实例分析ELF文件静态链接

参考文献：

《ELF V1.2》

《程序员的自我修养---链接、装载与库》第4章 静态链接

开发平台：

[thm@tanghuimin static_link]$ uname -a
Linux tanghuimin 2.6.-.el6.x86_64 # SMP Fri Feb  :: UTC  x86_64 x86_64 x86_64 GNU/Linux 

1.ELF文件格式概貌

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" 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readelf -h 查看elf文件头部信息可以看到Type值有三种：REL，EXEC，DYN。

REL文件是只被编译没有被链接过的文件，其格式属于左边一种，elf header+section1,2,3...+section header table，每个section对应一个section header table entry，section header table为各个section提供索引。没有被链接过的文件没有program header，不能被加载到内存中运行，readelf -l会提示”There are no program headers in this file”。

EXEC和DYN文件属于被链接过的文件，其格式属于右边一种，elf header+program header table+segment1,2,3...+section header table。每个segment对应一个program header table entry，program header table为各个segment提供索引。EXEC和DYN文件有program headers，可以被加载到内存中运行，readelf -l可以看到一个segment是由一个或多个section构成，Type为LOAD的segment可以被加载到内存中运行，其他类型的segment提供辅助信息。

2.实例分析

(1)创建文件

创建文件common.c

int val = ; 

int func(void)
{
    return (val+);
} 

创建文件test.c

extern int val;
extern int func(void); 

int main()
{
    val = ;
    func();
    return ;
} 

(2)编译

编译两个.c文件

gcc -c test.c

gcc -c common.c

生成的test.o和common.o属于REL类型

来分析一下编译后生成的REL文件

(2.1)先看看test.o:

readelf -s test.o查看test.o的符号表

[thm@tanghuimin static_link]$ readelf -s test.o 

Symbol table '.symtab' contains  entries:
   Num:    Value          Size Type    Bind   Vis      Ndx Name
     :       NOTYPE  LOCAL  DEFAULT  UND
     :       FILE    LOCAL  DEFAULT  ABS test.c
     :       SECTION LOCAL  DEFAULT
     :       SECTION LOCAL  DEFAULT
     :       SECTION LOCAL  DEFAULT
     :       SECTION LOCAL  DEFAULT
     :       SECTION LOCAL  DEFAULT
     :       SECTION LOCAL  DEFAULT
     :      FUNC    GLOBAL DEFAULT     main
     :       NOTYPE  GLOBAL DEFAULT  UND val
    :       NOTYPE  GLOBAL DEFAULT  UND func

因为val和func不是在test.c中定义的，所以这两个符号的Ndx（符号所在section的index）为UND。为了能让程序顺利执行，我们希望在未来链接的过程中可以从其他文件中找到val和func这两个符号，并确定这两个符号的地址，确定未定义符号的地址的过程即是“重定位”(relocation)。

readelf -S test.o可以看到test.o的section header table

[thm@tanghuimin static_link]$ readelf test.o -S
There are  section headers, starting at offset 0x128: 

Section Headers:
  [Nr] Name              Type             Address           Offset
       Size              EntSize          Flags  Link  Info  Align
  [ ]                   NULL                

  [ ] .text             PROGBITS
       000000000000001a    AX
  [ ] .rela.text        RELA                

  [ ] .data             PROGBITS           0000005c
           WA
  [ ] .bss              NOBITS             0000005c
           WA
  [ ] .comment          PROGBITS           0000005c
       000000000000002d    MS
  [ ] .note.GNU-stack   PROGBITS            

  [ ] .eh_frame         PROGBITS
            A
  [ ] .rela.eh_frame    RELA                

  [ ] .shstrtab         STRTAB             000000c8 

  [] .symtab           SYMTAB              

  [] .strtab           STRTAB              

Key to Flags:
  W (write), A (alloc), X (execute), M (merge), S (strings)
  I (info), L (link order), G (group), x (unknown)
  O (extra OS processing required) o (OS specific), p (processor specific) 

我们重点关注rela section。

可以看到rela.text entry的描述中，link=10，info=1，link表示被重定位的符号所在的符号表的section index，info表示需要被重定位的section的index，通俗点讲就是，将来有朝一日我知道了该符号的地址，我该把这个地址写到哪个section里面去，这里是.text。

readelf -r test.o可以看到rel section里的详细信息。

[thm@tanghuimin static_link]$ readelf test.o -r 

Relocation section '.rela.text' at offset 0x548 contains  entries:
  Offset          Info           Type           Sym. Value    Sym. Name + Addend
   R_X86_64_PC32      val -
00000000000f  000a00000002 R_X86_64_PC32      func -  

Relocation section '.rela.eh_frame' at offset 0x578 contains  entries:
  Offset          Info           Type           Sym. Value    Sym. Name + Addend
   R_X86_64_PC32      .text +  

offset表示该符号在被重定位的section中的偏移，info的高4个字节表示该符号在.symtab中的index，低4字节表示重定位的类型，不同的类型计算目标地址的方法不一样。

综上所述，我们可以得出符号val和func的种种信息：

val的重定位地址是在.text的偏移为6处，将来的链接过程中，连接器要将val的地址写到这个位置上来，val在.symtab中的index为9。

func的重定位地址是在.text的偏移为f处，将来的链接过程中，连接器要将func的地址写到这个位置上来，func在.symtab中的为a。

关于重定位的类型，《ELF V1.2》的第57和93页有详细说明。

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" alt="" />

这里两个符号的类型 R_X86_64_PC32，重定位地址的计算方法为S+A-P，即符号地址和下条指令间的偏移量。

objdump -S test.o查看汇编文件

[thm@tanghuimin static_link]$ objdump -S test.o 

test.o:     file format elf64-x86- 

Disassembly of section .text: 

 <main>:
   :                           push   %rbp
   :      e5                 mov    %rsp,%rbp
   :    c7      0a     movl   $0xa,0x0(%rip)        # e <main+0xe>
   b:
   e:    e8               callq   <main+0x13>
  :    b8               mov    $0x0,%eax
  :    c9                       leaveq
  :    c3                       retq   

可以看到.text中偏移6处四个字节(val的地址)为全0，偏移f处四个字节(func的地址)为全0。

(2.2)再来看看common.o:

readelf -s查看common.o的符号表

......
     :       OBJECT  GLOBAL DEFAULT     val
     :      FUNC    GLOBAL DEFAULT     func

可以看到val定义在index为3的.data里，func定义在index为1的.text里，这两个符号都是在common.c文件内部定义的。

readelf -S查看common.o的section header table

......
[ ] .rela.text        RELA                

......

readelf -r查看common.o的重定位详细信息

Relocation section '.rela.text' at offset 0x528 contains  entries:
  Offset          Info           Type           Sym. Value    Sym. Name + Addend
   R_X86_64_PC32      val –
......

以上信息可以得出，需要被重定位的符号是val，它在.symtab中的index为8，需要被重定位的地址是在.text中偏移为6处，重定位类型为 R_X86_64_PC32，即.text偏移为6处的地址是val地址和下一条指令间的偏移。

Objdump -S查看common.o的汇编文件：

......
 <func>:
   :                           push   %rbp
   :      e5                 mov    %rsp,%rbp
   :    8b             mov    0x0(%rip),%eax        # a <func+0xa>
   a:     c0 0a                 add    $0xa,%eax
   d:    c9                       leaveq
   e:    c3                       retq 

可以看到偏移为6处的四个字节(val的地址)全为0，需要在链接的时候写入val的地址。

(3)链接

将两个.o文件链接，

gcc -o test test.o common.o

生成的test为EXEC类型

静态链接的过程引用《程序员的自我修养》第101页的概述：

第一步：空间与地址分配

扫描所有的输入目标文件，获得它们的各个段的长度、属性和位置，并且将输入目标文件中的符号表中所有的符号定义和符号引用收集起来，统一放到一个全局符号表。这一步中，连接器将能获得所有输入目标文件的段长度，并且将它们合并，计算出输出文件中各个段合并后的长度与位置，并建立映射关系。

第二步：符号解析与重定位

使用上面第一步中收集到的所有信息，读取输入文件中段的数据、重定位信息，并且进行符号解析与重定位、调整代码中的地址等。事实上第二步是链接过程的核心，特别是重定位的过程。

提取关键字可以是:合并段，全局符号表，重定位

来看看重定位之后的test文件

readelf -l查看test进程在内存中的映像分布：

......
 LOAD           0x0000000000000000 0x0000000000400000 0x0000000000400000
                 0x0000000000000664 0x0000000000000664  R E
  LOAD           0x0000000000000668 0x0000000000600668 0x0000000000600668
                 0x00000000000001e8 0x00000000000001f8  RW
......

可以看到text segment被映射到虚拟地址0x400000处，data segment被映射到虚拟地址0x600668处。

readelf test -s查看test的符号表

......
   : 000000000060084c      OBJECT  GLOBAL DEFAULT    val
......
:      FUNC    GLOBAL DEFAULT    func
......
:      FUNC    GLOBAL DEFAULT    main
......

反汇编

objdump -S test > test.S

......
  <main>:
   :                             push   %rbp
   :         e5                mov    %rsp,%rbp
   :       c7  ca    0a    movl   $0xa,0x2003ca(%rip)        # 60084c <val>
   40047f:
   :       e8              callq   <func>
    :       b8              mov    $0x0,%eax
   40048c:       c9                      leaveq
   40048d:       c3                      retq
   40048e:                             nop
   40048f:                             nop 

  <func>:
   :                             push   %rbp
   :         e5                mov    %rsp,%rbp
   :       8b  b2          mov    0x2003b2(%rip),%eax        # 60084c <val>
   40049a:        c0 0a                add    $0xa,%eax
   40049d:       c9                      leaveq
   40049e:       c3                      retq
   40049f:                             nop
...... 

main函数中

地址0x400478处：

400478: c7 05 ca 03 20 00 0a movl $0xa,0x2003ca(%rip) # 60084c <val>

%rip+0x2003ca=0x400482+0x2003ca=0x60084c=val的地址

地址0x400482处：

118 400482: e8 09 00 00 00 callq 400490 <func>

该条指令的下一条指令地址为0x400487，0x400487+0x09=0x400490=func的地址

func中

地址0x 400494处：

128 400494: 8b 05 b2 03 20 00 mov 0x2003b2(%rip),%eax # 60084c <val>

%rip+ 0x2003b2= 0x40049a+0x2003b2=0x60084c=val的地址

由此可见这三处重定位的地址都为符号地址与下条指令间的偏移，符合上面分析的重定位类型。