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First reported · updated · 3 reports embracethered.com

AWS Kiro: Arbitrary Code Execution via Indirect Prompt Injection

Researchers found a vulnerability (CVE-2026-10591) in AWS Kiro, an agentic IDE, where hidden instructions planted in a web page or source file that Kiro processes can trigger indirect prompt injection to rewrite Kiro's own MCP server configuration (~/.kiro/settings/mcp.json) or allowlist arbitrary Bash commands in .vscode/settings.json, achieving arbitrary code execution on the developer's machine with no approval prompt. The human-in-the-loop approval boundary is bypassed because Kiro can write to these config files without user consent, and AWS has issued a fix and CVE.
Patched

indirect-prompt-injection · prompt-injection · remote-code-execution · tool-abuse · config-poisoning
ai-agents · mcp · llm · agentic-ide

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First reported · updated · 2 reports zafran.io

Hugging Face Diffusers Flaws Could Let Model Repositories Execute Arbitrary Code

Zafran Labs disclosed three high-severity flaws, collectively named FaceHugger, in Hugging Face's Diffusers library (CVE-2026-44827 CVSS 8.8, CVE-2026-45804 CVSS 7.5, and CVE-2026-44513 CVSS 8.8) that let a malicious model repository silently execute arbitrary code on any machine loading it. The flaws stem from a Time-of-Check to Time-of-Use race that bypasses the trust_remote_code safeguard by splitting a model download into two non-atomic HTTP requests, so a routine model load becomes an initial-access vector across CI/CD, container, and production pipelines.
PoCadvisorysupply-chainarbitrary-code-executionmodel-supply-chaintoctouhugging-facediffusersllmai-supply-chain
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First reported arxiv.org

The Balkanization of Execution-Security Research for AI Coding Agents: Isolation, Access Control, and Time-of-Check-to-Time-of-Use Vulnerabilities

A systematization-of-knowledge paper by Mohammadreza Rashidi organizes 39 works (2023-2026) on execution security for AI coding agents into 17 categories covering sandbox isolation, capability/access control, policy enforcement, TOCTOU races, and MCP threats, and verifies four disclosed, patched CVEs affecting production agent harnesses. It surfaces five cross-cutting gaps, including denylist policy failure rates of 69-98% and benign out-of-scope agent actions occurring at rates up to 17.1% under realistic prompting.
researchtoctoutool-abusesandbox-escapesupply-chainmcp-abuseai-agentsllmmcpcoding-agent
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