- 简介
- 一、基础知识篇
- 二、工具篇
- 三、分类专题篇
- 四、技巧篇
- 五、高级篇
- 六、题解篇
- 6.1 Pwn
- 6.1.1 pwn HCTF2016 brop
- 6.1.2 pwn NJCTF2017 pingme
- 6.1.3 pwn XDCTF2015 pwn200
- 6.1.4 pwn BackdoorCTF2017 Fun-Signals
- 6.1.5 pwn GreHackCTF2017 beerfighter
- 6.1.6 pwn DefconCTF2015 fuckup
- 6.1.7 pwn 0CTF2015 freenote
- 6.1.8 pwn DCTF2017 Flex
- 6.1.9 pwn RHme3 Exploitation
- 6.1.10 pwn 0CTF2017 BabyHeap2017
- 6.1.11 pwn 9447CTF2015 Search-Engine
- 6.1.12 pwn N1CTF2018 vote
- 6.1.13 pwn 34C3CTF2017 readme_revenge
- 6.1.14 pwn 32C3CTF2015 readme
- 6.1.15 pwn 34C3CTF2017 SimpleGC
- 6.1.16 pwn HITBCTF2017 1000levels
- 6.1.17 pwn SECCONCTF2016 jmper
- 6.1.18 pwn HITBCTF2017 Sentosa
- 6.1.19 pwn HITBCTF2018 gundam
- 6.1.20 pwn 33C3CTF2016 babyfengshui
- 6.1.21 pwn HITCONCTF2016 Secret_Holder
- 6.1.22 pwn HITCONCTF2016 Sleepy_Holder
- 6.1.23 pwn BCTF2016 bcloud
- 6.1.24 pwn HITCONCTF2016 HouseofOrange
- 6.1.25 pwn HCTF2017 babyprintf
- 6.1.26 pwn 34C3CTF2017 300
- 6.1.27 pwn SECCONCTF2016 tinypad
- 6.1.28 pwn ASISCTF2016 b00ks
- 6.1.29 pwn Insomni'hackteaserCTF2017 TheGreatEscapepart-3
- 6.1.30 pwn HITCONCTF2017 Ghostinthe_heap
- 6.1.31 pwn HITBCTF2018 mutepig
- 6.1.32 pwn SECCONCTF2017 vmnofun
- 6.1.33 pwn 34C3CTF2017 LFA
- 6.1.34 pwn N1CTF2018 memsafety
- 6.1.35 pwn 0CTF2018 heapstorm2
- 6.1.36 pwn NJCTF2017 messager
- 6.1.37 pwn sixstarctf2018 babystack
- 6.1.38 pwn HITCONCMT2017 pwn200
- 6.1.39 pwn BCTF2018 houseofAtum
- 6.1.40 pwn LCTF2016 pwn200
- 6.1.41 pwn PlaidCTF2015 PlaidDB
- 6.1.42 pwn hacklu2015 bookstore
- 6.1.43 pwn 0CTF2018 babyheap
- 6.1.44 pwn ASIS2017 start_hard
- 6.1.45 pwn LCTF2016 pwn100
- 6.2 Reverse
- 6.3 Web
- 6.1 Pwn
- 七、实战篇
- 7.1 CVE
- 7.1.1 CVE-2017-11543 tcpdump sliplink_print 栈溢出漏洞
- 7.1.2 CVE-2015-0235 glibc _nsshostnamedigitsdots 堆溢出漏洞
- 7.1.3 CVE-2016-4971 wget 任意文件上传漏洞
- 7.1.4 CVE-2017-13089 wget skipshortbody 栈溢出漏洞
- 7.1.5 CVE–2018-1000001 glibc realpath 缓冲区下溢漏洞
- 7.1.6 CVE-2017-9430 DNSTracer 栈溢出漏洞
- 7.1.7 CVE-2018-6323 GNU binutils elfobjectp 整型溢出漏洞
- 7.1.8 CVE-2010-2883 Adobe CoolType SING 表栈溢出漏洞
- 7.1.9 CVE-2010-3333 Microsoft Word RTF pFragments 栈溢出漏洞
- 7.1 CVE
- 八、学术篇
- 8.1 The Geometry of Innocent Flesh on the Bone: Return-into-libc without Function Calls (on the x86)
- 8.2 Return-Oriented Programming without Returns
- 8.3 Return-Oriented Rootkits: Bypassing Kernel Code Integrity Protection Mechanisms
- 8.4 ROPdefender: A Detection Tool to Defend Against Return-Oriented Programming Attacks
- 8.5 Data-Oriented Programming: On the Expressiveness of Non-Control Data Attacks
- 8.7 What Cannot Be Read, Cannot Be Leveraged? Revisiting Assumptions of JIT-ROP Defenses
- 8.9 Symbolic Execution for Software Testing: Three Decades Later
- 8.10 AEG: Automatic Exploit Generation
- 8.11 Address Space Layout Permutation (ASLP): Towards Fine-Grained Randomization of Commodity Software
- 8.13 New Frontiers of Reverse Engineering
- 8.14 Who Allocated My Memory? Detecting Custom Memory Allocators in C Binaries
- 8.21 Micro-Virtualization Memory Tracing to Detect and Prevent Spraying Attacks
- 8.22 Practical Memory Checking With Dr. Memory
- 8.23 Evaluating the Effectiveness of Current Anti-ROP Defenses
- 8.24 How to Make ASLR Win the Clone Wars: Runtime Re-Randomization
- 8.25 (State of) The Art of War: Offensive Techniques in Binary Analysis
- 8.26 Driller: Augmenting Fuzzing Through Selective Symbolic Execution
- 8.27 Firmalice - Automatic Detection of Authentication Bypass Vulnerabilities in Binary Firmware
- 8.28 Cross-Architecture Bug Search in Binary Executables
- 8.29 Dynamic Hooks: Hiding Control Flow Changes within Non-Control Data
- 8.30 Preventing brute force attacks against stack canary protection on networking servers
- 8.33 Under-Constrained Symbolic Execution: Correctness Checking for Real Code
- 8.34 Enhancing Symbolic Execution with Veritesting
- 8.38 TaintEraser: Protecting Sensitive Data Leaks Using Application-Level Taint Tracking
- 8.39 DART: Directed Automated Random Testing
- 8.40 EXE: Automatically Generating Inputs of Death
- 8.41 IntPatch: Automatically Fix Integer-Overflow-to-Buffer-Overflow Vulnerability at Compile-Time
- 8.42 Dynamic Taint Analysis for Automatic Detection, Analysis, and Signature Generation of Exploits on Commodity Software
- 8.43 DTA++: Dynamic Taint Analysis with Targeted Control-Flow Propagation
- 8.44 Superset Disassembly: Statically Rewriting x86 Binaries Without Heuristics
- 8.45 Ramblr: Making Reassembly Great Again
- 8.46 FreeGuard: A Faster Secure Heap Allocator
- 8.48 Reassembleable Disassembling
- 九、附录
8.4 ROPdefender: A Detection Tool to Defend Against Return-Oriented Programming Attacks
简介
论文设计并实现了工具 ROPdefender,可以动态地检测传统的 ROP 攻击(基于return指令)。ROPdefender 可以由用户来执行,而不依赖于源码、调试信息等在现实中很难获得的信息。
ROPdefender 基于二进制插桩框架 Pin 实现,作为一个 Pintool 使用,在运行时强制进行返回地址检查。
背景
现有的 ROP 检测方法会维护一个 shadow stack,作为返回地址的备份。当函数返回时,检查返回地址是否被修改。
这种方法有个明显的缺陷,它只能检测预期的返回(intended return),而对于非预期的返回(unintended return)无效。
intended instruction 是程序中明确存在的指令。而 unintended instruction 是正常指令通过偏移得到的指令。举个例子:
intended instruction:
b8 13 00 00 00 mov $0x13, %eax
e9 c3 f8 ff ff jmp 3aae9
偏移两个十六进制后的 unintended instruction:
00 00 add %al, (%eax)
00 e9 add %ch, %cl
c3 ret
这样的返回不会被备份到 shadow stack 中,因此也不会被检测到。
另外,如果攻击者修改的不是返回地址,而是函数的 GOT 表,则同样不会被检测到。
解决方案
ROPdefender 同样也使用 shadow stack 来储存每次函数调用的返回地址。在每次函数返回时进行返回地址检查。
与现有方法不同的是:
- ROPdefender 会检查传递给处理器的每个返回指令(基于JIT插桩工具),这样即使攻击者使用 unintended instruction 也会被检测到
- ROPdefender 还能处理各种特殊的情况
整体思想如下图所示:
在处理器执行指令时,对指令类别进行判断,如果是 call,将返回地址放进 shadow stack;如果是 return,则检查与 shadow stack 顶部的返回地址是否相同。这一方法不仅可用于检测 ROP 攻击,还可以检测所有利用缓冲区溢出改写返回地址的攻击。
实现细节
基于 Pin 动态二进制插桩(DBI)框架的实现如下图所示:
一般工作流程是这样的,程序在 DBI 框架下加载并启动。DBI 框架确保:
- 程序的每条指令都在 DBI 的控制下执行
- 所有指令都根据 ROPdefender 特定的检测代码执行,然后进行返回地址检查
ROPdefender 包含了多个 shadow stack 和一个 detection unit。detection unit 用于 shadow stack 返回地址的压入和弹出,并进行强制返回地址检查。使用多个 shadow stack 的原因是程序可能会有多个线程,这样就可以为每个线程都维护一个 shadow stack。
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