🗊Презентация Advanced Fuzzing with Peach 2

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Слайды и текст этой презентации

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Advanced Fuzzing with Peach 2 MICHAEL EDDINGTON MIKE@LEVIATHANSECURITY.COM
Описание слайда:
Advanced Fuzzing with Peach 2 MICHAEL EDDINGTON MIKE@LEVIATHANSECURITY.COM

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Agenda Introduction to Peach 2 Data mutations Peach State Machine Peach Farm Peach in The Middle
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Agenda Introduction to Peach 2 Data mutations Peach State Machine Peach Farm Peach in The Middle

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Introduction to Peach 2
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Introduction to Peach 2

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Peach 1 Framework for writing fuzzers Instrumentation via wrapper APIs No data definition layer (DDL), just fuzzer Steep learning curve Complex fuzzers result in complex fuzzer code
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Peach 1 Framework for writing fuzzers Instrumentation via wrapper APIs No data definition layer (DDL), just fuzzer Steep learning curve Complex fuzzers result in complex fuzzer code

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Peach 2 Reduce creation time and simplify fuzzer generation Fuzzer platform, not framework Modeling based approach Fault detection Lower learning curve
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Peach 2 Reduce creation time and simplify fuzzer generation Fuzzer platform, not framework Modeling based approach Fault detection Lower learning curve

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Modeling Based Fuzzing Model types and data Model state machine Support models with data sets Mutate models with mutators
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Modeling Based Fuzzing Model types and data Model state machine Support models with data sets Mutate models with mutators

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Model Data: Types
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Model Data: Types

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Model Data: Relationships
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Model Data: Relationships

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Model Data: State Model
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Model Data: State Model

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Benefits of Modeling Easy reuse of definitions Complex mutations can be applied to a model Improvements to data generation or mutation independent of model Data read into definition as well as generated
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Benefits of Modeling Easy reuse of definitions Complex mutations can be applied to a model Improvements to data generation or mutation independent of model Data read into definition as well as generated

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Data Modeling Define structure of data Define relations in data Reuse definitions
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Data Modeling Define structure of data Define relations in data Reuse definitions

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State Modeling
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State Modeling

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State Modeling Stream
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State Modeling Stream

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State Modeling: Stream
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State Modeling: Stream

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State Modeling: Stream
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State Modeling: Stream

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State Modeling: Stream
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State Modeling: Stream

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State Modeling: Call
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State Modeling: Call

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Data Mutations
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Data Mutations

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Mutation: String
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Mutation: String

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Mutation: Number
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Mutation: Number

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Mutation: Size Relation #1 Length: Data:
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Mutation: Size Relation #1 Length: Data:

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Mutation: Size Relation #2 Length: Data:
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Mutation: Size Relation #2 Length: Data:

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Mutation: Size Relation #3 Data & Length:
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Mutation: Size Relation #3 Data & Length:

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Mutation: State
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Mutation: State

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Mutation: State
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Mutation: State

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Mutation: State
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Mutation: State

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Add Custom Mutators Sling some Python Add additional mutations Specific mutations Etc.
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Add Custom Mutators Sling some Python Add additional mutations Specific mutations Etc.

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Fault Detection AND DATA COLLECTION
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Fault Detection AND DATA COLLECTION

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Agents & Monitors
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Agents & Monitors

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2 Tier Configuration
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2 Tier Configuration

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Monitors Debuggers Process Monitor Memory Monitor Network Capture VM Control (snapshot, revert) Networked Power Strips (cycle power) Easy to implement custom monitors
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Monitors Debuggers Process Monitor Memory Monitor Network Capture VM Control (snapshot, revert) Networked Power Strips (cycle power) Easy to implement custom monitors

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Peach Development
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Peach Development

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Documented XML Schema
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Documented XML Schema

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Peach Builder
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Peach Builder

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Peach Shark
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Peach Shark

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Peach Farm MASSIVELY PARALLEL FUZZING
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Peach Farm MASSIVELY PARALLEL FUZZING

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Peach Farm Adam Cecchetti Massively Parallel Fuzzing Scales from 1 to 10,000 nodes Choose your Virtual Platform/Hosting EC2, Xen, VMWare, Etc Utilizes Map/Reduce Algorithm Map: Maps the fuzzing cases to indexes and results Reduce: Reduces fuzzing results to interesting cases Metric based : Time, size, diff, expected errors, OS faults, crashes
Описание слайда:
Peach Farm Adam Cecchetti Massively Parallel Fuzzing Scales from 1 to 10,000 nodes Choose your Virtual Platform/Hosting EC2, Xen, VMWare, Etc Utilizes Map/Reduce Algorithm Map: Maps the fuzzing cases to indexes and results Reduce: Reduces fuzzing results to interesting cases Metric based : Time, size, diff, expected errors, OS faults, crashes

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Peach in The Middle WHAT’S NEXT?
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Peach in The Middle WHAT’S NEXT?

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Peach in The Middle
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Peach in The Middle

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Q & A HTTP://PEACHFUZZ.SF.NET HTTP://PHED.ORG MIKE@LEVIATHANSECURITY.COM
Описание слайда:
Q & A HTTP://PEACHFUZZ.SF.NET HTTP://PHED.ORG MIKE@LEVIATHANSECURITY.COM

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