chore: import upstream snapshot with attribution
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# CodeQL configuration for notebooklm-py.
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#
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# The default Python query pack flags ``print(... <sensitive value> ...)`` as
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# "clear-text logging of sensitive information" whenever a value tagged as
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# secret reaches a print statement, even if the value passed through a
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# project-local sanitiser first. ``notebooklm._logging.scrub_secrets`` IS
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# such a sanitiser — it applies the same redaction pattern set used by
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# ``RedactingFilter`` on the logging pipeline (cookies, CSRF tokens, OAuth
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# bearers, Set-Cookie response headers, etc.) — but CodeQL's default
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# allow-list doesn't know about it.
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#
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# Rather than peppering the codebase with per-line ``# noqa`` comments,
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# disable the ``py/clear-text-logging-sensitive-data`` query for paths
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# where scrub_secrets is the load-bearing redactor. The query still runs
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# everywhere else in the codebase, so a new clear-text leak in
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# (say) ``src/notebooklm/_*.py`` would still surface.
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#
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# Scoped narrowly to the rpc-health canary because (a) it's the only
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# place where decoded RPC responses are printed for diagnostics, and
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# (b) that path already routes through scrub_secrets at every site —
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# see the comments at each print site in scripts/check_rpc_health.py.
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#
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# References:
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# * https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/customizing-your-advanced-setup-for-code-scanning
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# * https://codeql.github.com/codeql-query-help/python/py-clear-text-logging-sensitive-data/
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# Exclude the rule globally. The standard CodeQL config schema for
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# ``query-filters`` does NOT accept a ``paths`` sub-key — attempting to
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# scope the suppression to a specific file via that field silently
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# evaluates to "no exclusion". Since the only Python sites that hit
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# ``py/clear-text-logging-sensitive-data`` in this codebase are the
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# scrub_secrets-wrapped print paths in ``scripts/check_rpc_health.py``
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# (the rpc-health canary script, which is the only place we deliberately
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# echo decoded RPC responses for diagnostics), and every such site is
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# already routed through ``scrub_secrets``, a global exclude is the
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# correct trade-off. The rule remains a noisy false-positive generator
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# for any sanitiser CodeQL doesn't recognise, and we don't have a custom
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# sanitiser-model query pack to teach it about scrub_secrets.
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query-filters:
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- exclude:
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id: py/clear-text-logging-sensitive-data
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paths-ignore:
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# scripts/check_rpc_health.py is a maintenance canary that prints
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# decoded RPC bodies for human diagnosis when the API drifts. Every
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# print site there calls scrub_secrets first. Belt-and-braces: also
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# mark the file as path-ignored so any future CodeQL rule that
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# similarly mis-models the local sanitiser won't gate the PR.
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- 'scripts/check_rpc_health.py'
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