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AI-GATEWAY

Ai-Gateway

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AI Gateways Targeted: LiteLLM, RAGFlow, Kestra Compromised

AI Gateways Targeted: LiteLLM, RAGFlow, Kestra Compromised

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 Microsoft Security Blog

Microsoft Security Research documented active intrusions targeting three distinct AI infrastructure components — a LiteLLM gateway, a RAGFlow retrieval platform, and a Kestra workflow orchestrator — revealing a pattern of attackers treating AI control planes as high-value targets for credential theft and compute abuse. Across all three cases, attackers converged on the same objectives: stealing model-provider API keys, establishing persistence, and monetising compromised compute resources. The findings signal that AI-specific middleware and orchestration layers require the same security rigour as traditional enterprise critical infrastructure.

CVE-2026-42208: LiteLLM SQL Injection Exposes API Keys

CVE-2026-42208: LiteLLM SQL Injection Exposes API Keys

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

A critical SQL injection vulnerability (CVE-2026-42208, CVSS 9.3) in BerriAI's LiteLLM AI gateway was actively exploited within 36 hours of public disclosure, targeting database tables storing upstream LLM provider API keys including OpenAI, Anthropic, and AWS Bedrock credentials. Attackers demonstrated prior knowledge of LiteLLM's internal schema, selectively probing credential and configuration tables while ignoring user and team tables. The blast radius extends far beyond a typical web-app SQL injection, as successful extraction equates to cloud-account-level compromise across multiple AI provider accounts.

GoModel AI Gateway Supply Chain Compromise

GoModel AI Gateway Supply Chain Compromise

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.2 HN AI Security

GoModel is an open-source AI gateway written in Go that provides a unified OpenAI-compatible API across multiple LLM providers including OpenAI, Anthropic, Gemini, Groq, xAI, and Ollama. As an infrastructure layer sitting between applications and AI backends, it introduces a significant supply chain and API security surface that warrants scrutiny. The project advertises built-in guardrails and observability, which are positive security signals, but open-source gateway projects centralising multi-provider API key management represent a meaningful attack vector if misconfigured or compromised.

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