PraisonAI Platform's multi-tenant project API contains an Insecure Direct Object Reference flaw where all four project endpoints — read, update, delete, and stats — gate access on workspace membership alone but perform resource lookups using only the project UUID, with no workspace-scoping predicate. Any authenticated tenant can read confidential AI agent project configurations, silently overwrite or archive projects, and permanently delete resources belonging to other workspaces by substituting a known project UUID into the URL path. With CVSS 8.1 (High) and no privileges beyond a basic workspace token required, exploitation is trivial — project UUIDs leak routinely via activity feeds, webhook payloads, and issue exports, so enumeration is accessible to any tenant on a shared deployment. Upgrade to praisonai-platform 0.1.4 immediately; if patching is blocked, restrict API routes at the network perimeter and audit logs for cross-workspace project UUID access patterns.
What is the risk?
High risk in any multi-tenant PraisonAI deployment. Exploitation requires only a valid workspace membership token and a known target project UUID — both low barriers in a shared environment where UUIDs routinely surface in application data. No public exploit code or scanner template exists yet, but the exploit chain is fully described in the advisory and reproducible in minutes. The CVSS 8.1 reflects network-accessible, low-complexity exploitation with high confidentiality and integrity impact across all tenants. AI agent projects typically contain operationally sensitive context — roadmaps, agent configurations, lead assignments — amplifying business impact well beyond a standard IDOR. The parallel gap identified in AgentService, IssueService, CommentService, and LabelService suggests a systemic authorization design defect rather than a one-off oversight.
Attack Kill Chain
What systems are affected?
| Package | Ecosystem | Vulnerable Range | Patched |
|---|---|---|---|
| praisonai-platform | pip | < 0.1.4 | 0.1.4 |
Do you use praisonai-platform? You're affected.
Severity & Risk
Attack Surface
What should I do?
6 steps-
Patch immediately: upgrade praisonai-platform to 0.1.4, which scopes all project lookups to the authenticated workspace using a composite (workspace_id, project_id) WHERE predicate.
-
If patching is blocked, restrict /workspaces/*/projects/* API routes to trusted internal IP ranges at the reverse proxy or WAF layer.
-
Audit API access logs for requests where the workspace_id in the URL path does not correspond to the project's actual workspace — these anomalies indicate active exploitation.
-
Review activity and audit logs for unexpected project reads, modifications, or deletions across workspace boundaries.
-
If compromise is suspected, notify affected tenant workspace owners and assess whether project UUIDs need rotation.
-
Apply the same workspace-scoped lookup fix to AgentService, IssueService, CommentService, and LabelService, which the advisory explicitly identifies as carrying the identical structural gap.
Classification
Compliance Impact
This CVE is relevant to:
Frequently Asked Questions
What is CVE-2026-47418?
PraisonAI Platform's multi-tenant project API contains an Insecure Direct Object Reference flaw where all four project endpoints — read, update, delete, and stats — gate access on workspace membership alone but perform resource lookups using only the project UUID, with no workspace-scoping predicate. Any authenticated tenant can read confidential AI agent project configurations, silently overwrite or archive projects, and permanently delete resources belonging to other workspaces by substituting a known project UUID into the URL path. With CVSS 8.1 (High) and no privileges beyond a basic workspace token required, exploitation is trivial — project UUIDs leak routinely via activity feeds, webhook payloads, and issue exports, so enumeration is accessible to any tenant on a shared deployment. Upgrade to praisonai-platform 0.1.4 immediately; if patching is blocked, restrict API routes at the network perimeter and audit logs for cross-workspace project UUID access patterns.
Is CVE-2026-47418 actively exploited?
No confirmed active exploitation of CVE-2026-47418 has been reported, but organizations should still patch proactively.
How to fix CVE-2026-47418?
1. Patch immediately: upgrade praisonai-platform to 0.1.4, which scopes all project lookups to the authenticated workspace using a composite (workspace_id, project_id) WHERE predicate. 2. If patching is blocked, restrict /workspaces/*/projects/* API routes to trusted internal IP ranges at the reverse proxy or WAF layer. 3. Audit API access logs for requests where the workspace_id in the URL path does not correspond to the project's actual workspace — these anomalies indicate active exploitation. 4. Review activity and audit logs for unexpected project reads, modifications, or deletions across workspace boundaries. 5. If compromise is suspected, notify affected tenant workspace owners and assess whether project UUIDs need rotation. 6. Apply the same workspace-scoped lookup fix to AgentService, IssueService, CommentService, and LabelService, which the advisory explicitly identifies as carrying the identical structural gap.
What systems are affected by CVE-2026-47418?
This vulnerability affects the following AI/ML architecture patterns: AI agent platforms, multi-tenant SaaS deployments, agent orchestration frameworks, agentic workflow management systems.
What is the CVSS score for CVE-2026-47418?
CVE-2026-47418 has a CVSS v3.1 base score of 8.1 (HIGH).
AI Security Impact
Affected AI Architectures
MITRE ATLAS Techniques
AML.T0007 Discover AI Artifacts AML.T0012 Valid Accounts AML.T0025 Exfiltration via Cyber Means AML.T0036 Data from Information Repositories AML.T0049 Exploit Public-Facing Application Compliance Controls Affected
Technical Details
Original Advisory
## Summary **Type:** Insecure Direct Object Reference. The project CRUD endpoints (`GET / PATCH / DELETE /workspaces/{workspace_id}/projects/{project_id}` and `GET .../{project_id}/stats`) gate access on `require_workspace_member(workspace_id)` only, then resolve `project_id` through `ProjectService.get(project_id)` / `update(project_id, ...)` / `delete(project_id)` / `get_stats(project_id)`. None of these calls thread `workspace_id` through to constrain the lookup. A user who is a member of any workspace `W1` can read, modify, delete, or read stats for projects that belong to a different workspace `W2`. **File:** `src/praisonai-platform/praisonai_platform/services/project_service.py`, lines 47-108; route handlers at `src/praisonai-platform/praisonai_platform/api/routes/projects.py`, lines 51-108. **Root cause:** identical to the agent and issue IDORs in this codebase. The route accepts `workspace_id` from URL, uses it solely for the membership gate, then calls `ProjectService.get(project_id)` which is `session.get(Project, project_id)` — a primary-key-only lookup with no `workspace_id` predicate. `update` and `delete` call `self.get(project_id)` first, inheriting the gap. `get_stats` likewise has no workspace check. ## Affected Code **File 1:** `src/praisonai-platform/praisonai_platform/services/project_service.py`, lines 47-108. ```python class ProjectService: ... async def get(self, project_id: str) -> Optional[Project]: """Get project by ID.""" return await self._session.get(Project, project_id) # <-- BUG: no workspace_id predicate async def update( self, project_id: str, ... ) -> Optional[Project]: project = await self.get(project_id) # <-- inherits the gap ... async def delete(self, project_id: str) -> bool: project = await self.get(project_id) # <-- inherits the gap ... async def get_stats(self, project_id: str) -> dict: ... # <-- also no workspace check; returns issue counts for any project ``` **File 2:** `src/praisonai-platform/praisonai_platform/api/routes/projects.py`, lines 51-108. ```python @router.get("/{project_id}", response_model=ProjectResponse) async def get_project( workspace_id: str, project_id: str, user: AuthIdentity = Depends(require_workspace_member), session: AsyncSession = Depends(get_db), ): svc = ProjectService(session) project = await svc.get(project_id) # <-- workspace_id never threaded through if project is None: raise HTTPException(status_code=404, detail="Project not found") return ProjectResponse.model_validate(project) @router.patch("/{project_id}", response_model=ProjectResponse) async def update_project(...): svc = ProjectService(session) project = await svc.update(project_id, title=body.title, ...) # <-- writes to any project in the DB @router.delete("/{project_id}", ...) async def delete_project(...): deleted = await svc.delete(project_id) # <-- deletes any project in the DB @router.get("/{project_id}/stats") async def project_stats(...): return await svc.get_stats(project_id) # <-- returns stats for any project in the DB ``` **Why it's wrong:** `workspace_id` from the route is treated as a UI hint (gates "are you in some workspace W?") rather than an authoritative predicate (should also gate "is the project you are addressing actually inside W?"). The `MemberService` in this same codebase uses a composite `(workspace_id, user_id)` key and demonstrates the safe pattern; the project service simply did not apply it. ## Exploit Chain 1. Attacker registers a workspace `W_attacker` (where they are a member) and harvests a target project UUID `P_T`. Project IDs leak through the activity feed (`act_svc.log` records `entity_id`), issue records (every issue carries `project_id`), webhook payloads, error messages, exported issue dumps, or operator screenshots. State: attacker holds `P_T`. 2. Attacker authenticates and sends `GET /workspaces/W_attacker/projects/P_T`. `require_workspace_member(W_attacker, attacker)` passes. State: control flow enters `get_project` with `workspace_id=W_attacker, project_id=P_T`. 3. `ProjectService.get(P_T)` runs `session.get(Project, "P_T")`, which is `SELECT * FROM projects WHERE id = 'P_T' LIMIT 1` with no `workspace_id` filter. The row is returned: `title`, `description` (often the project's confidential roadmap), `status`, `lead_type`, `lead_id`, `icon`, `created_at`, `workspace_id` (the foreign workspace's UUID is itself disclosed). State: response body is the JSON-serialised foreign project. 4. Attacker repeats with `PATCH /workspaces/W_attacker/projects/P_T` and `{"title": "<reset>", "description": "<wiped>", "status": "archived"}`. `update_project` calls `svc.update(P_T, ...)` and mutates the foreign row. State: target project is silently re-titled, re-described, and archived. 5. Attacker calls `DELETE /workspaces/W_attacker/projects/P_T` to delete the foreign project entirely. State: target project is gone (every issue still referencing it now has a dangling `project_id`). 6. Attacker calls `GET /workspaces/W_attacker/projects/P_T/stats` to read aggregate issue counts (open/closed/in-progress) for the foreign project — useful for competitive intelligence even when full-issue read is not possible. 7. Final state: any attacker with one workspace-member token can enumerate, exfiltrate, rewrite, and delete every project in the multi-tenant deployment given the project UUIDs. ## Security Impact **Severity:** sec-high. CVSS: network attack, low complexity, low privileges, no user interaction, scope unchanged, high confidentiality (project content + cross-workspace metadata via the leaked `workspace_id` field), high integrity (arbitrary writes / deletes), no availability claim (issue rows survive parent-project deletion). **Attacker capability:** read, edit, archive, delete, and stats-fingerprint any project in the multi-tenant deployment given the project UUID. Beyond plain content disclosure, the response also includes `workspace_id`, allowing the attacker to map the deployment's workspace topology (which workspaces exist, which projects each owns). **Preconditions:** `praisonai-platform` is deployed multi-tenant; the attacker has any membership token; the target project's UUID is known or guessable. **Differential:** source-inspection-verified end-to-end. The asymmetry between `ProjectService.get(project_id)` (no workspace check) and `MemberService.get(workspace_id, user_id)` (composite key check) confirms the gap. With the suggested fix below, `ProjectService.get(workspace_id, project_id)` returns `None` for foreign-workspace projects and the route handler returns 404. ## Suggested Fix Same shape as the companion agent and issue advisories. Make the resource-lookup query include the workspace predicate; treat foreign-workspace rows as 404. ```diff --- a/src/praisonai-platform/praisonai_platform/services/project_service.py +++ b/src/praisonai-platform/praisonai_platform/services/project_service.py @@ -45,9 +45,12 @@ class ProjectService: await self._session.flush() return project - async def get(self, project_id: str) -> Optional[Project]: - """Get project by ID.""" - return await self._session.get(Project, project_id) + async def get(self, workspace_id: str, project_id: str) -> Optional[Project]: + """Get project by ID, scoped to a workspace.""" + stmt = select(Project).where( + Project.id == project_id, Project.workspace_id == workspace_id + ) + return (await self._session.execute(stmt)).scalar_one_or_none() async def update( self, + workspace_id: str, project_id: str, ... ) -> Optional[Project]: - project = await self.get(project_id) + project = await self.get(workspace_id, project_id) - async def delete(self, project_id: str) -> bool: + async def delete(self, workspace_id: str, project_id: str) -> bool: - project = await self.get(project_id) + project = await self.get(workspace_id, project_id) - async def get_stats(self, project_id: str) -> dict: + async def get_stats(self, workspace_id: str, project_id: str) -> dict: + # Also constrain the underlying issue counts query by workspace_id. ``` Update the route handlers in `routes/projects.py` to thread `workspace_id` through every call. The same single-key-lookup pattern is filed separately for `AgentService`, `IssueService`, `CommentService`, and `LabelService`.
Exploitation Scenario
An attacker operating a competing organization signs up for a free account on a shared PraisonAI SaaS deployment and joins or creates their own workspace. Over several days they passively collect project UUIDs from their own activity feed, webhook notifications, and issue export files — these routinely expose project_id values from server-side cross-workspace logs. The attacker then issues authenticated GET requests substituting harvested project UUIDs against their own workspace_id path segment, reading confidential AI agent project configurations and roadmap descriptions belonging to enterprise customers. They follow up with PATCH requests to silently corrupt high-value competitor projects by overwriting titles and descriptions, then DELETE requests to permanently destroy them before the incident is detected — all while the authorization layer reports success because the attacker holds a valid workspace membership token.
Weaknesses (CWE)
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N References
Timeline
Related Vulnerabilities
CVE-2026-47392 9.9 praisonaiagents: RCE via Python sandbox bypass
Same package: praisonai GHSA-vc46-vw85-3wvm 9.8 PraisonAI: RCE via malicious workflow YAML execution
Same package: praisonai CVE-2026-39890 9.8 PraisonAI: YAML deserialization enables unauthenticated RCE
Same package: praisonai GHSA-9qhq-v63v-fv3j 9.8 PraisonAI: RCE via MCP command injection
Same package: praisonai CVE-2026-47410 9.8 praisonai-platform: hardcoded JWT → full account takeover
Same package: praisonai