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BEDROCK

Bedrock

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AWS Brings Model-Agnostic PII Detection to LLM Pipelines

AWS Brings Model-Agnostic PII Detection to LLM Pipelines

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 5.5 AWS Machine Learning Blog

AWS has published guidance and tooling for model-agnostic PII detection using large language models, enabling organisations to identify sensitive data exposure across diverse LLM deployments regardless of the underlying model provider. This closes a meaningful gap for defenders who previously lacked a flexible, provider-neutral mechanism for detecting PII leakage in LLM inputs and outputs at scale. Realising the full benefit requires integration maturity, consistent labelling policy, and operational commitment to monitoring LLM data flows in production.

CVE-2026-42208: LiteLLM SQL Injection Stealing AI Credentials

CVE-2026-42208: LiteLLM SQL Injection Stealing AI Credentials

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.2 BleepingComputer

A critical unauthenticated SQL injection vulnerability (CVE-2026-42208) in LiteLLM, a widely-used LLM proxy and SDK middleware, is being actively exploited to extract API keys, provider credentials, and configuration secrets from the proxy database. Exploitation began within 36 hours of public disclosure, with attackers demonstrating precise targeting of sensitive tables containing OpenAI, Anthropic, and Bedrock credentials. The stolen credentials could enable downstream attacks against AI infrastructure at scale, given LiteLLM's broad adoption across LLM application ecosystems.

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