Fetch GitHub issues, spawn sub-agents to implement fixes and open PRs, then monitor and address PR review comments. Usage: /gh-issues [owner/repo] [--label bug] [--limit 5] [--milestone v1.0] [--assignee @me] [--fork user/repo] [--watch] [--interval 5] [--reviews-only] [--cron] [--dry-run] [--model glm-5] [--notify-channel -1002381931352]
65
80%
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High
Do not use without reviewing
Fix and improve this skill with Tessl
tessl review fix ./openclaw/skills/gh-issues/SKILL.mdSecurity
1 high severity finding. You should review these findings carefully before considering using this skill.
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
The prompt repeatedly requires the agent to read and embed the GH_TOKEN in generated curl and git commands (including forming auth URLs and echoing token prefixes), which forces the LLM to handle and potentially output secret token values verbatim or partially.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Outsider free text is ingested into the LLM context via the issue `body` field (authored by external GitHub users) that is fetched at runtime in Phase 2 and then embedded verbatim into the sub-agent prompt in Phase 5 under `<issue> ... Body: {body}</issue>`.
92e7db0
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