CertiK launches AI Auditor with 88.6% hit rate & low-noise detection

CertiK, a Web3 security services provider, has announced the release of its AI Auditor, alongside a suite of open-source integrations for AI coding agents, according to an announcement shared with Finbold on April 7.

The system, initially developed as an internal tool for CertiK’s auditors, is now available publicly after more than six months of testing in real-world conditions.

AI-driven system delivers low-noise, high-signal intelligence

According to the company, AI Auditor was evaluated against 35 real-world Web3 security incidents from 2026, achieving an 88.6% cumulative exact hit rate while maintaining a low level of false positives.

The launch reflects a broader shift toward embedding security tools directly into development workflows, allowing teams to identify and address vulnerabilities earlier in the development process. CertiK said the system is designed to integrate with existing environments, providing real-time security insights and reducing response times to potential threats.

At the core of the system is a multi-layered architecture built around a MultiScanner framework and a proprietary Multi-Stage Validator. The MultiScanner runs multiple detection models in parallel to increase coverage, while the validator processes findings through deduplication and semantic evaluation to filter out irrelevant alerts and prioritize actionable issues.

CertiK also said the system is supported by a continuously updated Knowledge Base, which incorporates data from real-world exploits, audit findings, and emerging attack patterns. This allows the AI Auditor to apply up-to-date threat intelligence during analysis.

The platform is designed to complement human auditors by handling baseline detection, pre-audit triage, and continuous monitoring. According to the company, this enables security teams to focus on more complex vulnerabilities and protocol-level risks.

CertiK said the AI Auditor can be adapted to different project requirements, including variations in programming languages, system architecture, and risk profiles, making it applicable across decentralized finance (DeFi) and institutional use cases.

The release forms part of the company’s broader AI-focused strategy, with additional features expected to further integrate security into development tools and compliance workflows.

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