Free what is a binary code software for linux

Scriptol to binary Compiler is a C++ native compiler.

Installation:

It is better to install Scriptol at root of a disk, for example:
c:scriptolc

Once the archive is extracted into the scriptolc directory, you have just to change to this directory to run the compiler.

To use the compiler at command line from any directory, you have to put the compiler into the path variable.

The setup script installs required file into sub-directories, or into the directory given as argument. Before to use the compiler, you have to read the licence, in the doc
directory: licence.html.

Usage:

Just type:
./solc mysource

Type "solc" only to list the options.

If your program is a multi-file project, the source given as parameter must be the main source file, the compiler will know dependencies from "include" statements and will build what is needed.

Exemples:

Type from the main scriptol directory:
./solc -bre demosfibo

Configuring:

By editing the solc.ini file, you may change the second pass compiler (you may have to rebuild the libsol library for this compiler), change the options of the compiler or add header files to include.

To add header files, just add "header=someheader.hpp" lines into the config file.

A xxx.cfg file may be written for each project main source beeing xxx, and if present, it overloads the solc.ini file.

Search::Binary is a Perl module for generic binary search.

SYNOPSIS

use Seach::Binary;
$pos = binary_search($min, $max, $val, $read, $handle, [$size]);

binary_search implements a generic binary search algorithm returning the position of the first record whose index value is greater than or equal to $val. The search routine does not define any of the terms position, record or index value, but leaves their interpretation and implementation to the user supplied function &$read(). The only restriction is that positions must be integer scalars.

During the search the read function will be called with three arguments: the input parameters $handle and $val, and a position. If the position is not undef, the read function should read the first whole record starting at or after the position; otherwise, the read function should read the record immediately following the last record it read. The search algorithm will guarantee that the first call to the read function will not be with a position of undef. The read function needs to return a two element array consisting of the result of comparing $val with the index value of the read record and the position of the read record. The comparison value must be positive if $val is strictly greater than the index value of the read record, 0 if equal, and negative if strictly less. Furthermore, the returned position value must be greater than or equal to the position the read function was called with.

The input parameters $min and $max are positions and represents the extent of the search. Only records which begin at positions within this range (inclusive) will be searched. Moreover, $min must be the starting position of a record. If present $size is a difference between positions and determines when the algorithms switches to a sequential search. $val is an index value. The value of $handle is of no consequence to the binary search algorithm; it is merely passed as a convenience to the read function.

The Java Binary Enhancement Tool (JBET) is a general Java program analysis and manipulation tool. Existing class files can be disassembled, reassembled, or edited programmatically through the JBET API. JBET can also be used to create new Java class files from scratch. JBET uses a convenient internal representation of all the contents of Java binary (.class) files, allowing the user to edit the classes easily, in a structured manner.

JBET was developed as part of the DARPA Self-Protecting Mobile Agents project under the OASIS and Active Networks programs (contract number N66001-00-C-8602) in order to study automated software obfuscation.

The Java language was chosen for this project because of the (relative) ease of constructing binary editing tools provided by the large amount of type information present in the class files. Our two reports, the Obfuscation Techniques Evaluation Report, and the Obfuscation Report, are available from the download area. The obfuscation tool developed is not part of this release.

JBET was also used in the DARPA/AFRL Survivable Server project (contract number F30602-00-C-0183) to add additional security checks to the Java Standard Library. (The Java SecurityManager API does not support many desirable security checks, such as continued authorization of file accesses after opening.)

JBET was used to replace the native method references in the Java standard library with stubs that call a pluggable security policy. This tool, called Jpolicy, is also available for download at this website. Jpolicy is very incomplete at this time, but may be interesting to those working in Java security or changing the standard library themselves.

The internal representation of Java class files used by JBET is intented to make it easy for programmers to write Java binary code transforms. Each element of Java class files has a corresponding internal data structure: ClassInfo for entire classes, MethodInfo for methods, FieldInfo for fields, Snippit for code blocks, and Instruction for individual instructions. Snippit and Instruction understand Java opcode syntax and semantics, allowing automated creation of valid Java programs. A Java-compatible class verifier is also included.

Some code transforms are difficult to program directly by manipulating Java instructions. For those transforms, a directed acyclic graph (DAG) representation of code is available. In the DAG representation, each basic block has a corresponding DAG, with a set of input and output nodes. Edges in the graph connect "producer" nodes (such as constants, or the result of calculations) to "user" nodes (such as method calls or other calculations). Methods are divided into basic blocks and control flow is stored at the basic block level (possible because Java has only fixed jump targets)

JBET requires a Java 1.4 virtual machine to run, although it can operate on class files from earlier Java versions. The packaging and build environment supplied supports Linux and Windows with Cygwin; however, the build process is simple and could be performed manually on other platforms. Perl is required for regression testing.

Jpolicy requires a Java 1.4 virtual machine to build, either Linux or Windows NT/XP with Cygwin. gcc is required for building on Windows (supplied with Cygwin). The runtime system can be either Java 1.3 or 1.4 (with Suns JVM only), running on Linux or Windows NT/XP. Windows 9x and Windows 2000 may work as well, but have not been tested.

Installation

1. Install jdk 1.4.1.
2. Set CLASSPATH to jdk1.4.1/jre/lib/rt.jar
3. cd src; make
4. If that didnt work, examine the makefile. java or javac may not be in the path.
5. To build a jar file that can be used with "java -jar jbet.jar", run "make jar".
6. If you have perl installed, run the tests with "make test".
Optionally, run "make regen; make test".

Make a symbolic link from jbet3/bin/jbet to somewhere in your path.

Usage

JBET uses the JNI format for class names, and JNI type and method descriptors. For a summary of this syntax, use jbet help syntax. Suns JVM specification may also be helpful.

To look at a class disassembly, use jbet print. Try disassembling a class you have source for, and was built with debug info (-g): jbet -P < classpath > print < classname >. Suns JVM specification has an instruction reference.

Convert::Binary::C is a Binary Data Conversion using C Types.

SYNOPSIS

Simple
use Convert::Binary::C;

#---------------------------------------------
# Create a new object and parse embedded code
#---------------------------------------------
my $c = Convert::Binary::C->new->parse( DEC, day => 24 };

my $packed = $c->pack( Date, $date );
Advanced
use Convert::Binary::C;
use Data::Dumper;

#---------------------
# Create a new object
#---------------------
my $c = new Convert::Binary::C ByteOrder => BigEndian;

#---------------------------------------------------
# Add include paths and global preprocessor defines
#---------------------------------------------------
$c->Include( /usr/lib/gcc-lib/i686-pc-linux-gnu/3.3.6/include,
/usr/include )
->Define( qw( __USE_POSIX __USE_ISOC99=1 ) );

#----------------------------------
# Parse the time.h header file
#----------------------------------
$c->parse_file( time.h );

#---------------------------------------
# See which files the object depends on
#---------------------------------------
print Dumper( [$c->dependencies] );

#-----------------------------------------------------------
# See if struct timespec is defined and dump its definition
#-----------------------------------------------------------
if( $c->def( struct timespec ) ) {
print Dumper( $c->struct( timespec ) );
}

#-------------------------------
# Create some binary dummy data
#-------------------------------
my $data = "binaryteststring";

#--------------------------------------------------------
# Unpack $data according to struct timespec definition
#--------------------------------------------------------
if( length($data) >= $c->sizeof( timespec ) ) {
my $perl = $c->unpack( timespec, $data );
print Dumper( $perl );
}

#--------------------------------------------------------
# See which member lies at offset 5 of struct timespec
#--------------------------------------------------------
my $member = $c->member( timespec, 5 );
print "member( timespec, 5 ) = $membern";

Convert::Binary::C is a preprocessor and parser for C type definitions. It is highly configurable and should support arbitrarily complex data structures. Its object-oriented interface has pack and unpack methods that act as replacements for Perls pack and unpack and allow to use the C types instead of a string representation of the data structure for conversion of binary data from and to Perls complex data structures.

Actually, what Convert::Binary::C does is not very different from what a C compiler does, just that it doesnt compile the source code into an object file or executable, but only parses the code and allows Perl to use the enumerations, structs, unions and typedefs that have been defined within your C source for binary data conversion, similar to Perls pack and unpack.

Beyond that, the module offers a lot of convenience methods to retrieve information about the C types that have been parsed.

Parse::Binary::FixedFormat is a Perl module to convert between fixed-length fields and hashes.

SYNOPSIS

use Parse::Binary::FixedFormat;

my $tarhdr =
new Parse::Binary::FixedFormat [ qw(name:a100 mode:a8 uid:a8 gid:a8 size:a12
mtime:a12 chksum:a8 typeflag:a1 linkname:a100
magic:a6 version:a2 uname:a32 gname:a32
devmajor:a8 devminor:a8 prefix:a155) ];
my $buf;
read TARFILE, $buf, 512;

# create a hash from the buffer read from the file
my $hdr = $tarhdr->unformat($buf); # $hdr gets a hash ref

# create a flat record from a hash reference
my $buf = $tarhdr->format($hdr); # $hdr is a hash ref

# create a hash for a new record
my $newrec = $tarhdr->blank();

Parse::Binary::FixedFormat can be used to convert between a buffer with fixed-length field definitions and a hash with named entries for each field. The perl pack and unpack functions are used to perform the conversions. Parse::Binary::FixedFormat builds the format string by concatenating the field descriptions and converts between the lists used by pack and unpack and a hash that can be reference by field name.