praton1729 · April 13, 2025 19:25
diff --git a/elf_analyzer_aarch64.py b/elf_analyzer_aarch64.py
 #!/usr/bin/env python3
 """
 Binary Section Analyzer and Compressor with Final Binary Generator for AARCH64

 This script analyzes an ELF file, extracts its sections, compresses them with
 various algorithms, and creates a final compressed binary with metadata for decompression.
 Specifically configured for AARCH64 architecture.
 """

 import os
 import sys
 import subprocess
 import zlib
 import lzma
 import bz2
 import tempfile
 import shutil
 import struct
 import argparse
 import json
 import pickle
 from collections import defaultdict, Counter
 from pathlib import Path
 import math

 # Magic number for our custom compressed binary format
 MAGIC = b'SECCOMP'
 FORMAT_VERSION = 1

 def run_command(cmd):
    """Run a shell command and return the output."""
    try:
        result = subprocess.run(cmd, check=True, stdout=subprocess.PIPE, 
                               stderr=subprocess.PIPE, text=True, shell=True)
        return result.stdout
    except subprocess.CalledProcessError as e:
        print(f"Error executing command: {cmd}")
        print(f"Error: {e.stderr}")
        sys.exit(1)

 def extract_sections(elf_file, prefix="aarch64-linux-gnu-"):
    """Extract all sections from an ELF file and return a dictionary of their info."""
    sections = {}
    
    # Get section information using AARCH64 tools
    objdump_cmd = f"{prefix}objdump -h {elf_file}"
    objdump_output = run_command(objdump_cmd)
    
    # Parse the output
    current_section = None
    for line in objdump_output.splitlines():
        line = line.strip()
        if not line:
            continue
            
        if line.startswith('Idx'):  # Header line
            continue
            
        parts = line.split()
        if len(parts) >= 7 and parts[0].isdigit():
            section_name = parts[1]
            if section_name.startswith('.'):
                size_hex = parts[2]
                size = int(size_hex, 16)
                vma = parts[3]
                vma_int = int(vma, 16)
                lma = parts[4]
                file_off = parts[5]
                flags = parts[6]
                
                sections[section_name] = {
                    'size': size,
                    'vma': vma,
                    'vma_int': vma_int,
                    'lma': lma,
                    'file_off': file_off,
                    'flags': flags,
                    'alloc': 'ALLOC' in flags,
                    'data': None  # Will store actual binary data later
                }
    
    # Extract sections that have ALLOC flag set
    tmpdir = tempfile.mkdtemp()
    try:
        for section_name, info in sections.items():
            if info['size'] > 0:  # Only extract non-empty sections
                output_file = os.path.join(tmpdir, f"{section_name.replace('/', '_')}.bin")
                objcopy_cmd = f"{prefix}objcopy -O binary --only-section={section_name} {elf_file} {output_file}"
                run_command(objcopy_cmd)
                
                # Read the extracted binary data
                if os.path.exists(output_file) and os.path.getsize(output_file) > 0:
                    with open(output_file, 'rb') as f:
                        sections[section_name]['data'] = f.read()
                else:
                    # For sections like .bss that don't have actual file content
                    sections[section_name]['data'] = b'\x00' * info['size'] if info['alloc'] else None
    finally:
        shutil.rmtree(tmpdir)
    
    # Get entry point using AARCH64 readelf
    readelf_cmd = f"{prefix}readelf -h {elf_file}"
    readelf_output = run_command(readelf_cmd)
    entry_point = None
    for line in readelf_output.splitlines():
        if "Entry point address" in line:
            entry_point = int(line.split(':')[1].strip(), 16)
            break
    
    return sections, entry_point

 def analyze_section_entropy(data):
    """Calculate the entropy of a binary section."""
    if not data or len(data) == 0:
        return 0.0
        
    # Count byte frequencies
    freqs = Counter(data)
    total = len(data)
    
    # Calculate entropy
    entropy = 0
    for count in freqs.values():
        probability = count / total
        entropy -= probability * math.log2(probability)
    
    return entropy

 def find_repeating_patterns(data, min_length=4, max_length=32, step=4):
    """Find repeating byte patterns in the data."""
    if not data or len(data) < min_length:
        return {}
        
    patterns = defaultdict(int)
    
    # Check for patterns of different lengths
    for pattern_len in range(min_length, min(max_length, len(data)), step):
        for i in range(len(data) - pattern_len + 1):
            pattern = data[i:i+pattern_len]
            patterns[pattern] += 1
    
    # Filter out patterns that don't repeat
    repeating = {pattern: count for pattern, count in patterns.items() if count > 1}
    
    # Sort by (count * length) to find the most valuable patterns
    sorted_patterns = sorted(
        repeating.items(),
        key=lambda x: len(x[0]) * x[1],
        reverse=True
    )
    
    return dict(sorted_patterns[:20])  # Return top 20 most valuable patterns

 def simple_delta_encode(data):
    """Apply simple delta encoding to a byte array."""
    if not data or len(data) <= 1:
        return data
        
    delta_encoded = bytearray(len(data))
    delta_encoded[0] = data[0]
    for i in range(1, len(data)):
        delta_encoded[i] = (data[i] - data[i-1]) & 0xFF
    
    return bytes(delta_encoded)

 def simple_delta_decode(data):
    """Decode simple delta encoding."""
    if not data or len(data) <= 1:
        return data
        
    decoded = bytearray(len(data))
    decoded[0] = data[0]
    for i in range(1, len(data)):
        decoded[i] = (decoded[i-1] + data[i]) & 0xFF
    
    return bytes(decoded)

 def word_delta_encode(data):
    """Apply word-aligned delta encoding - optimized for AARCH64's 32-bit/64-bit instructions."""
    if len(data) < 4:
        return data
    
    # For AARCH64, we'll use 4-byte alignment 
    # (could also use 8 bytes for some instruction sets)
    word_size = 4
    
    # Ensure data length is multiple of word_size by padding if needed
    if len(data) % word_size != 0:
        padded_data = bytearray(data)
        padded_data.extend(b'\x00' * (word_size - (len(data) % word_size)))
        data = bytes(padded_data)
    
    result = bytearray()
    # First word is stored as-is
    result.extend(data[0:word_size])
    
    # Process remaining words
    for i in range(word_size, len(data), word_size):
        for j in range(word_size):
            result.append(data[i+j] ^ data[i-word_size+j])
    
    return bytes(result)

 def word_delta_decode(data):
    """Decode word-aligned delta encoding for AARCH64's word size."""
    if len(data) < 4:
        return data
    
    word_size = 4  # Using 4-byte words for AARCH64
    
    result = bytearray(len(data))
    # First word is copied as-is
    result[0:word_size] = data[0:word_size]
    
    # Process remaining words
    for i in range(word_size, len(data), word_size):
        for j in range(word_size):
            result[i+j] = data[i+j] ^ result[i-word_size+j]
    
    return bytes(result)

 def aarch64_instruction_encode(data):
    """Special encoding for AARCH64 instructions, looking for common patterns."""
    if len(data) < 4:
        return data
    
    # AARCH64 uses fixed 4-byte instructions
    # We can exploit patterns like:
    # - Common opcodes
    # - Register patterns
    # - Small immediate values
    
    # For now, a simplified approach:
    result = bytearray()
    
    # Check if it's likely code (high entropy but with patterns)
    entropy = analyze_section_entropy(data)
    if entropy < 6.0 or entropy > 7.5:
        return data  # Probably not instructions, use default
    
    # Extract 4-byte chunks
    chunks = []
    for i in range(0, len(data), 4):
        if i + 4 <= len(data):
            chunks.append(data[i:i+4])
    
    if not chunks:
        return data
    
    # Look for similar chunks (differing only in registers or immediates)
    similarities = []
    for i in range(len(chunks)):
        for j in range(i+1, len(chunks)):
            # Count differing bytes
            diff_count = sum(b1 != b2 for b1, b2 in zip(chunks[i], chunks[j]))
            if diff_count <= 2:  # Similar instructions
                similarities.append((i, j, diff_count))
    
    # If we found many similarities, use delta encoding
    if len(similarities) > len(chunks) // 4:
        return word_delta_encode(data)
    
    # Otherwise fall back to regular data
    return data

 def aarch64_instruction_decode(data):
    """Decode the AARCH64 instruction encoding."""
    # For now, we'll just call word_delta_decode since our encoder is simplified
    return word_delta_decode(data)

 def dictionary_encode(data):
    """Apply simple dictionary encoding to the data."""
    if len(data) < 16:
        return data  # Too small to be worth it
    
    # Find repeating patterns
    patterns = find_repeating_patterns(data, min_length=8, max_length=64)
    if not patterns:
        return data  # No good patterns found
    
    # Sort patterns by value (bytes saved)
    sorted_patterns = sorted(
        patterns.items(),
        key=lambda x: (len(x[0]) - 2) * x[1],  # Value minus overhead
        reverse=True
    )
    
    # Use top patterns (limit dictionary size)
    dictionary = []
    for pattern, _ in sorted_patterns[:16]:  # Limit to 16 entries
        if len(pattern) >= 8:  # Only use if pattern is long enough
            dictionary.append(pattern)
    
    if not dictionary:
        return data
    
    # Encode the data
    result = bytearray()
    # First byte is dictionary size
    result.append(len(dictionary))
    
    # Add dictionary entries (length + pattern)
    for pattern in dictionary:
        result.append(len(pattern))
        result.extend(pattern)
    
    # Process the data
    i = 0
    while i < len(data):
        # Check if current position matches any pattern
        found = False
        for idx, pattern in enumerate(dictionary):
            if i + len(pattern) <= len(data) and data[i:i+len(pattern)] == pattern:
                # Found a match - use index (0x80 and above are dictionary references)
                result.append(0x80 | idx)
                i += len(pattern)
                found = True
                break
        
        if not found:
            # No match, copy the byte literally
            result.append(data[i])
            i += 1
    
    # Return original if our encoding is larger
    return bytes(result) if len(result) < len(data) else data

 def dictionary_decode(data):
    """Decode dictionary-encoded data."""
    if not data or len(data) < 2:
        return data
    
    # First byte is dictionary size
    dict_size = data[0]
    if dict_size == 0 or dict_size > 16:
        return data  # Invalid dictionary size or not dictionary encoded
    
    # Read dictionary
    dictionary = []
    pos = 1
    for _ in range(dict_size):
        if pos >= len(data):
            return data  # Invalid format
        pattern_len = data[pos]
        pos += 1
        if pos + pattern_len > len(data):
            return data  # Invalid format
        pattern = data[pos:pos+pattern_len]
        dictionary.append(pattern)
        pos += pattern_len
    
    # Decode the data
    result = bytearray()
    while pos < len(data):
        byte = data[pos]
        pos += 1
        
        if byte & 0x80:  # Dictionary reference
            idx = byte & 0x7F
            if idx < len(dictionary):
                result.extend(dictionary[idx])
            else:
                return data  # Invalid reference
        else:
            # Literal byte
            result.append(byte)
    
    return bytes(result)

 def compress_with_algorithms(data, is_code=False):
    """Compress data with various algorithms and return results."""
    if not data:
        return {}
        
    results = {}
    
    # Standard compression algorithms with their implementation
    results['none'] = {
        'size': len(data),
        'data': data,
        'encode': lambda x: x,
        'decode': lambda x: x
    }
    
    # Standard compression algorithms
    try:
        compressed = zlib.compress(data)
        results['zlib'] = {
            'size': len(compressed),
            'data': compressed,
            'encode': zlib.compress,
            'decode': zlib.decompress
        }
    except:
        pass
    
    try:
        compressed = lzma.compress(data)
        results['lzma'] = {
            'size': len(compressed),
            'data': compressed,
            'encode': lzma.compress,
            'decode': lzma.decompress
        }
    except:
        pass
    
    try:
        compressed = bz2.compress(data)
        results['bz2'] = {
            'size': len(compressed),
            'data': compressed,
            'encode': bz2.compress,
            'decode': bz2.decompress
        }
    except:
        pass
    
    # Simple delta encoding
    if len(data) > 1:
        try:
            delta_encoded = simple_delta_encode(data)
            compressed = zlib.compress(delta_encoded)
            results['delta'] = {
                'size': len(compressed),
                'data': compressed,
                'encode': lambda x: zlib.compress(simple_delta_encode(x)),
                'decode': lambda x: simple_delta_decode(zlib.decompress(x))
            }
        except:
            pass
    
    # Word-aligned delta - good for AARCH64 instructions
    if len(data) >= 4:
        try:
            word_delta = word_delta_encode(data)
            compressed = zlib.compress(word_delta)
            results['word_delta'] = {
                'size': len(compressed),
                'data': compressed,
                'encode': lambda x: zlib.compress(word_delta_encode(x)),
                'decode': lambda x: word_delta_decode(zlib.decompress(x))
            }
        except:
            pass
    
    # AARCH64-specific instruction encoding - only if code section
    if is_code and len(data) >= 8:
        try:
            aarch_encoded = aarch64_instruction_encode(data)
            compressed = zlib.compress(aarch_encoded)
            results['aarch64_code'] = {
                'size': len(compressed),
                'data': compressed,
                'encode': lambda x: zlib.compress(aarch64_instruction_encode(x)),
                'decode': lambda x: aarch64_instruction_decode(zlib.decompress(x))
            }
        except:
            pass
    
    # Dictionary-based approach
    if len(data) > 32:
        try:
            dict_encoded = dictionary_encode(data)
            if len(dict_encoded) < len(data):
                compressed = zlib.compress(dict_encoded)
                results['dictionary'] = {
                    'size': len(compressed),
                    'data': compressed,
                    'encode': lambda x: zlib.compress(dictionary_encode(x)),
                    'decode': lambda x: dictionary_decode(zlib.decompress(x))
                }
        except:
            pass
    
    return results

 def analyze_elf(elf_file, create_binary=False, output_file=None, decompressor=False, prefix="aarch64-linux-gnu-"):
    """Analyze an ELF file's sections and compression potential."""
    print(f"Analyzing AARCH64 ELF file: {elf_file}")
    
    # Extract sections using AARCH64 tools
    sections, entry_point = extract_sections(elf_file, prefix)
    
    # Analyze and compress each section
    results = []
    
    print("\nSection Analysis:")
    print("-" * 80)
    print(f"{'Section':<20} {'Size':<10} {'Entropy':<10} {'Best Algorithm':<16} {'Comp Size':<10} {'Ratio':<10}")
    print("-" * 80)
    
    section_results = {}
    for name, info in sorted(sections.items(), key=lambda x: x[1]['size'], reverse=True):
        data = info['data']
        if data is None or len(data) == 0:
            continue
            
        # Skip non-ALLOC sections if we're creating a binary
        if create_binary and not info['alloc']:
            continue
            
        orig_size = len(data)
        entropy = analyze_section_entropy(data)
        
        # Check if this is likely a code section
        is_code = name in ('.text', '.init', '.fini', '.plt') or 'CODE' in info['flags']
        
        compression_results = compress_with_algorithms(data, is_code)
        
        # Find best compression
        best_algo = min(compression_results.items(), key=lambda x: x[1]['size'])
        algo_name = best_algo[0]
        best_size = best_algo[1]['size']
        best_ratio = best_size / orig_size if orig_size > 0 else 1.0
        
        # Store result
        section_results[name] = {
            'name': name,
            'size': orig_size,
            'entropy': entropy,
            'vma': info['vma_int'],
            'alloc': info['alloc'],
            'flags': info['flags'],
            'is_code': is_code,
            'algo': algo_name,
            'comp_size': best_size,
            'comp_data': best_algo[1]['data'],
            'encode': best_algo[1]['encode'],
            'decode': best_algo[1]['decode'],
            'ratio': best_ratio
        }
        
        print(f"{name:<20} {orig_size:<10} {entropy:<10.2f} {algo_name:<16} {best_size:<10} {best_ratio:<10.2f}")
        
        results.append(section_results[name])
    
    # Print summary
    print("\nCompression Summary:")
    print("-" * 80)
    
    # Group sections by type
    section_types = defaultdict(list)
    for r in results:
        # Determine section type based on name and flags
        if r['is_code']:
            section_type = 'Code'
        elif r['name'] in ('.data', '.rodata'):
            section_type = 'Data'
        elif r['name'].startswith('.debug'):
            section_type = 'Debug'
        else:
            section_type = 'Other'
        
        section_types[section_type].append(r)
    
    # Print results by section type
    for section_type, sections in section_types.items():
        total_size = sum(s['size'] for s in sections)
        best_size = sum(s['comp_size'] for s in sections)
        
        print(f"{section_type} sections:")
        print(f"  Total size: {total_size} bytes")
        print(f"  Compressed size: {best_size} bytes")
        print(f"  Overall ratio: {best_size/total_size:.2f}")
        
        # Best algorithms per type
        algo_counts = Counter(s['algo'] for s in sections)
        best_algos = algo_counts.most_common(2)
        print(f"  Best algorithms: {', '.join(f'{algo} ({count})' for algo, count in best_algos)}")
        print()
    
    # Create compressed binary if requested
    if create_binary and output_file:
        create_compressed_binary(output_file, section_results, entry_point, decompressor)
    
    return section_results, entry_point

 def create_compressed_binary(output_file, section_results, entry_point, include_decompressor=False):
    """Create a compressed binary file using the best compression for each section."""
    # Filter to only include ALLOC sections
    alloc_sections = {name: info for name, info in section_results.items() if info['alloc']}
    
    # Create header
    header = bytearray()
    
    # Magic number
    header.extend(MAGIC)
    
    # Format version (1 byte)
    header.append(FORMAT_VERSION)
    
    # Entry point (8 bytes for AARCH64 to support full 64-bit addresses)
    header.extend(struct.pack("<Q", entry_point))
    
    # Number of sections (2 bytes)
    header.extend(struct.pack("<H", len(alloc_sections)))
    
    # Section directory
    section_data = bytearray()
    
    for name, info in sorted(alloc_sections.items(), key=lambda x: x[1]['vma']):
        # Section name (null-terminated, max 16 chars)
        name_bytes = name.encode('ascii')[:15] + b'\0'
        header.extend(name_bytes.ljust(16, b'\0'))
        
        # Virtual memory address (8 bytes for AARCH64)
        header.extend(struct.pack("<Q", info['vma']))
        
        # Uncompressed size (4 bytes)
        header.extend(struct.pack("<I", info['size']))
        
        # Compression algorithm (1 byte)
        algo_id = {
            'none': 0,
            'zlib': 1,
            'lzma': 2,
            'bz2': 3,
            'delta': 4,
            'word_delta': 5,
            'dictionary': 6,
            'aarch64_code': 7
        }.get(info['algo'], 0)
        header.append(algo_id)
        
        # Offset to compressed data (4 bytes) - will be filled in later
        offset_pos = len(header)
        header.extend(b'\0\0\0\0')
        
        # Compressed size (4 bytes)
        header.extend(struct.pack("<I", info['comp_size']))
        
        # Store the compressed data
        data_offset = len(section_data)
        section_data.extend(info['comp_data'])
        
        # Update the offset in the header
        struct.pack_into("<I", header, offset_pos, len(header) + data_offset)
    
    # If including a decompressor, add it here
    if include_decompressor:
        # Create a minimal decompressor in C
        decompressor_code = generate_aarch64_decompressor_code()
        decompressor_size = len(decompressor_code)
        
        # Add decompressor info to header
        header.extend(struct.pack("<I", decompressor_size))
        header.extend(decompressor_code)
    else:
        # No decompressor
        header.extend(struct.pack("<I", 0))
    
    # Write the final binary
    with open(output_file, 'wb') as f:
        f.write(header)
        f.write(section_data)
    
    print(f"\nCreated compressed binary: {output_file}")
    print(f"  Header size: {len(header)} bytes")
    print(f"  Data size: {len(section_data)} bytes")
    print(f"  Total size: {len(header) + len(section_data)} bytes")
    
    # Create JSON metadata file
    metadata = {
        'architecture': 'aarch64',
        'entry_point': entry_point,
        'sections': []
    }
    
    for name, info in alloc_sections.items():
        metadata['sections'].append({
            'name': name,
            'vma': info['vma'],
            'size': info['size'],
            'comp_size': info['comp_size'],
            'algo': info['algo'],
            'is_code': info['is_code']
        })
    
    meta_file = f"{output_file}.meta.json"
    with open(meta_file, 'w') as f:
        json.dump(metadata, f, indent=2)
    
    print(f"Created metadata file: {meta_file}")

 def generate_aarch64_decompressor_code():
    """Generate a minimal AARCH64 decompressor."""
    # This would be a simple ARM assembly decompressor
    # For simplicity, we'll just return placeholder bytes
    return b'AARCH64_DECOMPRESSOR_PLACEHOLDER'

 def create_aarch64_decompressor(output_file, section_results, entry_point, prefix="aarch64-linux-gnu-"):
    """Create a standalone decompressor executable for AARCH64."""
    # This would generate a C file with the decompression logic
    # For now, we'll just create a simple C file stub
    c_code = """
    #include <stdio.h>
    #include <stdlib.h>
    
    int main(int argc, char **argv) {
        if (argc != 3) {
            printf("Usage: %s input.bin output.bin\\n", argv[0]);
            return 1;
        }
        
        printf("AARCH64 Decompressor stub - would decompress %s to %s\\n", argv[1], argv[2]);
        return 0;
    }
    """
    
    c_file = f"{output_file}.c"
    with open(c_file, 'w') as f:
        f.write(c_code)
    
    # Compile with AARCH64 toolchain
    gcc_cmd = f"{prefix}gcc -o {output_file} {c_file}"
    try:
        run_command(gcc_cmd)
        print(f"Created AARCH64 decompressor: {output_file}")
    except:
        print(f"Created decompressor source: {c_file}")
        print(f"Compile with: {gcc_cmd}")

 def main():
    parser = argparse.ArgumentParser(description='Analyze AARCH64 ELF file sections and create optimized binary')
    parser.add_argument('elf_file', help='Path to the AARCH64 ELF file to analyze')
    parser.add_argument('-o', '--output', help='Output file for compressed binary')
    parser.add_argument('-c', '--create-binary', action='store_true', help='Create compressed binary')
    parser.add_argument('-d', '--decompressor', action='store_true', help='Include decompressor in binary')
    parser.add_argument('-p', '--prefix', default='aarch64-linux-gnu-', help='Toolchain prefix (default: aarch64-linux-gnu-)')
    args = parser.parse_args()
    
    if not os.path.exists(args.elf_file):
        print(f"Error: File {args.elf_file} not found")
        sys.exit(1)
    
    output_file = args.output or f"{args.elf_file}.compressed.bin"
    
    analyze_elf(args.elf_file, args.create_binary, output_file, args.decompressor, args.prefix)
    
    if args.create_binary and args.decompressor:
        create_aarch64_decompressor(f"{output_file}.decomp", None, None, args.prefix)

 if __name__ == "__main__":
    main()
	#!/usr/bin/env python3
	"""
	Binary Section Analyzer and Compressor with Final Binary Generator for AARCH64

	This script analyzes an ELF file, extracts its sections, compresses them with
	various algorithms, and creates a final compressed binary with metadata for decompression.
	Specifically configured for AARCH64 architecture.
	"""

	import os
	import sys
	import subprocess
	import zlib
	import lzma
	import bz2
	import tempfile
	import shutil
	import struct
	import argparse
	import json
	import pickle
	from collections import defaultdict, Counter
	from pathlib import Path
	import math

	# Magic number for our custom compressed binary format
	MAGIC = b'SECCOMP'
	FORMAT_VERSION = 1

	def run_command(cmd):
	"""Run a shell command and return the output."""
	try:
	result = subprocess.run(cmd, check=True, stdout=subprocess.PIPE,
	stderr=subprocess.PIPE, text=True, shell=True)
	return result.stdout
	except subprocess.CalledProcessError as e:
	print(f"Error executing command: {cmd}")
	print(f"Error: {e.stderr}")
	sys.exit(1)

	def extract_sections(elf_file, prefix="aarch64-linux-gnu-"):
	"""Extract all sections from an ELF file and return a dictionary of their info."""
	sections = {}

	# Get section information using AARCH64 tools
	objdump_cmd = f"{prefix}objdump -h {elf_file}"
	objdump_output = run_command(objdump_cmd)

	# Parse the output
	current_section = None
	for line in objdump_output.splitlines():
	line = line.strip()
	if not line:
	continue

	if line.startswith('Idx'): # Header line
	continue

	parts = line.split()
	if len(parts) >= 7 and parts[0].isdigit():
	section_name = parts[1]
	if section_name.startswith('.'):
	size_hex = parts[2]
	size = int(size_hex, 16)
	vma = parts[3]
	vma_int = int(vma, 16)
	lma = parts[4]
	file_off = parts[5]
	flags = parts[6]

	sections[section_name] = {
	'size': size,
	'vma': vma,
	'vma_int': vma_int,
	'lma': lma,
	'file_off': file_off,
	'flags': flags,
	'alloc': 'ALLOC' in flags,
	'data': None # Will store actual binary data later
	}

	# Extract sections that have ALLOC flag set
	tmpdir = tempfile.mkdtemp()
	try:
	for section_name, info in sections.items():
	if info['size'] > 0: # Only extract non-empty sections
	output_file = os.path.join(tmpdir, f"{section_name.replace('/', '_')}.bin")
	objcopy_cmd = f"{prefix}objcopy -O binary --only-section={section_name} {elf_file} {output_file}"
	run_command(objcopy_cmd)

	# Read the extracted binary data
	if os.path.exists(output_file) and os.path.getsize(output_file) > 0:
	with open(output_file, 'rb') as f:
	sections[section_name]['data'] = f.read()
	else:
	# For sections like .bss that don't have actual file content
	sections[section_name]['data'] = b'\x00' * info['size'] if info['alloc'] else None
	finally:
	shutil.rmtree(tmpdir)

	# Get entry point using AARCH64 readelf
	readelf_cmd = f"{prefix}readelf -h {elf_file}"
	readelf_output = run_command(readelf_cmd)
	entry_point = None
	for line in readelf_output.splitlines():
	if "Entry point address" in line:
	entry_point = int(line.split(':')[1].strip(), 16)
	break

	return sections, entry_point

	def analyze_section_entropy(data):
	"""Calculate the entropy of a binary section."""
	if not data or len(data) == 0:
	return 0.0

	# Count byte frequencies
	freqs = Counter(data)
	total = len(data)

	# Calculate entropy
	entropy = 0
	for count in freqs.values():
	probability = count / total
	entropy -= probability * math.log2(probability)

	return entropy

	def find_repeating_patterns(data, min_length=4, max_length=32, step=4):
	"""Find repeating byte patterns in the data."""
	if not data or len(data) < min_length:
	return {}

	patterns = defaultdict(int)

	# Check for patterns of different lengths
	for pattern_len in range(min_length, min(max_length, len(data)), step):
	for i in range(len(data) - pattern_len + 1):
	pattern = data[i:i+pattern_len]
	patterns[pattern] += 1

	# Filter out patterns that don't repeat
	repeating = {pattern: count for pattern, count in patterns.items() if count > 1}

	# Sort by (count * length) to find the most valuable patterns
	sorted_patterns = sorted(
	repeating.items(),
	key=lambda x: len(x[0]) * x[1],
	reverse=True
	)

	return dict(sorted_patterns[:20]) # Return top 20 most valuable patterns

	def simple_delta_encode(data):
	"""Apply simple delta encoding to a byte array."""
	if not data or len(data) <= 1:
	return data

	delta_encoded = bytearray(len(data))
	delta_encoded[0] = data[0]
	for i in range(1, len(data)):
	delta_encoded[i] = (data[i] - data[i-1]) & 0xFF

	return bytes(delta_encoded)

	def simple_delta_decode(data):
	"""Decode simple delta encoding."""
	if not data or len(data) <= 1:
	return data

	decoded = bytearray(len(data))
	decoded[0] = data[0]
	for i in range(1, len(data)):
	decoded[i] = (decoded[i-1] + data[i]) & 0xFF

	return bytes(decoded)

	def word_delta_encode(data):
	"""Apply word-aligned delta encoding - optimized for AARCH64's 32-bit/64-bit instructions."""
	if len(data) < 4:
	return data

	# For AARCH64, we'll use 4-byte alignment
	# (could also use 8 bytes for some instruction sets)
	word_size = 4

	# Ensure data length is multiple of word_size by padding if needed
	if len(data) % word_size != 0:
	padded_data = bytearray(data)
	padded_data.extend(b'\x00' * (word_size - (len(data) % word_size)))
	data = bytes(padded_data)

	result = bytearray()
	# First word is stored as-is
	result.extend(data[0:word_size])

	# Process remaining words
	for i in range(word_size, len(data), word_size):
	for j in range(word_size):
	result.append(data[i+j] ^ data[i-word_size+j])

	return bytes(result)

	def word_delta_decode(data):
	"""Decode word-aligned delta encoding for AARCH64's word size."""
	if len(data) < 4:
	return data

	word_size = 4 # Using 4-byte words for AARCH64

	result = bytearray(len(data))
	# First word is copied as-is
	result[0:word_size] = data[0:word_size]

	# Process remaining words
	for i in range(word_size, len(data), word_size):
	for j in range(word_size):
	result[i+j] = data[i+j] ^ result[i-word_size+j]

	return bytes(result)

	def aarch64_instruction_encode(data):
	"""Special encoding for AARCH64 instructions, looking for common patterns."""
	if len(data) < 4:
	return data

	# AARCH64 uses fixed 4-byte instructions
	# We can exploit patterns like:
	# - Common opcodes
	# - Register patterns
	# - Small immediate values

	# For now, a simplified approach:
	result = bytearray()

	# Check if it's likely code (high entropy but with patterns)
	entropy = analyze_section_entropy(data)
	if entropy < 6.0 or entropy > 7.5:
	return data # Probably not instructions, use default

	# Extract 4-byte chunks
	chunks = []
	for i in range(0, len(data), 4):
	if i + 4 <= len(data):
	chunks.append(data[i:i+4])

	if not chunks:
	return data

	# Look for similar chunks (differing only in registers or immediates)
	similarities = []
	for i in range(len(chunks)):
	for j in range(i+1, len(chunks)):
	# Count differing bytes
	diff_count = sum(b1 != b2 for b1, b2 in zip(chunks[i], chunks[j]))
	if diff_count <= 2: # Similar instructions
	similarities.append((i, j, diff_count))

	# If we found many similarities, use delta encoding
	if len(similarities) > len(chunks) // 4:
	return word_delta_encode(data)

	# Otherwise fall back to regular data
	return data

	def aarch64_instruction_decode(data):
	"""Decode the AARCH64 instruction encoding."""
	# For now, we'll just call word_delta_decode since our encoder is simplified
	return word_delta_decode(data)

	def dictionary_encode(data):
	"""Apply simple dictionary encoding to the data."""
	if len(data) < 16:
	return data # Too small to be worth it

	# Find repeating patterns
	patterns = find_repeating_patterns(data, min_length=8, max_length=64)
	if not patterns:
	return data # No good patterns found

	# Sort patterns by value (bytes saved)
	sorted_patterns = sorted(
	patterns.items(),
	key=lambda x: (len(x[0]) - 2) * x[1], # Value minus overhead
	reverse=True
	)

	# Use top patterns (limit dictionary size)
	dictionary = []
	for pattern, _ in sorted_patterns[:16]: # Limit to 16 entries
	if len(pattern) >= 8: # Only use if pattern is long enough
	dictionary.append(pattern)

	if not dictionary:
	return data

	# Encode the data
	result = bytearray()
	# First byte is dictionary size
	result.append(len(dictionary))

	# Add dictionary entries (length + pattern)
	for pattern in dictionary:
	result.append(len(pattern))
	result.extend(pattern)

	# Process the data
	i = 0
	while i < len(data):
	# Check if current position matches any pattern
	found = False
	for idx, pattern in enumerate(dictionary):
	if i + len(pattern) <= len(data) and data[i:i+len(pattern)] == pattern:
	# Found a match - use index (0x80 and above are dictionary references)
	result.append(0x80 \| idx)
	i += len(pattern)
	found = True
	break

	if not found:
	# No match, copy the byte literally
	result.append(data[i])
	i += 1

	# Return original if our encoding is larger
	return bytes(result) if len(result) < len(data) else data

	def dictionary_decode(data):
	"""Decode dictionary-encoded data."""
	if not data or len(data) < 2:
	return data

	# First byte is dictionary size
	dict_size = data[0]
	if dict_size == 0 or dict_size > 16:
	return data # Invalid dictionary size or not dictionary encoded

	# Read dictionary
	dictionary = []
	pos = 1
	for _ in range(dict_size):
	if pos >= len(data):
	return data # Invalid format
	pattern_len = data[pos]
	pos += 1
	if pos + pattern_len > len(data):
	return data # Invalid format
	pattern = data[pos:pos+pattern_len]
	dictionary.append(pattern)
	pos += pattern_len

	# Decode the data
	result = bytearray()
	while pos < len(data):
	byte = data[pos]
	pos += 1

	if byte & 0x80: # Dictionary reference
	idx = byte & 0x7F
	if idx < len(dictionary):
	result.extend(dictionary[idx])
	else:
	return data # Invalid reference
	else:
	# Literal byte
	result.append(byte)

	return bytes(result)

	def compress_with_algorithms(data, is_code=False):
	"""Compress data with various algorithms and return results."""
	if not data:
	return {}

	results = {}

	# Standard compression algorithms with their implementation
	results['none'] = {
	'size': len(data),
	'data': data,
	'encode': lambda x: x,
	'decode': lambda x: x
	}

	# Standard compression algorithms
	try:
	compressed = zlib.compress(data)
	results['zlib'] = {
	'size': len(compressed),
	'data': compressed,
	'encode': zlib.compress,
	'decode': zlib.decompress
	}
	except:
	pass

	try:
	compressed = lzma.compress(data)
	results['lzma'] = {
	'size': len(compressed),
	'data': compressed,
	'encode': lzma.compress,
	'decode': lzma.decompress
	}
	except:
	pass

	try:
	compressed = bz2.compress(data)
	results['bz2'] = {
	'size': len(compressed),
	'data': compressed,
	'encode': bz2.compress,
	'decode': bz2.decompress
	}
	except:
	pass

	# Simple delta encoding
	if len(data) > 1:
	try:
	delta_encoded = simple_delta_encode(data)
	compressed = zlib.compress(delta_encoded)
	results['delta'] = {
	'size': len(compressed),
	'data': compressed,
	'encode': lambda x: zlib.compress(simple_delta_encode(x)),
	'decode': lambda x: simple_delta_decode(zlib.decompress(x))
	}
	except:
	pass

	# Word-aligned delta - good for AARCH64 instructions
	if len(data) >= 4:
	try:
	word_delta = word_delta_encode(data)
	compressed = zlib.compress(word_delta)
	results['word_delta'] = {
	'size': len(compressed),
	'data': compressed,
	'encode': lambda x: zlib.compress(word_delta_encode(x)),
	'decode': lambda x: word_delta_decode(zlib.decompress(x))
	}
	except:
	pass

	# AARCH64-specific instruction encoding - only if code section
	if is_code and len(data) >= 8:
	try:
	aarch_encoded = aarch64_instruction_encode(data)
	compressed = zlib.compress(aarch_encoded)
	results['aarch64_code'] = {
	'size': len(compressed),
	'data': compressed,
	'encode': lambda x: zlib.compress(aarch64_instruction_encode(x)),
	'decode': lambda x: aarch64_instruction_decode(zlib.decompress(x))
	}
	except:
	pass

	# Dictionary-based approach
	if len(data) > 32:
	try:
	dict_encoded = dictionary_encode(data)
	if len(dict_encoded) < len(data):
	compressed = zlib.compress(dict_encoded)
	results['dictionary'] = {
	'size': len(compressed),
	'data': compressed,
	'encode': lambda x: zlib.compress(dictionary_encode(x)),
	'decode': lambda x: dictionary_decode(zlib.decompress(x))
	}
	except:
	pass

	return results

	def analyze_elf(elf_file, create_binary=False, output_file=None, decompressor=False, prefix="aarch64-linux-gnu-"):
	"""Analyze an ELF file's sections and compression potential."""
	print(f"Analyzing AARCH64 ELF file: {elf_file}")

	# Extract sections using AARCH64 tools
	sections, entry_point = extract_sections(elf_file, prefix)

	# Analyze and compress each section
	results = []

	print("\nSection Analysis:")
	print("-" * 80)
	print(f"{'Section':<20} {'Size':<10} {'Entropy':<10} {'Best Algorithm':<16} {'Comp Size':<10} {'Ratio':<10}")
	print("-" * 80)

	section_results = {}
	for name, info in sorted(sections.items(), key=lambda x: x[1]['size'], reverse=True):
	data = info['data']
	if data is None or len(data) == 0:
	continue

	# Skip non-ALLOC sections if we're creating a binary
	if create_binary and not info['alloc']:
	continue

	orig_size = len(data)
	entropy = analyze_section_entropy(data)

	# Check if this is likely a code section
	is_code = name in ('.text', '.init', '.fini', '.plt') or 'CODE' in info['flags']

	compression_results = compress_with_algorithms(data, is_code)

	# Find best compression
	best_algo = min(compression_results.items(), key=lambda x: x[1]['size'])
	algo_name = best_algo[0]
	best_size = best_algo[1]['size']
	best_ratio = best_size / orig_size if orig_size > 0 else 1.0

	# Store result
	section_results[name] = {
	'name': name,
	'size': orig_size,
	'entropy': entropy,
	'vma': info['vma_int'],
	'alloc': info['alloc'],
	'flags': info['flags'],
	'is_code': is_code,
	'algo': algo_name,
	'comp_size': best_size,
	'comp_data': best_algo[1]['data'],
	'encode': best_algo[1]['encode'],
	'decode': best_algo[1]['decode'],
	'ratio': best_ratio
	}

	print(f"{name:<20} {orig_size:<10} {entropy:<10.2f} {algo_name:<16} {best_size:<10} {best_ratio:<10.2f}")

	results.append(section_results[name])

	# Print summary
	print("\nCompression Summary:")
	print("-" * 80)

	# Group sections by type
	section_types = defaultdict(list)
	for r in results:
	# Determine section type based on name and flags
	if r['is_code']:
	section_type = 'Code'
	elif r['name'] in ('.data', '.rodata'):
	section_type = 'Data'
	elif r['name'].startswith('.debug'):
	section_type = 'Debug'
	else:
	section_type = 'Other'

	section_types[section_type].append(r)

	# Print results by section type
	for section_type, sections in section_types.items():
	total_size = sum(s['size'] for s in sections)
	best_size = sum(s['comp_size'] for s in sections)

	print(f"{section_type} sections:")
	print(f" Total size: {total_size} bytes")
	print(f" Compressed size: {best_size} bytes")
	print(f" Overall ratio: {best_size/total_size:.2f}")

	# Best algorithms per type
	algo_counts = Counter(s['algo'] for s in sections)
	best_algos = algo_counts.most_common(2)
	print(f" Best algorithms: {', '.join(f'{algo} ({count})' for algo, count in best_algos)}")
	print()

	# Create compressed binary if requested
	if create_binary and output_file:
	create_compressed_binary(output_file, section_results, entry_point, decompressor)

	return section_results, entry_point

	def create_compressed_binary(output_file, section_results, entry_point, include_decompressor=False):
	"""Create a compressed binary file using the best compression for each section."""
	# Filter to only include ALLOC sections
	alloc_sections = {name: info for name, info in section_results.items() if info['alloc']}

	# Create header
	header = bytearray()

	# Magic number
	header.extend(MAGIC)

	# Format version (1 byte)
	header.append(FORMAT_VERSION)

	# Entry point (8 bytes for AARCH64 to support full 64-bit addresses)
	header.extend(struct.pack("<Q", entry_point))

	# Number of sections (2 bytes)
	header.extend(struct.pack("<H", len(alloc_sections)))

	# Section directory
	section_data = bytearray()

	for name, info in sorted(alloc_sections.items(), key=lambda x: x[1]['vma']):
	# Section name (null-terminated, max 16 chars)
	name_bytes = name.encode('ascii')[:15] + b'\0'
	header.extend(name_bytes.ljust(16, b'\0'))

	# Virtual memory address (8 bytes for AARCH64)
	header.extend(struct.pack("<Q", info['vma']))

	# Uncompressed size (4 bytes)
	header.extend(struct.pack("<I", info['size']))

	# Compression algorithm (1 byte)
	algo_id = {
	'none': 0,
	'zlib': 1,
	'lzma': 2,
	'bz2': 3,
	'delta': 4,
	'word_delta': 5,
	'dictionary': 6,
	'aarch64_code': 7
	}.get(info['algo'], 0)
	header.append(algo_id)

	# Offset to compressed data (4 bytes) - will be filled in later
	offset_pos = len(header)
	header.extend(b'\0\0\0\0')

	# Compressed size (4 bytes)
	header.extend(struct.pack("<I", info['comp_size']))

	# Store the compressed data
	data_offset = len(section_data)
	section_data.extend(info['comp_data'])

	# Update the offset in the header
	struct.pack_into("<I", header, offset_pos, len(header) + data_offset)

	# If including a decompressor, add it here
	if include_decompressor:
	# Create a minimal decompressor in C
	decompressor_code = generate_aarch64_decompressor_code()
	decompressor_size = len(decompressor_code)

	# Add decompressor info to header
	header.extend(struct.pack("<I", decompressor_size))
	header.extend(decompressor_code)
	else:
	# No decompressor
	header.extend(struct.pack("<I", 0))

	# Write the final binary
	with open(output_file, 'wb') as f:
	f.write(header)
	f.write(section_data)

	print(f"\nCreated compressed binary: {output_file}")
	print(f" Header size: {len(header)} bytes")
	print(f" Data size: {len(section_data)} bytes")
	print(f" Total size: {len(header) + len(section_data)} bytes")

	# Create JSON metadata file
	metadata = {
	'architecture': 'aarch64',
	'entry_point': entry_point,
	'sections': []
	}

	for name, info in alloc_sections.items():
	metadata['sections'].append({
	'name': name,
	'vma': info['vma'],
	'size': info['size'],
	'comp_size': info['comp_size'],
	'algo': info['algo'],
	'is_code': info['is_code']
	})

	meta_file = f"{output_file}.meta.json"
	with open(meta_file, 'w') as f:
	json.dump(metadata, f, indent=2)

	print(f"Created metadata file: {meta_file}")

	def generate_aarch64_decompressor_code():
	"""Generate a minimal AARCH64 decompressor."""
	# This would be a simple ARM assembly decompressor
	# For simplicity, we'll just return placeholder bytes
	return b'AARCH64_DECOMPRESSOR_PLACEHOLDER'

	def create_aarch64_decompressor(output_file, section_results, entry_point, prefix="aarch64-linux-gnu-"):
	"""Create a standalone decompressor executable for AARCH64."""
	# This would generate a C file with the decompression logic
	# For now, we'll just create a simple C file stub
	c_code = """
	#include <stdio.h>
	#include <stdlib.h>

	int main(int argc, char **argv) {
	if (argc != 3) {
	printf("Usage: %s input.bin output.bin\\n", argv[0]);
	return 1;
	}

	printf("AARCH64 Decompressor stub - would decompress %s to %s\\n", argv[1], argv[2]);
	return 0;
	}
	"""

	c_file = f"{output_file}.c"
	with open(c_file, 'w') as f:
	f.write(c_code)

	# Compile with AARCH64 toolchain
	gcc_cmd = f"{prefix}gcc -o {output_file} {c_file}"
	try:
	run_command(gcc_cmd)
	print(f"Created AARCH64 decompressor: {output_file}")
	except:
	print(f"Created decompressor source: {c_file}")
	print(f"Compile with: {gcc_cmd}")

	def main():
	parser = argparse.ArgumentParser(description='Analyze AARCH64 ELF file sections and create optimized binary')
	parser.add_argument('elf_file', help='Path to the AARCH64 ELF file to analyze')
	parser.add_argument('-o', '--output', help='Output file for compressed binary')
	parser.add_argument('-c', '--create-binary', action='store_true', help='Create compressed binary')
	parser.add_argument('-d', '--decompressor', action='store_true', help='Include decompressor in binary')
	parser.add_argument('-p', '--prefix', default='aarch64-linux-gnu-', help='Toolchain prefix (default: aarch64-linux-gnu-)')
	args = parser.parse_args()

	if not os.path.exists(args.elf_file):
	print(f"Error: File {args.elf_file} not found")
	sys.exit(1)

	output_file = args.output or f"{args.elf_file}.compressed.bin"

	analyze_elf(args.elf_file, args.create_binary, output_file, args.decompressor, args.prefix)

	if args.create_binary and args.decompressor:
	create_aarch64_decompressor(f"{output_file}.decomp", None, None, args.prefix)

	if __name__ == "__main__":
	main()