Request a Demo

Simultaneously test multiple layers to simulate cascading effects, increasing the likelihood of identifying the 0-day vulnerabilities that arise from complex, layered interactions.

Uncover 0-day Vulnerabilities

Combine continuous testing and learning to adapt to post-deployment changes. We leverage reinforcement learning (RL) to allow the agents to identify and develop new attack vectors.

Continuous Testing & Learning

Since agents use emergent behaviors to creatively test systems, agents execute the exploit to confirm attack vectors that are beyond human imagination.

No False Positives

Operate in a decentralized manner, distributing tasks like threat modeling, attack execution, and validation. This enables them to efficiently test large code bases and composable systems at scale.

Parallel Execution

ELEVATE YOUR SECURITY GAME

On-chain agents provide real-time monitoring, attack simulation, and post-mortem analysis. Using a stake-to-use model and adaptive LLMs, it detects zero-day exploits and automates threat responses.

Post-Deployment Module

Our multi-agent systems simulate red team behaviors, uncovering vulnerabilities like reentrancy flaws, logical exploits, economic attacks, and governance manipulation.

Pre-Deployment Engine

INTRODUCING SHEPHERD

An all-encompassing security suite that uses multi-agent systems to model the cognitive structure of a red team to secure dApps.

PRODUCTS

COMING SOON

Our multi-agent systems simulate red team behaviors, uncovering vulnerabilities like reentrancy flaws, logical exploits, economic attacks, and governance manipulation.

Pre-Deployment Engine

On-chain agents provide real-time monitoring, attack simulation, and post-mortem analysis. Using a stake-to-use model and adaptive LLMs, it detects zero-day exploits and automates threat responses.

Post-Deployment Module

PRODUCTS

COMING SOON

ELEVATE YOUR SECURITY GAME

© Shepherd Security 2024

Simultaneously test multiple layers to simulate cascading effects, increasing the likelihood of identifying the 0-day vulnerabilities that arise from complex, layered interactions.

Uncover 0-day Vulnerabilities

Combine continuous testing and learning to adapt to post-deployment changes. We leverage reinforcement learning (RL) to allow the agents to identify and develop new attack vectors.

Continuous Testing & Learning

Since agents use emergent behaviors to creatively test systems, agents execute the exploit to confirm attack vectors that are beyond human imagination.

No False Positives

Operate in a decentralized manner, distributing tasks like threat modeling, attack execution, and validation. This enables them to efficiently test large code bases and composable systems at scale.

Parallel Execution

INTRODUCING SHEPHERD

An all-encompassing security suite that uses multi-agent systems to model the cognitive structure of a red team to secure dApps.

© Shepherd Security2024

.

Request a Demo

The all-in-one operating system for dApp security.

The all-in-one operating system for dApp security.

Request a Demo

Request a Demo

Request a Demo

Request a Demo

Request a Demo

Request a Demo

REDEFINING WEB3 SECURITY

REDEFINING WEB3 SECURITY