# litellm LiteLLM is an open-source AI gateway and Python SDK that provides a unified OpenAI-compatible interface for accessing multiple large language models, with routing, retries, authentication, cost tracking, and rate limiting. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## AI gateways: why and how DevFeed: [AI gateways: why and how]() Original publisher: [Read original article]() Author: Nicolas Fränkel Published: 2026-05-31T00:00:00Z Content type: article Language: en Sources: [Nicolas Fränkel]() Topics: [Amazon API Gateway](), [LLMs](), [Artificial Intelligence](), [Routing (disambiguation)](), [Claude](), [Security](), [litellm](), [Caching](), [Scalability](), [Load Balancing](), [observability]() Tags: [ai](), [ai-gateway](), [anthropic](), [api-gateway](), [backend](), [caching](), [claude](), [claude-code](), [coding-assistant](), [decoupling](), [devstral](), [gateway](), [litellm](), [llm](), [llms](), [load-balancing](), [mistral](), [observability](), [open-source](), [routing](), [scalability](), [security](), [technical]() ### AI overview This article explains how AI gateways apply the API gateway pattern to AI clients and LLM backends. It discusses using a gateway to centralize model and provider management, governance, cost control, routing, caching, failover, load balancing, and observability, and considers routing Claude Code requests to another provider. ### Source excerpt Before working for 2 years on the Apache APISIX API gateway, I was mainly oblivious to API gateways. It's only by working with them that I understood their value. Decoupling the client and the server unlocks a lot of options: moving authentication to the API Gateway, securing APIs, deduplicating API requests, etc. In this post, I want to describe how the same pattern applies to AI. AI gateways AI gateways work in a similar way. ## Cyber resiliency in practice: Lessons from recent supply chain attacks DevFeed: [Cyber resiliency in practice: Lessons from recent supply chain attacks]() Original publisher: [Read original article]() Published: 2026-05-08T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [resiliency](), [supply chain attacks](), [supply-chain-security](), [axios](), [GitHub Actions](), [litellm](), [trivy](), [npm](), [PyPI](), [Python](), [Large Language Model]() Tags: [axios](), [chainguard-libraries](), [cyber-resiliency](), [cybersecurity](), [github-actions](), [litellm](), [malware](), [npm](), [pypi](), [python](), [security](), [security-attacks](), [social-engineering](), [software-supply-chain-security](), [supply-chain-attacks](), [trivy](), [worm]() ### AI overview The article defines cyber resiliency as an integrated ability to anticipate, withstand, recover from, and adapt to attacks across the full Protect, Detect, Respond, and Recover lifecycle. It examines recent supply chain attacks involving Trivy, Axios, and LiteLLM, highlighting risks such as GitHub Actions misconfiguration, long-lived tokens, incomplete credential rotation, mutable Git tags, maintainer-account compromise, and malicious package releases. ### Source excerpt Learn how modern cyber resiliency helps organizations prevent, detect, and recover from supply chain attacks like Trivy, Axios, and LiteLLM. ## Security Week 2614: атака класса supply chain на библиотеку LiteLLM DevFeed: [Security Week 2614: атака класса supply chain на библиотеку LiteLLM]() Original publisher: [Read original article]() Author: Kaspersky\_Lab ("Лаборатория Касперского") Published: 2026-03-30T17:00:04Z Content type: news Language: ru Sources: ["Лаборатория Касперского" RU]() Topics: [litellm](), [Security](), [PyPI](), [Python]() Tags: [discord](), [kubernetes](), [litellm](), [pypi](), [python](), [security](), [slack](), [ssh](), [supply-chain](), [tag-9fe8963de219](), [terraform](), [tls]() ### AI overview The article reports a supply-chain compromise affecting LiteLLM versions 1.82.7 and 1.82.8 uploaded to PyPI. The malicious code searched victims' systems for files, credentials, secrets, and cloud infrastructure data, could contact a command server, and included Kubernetes persistence capabilities. Researchers also found similar malware in two Checkmarx extensions; the malicious versions were removed, and affected users were advised to rotate credentials and secrets. ### Source excerpt Громкой новостью прошлой недели стал взлом библиотеки LiteLLM, используемой в качестве посредника для коммуникации с большим количеством языковых моделей (сообщение от разработчиков, новость на Хабре). Через другое вредоносное приложение на Python была взломана учетная запись мейнтейнера проекта, после чего сразу две версии LiteLLM (1.82.7 и 1.82.8) с вредоносными модулями были загружены в репозиторий PyPI. Отчет с анализом вредоносного кода опубликовали эксперты "Лаборатории Касперского". В версии 1.82.7 вредоносный код был встроен в файл proxy_server.py. В версии 1.82.8 дополнительно появился .pth-файл, благодаря которому вредоносный код выполнялся при каждом запуске интерпретатора, даже если зараженная библиотека не использовалась. После запуска зараженный скрипт начинал рекурсивный обход рабочих директорий в системе жертвы. В каждой директории скрипт просматривал содержимое файлов, которое выводил в буфер stdout и сохранял в файл для последующей отправки на командный сервер злоумышленников. Далее скрипт собирал информацию о системе и также сохранял в файл. После этого он переходил к поиску конфиденциальных данных, включая следующие типы: Читать далее ## The litellm PyPI compromise and how Chainguard Libraries blocked malicious releases DevFeed: [The litellm PyPI compromise and how Chainguard Libraries blocked malicious releases]() Original publisher: [Read original article]() Published: 2026-03-24T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [litellm](), [chainguard libraries](), [open-source-security]() Tags: [chainguard-libraries](), [chainguard-libraries-for-python](), [litellm](), [litellm-attack](), [litellm-package](), [litellm-supply-chain-attack](), [open-source-security](), [pypi](), [secure-packages](), [security](), [supply-chain-attacks]() ### AI overview The article describes a litellm compromise on PyPI in which malicious releases were used to steal secrets. It states that Chainguard Libraries prevented exposure by rebuilding only verified source and blocking the malicious releases. ### Source excerpt Hackers compromised litellm on PyPI to steal secrets. Chainguard Libraries prevented exposure by rebuilding only verified source, blocking malicious releases. ## Introducing the DigitalOcean AI Ecosystem DevFeed: [Introducing the DigitalOcean AI Ecosystem]() Original publisher: [Read original article]() Author: Meghan Grady Published: 2025-10-06T20:07:17Z Content type: release Language: en Sources: [DigitalOcean]() Topics: [Digital Ocean](), [Artificial Intelligence](), [AI Development](), [Cloud](), [LangChain](), [litellm]() Tags: [ai](), [amd](), [build](), [cloud](), [deepseek](), [dev-tools](), [digitalocean](), [gradient-platform](), [integrations](), [meta](), [models](), [nvidia](), [openai](), [partner]() ### AI overview DigitalOcean announced an expansion of its AI Ecosystem and introduced the DigitalOcean AI Partner Program. Through the Gradient AI Agent Cloud, the ecosystem brings together infrastructure, AI models, development tools, integration frameworks, and specialist partners for building AI applications. ### Source excerpt Last week at Deploy London, we announced a significant expansion of our offerings within the DigitalOcean AI Ecosystem and introduced the DigitalOcean AI Partner Program. A platform is only as strong as its ecosystem, and these initiatives are designed to create a comprehensive, flexible, and powerful environment for startups, builders, and developers to create the next generation of AI applications. Explore What's Possible with the DigitalOcean AI Ecosystem We're collaborating with industry leaders and innovative startups to provide access to all of the AI products and services you need through the Gradient AI Agent Cloud. DigitalOcean's comprehensive AI Ecosystem empowers startups and enterprises to build next-gen AI applications, offering choice and flexibility through embedded partner integrations and workflows. DigitalOcean's AI Ecosystem provides access to: Powerful Infrastructure: Efficient AMD and NVIDIA GPUs to power your applications. Advanced Models: Access to leading models from companies like OpenAI, DeepSeek, Meta, and Mistral. Applications & Frameworks: Popular AI dev tools and integration frameworks such as LangChain, LiteLLM, and dStack. Integrators: A network of AI specialists to help you migrate workflows and build robust new AI implementations. The DigitalAI Ecosystem "At the heart of AI's progress are the developers who are turning ideas into reality. The Gradient AI Ecosystem is a powerful force multiplier for them, proving that the future isn't just about silicon--it's about software and the collaborative community built on top of it," said Anush Elangovan, VP of AI Software at AMD. "By providing high-performance AMD GPUs through DigitalOcean's Gradient AI Agentic Cloud, we ensure the ecosystem is powered by world-class, open-standard hardware. We're not just providing infrastructure; together we're powering the software and the community that will invent tomorrow's AI." Through the dynamic Gradient AI Ecosystem, AI startups and digital native