DATA
6de0bf9f5b
Vendored deer-flow upstream (bytedance/deer-flow) plus prompt-injection hardening: - New deerflow.security package: content_delimiter, html_cleaner, sanitizer (8 layers — invisible chars, control chars, symbols, NFC, PUA, tag chars, horizontal whitespace collapse with newline/tab preservation, length cap) - New deerflow.community.searx package: web_search, web_fetch, image_search backed by a private SearX instance, every external string sanitized and wrapped in <<<EXTERNAL_UNTRUSTED_CONTENT>>> delimiters - All native community web providers (ddg_search, tavily, exa, firecrawl, jina_ai, infoquest, image_search) replaced with hard-fail stubs that raise NativeWebToolDisabledError at import time, so a misconfigured tool.use path fails loud rather than silently falling back to unsanitized output - Native client back-doors (jina_client.py, infoquest_client.py) stubbed too - Native-tool tests quarantined under tests/_disabled_native/ (collect_ignore_glob via local conftest.py) - Sanitizer Layer 7 fix: only collapse horizontal whitespace, preserve newlines and tabs so list/table structure survives - Hardened runtime config.yaml references only the searx-backed tools - Factory overlay (backend/) kept in sync with deer-flow tree as a reference / source See HARDENING.md for the full audit trail and verification steps.
57 lines
1.5 KiB
Python
57 lines
1.5 KiB
Python
"""GuardrailProvider protocol and data structures for pre-tool-call authorization."""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Any, Protocol, runtime_checkable
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@dataclass
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class GuardrailRequest:
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"""Context passed to the provider for each tool call."""
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tool_name: str
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tool_input: dict[str, Any]
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agent_id: str | None = None
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thread_id: str | None = None
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is_subagent: bool = False
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timestamp: str = ""
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@dataclass
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class GuardrailReason:
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"""Structured reason for an allow/deny decision (OAP reason object)."""
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code: str
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message: str = ""
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@dataclass
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class GuardrailDecision:
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"""Provider's allow/deny verdict (aligned with OAP Decision object)."""
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allow: bool
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reasons: list[GuardrailReason] = field(default_factory=list)
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policy_id: str | None = None
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metadata: dict[str, Any] = field(default_factory=dict)
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@runtime_checkable
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class GuardrailProvider(Protocol):
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"""Contract for pluggable tool-call authorization.
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Any class with these methods works - no base class required.
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Providers are loaded by class path via resolve_variable(),
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the same mechanism DeerFlow uses for models, tools, and sandbox.
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"""
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name: str
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def evaluate(self, request: GuardrailRequest) -> GuardrailDecision:
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"""Evaluate whether a tool call should proceed."""
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...
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async def aevaluate(self, request: GuardrailRequest) -> GuardrailDecision:
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"""Async variant."""
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...
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