Blockchain Security Firm Forta Upgrades Its Scam Detector to Battle Growing Crypto Fraud

Scam alert (Getty)

The blockchain security firm Forta Network upgraded its scam detector service to include malicious URL data, new types of threats and smart contract scanners that account for the latest types of crypto attacks, a representative told CoinDesk.

The move comes as crypto developers are ramping up security measures for users in an increasingly-growing ecosystem, one that is susceptible to malicious code, rogue coders and hacks.

The service, which will be online on Tuesday, runs across the seven Ethereum Virtual Machine chains supported by Forta, including Ethereum, Polygon and BNB Chain. A previous version focused on on-chain data only, such as smart contracts involved in scam activity. The latest version also incorporates malicious URLs.

The new version, built with contributions from security firms like Blocksec and Nethermind, uses predictive techniques to flag on-chain addresses associated with known scammers and contracts that closely resemble known scammers.

Forta claimed that wallets like Zengo had used the Scam Detector to warn their users about malicious addresses during the pre-signed transaction screening process.

The company’s service relies on a group of Forta bots that monitor different threat types to detect scam behavior in real-time. When these bots suspect a scammer, they emit a real-time alert for the user’s perusal.

The cryptocurrency ecosystem has long been a target for hackers due to its inherent vulnerabilities, such as complex code, a massively correlated ecosystem, and millions of dollars stored on sometimes obscure platforms.

Crypto traders lost some $303 million worth of tokens in July alone, as CoinDesk previously reported. Roughly $125 million of assets were drained from blockchain bridging protocol Multichain, and a $72 million exploit hit DeFi powerhouse Curve Finance as hackers exploited a vulnerability in some versions of the smart contract coding language Vyper.

Edited by Aoyon Ashraf.

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