litellm
10 articles about litellm in AI news
3 MCP Gateway Security Gaps LiteLLM's Audit Found (And How to Fix Them in
LiteLLM's audit revealed 3 MCP gateway gaps: fail-open resolver, unpinned servers, opt-in least-privilege. Fix them in Claude Code with version pinning and allowed_tools.
PyPI Quarantines LiteLLM Package After Supply Chain Attack Compromises AI Integration Tool
The Python Package Index (PyPI) has quarantined the LiteLLM package after a supply chain attack distributed a malicious update. The action prevents automatic installation of the compromised version via pip.
Claude Code Digest — Jun 28–Jul 01
Claude Code’s biggest shift this week: teams are replacing “let the model figure it out” with hard guardrails, and one pair of Bash hooks cut an Anthropic bill from $312 to $156.
MiniMax Added as Official Provider for OpenClaude AI Framework
MiniMax has been integrated as an officially supported provider for the OpenClaude framework, giving developers a new, enterprise-backed model option for running the open-source Claude alternative.
Claude 4.6 Migration Deadline
Anthropic is retiring Opus 4 and Sonnet 4 on June 15, 2026. Migrate to 4.6 models now to gain 1M context and higher output limits, but update your code for adaptive thinking and output_config changes.
Block Compromised NPM/PyPI Packages Automatically with attach-guard
A new Claude Code plugin uses PreToolUse hooks to automatically block compromised packages like the recent axios hijack before they install.
Inside Claude Code’s Leaked Source: A 512,000-Line Blueprint for AI Agent Engineering
A misconfigured npm publish exposed ~512,000 lines of Claude Code's TypeScript source, detailing a production-ready AI agent system with background operation, long-horizon planning, and multi-agent orchestration. This leak provides an unprecedented look at how a leading AI company engineers complex agentic systems at scale.
How to Lock Down Claude Code After the Cowork Prompt Injection Scandal
Claude Code's new Computer Use feature expands attack surfaces. Here's how to configure permissions and audit dependencies to prevent data exfiltration.
Building a Store Performance Monitoring Agent: LLMs, Maps, and Actionable Retail Insights
A technical walkthrough demonstrates how to build an AI agent that analyzes store performance data, uses an LLM to generate explanations for underperformance, and visualizes results on a map. This agentic pattern moves beyond dashboards to actively identify and diagnose location-specific issues.
Headroom AI: The Open-Source Context Optimization Layer That Could Revolutionize Agent Efficiency
Headroom AI introduces a zero-code context optimization layer that compresses LLM inputs by 60-90% while preserving critical information. This open-source proxy solution could dramatically reduce costs and improve performance for AI agents.