When working with encrypted files, particularly those using AES symmetric encryption, many developers face a common dilemma: compression seems to introduce risks of corrupting the ciphertext. The good news is that properly structured compression can actually work in harmony with encryption when following best practices.

The fundamental principle is that encrypted data appears random, making traditional compression algorithms less effective. The optimal approach is to:

1. Compress the original data first
2. Then apply encryption
3. For already encrypted files, use specialized techniques

For existing AES-encrypted files, these tools have proven effective:

# Using zstd (modern high-ratio compression)
zstd --ultra -22 encrypted_file.aes -o encrypted_file.aes.zst

# Parallel compression with pigz
pigz -k -9 encrypted_file.aes

When dealing with encrypted archives, the file structure matters:

• Single encrypted files: Can be compressed directly
• Encrypted containers: May require special handling

Here's a complete workflow for handling compressed encrypted files:

import zstandard as zstd
import os

def compress_encrypted(input_path, output_path):
    cctx = zstd.ZstdCompressor(level=22)
    with open(input_path, 'rb') as f_in:
        with open(output_path, 'wb') as f_out:
            cctx.copy_stream(f_in, f_out)

# Usage:
compress_encrypted('secret_data.aes', 'secret_data.aes.zst')

Always remember that compression may preserve or expose metadata unintentionally. Consider:

• File timestamps
• Original filenames
• Compression dictionary patterns

For maximum space savings with encrypted files:

# First pass with high-ratio compression
xz -9e encrypted_file.aes

# Then apply byte-level compression
precomp -cnv encrypted_file.aes.xz

When working with AES-encrypted files (typically .aes or .enc extensions), the encrypted output appears as random data to compression algorithms. This creates an interesting technical challenge for developers needing both security and storage efficiency.

// Recommended workflow:
plaintext -> compress -> encrypt -> store

// Problematic alternative:
plaintext -> encrypt -> compress -> store (usually ineffective)

Since AES encryption produces high-entropy output, attempting compression post-encryption typically yields minimal size reduction (often 0-1%). The optimal approach is to compress data before encryption.

Option 1: Using OpenSSL with Compression

# Compress then encrypt:
gzip -c plainfile.txt | openssl enc -aes-256-cbc -salt -out encryptedfile.aes

# Decrypt then decompress:
openssl enc -d -aes-256-cbc -in encryptedfile.aes | gunzip -c > plainfile.txt

Option 2: 7-Zip with AES

# Windows/Linux command line:
7z a -t7z -m0=lzma2 -mx=9 -mhe=on -pYourPassword secured.7z plainfile.txt

For already-encrypted files, consider these specialized tools:

• Precomp: Handles some pre-compressed formats within encrypted files
• ZPAQ: Advanced context modeling can sometimes find patterns

# Example using precomp:
precomp -cn encrypted.aes | pcompress -o compressed.pcf

Testing with 1GB SQL dump file:

When implementing in code:

// Python example using PyCryptodome
from Crypto.Cipher import AES
import zlib

def compress_encrypt(input_file, output_file, password):
    with open(input_file, 'rb') as f:
        data = zlib.compress(f.read(), level=9)
    
    cipher = AES.new(password, AES.MODE_GCM)
    ciphertext, tag = cipher.encrypt_and_digest(data)
    
    with open(output_file, 'wb') as f:
        [f.write(x) for x in (cipher.nonce, tag, ciphertext)]