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Anthropic launches critical infrastructure program and free OSS Scanner for open source

Anthropic PBC today launched a program that brings its frontier models and onsite engineers to the security companies protecting power grids, water systems and other critical infrastructure. OSS Scanner, launched with it, offers open-source projects free periodic vulnerability scans from the company’s strongest models. Both fall under a new effort Anthropic calls the Anthropic Cyber […] The post…

Anthropic launches critical infrastructure program and free OSS Scanner for open source

Anthropic PBC has introduced a new cybersecurity initiative, the Anthropic Cyber Mission, which includes a critical infrastructure defense program and a free Open Source Scanner (OSS Scanner) for open source projects. The program is designed to provide frontier models and onsite engineers to security companies that safeguard power grids, water systems, and other critical infrastructure.

Eleven establishment partners from the consulting side and security vendors, including Dragos, Insanity Cyber, and Nozomi Networks, have signed on as founding partners. The program aims to address operational technology in plants, substations, and water systems, where equipment often cannot be taken offline for patching. Several partners are already utilizing Claude to address vulnerabilities and assist their clients.

The open-source component of the program emerged from Anthropic's backlog of vulnerabilities discovered in widely used software. Over 29,000 candidate vulnerabilities were identified in the past six months, with staff manually reviewing approximately 6,000. A growing number of maintainers requested the entire unreviewed batch of findings and nearly 5,000 reports have been distributed so far.

The OSS Scanner provides a continuous service for eligible projects, delivering self-contained reproducer reports to maintainers without human review, enabling faster detection and response.

Written by urgent.news from SiliconANGLE's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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