) { int cnt = 0; if (input[0] == ‘b’) cnt++; if (input[1] == ‘a’) cnt++; if (input[2] == ‘d’) cnt++; if (input[3] == ‘!’) cnt++; if (cnt >= 3) crash();}

I0 == ‘b’I1 == ‘a’I2 == ‘d’I3 == ‘!’

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void top(char input[4]) { int cnt = 0; if (input[0] == ‘b’) cnt++; if (input[1] == ‘a’) cnt++; if (input[2] == ‘d’) cnt++; if (input[3] == ‘!’) cnt++; if (cnt >= 3) crash();}

0good

1goo!

1godd

2god!

1gaod

2gao!

2gadd

gad!

1bood

2boo!

2bodd

2baod

bod! bad!

badd baod

The Generational Search Space

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SAGE Architecture(Scalable Automated Guided Execution)

Check forCrashes

(AppVerifier)

Trace Program(Nirvana)

Gather Constraints(Truscan)

SolveConstraints(Disolver)

Input0 Trace File Constraints

Input1Input2

InputN

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• Since 1st MS internal release in April’07: dozens of new security bugs found (most missed by blackbox fuzzers, static analysis)

• Apps: image processors, media players, file decoders,…

• Many bugs found rated as “security critical, severity 1, priority 1”

• Now used by several teams regularly as part of QA process

Initial Experiences with SAGE

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ExperimentsANI Parsing - MS07-017

RIFF...ACONLISTB...INFOINAM....3D Blue Alternate v1.1..IART....................1996..anih$...$...................................rate....................seq ....................LIST....framicon......... ..

RIFF...ACONBB...INFOINAM....3D Blue Alternate v1.1..IART....................1996..anih$...$...................................rate....................seq ....................anih....framicon......... ..

Initial input Crashing test case

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ANI Parsing - MS07-017

RIFF...ACONLISTB...INFOINAM....3D Blue Alternate v1.1..IART....................1996..anih$...$...................................rate....................seq ....................LIST....framicon......... ..

RIFF...ACONBB...INFOINAM....3D Blue Alternate v1.1..IART....................1996..anih$...$...................................rate....................seq ....................anih....framicon......... ..

Only 1 in 232 chance at random!

Initial input Crashing test case

Initial input : 341 branch constraints, 1,279,939 total instructions. Crash test cases: 7706 test cases, 7hrs 36 mins

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000040h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000060h: 00 00 00 00 ; ....

Generation 0 – initial input – 100 bytes of “00”

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 52 49 46 46 00 00 00 00 00 00 00 00 00 00 00 00 ; RIFF............00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000040h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000060h: 00 00 00 00 ; ....

Generation 1

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 52 49 46 46 00 00 00 00 ** ** ** 20 00 00 00 00 ; RIFF....*** ....00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000040h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000060h: 00 00 00 00 ; ....

Generation 2

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 52 49 46 46 3D 00 00 00 ** ** ** 20 00 00 00 00 ; RIFF=...*** ....00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000040h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000060h: 00 00 00 00 ; ....

Generation 3

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 52 49 46 46 3D 00 00 00 ** ** ** 20 00 00 00 00 ; RIFF=...*** ....00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 73 74 72 68 00 00 00 00 00 00 00 00 ; ....strh........00000040h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000060h: 00 00 00 00 ; ....

Generation 4

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 52 49 46 46 3D 00 00 00 ** ** ** 20 00 00 00 00 ; RIFF=...*** ....00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 73 74 72 68 00 00 00 00 76 69 64 73 ; ....strh....vids00000040h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000060h: 00 00 00 00 ; ....

Generation 5

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 52 49 46 46 3D 00 00 00 ** ** ** 20 00 00 00 00 ; RIFF=...*** ....00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 73 74 72 68 00 00 00 00 76 69 64 73 ; ....strh....vids00000040h: 00 00 00 00 73 74 72 66 00 00 00 00 00 00 00 00 ; ....strf........00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000060h: 00 00 00 00 ; ....

Generation 6

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 52 49 46 46 3D 00 00 00 ** ** ** 20 00 00 00 00 ; RIFF=...*** ....00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 73 74 72 68 00 00 00 00 76 69 64 73 ; ....strh....vids00000040h: 00 00 00 00 73 74 72 66 00 00 00 00 28 00 00 00 ; ....strf....(...00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000060h: 00 00 00 00 ; ....

Generation 7

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 52 49 46 46 3D 00 00 00 ** ** ** 20 00 00 00 00 ; RIFF=...*** ....00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 73 74 72 68 00 00 00 00 76 69 64 73 ; ....strh....vids00000040h: 00 00 00 00 73 74 72 66 00 00 00 00 28 00 00 00 ; ....strf....(...00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 C9 9D E4 4E ; ............ÉäN00000060h: 00 00 00 00 ; ....

Generation 8

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 52 49 46 46 3D 00 00 00 ** ** ** 20 00 00 00 00 ; RIFF=...*** ....00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 73 74 72 68 00 00 00 00 76 69 64 73 ; ....strh....vids00000040h: 00 00 00 00 73 74 72 66 00 00 00 00 28 00 00 00 ; ....strf....(...00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 01 00 00 00 ; ................00000060h: 00 00 00 00 ; ....

Generation 9

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Zero to Crash in 10 Generations

• Starting with 100 zero bytes …

• SAGE generates a crashing test:

00000000h: 52 49 46 46 3D 00 00 00 ** ** ** 20 00 00 00 00 ; RIFF=...*** ....00000010h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000020h: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ; ................00000030h: 00 00 00 00 73 74 72 68 00 00 00 00 76 69 64 73 ; ....strh....vids00000040h: 00 00 00 00 73 74 72 66 B2 75 76 3A 28 00 00 00 ; ....strf²uv:(...00000050h: 00 00 00 00 00 00 00 00 00 00 00 00 01 00 00 00 ; ................00000060h: 00 00 00 00 ; ....

Generation 10 – bug ID 1212954973!

Found after only 3 generations starting from “well-formed” seed file

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Different Crashes From Different Initial Input Files 100

zerobytes

1867196225 X X X X X2031962117 X X X X X612334691 X X1061959981 X X1212954973 X X1011628381 X X X842674295 X1246509355 X X X1527393075 X1277839407 X1951025690 X

Media 1: 60 machine-hours, 44,598 total tests, 357 crashes, 12 bugs

Bug ID seed1 seed2 seed3 seed4 seed5 seed6 seed7

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Most Bugs Found are “Shallow”

1 2 3 4 5 6 70

0.5

1

1.5

2

2.5

3

3.5

# Unique First-Found Bugs

Generation

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Conclusion Blackbox vs. Whitebox Fuzzing

• Cost/precision tradeoffs

– Blackbox is lightweight, easy and fast, but poor coverage

– Whitebox is smarter, but complex and slower

– Recent “semi-whitebox” approaches• Less smart but more lightweight: Flayer (taint-flow analysis, may

generate false alarms), Bunny-the-fuzzer (taint-flow, source-based, heuristics to fuzz based on input usage), autodafe, etc.

• Which is more effective at finding bugs? It depends…

– Many apps are so buggy, any form of fuzzing finds bugs!

– Once low-hanging bugs are gone, fuzzing must become smarter: use whitebox and/or user-provided guidance (grammars, etc.)

• Bottom-line: in practice, use both!

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Thank you!Questions?