CRAXweb: Automatic Exploit Generation for Web Applications

Lehrstuhl für Informatik 4
1/161/2012 <Title> <Name LastName> Seminar in Computer Science
Kip IrvineCRAXweb: Automatic Web Application
Testing and Attack Generation1
Shih-Kun Huang ,Han-Lin Lu, Wai-Meng Leong ,Huan Liu
National Chiao Tung University
Presented by
Aung Thu Rha Hein
5536871
1 “CRAXWweb:Automatic Web Application Testing and Attack Generation”, Software Security and Reliability
(SERE), June 2013 IEEE 7th International Conference.

Outline
1. Introduction
2. Background
-What is an exploit?
-Dynamic Analysis
-Semantic Execution
2. CRAXWeb: Automatic Web Application Testing and
Attack Generation
4. Conclusions
5. References

●
Software bugs are common
●
Especially in web applications
●
Some bugs are more harmful
●
It is difficult to detect manually
●
Static analysis gives developer confusion and false
positives
●
Manual testing is not effective
Introduction
Motivation

●
Challenge
●
How to find exploits, shellcode in the program
●
Source code analysis alone is not enough
●
Finding exploitable paths among program execution
paths
Introduction
Problem Statements

●
To generate exploits for web-applications
Introduction
Research Objectives

●
Exploits techniques vary upon OS architectures
●
Type of Exploits
●
Stack Overflow Exploit
●
Heap Corruption Exploit
●
Format String Attack
●
Attack Methodologies
●
Remote Exploit
●
Local Exploit
●
Two Stage Exploit
●
Tools for writing Exploits: LibExploit, Metasploit,
CANVAS
Background: Exploits
What is an exploit?

Stack Overflow Exploit Example
#include <string.h>
void foo (char *bar)
{
char c[12];
strcpy(c, bar);
}
int main (int argc, char **argv)
{
foo(argv[1]);
}

Stack Overflow Exploit Example

Background: Dynamic analysis
Introduction
●
Monitor code as it executes
●
Usefulness of Dynamic analysis
●
Precision of information
●
Dependence on program inputs
●
Four common dynamic analysis techniques:
●
Dynamic taint analysis
●
Forward symbolic execution
●
Frequency Spectrum Analysis
●
Coverage Concept Analysis ...

Dynamic Taint Analysis
●
To exploit program execution,
●
use values from a trusted source
●
attackers overwrite, tainted these values
●
Taint Analysis Process
1. mark input data from untrusted sources tainted
2. monitor program execution to track how they
propagated
3. check when tainted data is used in dangerous ways

Dynamic Taint Analysis
Attack detected using TaintCheck

Background:Dynamic analysis
Symbolic Execution
●
Key idea: generalize testing by using unknown
●
symbolic variables in evaluation
●
int f(1, 2)= int f(α1 , α2)
●
Allows unknown symbolic variables in evaluation
●
y = α; assert(f(y) == 2*y-1);
●
If execution path depends on unknown, conceptually
fork symbolic executor
●
int f(int x)
{if(x > 0) then return 2*x - 1; else return 10;}

Symbolic Execution Example
l …

Symbolic Execution: Purpose
●
E.g. Particular program points reachable?
●
E.g. Is array access a[i] out of bounds?
●
E.g. Generate concrete inputs that execute same
paths
●
With constraints solvers
●
E.g. Z3, Yices, STP

Symbolic Execution Limitations
●
Scalability Issue when execution paths are large
●
Source code, or equivalent is required
●
Limitations in solving constraints
●
cannot handle non-linear and very complex constraints

Research Paper
CRAXweb: Automatic Web Application
Testing and Attack Generation

Research Paper
●
Implement AEG for large-scaled web applications
●
Focus on XSS and SQLi attacks
●
Based on Symbolic Socket or symbolic execution
●
Single path concolic mode is used to reduce path-
explosion
●
Selective Symbolic Execution(S2E)
●
Provide the ability to execute a specific part of
program
●
Simple Theorem Prover(STP) as a constraint solver
●
Acunetix as web crawler
Overview of CRAXweb

Research Paper
●
Generate test cases and exploits
Exploit Generation: Constraint Solving

Research Paper
Exploit Generation:Constraint Solving
x- exploit
f(x)- expected attack script

Research Paper
●
To reduce overhead caused by symbolic execution
●
Explore one path at a time
Single Path Concolic Mode

Research Paper
Flow diagram of automatic process

Research Paper
●
S2E as symbolic environment
Implementation:Symbolic Socket

Research Paper
●
Overall architecture for automatic exploit generator
Implementation: Architecture

Research Paper
Implementation: Symbolic Response and Query Handler
●
From Web Crawler to Symbolic Request

Research Paper
Implementation: Symbolic Response and Query Handler
●
From symbolic response or query to exploit generator

Research Paper
Implementation: Exploit Generation

Research Paper
Implementation: Exploit Generation
●
Algorithm to solve the exploit constraint

Research Paper
Results: Experiment Environment
●
Host OS- Ubuntu 10.10
●
Guest Environment- emulated by Qemu
●
Qemu- hosted Debian 5.07 and Windows XP
●
Softwares- S2E 1.0 and MySQL as database handler

Research Paper
Results: Evaluation for different platforms

Research Paper
Results: Evaluation for Exploit Generation
●
With test cases from Ardilla

Research Paper
●
With test cases from Ardilla

Research Paper
●
With Real world Applications

Research Paper
Results: Related works

Conclusions
●
AEG is possible for web applications
●
CRAXWeb uses
●
Symbolic execution
●
Concolic Testing
●
However,Still have rooms for development
●
for more exploit types
●
to integration with browser

References
Shih-Kun Huang,Han-Lin Lu ; Wai-Meng Leong ; Huan Liu,
”CRAXweb: Automatic Web Application Testing and Attack
Generation”, Software Security and Reliability (SERE),IEEE 7th
International Conference, June 2013
Shih-Kun Huang,Min-Hsiang Huang ; Po-Yen Huang ; Chung-Wei
Lai ; Han-Lin Lu ; Wai-Meng Leong, “CRAX: Software Crash
Analysis for Automatic Exploit Generation by Modeling Attacks as
Symbolic Continuations” ,Software Security and Reliability
(SERE), 2012 IEEE Sixth International Conference, June 2012
Thanassis Avgerinos and Sang Kil Cha and Brent Lim Tze Hao
and David Brumley, “AEG: Automatic Exploit Generation”,Network
and Distributed System Security Symposium, Feb 2012

References
James Newsome,Dawn Song,”Dynamic Taint Analysis for
Automatic Detection,An alysis, and Signature Generation of
Exploitson Commodity Software”, Network and Distributed System
Security Symposium, 2005
Cristian Cadar, Daniel Dunbar, Dawson Engler, “KLEE:
Unassisted and Automatic Generation of High-CoverageTests for
Complex Systems Programs”, USENIX Symposium on Operating
Systems Design and Implementation, December 2008

CRAXweb: Automatic Exploit Generation for Web Applications

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