AI Agent Security Series: 2. Deriving the Attack Surfaces

In December 2025, OWASP released the 2026 edition of its Agentic Applications Top 10 [1], consolidating the threats to agentic applications into a standard list; the derivation below uses it as a reference. The first article took the agent runtime apart into six layers and two components and left behind two structural facts: structural fact 1 is that all external content converges at assembly into one flat token stream with no provenance markers, and structural fact 2 is that the permission checkpoint covers only the model-to-action segment, so content ingestion and configuration loading never pass through it. Derived along that structural diagram, the attack surfaces differ from the threat list: their value lies in testability, in that any new vulnerability or new technique can be located on one of the attack surfaces, while whatever fails to locate exposes a gap in the structural diagram, and both outcomes advance understanding. ...

October 12, 2026 · 17 min · iamelli0t

AI Agent Security Series: 1. Taking an AI Agent Apart

Since 2025, mainstream coding agents have entered a period of frequent severe-vulnerability disclosures: Claude Code, Codex, Cursor, Gemini CLI, and GitHub Copilot have each produced vulnerabilities that a malicious repository can trigger remotely. In Claude Code’s CVE-2025-59536, once the user clicked through the trust dialog, hooks configuration shipped by a malicious repository executed without any per-command confirmation [1]; in Codex CLI’s CVE-2025-61260, project-local MCP configuration was auto-loaded, so cloning a single repository handed over execution and the GitHub token [2]; in Cursor’s DuneSlide (CVE-2026-50548/49), the sandbox write allowlist was built from model-supplied parameters, letting injected content point the allowlist at the sandbox executor itself [4]. ...

October 10, 2026 · 20 min · iamelli0t