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fix(security): deduplicate imports using authorized tracker body index - #1750
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KatalKavya96 wants to merge 1 commit into
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KatalKavya96 wants to merge 1 commit into
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@potiuk , Implemented the fix for #1730 and completed validation. The security-import workflow now uses deterministic matching against an authorized tracker body index instead of relying on GitHub issue search, which can miss backtick-wrapped thread IDs. Validation:
The implementation also fails closed when tracker completeness cannot be established, preventing unsafe duplicate imports. Thanks! |
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Summary
Type of change
.claude/skills/<name>/) — eval fixtures updated belowtools/<system>/*.md)tools/*/withpyproject.toml)docs/,README.md,CONTRIBUTING.md)projects/_template/)prek, workflows, validators)Test plan
prek run --all-filespasses — all hooks green.uv run pytest/ruff check/mypypasses — verified through workspace hooks and targeted package tests.security-issue-import/step-2-dedup: 4/4 passed, 0 failed, 0 manual, 0 errored.dedup-indexresults.case-4-backtick-threadid-matchto reproduce the reported failure.issue-listoperation does not expose bodies.RFC-AI-0004 compliance
check-placeholderspasses.Linked issues
Fixes #1730.
Notes for reviewers (optional)
Implementation: The new
issue-import dedup-indexcommand reads a saved tracker index and compares identifiers against the authoritative Security mailing list thread field. A dedicatedissue-list-with-bodiesvetted operation requires explicit caller authorization.Safety: A missing body, ambiguous mailing-thread identity, or potentially truncated 1000-issue index prevents negative deduplication claims. Jira and local-files backends are explicitly unsupported by this new body-index operation rather than silently treated as having no matches.
Trade-off: The bounded index avoids relying on GitHub's inconsistent search indexing, but trackers with 1000 or more returned issues require a further completeness-safe solution. This PR prioritizes preventing duplicate security imports over automatically proceeding when completeness cannot be established.
Validation scope: The four model evaluations use mocked tool outputs; deterministic Python tests separately verify the matching logic and vetted-ops authorization boundaries.