Metadata-Version: 2.4
Name: sqrypt-cyber-sdk
Version: 0.1.0
Summary: Enterprise Hybrid Post-Quantum Cryptography SDK wrapping NIST FIPS-203 (ML-KEM)
Author-email: Aryan Sujay <your.email@example.com>
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Security :: Cryptography
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Requires-Dist: requests>=2.31.0

# SQrypt Post-Quantum Cybersecurity SDK 🛡️

SQrypt is an enterprise-grade developer kit designed to secure high-stakes data ingestion layers against future quantum threats. It provides an optimized, drop-in abstraction layer wrapping **NIST FIPS-203 (ML-KEM)** lattice cryptography.

## Key Features
* **One-Line Implementation:** Secure runtime data routing via native Python decorators.
* **Hybrid Defense Architecture:** Merges classical AES-256-GCM symmetric block ciphers with post-quantum asymmetric encapsulation.
* **Zero-Knowledge Target Mutation:** Secure specific nested keys within complex JSON payloads without exposing metadata.

## Installation
```bash
pip install sqrypt-cyber-sdk
```

## Quick Start Guide
* **Initialize the Secure Client:** Connect the SDK to your isolated enterprise infrastructure instance by instantiating the client engine with your secret keys:
```bash
from sqrypt import SQryptClient

client = SQryptClient(
    server_url="[http://127.0.0.1:8500](http://127.0.0.1:8500)", 
    api_key="YOUR_ENTERPRISE_API_KEY"
)
```

* **Runtime Interception (Pattern A):** Protect live string streams dynamically at the functional boundary using the automatic encryption decorator:
```bash
@client.auto_encrypt()
def process_runtime_transaction(user_id: str, card_data: str) -> str:
    # Data is automatically encapsulated before network dispatch
    return f"USER:{user_id}|RAW_CARD:{card_data}"

# Executes lattice-based key encapsulation
protected_payload = process_runtime_transaction("usr_998", "4111-2222-3333-4444")

# Reclaim the plaintext string through zero-knowledge decapsulation
recovered_string = client.decrypt(protected_payload)
```

* **Granular Field Masking (Pattern B):** To protect structural records or transactional documents before database insertion, mask target keys selectively:
```bash
database_document = {
    "account_id": "acc_001",
    "status": "active",
    "tax_id": "999-12-3456",
    "secret_token": "token_xyz123"
}

# Mutates specified targets into quantum-secure ciphertext bundles
masked_document = client.protect_dict(
    data=database_document, 
    sensitive_keys=["tax_id", "secret_token"]
)
```

## SECURITY SPECIFICATIONS
SQrypt's design parameters conform strictly to the modern cryptographic primitives evaluated by the National Institute of Standards and Technology (NIST):
| Layer / Algorithm / Standard        | Target Bit Security         | Notes / Details                  |
|-------------------------------------|------------------------------|-----------------------------------|
| Asymmetric Key Encapsulation        | ML-KEM-768 (FIPS 203)        | 192-bit (Quantum-Secure)          |
| Symmetric Bulk Encryption           | AES-256-GCM                  | 256-bit (Classical/Quantum-Safe)  |
| Key Derivation Function             | HKDF-SHA256                  | High-Entropy Expansion            |


## License
This SDK is distributed under the terms of the MIT License.
