devloop
Warn
Audited by Gen Agent Trust Hub on Sep 2, 2026
Risk Level: MEDIUMREMOTE_CODE_EXECUTIONPRIVILEGE_ESCALATIONCOMMAND_EXECUTIONINDIRECT_PROMPT_INJECTIONEXTERNAL_DOWNLOADS
Full Analysis
- [REMOTE_CODE_EXECUTION]: The skill recommends installing third-party extensions from untrusted GitHub repositories (
mattpocock/skillsandjoeseesun/qiaomu-goal-meta-skill) using thenpx skills addcommand. This execution method allows for arbitrary code to be downloaded and integrated into the agent's environment.\n- [PRIVILEGE_ESCALATION]: The skill's implementation templates (e.g.,scripts/launch-runner-template.sh) and instructions suggest using the--permission-mode bypassPermissionsflag for agents likeclaude-code. This flag explicitly disables safety filters and user-permission prompts for file system and shell operations, effectively escalating the agent's autonomous privileges.\n- [COMMAND_EXECUTION]: The skill uses a 'Control-plane kernel' consisting of multiple shell scripts (e.g.,scripts/adr,scripts/detect-runtime-host.sh) to manage state, detect execution hosts, and orchestrate the implementation loop. These scripts execute various system commands and manage external agent terminals, creating a complex execution chain.\n- [INDIRECT_PROMPT_INJECTION]: The 'devloop' architecture involves multiple agents (compiler, impl runner, and reviewer) processing requirements and code. This creates a vulnerability surface for indirect prompt injection where malicious instructions embedded in a requirement or code comment could influence the behavior of downstream agents.\n - Ingestion points: Requirement data is processed into
plan.mdandnext-goal.md(SKILL.md, references/goal-template.md).\n - Boundary markers: The skill uses structured templates but lacks robust delimiters or escaping to separate untrusted user data from agent instructions.\n
- Capability inventory: The system performs file writes, subprocess execution, and handles git operations across multiple worktrees (scripts/adr, references/orca-host.md).\n
- Sanitization: No explicit sanitization or filtering of external content is performed before interpolation into agent prompts.
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