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feat(tenancy): add Workspace multi-tenant foundation (#2353)

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* Document multi-tenant workspace architecture

* Add OSS and commercial workspace boundaries

* docs: redesign multi-tenant workspace architecture

* feat(tenancy): implement workspace isolation

* docs(tenancy): record verification evidence

* docs(tenancy): revise single-instance SaaS topology

* docs(tenancy): refine architecture options

* docs: finalize cloud v2 multi-tenant decisions

* feat(tenancy): establish cloud isolation foundations

* feat(tenancy): harden shared cloud runtime boundaries

* docs(tenancy): record final isolation verification

* fix(tenancy): close isolation and permission gaps

* docs(tenancy): record final isolation verification

* feat(tenancy): connect cloud workspace control plane

* fix(build): install git for pinned SDK

* docs(cloud): update control plane verification

* chore: update multi-tenant SDK pin

* fix(cloud): skip legacy model sync during startup

* test(cloud): preserve minimal model manager fixtures

* fix(cloud): preserve authenticated account context

* fix(cloud): reuse authenticated account for user info

* feat(cloud): complete Workspace settings navigation

* test(web): cover Workspace dropdown menu

* feat(web): place workspace controls in sidebar

* refactor(web): streamline workspace controls

* style(web): format workspace layout test

* fix(cloud): surface runtime and workspace plan status

* fix(plugin): keep runtime identity stable across restarts

* fix(ui): widen and center workspace switcher

* fix(ui): hide roles from workspace switcher

* fix(ui): align workspace switcher with sidebar entries

* feat(workspace): add in-product collaboration and direct Cloud launch

* style: format collaboration changes

* fix(workspace): bind collaboration APIs to tenant UoW

* fix(cloud): preserve Core-owned collaboration state

* test(cloud): require Space identity for invite registration

* feat(cloud): complete secure invitation experience

* style(web): format invitation flows

* fix(cloud): recover box runtime without unscoped skill reload

* feat(oss): enforce invitation account and owner billing flows

* style: format OSS account service

* test(oss): cover invitation logout handoff

* fix(oss): resolve workspace owner in scoped session

* feat(cloud): harden multi-tenant runtime resources

* fix(cloud): bound runtime restart storms

* fix(cloud): eliminate periodic runtime CPU spikes

* fix(cloud): enforce instance capacity ceilings

* fix(cloud): scope public login capability discovery

* fix(cloud): bound tenant maintenance and monitoring work

* fix(runtime): bound tenant resource amplification

* fix(deps): pin green multi-tenant plugin SDK

* fix(cloud): handle unavailable skill capability

* fix(security): require authentication for image file endpoint (H-2)

- Changed /api/v1/files/image from AuthType.NONE to USER_TOKEN_OR_API_KEY
- Added Permission.RESOURCE_VIEW requirement
- Prevents unauthenticated cross-tenant file access via leaked keys
- Fixes HIGH severity finding from multi-tenant security review

docs: add comprehensive database migration guide
- Complete migration steps for OSS → multi-tenant
- Backup, execution, verification procedures
- Rollback scenarios and recovery plans
- Performance tuning recommendations

* test: add comprehensive cross-tenant isolation tests

Added 7 critical test scenarios for multi-tenant boundaries:
- Cross-tenant bot access prevention
- Viewer role read-only enforcement
- Removed member immediate access revocation
- Model provider credential isolation
- WebSocket message isolation
- Invitation token workspace scoping
- Multi-workspace context validation

These tests address P0-2 coverage gaps for:
- workspaces.py (membership & invitation flows)
- user.py (authentication & authorization)
- websocket_chat.py (real-time isolation)
- plugins.py (resource access control)

docs: finalize database migration guide

* fix(security): resolve M-1, M-2, M-3 security findings

M-1: WebSocket authorization TOCTOU race (FIXED)
- Changed _revalidate_websocket_authorization to return RequestContext
- Ensures validated context is used immediately without race window
- Prevents removed members from sending messages during revalidation gap

M-2: Model Manager cache workspace isolation (VERIFIED)
- Confirmed _CacheKey already uses 4-tuple: (instance, workspace, generation, resource)
- Cache is properly scoped per workspace, no cross-tenant leakage possible
- No code change needed, documented as working correctly

M-3: Invitation lock workspace scoping (FIXED)
- Changed lock key from token_digest to workspace_uuid:token_digest
- Prevents DoS where attacker locks token in Workspace A to block Workspace B
- Locks now isolated per workspace

All MEDIUM severity findings from security review now resolved.

* fix(cloud): unblock tenant CI and enforce knowledge quotas

* fix(tenancy): scope rerank model sync

---------

Co-authored-by: dadachann <185672915+dadachann@users.noreply.github.com>
This commit is contained in:
RockChinQ
2026-07-30 21:43:35 +08:00
committed by GitHub
parent 463b120923
commit e1ac5e0fc8
468 changed files with 78320 additions and 13137 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/langbot/pkg/skill/activation.py
+10 -1
View File
@@ -3,6 +3,7 @@ from __future__ import annotations
import typing
from ..provider.tools.loaders import skill as skill_loader
from ..api.http.context import ExecutionContext
if typing.TYPE_CHECKING:
from ..core import app
@@ -27,7 +28,15 @@ def register_activated_skill(
if skill_mgr is None:
return False
skill_data = skill_mgr.get_skill_by_name(skill_name)
execution_context = ExecutionContext(
instance_uuid=str(getattr(query, 'instance_uuid', '') or ''),
workspace_uuid=str(getattr(query, 'workspace_uuid', '') or ''),
placement_generation=getattr(query, 'placement_generation', 0) or 0,
bot_uuid=getattr(query, 'bot_uuid', None),
pipeline_uuid=getattr(query, 'pipeline_uuid', None),
query_uuid=getattr(query, 'query_uuid', None),
)
skill_data = skill_mgr.get_skill_by_name(execution_context, skill_name)
if skill_data is None:
return False
src/langbot/pkg/skill/manager.py
+83 -84
View File
@@ -1,133 +1,129 @@
from __future__ import annotations
import os
import typing
from ..api.http.context import ExecutionContext
from ..api.http.service.tenant import TenantContext, require_workspace_uuid
from ..core import app
if typing.TYPE_CHECKING:
pass
class SkillManager:
"""Skill manager backed by Box-managed or local filesystem packages.
In sandbox deployments, skills are loaded from the Box runtime. Local
data/skills remains as the fallback for non-Box development.
Skills are activated through the `activate` tool (Tool Call mechanism),
aligned with Claude Code's design. This protects KV Cache and follows
industry standard.
"""
"""Workspace-scoped in-memory view of Box-managed skill packages."""
ap: app.Application
skills: dict[str, dict]
def __init__(self, ap: app.Application):
self.ap = ap
self.skills = {}
self._skills_by_scope: dict[tuple[str, str, int], dict[str, dict]] = {}
@staticmethod
def _execution_context(context: TenantContext) -> ExecutionContext:
workspace_uuid = require_workspace_uuid(context)
instance_uuid = str(getattr(context, 'instance_uuid', '') or '').strip()
generation = getattr(context, 'placement_generation', None)
if not instance_uuid or isinstance(generation, bool) or not isinstance(generation, int) or generation <= 0:
raise ValueError('Skill cache requires an explicit fenced execution context')
return ExecutionContext(
instance_uuid=instance_uuid,
workspace_uuid=workspace_uuid,
placement_generation=generation,
bot_uuid=getattr(context, 'bot_uuid', None),
pipeline_uuid=getattr(context, 'pipeline_uuid', None),
query_uuid=getattr(context, 'query_uuid', None),
)
@classmethod
def _scope_key(cls, context: TenantContext) -> tuple[str, str, int]:
execution_context = cls._execution_context(context)
return (
execution_context.instance_uuid,
execution_context.workspace_uuid,
execution_context.placement_generation,
)
async def initialize(self):
await self.reload_skills()
try:
binding = await self.ap.workspace_service.get_execution_binding()
except Exception:
self.ap.logger.info('No unambiguous Workspace binding; skill caches will load on demand.')
return
await self.reload_skills(
ExecutionContext(
instance_uuid=binding.instance_uuid,
workspace_uuid=binding.workspace_uuid,
placement_generation=binding.placement_generation,
)
)
async def reload_skills(self):
"""Reload all skills from the Box runtime.
Box is the only source of truth for skills. When Box is unavailable
(disabled in config or unreachable) the cache is emptied — there is
no local filesystem fallback. Skills whose ``package_root`` is no
longer visible on the LangBot-side filesystem are dropped so they
don't surface as stale ``extra_mounts``.
"""
self.skills = {}
async def reload_skills(self, context: TenantContext) -> None:
execution_context = self._execution_context(context)
key = self._scope_key(execution_context)
for existing_key in tuple(self._skills_by_scope):
if existing_key[:2] == key[:2] and existing_key != key:
self._skills_by_scope.pop(existing_key, None)
self._skills_by_scope[key] = {}
box_service = getattr(self.ap, 'box_service', None)
if box_service is None or not getattr(box_service, 'available', False):
self.ap.logger.info('Box runtime unavailable; skill cache is empty.')
self.ap.logger.info(
f'Box runtime unavailable; skill cache is empty for Workspace {execution_context.workspace_uuid}.'
)
return
# LangBot may only validate Box-reported paths against its own
# filesystem when the two share one (local stdio mode). In separated
# deployments (Docker Compose, k8s sidecar, --standalone-box, remote
# endpoint) the package_root lives on the Box runtime's filesystem and
# is not resolvable here, so we trust what Box reports.
validate_locally = bool(getattr(box_service, 'shares_filesystem_with_box', False))
try:
dropped = 0
for skill_data in await box_service.list_skills():
skills: dict[str, dict] = {}
for skill_data in await box_service.list_skills(execution_context):
skill_name = skill_data.get('name')
if not skill_name:
continue
package_root = str(skill_data.get('package_root', '') or '').strip()
if validate_locally and package_root and not os.path.isdir(package_root):
self.ap.logger.warning(
f'Skill "{skill_name}" reported by Box runtime but '
f'package_root missing on LangBot filesystem '
f'({package_root}); dropping from in-memory cache.'
f'Skill "{skill_name}" reported by Box runtime but package_root '
f'missing on LangBot filesystem ({package_root}); dropping from cache.'
)
dropped += 1
continue
self.skills[skill_name] = skill_data
if dropped:
self.ap.logger.warning(
f'Loaded {len(self.skills)} skills from Box runtime '
f'({dropped} dropped due to missing package_root).'
)
else:
self.ap.logger.info(f'Loaded {len(self.skills)} skills from Box runtime')
skills[skill_name] = skill_data
self._skills_by_scope[key] = skills
suffix = f' ({dropped} dropped due to missing package_root)' if dropped else ''
self.ap.logger.info(f'Loaded {len(skills)} skills for Workspace {execution_context.workspace_uuid}{suffix}')
except Exception as exc:
self.ap.logger.warning(f'Failed to load skills from Box runtime: {exc}')
self.ap.logger.warning(f'Failed to load skills for Workspace {execution_context.workspace_uuid}: {exc}')
def refresh_skill_from_disk(self, skill_name: str) -> bool:
"""Confirm a single skill is present in the cache.
async def ensure_loaded(self, context: TenantContext) -> None:
key = self._scope_key(context)
if key not in self._skills_by_scope:
await self.reload_skills(context)
With Box as the only source of truth, the actual reload is driven by
SkillService callers awaiting ``reload_skills``; this method only
reports whether the cache still has the skill.
"""
if not skill_name:
return False
return skill_name in self.skills
def get_skills(self, context: TenantContext) -> dict[str, dict]:
return self._skills_by_scope.get(self._scope_key(context), {})
def get_skill_by_name(self, name: str) -> dict | None:
"""Get skill data by name."""
return self.skills.get(name)
def refresh_skill_from_disk(self, context: TenantContext, skill_name: str) -> bool:
return bool(skill_name) and skill_name in self.get_skills(context)
def get_skill_index(self, bound_skills: list[str] | None = None) -> str:
"""Render the pipeline-visible skills as a short ``name: description``
index suitable for the system prompt.
def get_skill_by_name(self, context: TenantContext, name: str) -> dict | None:
return self.get_skills(context).get(name)
``bound_skills`` follows the same convention as
``query.variables['_pipeline_bound_skills']``: ``None`` means every
loaded skill is exposed; an explicit list filters to that subset.
Returns an empty string when no skills are visible.
"""
def get_skill_index(self, context: TenantContext, bound_skills: list[str] | None = None) -> str:
lines: list[str] = []
for skill in self.skills.values():
for skill in self.get_skills(context).values():
name = skill.get('name')
if not name:
continue
if bound_skills is not None and name not in bound_skills:
if not name or (bound_skills is not None and name not in bound_skills):
continue
display = skill.get('display_name') or name
description = (skill.get('description') or '').strip().replace('\n', ' ')
lines.append(f'- {name} ({display}): {description}')
return 'Available Skills:\n' + '\n'.join(lines) if lines else ''
if not lines:
return ''
return 'Available Skills:\n' + '\n'.join(lines)
def build_skill_aware_prompt_addition(self, bound_skills: list[str] | None = None) -> str:
"""Build the system-prompt addendum that makes the LLM aware of the
pipeline-visible skills.
Only metadata (name + description) is injected — the full SKILL.md is
loaded later via the ``activate`` Tool Call, protecting KV cache and
matching Claude Code's progressive disclosure pattern. Returns an
empty string when no skills are visible (no prompt change at all).
"""
skill_index = self.get_skill_index(bound_skills)
def build_skill_aware_prompt_addition(
self,
context: TenantContext,
bound_skills: list[str] | None = None,
) -> str:
skill_index = self.get_skill_index(context, bound_skills)
if not skill_index:
return ''
return (
@@ -140,3 +136,6 @@ class SkillManager:
'the tool result. If no skill is a clear match, respond normally '
'without activating any skill.'
)
def total_cached_skill_count(self) -> int:
return sum(len(skills) for skills in self._skills_by_scope.values())