Windows

LiteLLM 1.107.0 Supply Chain Attack Steals AI Credentials

ATLAS OWASP CRITICAL ▲ 9.2 Microsoft Security Blog Oct 24, 2026

A malicious version of LiteLLM 1.107.0 was published to PyPI on October 21, 2026, embedding credential-harvesting payloads that execute automatically during Python interpreter startup—before any import statement is reached. The attack targeted authentication material across developer tools, AI applications, cloud environments, and browsers, with a secondary module specifically targeting LiteLLM proxy credential and model-configuration records. Defenders are warned not to invoke Python or pip inside suspect environments, as doing so can trigger the payload.

Microsoft Copilot Gains Local File Access via Hybrid Intelligence

FIRST LOOK ATLAS OWASP MEDIUM ▲ 5.8 The Verge AI Oct 08, 2026

Microsoft has announced Hybrid Intelligence for Copilot, enabling the AI assistant to access local files, execute multi-step OS-level actions, and coordinate between local and cloud AI models on Windows PCs. For defenders, this represents a meaningful evolution in understanding how agentic AI systems interact with endpoint data and OS surfaces — a pattern that security teams now need to account for in endpoint policy and data governance frameworks. The capability arrives without detailed disclosure of permission scoping, audit logging, or consent controls, leaving security teams with open questions about how to govern Copilot's access to sensitive local assets.

Perplexity Launches Personal Computer AI Agent for Windows PCs

FIRST LOOK ATLAS OWASP HIGH ▲ 8.2 The Verge AI Jul 29, 2026

Perplexity has expanded its Personal Computer agentic tool to Windows, enabling a locally-run AI agent that can access files, Office 365 apps, and the web on behalf of enterprise users. This significantly expands the attack surface for defenders: a compromised or manipulated agent running with local system access can exfiltrate files, execute unauthorised actions, and pivot across cloud-connected Microsoft 365 services. Security teams should treat this as a high-privilege process requiring the same scrutiny as endpoint detection tools, with particular attention to prompt injection via locally-processed documents.

Microsoft MDASH Brings AI-Powered Windows Vulnerability Discovery

FIRST LOOK ATLAS OWASP HIGH ▲ 7.2 BleepingComputer Jul 10, 2026

Microsoft has deployed MDASH (Multi-model Agentic Scanning Harness), an AI-powered agentic system that autonomously scans Windows binaries for vulnerabilities and validates findings through multiple AI models before human engineer review. The accelerated discovery pipeline means defenders will see a higher volume of Patch Tuesday fixes, compressing patch deployment windows and increasing pressure on enterprise patch management processes. Simultaneously, the same AI-accelerated vulnerability discovery capability is available to adversaries, raising the risk that threat actors identify and weaponise flaws faster than Microsoft's pipeline can remediate them.

Claude Mythos Generates Working Exploits for Firefox, Windows

ATLAS OWASP CRITICAL ▲ 9.2 SecurityWeek Jun 10, 2026

Anthropic's Claude Mythos Preview model demonstrated the ability to generate functional proof-of-concept exploits targeting known Firefox and Windows vulnerabilities within minutes to hours, compressing the traditional patch gap window dramatically. Testing also revealed that public Anthropic models with safety guardrails disabled could produce working exploits, though at a lower success rate than Mythos. The findings underscore how frontier LLMs are shifting the threat landscape for unpatched N-day vulnerabilities by automating and accelerating exploit development previously bottlenecked by scarce reverse engineering expertise.

Typosquatted OpenAI Repo Delivers Rust Infostealer to 244K Users

ATLAS OWASP CRITICAL ▲ 8.5 The Hacker News May 11, 2026

A malicious Hugging Face repository impersonated OpenAI's legitimate Privacy Filter model, cloning its description verbatim to gain credibility and reach the platform's trending list with 244,000 downloads. The repository delivered a multi-stage attack chain culminating in a Rust-based information stealer targeting browser credentials, cryptocurrency wallets, and Discord data on Windows machines. The attack leveraged a dead-drop resolver pattern via a public JSON paste service, allowing operators to swap payloads without modifying the repository itself.