npm / emoji-regex / 11.0.0
emoji-regex 11.0.0
- Source
- https://github.com/mathiasbynens/emoji-regex
- Tag scanned
v11.0.0- Compared with
v10.6.0(3 signals introduced since)- Files
- 10 scanned, 0 skipped (binary, oversized, or unrecognised)
- Signals
- 0 critical · 0 warn · 3 info
- Scan time
- 2.9 s
- LLM review
- Reviewed by claude-haiku-5-5 (Anthropic): 3 of 3 warn and critical signals; 3 demoted to info.
- Disclude version
- 4.0.0
- Scanned (UTC)
- 2026-10-14 19:03
Signals
Ordered by severity, then signals introduced in this release. Hidden characters are shown as ⟨U+…⟩.
-
return /[#*0-9]\uFE0F?\u20E3|[\xA9\xAE\u203C\u2049\u2122\u2139\u2194-\u2199\u21A9\u21AA\u231A\u231B\u2328\u23CF\u23ED-\u23EF\u23F1\u23F2\u23F8-\u23FA\u24C2\u25AA\u25AB\u25B6\u25C0\u25FB\u25FC\u25FE\u2600-\u2604\u260E\u2611\u2614\u2615\u2618\u2620\u2622\u2623\u2626\u262A\u262E\u262F\u2638-\u263A\u2640\u2642\u2648-\u265likely benign Minified generated emoji regex literal on one very long line.Reasoning
A 14115-character line is a generated regex character class of emoji codepoints, typical of emoji-regex style libraries. The long-line signal on a raw pass has a high false-positive rate, and the visible content is a plain regex literal with no encoding or execution.
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const = await ;likely benign Test helper dynamically imports Unicode emoji sequence data from a package.Reasoning
This is a test script importing a Unicode data package by a template path built from a package constant. The specifier is not attacker-controlled input and the import target is a fixed data module, so it is a common build/test pattern rather than a dropper.
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const = await ;likely benign Test file dynamically imports Unicode emoji modifier data from a package.Reasoning
Same pattern as the sibling test file: a dynamic import of a fixed Unicode property module via a package-name template. It is a test fixture loader with no network, decoding, or execution of untrusted content.
Reproduce This Scan
Run disclude locally to verify. Add --format sarif for SARIF output. Add --llm (with an API key in the environment) to include the LLM review.
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