Securing the Web3 frontier in real time.

Fraudalysis is a real-time blockchain monitoring and threat prevention platform. We build the intelligence layer that protects builders, users, and ecosystems from complex on-chain fraud.

Our mission

The full promise of the decentralised economy can only be realised if everyone can transact with confidence. As digital assets gain adoption, malicious actors have evolved: standard blockchain forensics trace stolen funds only after they've been siphoned and laundered. We believe that reactive model is fundamentally broken.

Our mission is to replace forensic post-mortems with active, machine-learning surveillance — mapping and flagging threats before they materialise, preserving capital and building trust across the decentralised web.

What guides our work

Science-first machine learning

We don't rely on simple heuristics or static wallet blacklists. We build models that understand the behavioural fingerprints of malicious smart contracts, wash trading rings, and multi-hop mixers — and the platform evolves with the threat landscape.

Radical transparency

Our analysis is grounded in raw on-chain truth. Every alert and risk score is supported by verifiable on-chain evidence, so security teams can act with confidence.

Collaborative security

We work with DeFi protocols, launchpads, and Web3 developers. Sharing anonymised, aggregated threat telemetry builds a defensive shield across every ecosystem we support.

How we support the ecosystem

For DeFi protocols

Integrate real-time screening into your gates: prevent known drainers and malicious exploit-preparation addresses from touching your liquidity pools.

For Web3 projects and launchpads

Secure launches by scanning contract bytecode for hidden backdoors, proxy vulnerabilities, and rogue minting functions that expose communities to dev-led rug pulls.

For compliance and operations

Automate wallet screening and transaction scoring to surface threat networks, sanctions evasion, and mixer flows — without slowing honest users down.

Get in touch

Want to see Fraudalysis in action, build on our API, or partner with us? Contact the team →