Popular GitHub Repositories for Cryptographic

Embedded no-code VM executing human-like language to manipulate data and process cryptographic operations.

Privacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradients. To achieve robustness to users dropping out, existing practical privacy-preserving federated learning schemes are based on (t, N)-threshold secret sharing. Such schemes rely on a strong assumption to guarantee security: the threshold t must be greater than half of the number of users. The assumption is so rigorous that in some scenarios the schemes may not be appropriate. Motivated by the issue, we first introduce membership proof for federated learning, which leverages cryptographic accumulators to generate membership proofs by accumulating users IDs. The proofs are issued in a public blockchain for users to verify. With membership proof, we propose a privacy-preserving federated learning

A Model Context Protocol server providing LLM Agents with system utilities and tools, including IP geolocation, network diagnostics, system monitoring, cryptographic operations, and QR code generation.

AIVM is a cutting-edge framework designed for privacy-preserving inference using advanced cryptographic protocols. With AIVM, you can deploy a local development network (devnet) to explore private inference using provided examples or custom models.

Asymmetric cryptographic scheme for encryption and decryption of medical images using GANs.

Smart Transformers are a versatile machine learning tool that can be integrated with Pytorch, TensorFlow, and JAX. Smart transformers provide accurate computations required for cryptographic algorithms. These transformers is that they are independent modules, making it efficient to experiment with various research projects related to cryptanalysis

A curated list of awesome libraries, tools, frameworks, and resources for Zero-Knowledge Proofs (ZKPs) including zk-SNARKs, zk-STARKs, and other privacy-preserving cryptographic protocols.

AWO formalizes AI-human research into verifiable, reproducible workflows. Each run generates cryptographically signed provenance records, ensuring transparency, falsifiability, and DOI-registered reproducibility under Waveframe Labs governance.

A procedurally generated dataset of cryptographic CTF challenges for training and evaluating LLM agents with Reinforcement Learning.

The definitive CLI for validating A2A (Agent-to-Agent) protocol agent cards. Validates cryptographic trust, schema compliance, and live endpoint functionality.

The definitive CLI for validating A2A (Agent-to-Agent) protocol agent cards. Validates cryptographic trust, schema compliance, and live endpoint functionality.

A dangerously functional collection of experiments. This repository exists at the intersection of “I wonder if this works” and “oh no, it worked”. Expect questionable Terraform, overly caffeinated Bash scripts, and Python that may or may not summon cryptographic demons. Perfect for educational purposes and reminding PoC can mean Proof of Coffee.

Cryptix Security cryptographic boundaries that make untrusted LLM content inert by default

Unified deterministic architecture combining verifiable time, consent, policy enforcement, runtime integrity, AI safety, and custody into a single post-quantum security stack.

This repository implements an AI/ML-based solution for identifying cryptographic algorithms from given datasets.

The Identity Authority and Trust Gateway for the AI Agent economy. Issues and verifies cryptographic TrustBadges to secure cross-cloud Agent-to-Agent (A2A) communication.

The MCP ZK Integrity Layer enables cryptographic proof of computational integrity and data authenticity using zero-knowledge protocols, ensuring trust without exposing sensitive information. It provides modular circuits (e.g., Poseidon, Keccak) for seamless integration into MCP workflows.

Comparative benchmark of SMT solver effectiveness in cryptographic hash collision discovery for SHA-2 algorithms.

airlock is a cryptographic handshake protocol for verifying AI model identity at runtime. It enables real-time attestation of model provenance, environment integrity, and agent authenticity — without relying on vendor trust or static manifests.

A research implementation of an intelligent, energy-aware log routing system. This system dynamically routes log entries to one of three specialized storage tiers (MySQL, ELK, IPFS) based on Intelligent Routing balancing performance, analytical capability, and cryptographic integrity.