Ollama

Software Supply Chain and AI Exploitation Dominate Threat Landscape The software supply chain has become the primary battlefield for attackers because compromising a single developer tool can cascade into thousands of enterprise networks. Campaigns like Mini Shai-Hulud and TrapDoor are stealing credentials and injecting backdoors across major code registries, while the Laravel Lang Compromise and the Coruna Exploit Kit show how malicious code can automatically execute to steal secrets or exploit end users. As a result, organizations must treat developer environments as high-value targets, because a single compromised package or malicious VS Code extension can lead to catastrophic breaches like the GitHub internal repository theft by TeamPCP. In parallel, artificial intelligence is simultaneously accelerating attacks and creating dangerous new attack surfaces. Threat actors are using AI to automate influence campaigns like Patriot Bait and crack passwords, while also impersonating AI tools like Gemini CLI and Claude Code to deliver infostealers. Furthermore, attackers are directly targeting exposed AI infrastructure, such as Ollama AI endpoints, and manipulating AI coding assistants via hidden prompt injections in campaigns like TrapDoor, which means AI systems are both the weapon and the target. These trends together suggest that traditional perimeter defenses are failing against supply chain and AI-driven threats. Managers should immediately enforce strict vetting of open-source packages, restrict developer access to unverified extensions, and ensure AI infrastructure is not exposed to the public internet.

2026-05-226 minAkamaihigh

A sophisticated attack campaign is targeting Ollama AI endpoints to deploy a custom Go-based P2P remote access Trojan (RAT) and cryptominer. The malware, named 'vc', leverages decentralized networking via libp2p to evade traditional C2 blocking and utilizes RAM disk execution and process masquerading to maintain stealth.

2026-05-134 minSentinelOnehigh

A joint research project by SentinelLABS and Censys discovered a massive, unmanaged network of over 175,000 publicly exposed Ollama instances. Many of these self-hosted AI models possess tool-calling and vision capabilities, creating significant security risks such as resource hijacking, prompt injection, and identity laundering through residential proxy abuse.