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CVE-2026-93680: Langflow RCE via Auth Bypass Hits All 1.x

CVE-2026-93680: Langflow RCE via Auth Bypass Hits All 1.x

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.2 The Hacker News

Two critical vulnerabilities in Langflow, the widely-used open-source AI agent and workflow builder, allow unauthenticated remote attackers to bypass authentication and execute arbitrary code on affected servers running versions 1.0.0 through 1.12.8. A Metasploit module already targets the authentication bypass flaw (CVE-2026-93680) via Langflow's Model Context Protocol endpoint, lowering the bar for exploitation. The only remediation is upgrading to version 1.13.0, with no available workaround for systems that cannot immediately patch.

CVE-2026-81578: PaperCut Exploited by AI Agents at Scale

CVE-2026-81578: PaperCut Exploited by AI Agents at Scale

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 6.2 The Hacker News

Two actively exploited PaperCut vulnerabilities (CVE-2026-81578 and CVE-2026-82078) are being weaponised by a suspected Russian-speaking threat actor using hundreds of AI agents powered by OpenAI Codex and a DeepSeek model to conduct large-scale authentication bypass and code execution attacks. The campaign has compromised at least 395 organisations across 48 countries, with a heavy focus on the U.S. education sector. PaperCut has released full maintenance releases superseding earlier emergency patches, and immediate upgrade is advised.

Flowise and n8n: Auth Bypass in Exposed LLM Services

Flowise and n8n: Auth Bypass in Exposed LLM Services

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

A scan of over one million exposed AI services found pervasive security failures including absent authentication, leaked API keys, and exposed business logic across self-hosted LLM deployments. Agent management platforms such as Flowise and n8n were discovered internet-exposed without access controls, revealing credential lists and internal workflows. The findings indicate systemic misconfiguration risk as enterprises race to self-host AI infrastructure without applying baseline security practices.

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