Fake Claude Code site served trojan — detected by Windows Defender as Trojan:Win32/Kepavll!rfn

A Reddit user on r/ClaudeAI reported that the first Google search result for "Claude Code" was a fake website with the exact same design language as the official Anthropic site. After downloading and running a PowerShell install command, Windows Defender caught the payload as Trojan:Win32/Kepavll!rfn.
What happened
- The user, who has been online since 1996 and works mostly on macOS, needed to use Claude Code on a rarely used Windows PC.
- Clicked the first Google result for "Claude Code" — the site looked identical to the official one.
- Ran the PowerShell install command (similar to the legitimate
iex (irm <url>)pattern) without verifying the URL. - Windows Defender immediately flagged the download as
Trojan:Win32/Kepavll!rfn.
How to avoid this
- Always check the domain: official Claude Code downloads are on
docs.anthropic.comor the official GitHub repository, not a lookalike. - For Windows, use
winget install ClaudeCodeor download the MSI directly from the official source. - Never run
iex (irm ...)from a search result — manually verify the URL before pasting into PowerShell.
📖 Read the full source: r/ClaudeAI
👀 See Also

VulnHunter: Capital One's Agentic AI Code Security Tool Now Open Source
Capital One open-sourced VulnHunter, an agentic AI tool that simulates attacker entry points, falsifies findings to cut false positives, and generates targeted code fixes.

Critical Cowork Bug: AI Agent Deleted Files Without User Approval
A critical bug in Claude's Cowork mode allowed the AI to execute destructive actions without user consent. The ExitPlanMode tool falsely reported user approval, triggering an autonomous agent that deleted 12 files from a React/TypeScript codebase.

Endo Familiar: Object-Capability Sandbox for AI Agents
Endo Familiar implements object-capability security for AI agents: agents start with zero ambient authority, receive only explicit references to specific files or directories, and can derive narrower capabilities in sandboxed code.

Hidden Audio Signals Hijack Voice AI Systems with 79-96% Success Rate
Research shows imperceptible audio clips can force LALMs to execute unauthorized commands like web searches, file downloads, and email exfiltration with 79-96% success across 13 models including Mistral and Microsoft services.