Data Representation in Binaries
Learn how data types (integers, floats, strings) are stored in memory and files, including concepts like endianness.
Data Representation in Binaries is a free Reverse Engineering & Binary Analysis Basics lesson on CoddyKit — lesson 2 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Reverse Engineering & Binary Analysis Basics learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
What is Binary Data?
When you reverse engineer, you're looking at a program's raw binary form. This means understanding how all kinds of data—numbers, text, and more—are stored as sequences of bits and bytes.
A bit is the smallest unit, either 0 or 1. Eight bits make a byte. Everything a computer does, from calculations to displaying text, relies on these fundamental units.
Numbers as Bits: Integers
Integers are whole numbers. They can be signed (positive or negative) or unsigned (only non-negative). The number of bytes used determines the range of values an integer can hold.
- Byte (8-bit): 0 to 255 (unsigned) or -128 to 127 (signed).
- Word (16-bit): Up to 65,535 (unsigned).
- DWord (32-bit): Up to ~4 billion (unsigned).
- QWord (64-bit): Much larger numbers!
Integer Size Matters
Let's see how different integer sizes affect the maximum value. This Python code shows the max value for an unsigned 8-bit integer (a byte) and a signed 8-bit integer.
# Max unsigned 8-bit integer
max_8_bit_unsigned = 2**8 - 1
print(f"Max 8-bit unsigned: {max_8_bit_unsigned}")
# Max signed 8-bit integer
max_8_bit_signed = 2**7 - 1
min_8_bit_signed = -2**7
print(f"Max 8-bit signed: {max_8_bit_signed}")
print(f"Min 8-bit signed: {min_8_bit_signed}")Floating-Point Numbers (Floats)
Numbers with decimal points, like 3.14 or -0.5, are called floating-point numbers. They are stored differently from integers to handle their fractional parts.
Most systems use the IEEE 754 standard for floats. This standard defines how a number's sign, exponent, and fractional part are represented in bits. Common sizes are 32-bit (single-precision) and 64-bit (double-precision).
Text: Characters & Strings
Text characters are also stored as numbers. The most common mapping for English characters is ASCII, where each character (like 'A' or '!') corresponds to a specific 8-bit number.
For a wider range of characters (emojis, foreign languages), Unicode is used. UTF-8 is a popular Unicode encoding that uses 1 to 4 bytes per character, making it flexible and backward-compatible with ASCII.
A string is simply a sequence of these characters, often ending with a special null byte (0x00) to mark its end.
How Strings Become Bytes
Here's how a simple string is represented as bytes using UTF-8. Notice how each character gets a numerical value.
message = "Hello"
bytes_message = message.encode('utf-8')
print(f"String: '{message}'")
print(f"Bytes (UTF-8): {bytes_message}")
# Example with a non-ASCII character
smiley = "😊"
bytes_smiley = smiley.encode('utf-8')
print(f"String: '{smiley}'")
print(f"Bytes (UTF-8): {bytes_smiley}")Endianness: Byte Order
When a piece of data, like a 32-bit integer, takes up more than one byte, there's a choice to be made: which byte comes first in memory? This order is called endianness.
- Big-endian: The most significant byte (MSB) comes first. Think of reading numbers left-to-right, like "123" where '1' is the most significant digit.
- Little-endian: The least significant byte (LSB) comes first. This is like writing "321" if '1' were the most significant.
Visualizing Endianness
Let's take the 32-bit hexadecimal number 0x12345678. This number has four bytes: 12, 34, 56, 78.
- Big-endian: Stores bytes in memory as
12 34 56 78(MSB first). - Little-endian: Stores bytes in memory as
78 56 34 12(LSB first).
Most modern Intel/AMD CPUs (x86/x64) are little-endian. Network protocols often use big-endian.
Endianness & Reverse Engineering
Understanding endianness is crucial when you're working with raw binary data, especially across different systems or file formats.
- If you read a 32-bit integer from a big-endian file on a little-endian system without conversion, the value will be incorrect.
- Network packets often use big-endian, so analyzing network traffic requires awareness.
- Many embedded systems (like ARM processors) can be configured for either, adding complexity.
Endianness Check
Imagine a 32-bit integer with the hexadecimal value 0xAABBCCDD is stored in memory. If the system is little-endian, what would be the order of bytes in memory, starting from the lowest address?
Data Representation Recap
Great job! In this lesson, we explored how data is represented in binaries:
- Integers: Stored as signed or unsigned numbers, with size determining range.
- Floating-points: Use standards like IEEE 754 for decimals.
- Characters & Strings: Mapped to numbers (ASCII, UTF-8) and often null-terminated.
- Endianness: The byte order (big-endian or little-endian) for multi-byte data, critical for correct interpretation.
Understanding these fundamentals is key to interpreting any binary file or memory dump. Next, we'll look at common binary file formats!
Frequently asked questions
Is the “Data Representation in Binaries” lesson free?
Yes — the full text of “Data Representation in Binaries” is free to read here on the web, and the Reverse Engineering & Binary Analysis Basics course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Reverse Engineering & Binary Analysis Basics course, upgrade to CoddyKit PRO.
What will I learn in “Data Representation in Binaries”?
Learn how data types (integers, floats, strings) are stored in memory and files, including concepts like endianness. You practise Reverse Engineering & Binary Analysis Basics with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Reverse Engineering & Binary Analysis Basics?
No prior experience is required. Reverse Engineering & Binary Analysis Basics on CoddyKit is structured for beginners through advanced learners; this is — lesson 2 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Data Representation in Binaries” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Reverse Engineering & Binary Analysis Basics lesson?
Yes. Every Reverse Engineering & Binary Analysis Basics lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- CPU Architectures Overview
- Data Representation in Binaries
- Common Binary File Formats
- Endianness & Byte Ordering