# ASI Tracker: Add CVE-2026-28353 - Trivy VSCode Extension Agentic Supply Chain Compromise#824
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# ASI Tracker: Add CVE-2026-28353 - Trivy VSCode Extension Agentic Supply Chain Compromise#824arshi016 wants to merge 2 commits into
arshi016 wants to merge 2 commits into
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… chain compromise Adds the March 2026 Trivy VSCode Extension supply chain compromise to the Agentic Exploits & Incidents tracker. The incident is notable as a publicly documented in-the-wild case where an AI coding agent was weaponized as an autonomous exfiltration channel. CVSS 4.0 base score 10.0. Mapped to ASI01, ASI02, ASI04, and ASI05.
- Date corrected from Mar 2026 to Feb 2026 (exposure window Feb 27-28) - Added Aqua Security vendor advisory (GHSA-8mr6-gf9x-j8qg) - Added Socket.dev analysis as discoverer link - Impact summary now names the five targeted AI CLIs (Claude, Codex, Gemini, Copilot, Kiro), the prompt injection mechanism, and the permissive-mode bypass of human-in-the-loop controls - Added affected versions (v1.8.12-1.8.13) and exposure window
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ASI Tracker: Add CVE-2026-28353 - Trivy VSCode Extension Agentic Supply Chain Compromise
Key Changes:
Summary
Adds the March 2026 Trivy VSCode Extension supply chain compromise (CVE-2026-28353, CVSS 4.0 base score 10.0) to the Agentic Exploits & Incidents tracker.
Why this incident belongs in the tracker
This is a publicly documented, in-the-wild incident where an AI coding agent was weaponized as an autonomous exfiltration channel, not just a traditional supply chain compromise that happened to involve an AI-adjacent tool. The NVD description explicitly states the malicious code was "designed to leverage local AI coding agent to collect and exfiltrate sensitive information."
The incident was filed under CWE-506 (Embedded Malicious Code), a classification that captures the payload delivery but omits the agentic exploit primitive, specifically, that the AI coding assistant's legitimate capabilities (file access, code analysis, context gathering) were repurposed as the exfiltration mechanism. This mis-classification pattern is relevant to the ASI initiative's goal of distinguishing agentic threats from traditional LLM classifications.
ASI mapping rationale
Scope