Table of Contents

The Three Pillars of Digital Trust: Encoding, Hashing, and Encryption

Confused about encoding, hashing, and encryption? This cybersecurity guide explains how to protect data and ensure digital system trust.
Technology
Digital Transformation
App Development
Digital Product Development

Author

Pushkar Kumar
Pushkar KumarSenior Technical Consultant

Date

Sep 24, 2025

In today’s digital economy, trust is the real currency. Every application we build — whether it’s a consumer app, an enterprise workflow, or an internet-scale platform — depends on how we handle data. Yet even among seasoned engineers, there’s persistent confusion between encoding, hashing, and encryption.

As someone who has led architecture reviews across large-scale systems, I’ve seen this confusion surface everywhere: in design documents, security audits, and even senior-level interviews. A simple misstatement like “we encrypt passwords using bcrypt” isn’t just a slip of terminology — it signals a gap that can cascade into design flaws, compliance failures, and security vulnerabilities.

This article is not just a refresher on definitions. It’s a field guide for technical leaders, engineers, and architects who want to make deliberate, correct choices about data handling. By the end, you’ll have absolute clarity on when to encode, when to hash, and when to encrypt — and why getting this right is foundational for building resilient, trustworthy systems at scale.

What is Encoding?

Encoding transforms data into a format that's safe to transmit or store — especially across systems that expect text, not raw binary.

It’s not about hiding data — it’s about making sure it doesn’t break things when passed through a browser, stored in a file, or sent over a network.

Why Do We Encode?

Imagine you're sending a binary file (like an image or a PDF) in an email. Email protocols expect text, not raw binary bytes. You need to transform that file into a format that plays nicely with the medium. That’s what encoding does.

Key Traits:

  • Reversible: Anyone can decode it — no secrets involved
  • Not secure: Base64 is not protection; it’s just translation
  • Used for compatibility: Across systems, platforms, and protocols

Purpose: Format compatibility, not confidentiality

Common Types of Encoding:

Code Example

Base64 inflates the data by ~33%, but makes it safe to transmit over text-based channels.

Real-World Use Cases

  1. Emails: Attachments are encoded in Base64 so they don’t break email formatting
  2. URLs: Query strings need URL encoding so special characters don’t confuse browsers
  3. HTML Pages: Displaying <script> without it executing? Use &lt;script&gt;
  4. APIs: Some APIs require encoded payloads to ensure safe transmission

Encoding ≠ Security

Many developers confuse Base64 with encryption. That’s dangerous.

Here’s what anyone can do:

No key, no secret — just a simple tool. That’s why encoding should never be used to store or protect sensitive information.

Analogy: The Universal Translator

Imagine sending a handwritten note to someone in another country.
  • Encoding is like using Google Translate so their email system understands your text.
  • It’s not private — the mailman, post office, or anyone in-between can read it.
  • But it ensures the message doesn’t get corrupted in transit.
So, when you Base64-encode a token or a file, you're just making sure it survives the journey — not locking it away.

Common Mistakes to Avoid

We store the API token in Base64 so it’s safe.”

✅ It’s compatible. ❌ It’s not secure.

Anyone can decode Base64 in milliseconds. Always pair encoding with encryption if you need protection.

Flowchart of the Data encoding and decoding process

What is Hashing?

Hashing is the process of turning any data — a password, a file, or a string — into a fixed-length, irreversible fingerprint.

It’s how we verify something hasn’t been tampered with, without needing to look at the original.

Why Do We Hash?

Let’s say you download a 2 GB file. How do you check it hasn’t been corrupted or altered in transit? You compare its hash with the official hash published by the source. If they match, you’re good.

Key Traits

One-way: You can’t reverse it to get the original data
Deterministic: Same input → same hash
Fixed-size output: No matter the input size
Collision-resistant: Hard to find two different inputs with the same hash

Purpose: Verify identity or detect change

Common Hash Algorithms

Algorithm Output Length Use Case

MD5 128 bits Legacy checksums (not secure)

SHA-1 160 bits Git commits (deprecated)

SHA-256 256 bits File integrity, blockchain

bcrypt Variable Password hashing (with salt)

scrypt Variable Password hashing (slower, safer)

argon2 Variable Modern password hashing standard


You can compare hashes, but you can’t go backward.

Flowchart showing Hashing process

Hashing Passwords (with Salt)

Hashing alone isn’t enough for passwords. You also need salt — a unique random value added to the input to prevent dictionary and rainbow table attacks.

Salting ensures that even if two users have the same password, their hashes will be completely different — defeating precomputed attacks.

Real-World Use Cases

  • Password storage (with bcrypt, scrypt, or argon2)
  • Git commits: Each commit has a SHA-1 hash
  • File checksums: Validate downloaded files
  • Cache keys: Quickly compare request payloads

Analogy: The Fingerprint Scanner

Hashing is like scanning your fingerprint:

  • It’s unique to you
  • It doesn’t store your actual finger
  • If someone tampers with it, it won’t match again

What is Encryption?

Encryption is the process of locking data so only the right person can unlock it. It's the cornerstone of confidentiality in digital systems.

Unlike encoding (which changes format) or hashing (which verifies identity), encryption transforms readable data into unreadable gibberish — but in a way that can be reversed if you have the key.

Why Do We Encrypt?

If you’re handling personal data, sensitive files, or confidential messages, you don’t want anyone snooping on them during transit or storage. Encryption ensures:
  • Only the right person can read it
  • Even if intercepted, it’s meaningless without the key
  • You stay compliant with regulations (GDPR, HIPAA, PCI-DSS)

Key Properties of Encryption

  • Reversible: Data can be decrypted using the correct key
  • Key-based: Requires either a single key (symmetric) or key pair (asymmetric)
  • Confidential: Protects the contents of data from unauthorized access

Types of Encryption

Symmetric Encryption

  • One key used for both encryption and decryption
  • Fast & efficient, best for large data
  • Examples: AES, DES, ChaCha20
  • Use Cases: Disk encryption (BitLocker, FileVault)
Asymmetric Encryption
  • Uses a key pair:
  • Enables secure communication over public networks
  • Examples: RSA, ECC
  • Use Cases: TLS handshakes (HTTPS)
Hybrid Encryption
  • Combines both types:
  • Gets the best of both: security + speed
  • Examples: TLS (HTTPS), Signal Protocol
  • Use Cases: Secure web traffic

Protecting Your Keys

Encryption is only as strong as key management. Here’s how to do it right:

Key Management Best Practices
  1. Never hardcode keys in your source code
  2. Use a Key Management Service (KMS) like:
  3. Rotate keys regularly (e.g., every 90 days)
  4. Use environment variables (as a baseline)
  5. Encrypt your config files
  6. Don’t log secrets (even in dev!)

Authenticated Encryption (AEAD)

Standard encryption doesn't always protect against tampering. Use AEAD (Authenticated Encryption with Associated Data) to defend against both snooping and forgery.
Recommended Algorithms:
  • AES-GCM
  • ChaCha20-Poly1305
These algorithms ensure:
  • The data is unreadable and
  • Any modifications are detected and rejected

Common Encryption Mistakes

  • Using ECB mode (Electronic Codebook) with AES ➤ This mode always encrypts the same input the same way — so patterns in your data become visible. Think of it like using the same lock for every box: an attacker can spot repeated patterns.
  • Reusing IVs (Initialization Vectors) ➤ An IV is like a random “starting point” for encryption. If you reuse it, attackers can start guessing how your encryption works. Always use a new IV for each encryption operation — most libraries can do this automatically.
  • Writing your own encryption code ➤ Cryptography is notoriously tricky — even small mistakes can break your entire system. Stick to well-vetted libraries unless you're a cryptographer. Always use trusted libraries that are battle-tested and audited.
  • Storing encryption keys in plain files or GitHub ➤ Never save your secret keys in .env, .js, .txt, or GitHub. If someone finds the key, your encryption is useless — they can read everything. Use a secure key storage tool like AWS KMS, HashiCorp Vault, or environment secrets managers.

Better Way to Say It

If you’re locking your secrets, don’t leave the key under the doormat — or use the same key for every door.
Always use well-tested libraries like libsodium, crypto, or OpenSSL — and follow NIST guidelines. Analogy: Sending a Locked Box
Encryption is like placing your message in a locked box:
  • Symmetric: You and the recipient share the same key to lock/unlock
  • Asymmetric: You send the recipient a locked box (using their public key), and only they can open it (with their private key)
  • Hybrid: You mail them a box with a padlock key inside, and only they can open the box (asymmetric), then both use that key to send more stuff (symmetric)

Common Mistakes We As Developers Make

🔄 Use Encoding
When: You need to safely transmit data (like in a URL, email, or HTTP header)
Why: It converts data into a readable and compatible format — not secret, just safe to transport
Example: Base64 for image data, %20 in URLs
🧮 Use Hashing
When: You want to create a fingerprint of data or check if something has changed
Why: A hash is a one-way, fixed-length output that changes drastically with even 1-bit of difference
Example: SHA-256 for file verification, bcrypt for passwords
🔐 Use Encryption
When: You need to protect data from being read by anyone else
Why: Encryption scrambles data so only someone with the correct key can read it
Example: HTTPS, AES-encrypted files, secure messaging apps
🛡️Use Hashing (with salt)
When: You’re storing user passwords
Why: Hashing ensures you can verify passwords without ever knowing the original. Salt makes each hash unique and secure
Example: bcrypt, argon2, scrypt
📬Use Encryption
When: You’re sending secrets over public networks
Why: Without encryption, anyone in the middle (like on public Wi-Fi) could read your data
Example: TLS/SSL for websites, VPNs for secure tunneling
Quick Rule of Thumb
  • Use Encoding when you want to make data compatible
  • Use Hashing when you want to verify or fingerprint
  • Use Encryption when you want to protect and hide data

Final Thoughts

Encoding, hashing, and encryption aren’t just technical details — they are the foundations of digital trust. Misusing them can mean the difference between a resilient system and one that silently carries risk.
As engineers and architects, our responsibility goes beyond “making things work.” We are building platforms that handle personal data, financial transactions, and critical infrastructure. Getting these fundamentals right is non-negotiable.
At GeekAnts, we invest deeply in engineering practices that balance performance, security, and clarity. Our teams are trained to ask the right questions at the right time:
👉 “Do I need format compatibility, verification, or confidentiality?”
That simple pause ensures the correct choice between encoding, hashing, or encryption — and prevents costly mistakes down the road.
If you’re an engineer, product owner, or technology leader navigating these decisions, I encourage you to treat this not as a checklist but as a mindset:
  • Encoding makes systems talk.
  • Hashing verifies integrity.
  • Encryption protects secrets.
Get those right, and you’re not just solving today’s problem — you’re designing for the future of secure, trustworthy digital systems.

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