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github/gh-aw is a Go + Node.js/CJS GitHub CLI extension orchestrating agentic workflows (Copilot, Claude, Codex, Gemini, Pi). The 7-day window shows a high-velocity, well-governed cycle: active daily static-analysis gates, responsive remediation, and no critical or secret-scanning alerts. Two residual concerns require continued attention: (1) CodeQL HIGH alert #635 (insecure temp file) is actively tracked but unresolved; (2) a confirmed cross-run prompt injection (XPIA) surface in the cache-memory subsystem (#28830) remains open and unassigned since 2026-04-28 — the highest AI-amplified risk in the repository.
Overall posture: Tier B — Open With Conditions (one surface at Tier C).
*RGS-004 at Tier A: upstream author_association guard confirmed in pre_activation jobs.
Top 3 AI-specific risks: (1) Cache XPIA #28830 — injected markdown reaches LLM context on next run; (2) Token exhaustion via retry loops — fix merged but no circuit-breaker framework yet (#28776); (3) Temp file race on evaluation script — could corrupt AI decision data silently.
Remediation Queue
#
Finding
SLA
Action
1
Alert #635 insecure temp file
High — 7 days
Use tmp.fileSync() / fs.mkdtemp() mode 0o600 (issue #41061 active)
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Executive Summary
github/gh-awis a Go + Node.js/CJS GitHub CLI extension orchestrating agentic workflows (Copilot, Claude, Codex, Gemini, Pi). The 7-day window shows a high-velocity, well-governed cycle: active daily static-analysis gates, responsive remediation, and no critical or secret-scanning alerts. Two residual concerns require continued attention: (1) CodeQL HIGH alert #635 (insecure temp file) is actively tracked but unresolved; (2) a confirmed cross-run prompt injection (XPIA) surface in the cache-memory subsystem (#28830) remains open and unassigned since 2026-04-28 — the highest AI-amplified risk in the repository.Overall posture: Tier B — Open With Conditions (one surface at Tier C).
Tier Classification
project_command.go)Control Verification
AI-Aware Risk Scoring
*RGS-004 at Tier A: upstream
author_associationguard confirmed in pre_activation jobs.Top 3 AI-specific risks: (1) Cache XPIA #28830 — injected markdown reaches LLM context on next run; (2) Token exhaustion via retry loops — fix merged but no circuit-breaker framework yet (#28776); (3) Temp file race on evaluation script — could corrupt AI decision data silently.
Remediation Queue
tmp.fileSync()/fs.mkdtemp()mode 0o600 (issue #41061 active)git add -A; quarantine suspicious filesownerId/projectIdwithescapeGraphQLString()or use parameterized variablescircuit-breakerfrontmatter field with failure counter via artifacts${{ steps.X.outputs.Y }}inrun:with env varsException Register
author_associationguard confirmed; not exploitableworkflow-graphql-static-concatOperational Metrics
References:
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