Merge pull request #1225 from MemPalace/feat/privacy-warn-tailscale-cgnat
feat(privacy): treat Tailscale CGNAT range (100.64.0.0/10) as local
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@@ -49,6 +49,8 @@ def _endpoint_is_local(url: Optional[str]) -> bool:
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- localhost, 127.0.0.1, ::1
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- hostnames ending in .local (mDNS/Bonjour)
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- IPv4 RFC1918: 10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16
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- IPv4 CGNAT (Tailscale and similar VPN/tunnel networks):
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100.64.0.0/10 — first octet 100, second octet 64-127 inclusive
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- IPv6 unique-local addresses (fc00::/7) — fc.../fd... prefixes
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None / empty / unparseable URLs are treated as local (defensive default —
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@@ -81,6 +83,20 @@ def _endpoint_is_local(url: Optional[str]) -> bool:
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return True
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except ValueError:
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pass
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if host.startswith("100."):
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# 100.64.0.0/10 — Tailscale CGNAT range. First octet 100, second
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# octet 64-127 inclusive. Users running a local LLM (LM Studio,
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# Ollama, etc.) accessible via Tailscale on a 100.x.x.x address
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# should not trigger the external-API privacy warning.
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# 100.x.x.x outside this range is regular allocated public space
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# and remains external.
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parts = host.split(".")
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if len(parts) >= 2:
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try:
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if 64 <= int(parts[1]) <= 127:
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return True
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except ValueError:
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pass
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# IPv6 unique-local addresses fc00::/7 — match leading hex chars
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if host.startswith("fc") or host.startswith("fd"):
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return True
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@@ -378,3 +378,51 @@ def test_anthropic_provider_default_endpoint_is_external():
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f"Default AnthropicProvider endpoint must be external; got "
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f"is_external_service={p.is_external_service} for endpoint={p.endpoint}"
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)
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# ── Tailscale CGNAT range (issue #25 follow-up to #24) ──────────────────
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#
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# Tailscale assigns addresses in 100.64.0.0/10 (CGNAT range): first octet
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# always 100, second octet 64-127 inclusive. Users running LM Studio /
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# Ollama / any local LLM accessible via Tailscale would currently
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# (post-#24, pre-#25) get a wrong privacy warning because the heuristic
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# doesn't recognize CGNAT as private. These tests pin the fix.
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def test_openai_compat_provider_tailscale_cgnat_endpoint_is_local():
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"""Tailscale CGNAT range (100.64.0.0/10) — IPs where the first octet
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is 100 AND the second octet is 64-127 inclusive — must be classified
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as local. Tailscale users running LM Studio on their Tailnet should
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not trigger the external-API warning.
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"""
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cases = [
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("http://100.64.0.1:1234", "start of CGNAT"),
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("http://100.100.50.50:1234", "middle of CGNAT (typical Tailscale assignment)"),
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("http://100.127.255.254:1234", "near end of CGNAT"),
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]
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for endpoint, label in cases:
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p = OpenAICompatProvider(model="any", endpoint=endpoint)
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assert p.is_external_service is False, (
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f"Tailscale CGNAT address {endpoint} ({label}) must be classified "
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f"local; got is_external_service={p.is_external_service}"
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)
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def test_openai_compat_provider_outside_tailscale_cgnat_is_external():
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"""Addresses in 100.x.x.x that fall OUTSIDE the CGNAT range
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(100.64.0.0 - 100.127.255.255) are public IPs in regular allocated
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space and must remain classified as external. Specifically: anything
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where the second octet is < 64 or > 127.
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"""
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cases = [
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("http://100.0.0.1:1234", "below CGNAT (public)"),
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("http://100.63.255.255:1234", "just below CGNAT (boundary)"),
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("http://100.128.0.0:1234", "just above CGNAT (boundary)"),
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("http://100.255.255.255:1234", "well above CGNAT"),
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]
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for endpoint, label in cases:
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p = OpenAICompatProvider(model="any", endpoint=endpoint)
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assert p.is_external_service is True, (
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f"Address {endpoint} ({label}) is OUTSIDE Tailscale CGNAT and "
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f"should remain external; got is_external_service={p.is_external_service}"
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)
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