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Anthropic Brings Voice Mode to Claude Opus and Sonnet Models

Anthropic Brings Voice Mode to Claude Opus and Sonnet Models

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 The Verge AI

Anthropic has expanded Claude's voice mode to its more capable Opus and Sonnet models, with agentic integrations into productivity apps including Gmail, Slack, and Canva. This significantly widens the attack surface by combining a natural-language voice input channel with agentic action-taking capabilities across third-party platforms. Defenders must now account for voice-based prompt injection, cross-app lateral movement via conversational instruction, and the difficulty of auditing spoken-language interactions at scale.

Claude Opus Discovers API Flaw Enabling Ticket Fraud

Claude Opus Discovers API Flaw Enabling Ticket Fraud

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 Wired Security

Security researcher Ian Carroll leveraged Anthropic's Claude Opus 4.7 to identify a critical vulnerability in Front Gate Tickets—a Live Nation subsidiary handling ticketing for major US festivals—that granted super-administrator access and the ability to freely issue tickets of any value. The case demonstrates LLM-assisted autonomous vulnerability discovery at scale, with Carroll noting the AI could likely have completed the full exploit chain without human intervention. Front Gate patched the flaw within 24 hours of disclosure, confirming no evidence of prior exploitation.

Famous Chollima Poisons npm With LLM-Assisted Malware

Famous Chollima Poisons npm With LLM-Assisted Malware

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 The Hacker News

North Korean threat group Famous Chollima (Shifty Corsair) has weaponised AI-assisted code generation to embed malicious npm packages into autonomous AI agent projects, targeting cryptocurrency wallets. The campaign, dubbed PromptMink, exploited Anthropic's Claude Opus to co-author a malicious dependency commit, demonstrating a novel abuse of LLM coding agents for supply chain infiltration. The attack uses a multi-layer dependency structure to evade detection, with second-layer malicious packages swiftly rotated when identified.

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