Summary
Langflow: Unauthenticated Shareable Playground arbitrary local or S3 file read
The "Shareable Playground" (or "Public Flows" in code) contains a potential arbitrary file-read vulnerability, depending on the exact flow configuration used.
By making a flow public, public execution of the flow is allowed. The execution request can contain a list of files that gets read by Langflow and fed into the LLM.
The files path can be any path supported by the storage - it can be either a local file or S3 path if supported by the local configuration
Details
Shareable Playground feature works by enabling the execution of workflows by unauthenticated users, by accessing a link.
Specifically, it enables the route /api/v1/build_public_tmp to execute any public flow, given a public flow ID.
This request contains a files field that can contain a list of files. The files get read in LCModelComponent._get_chat_result in a call to to_lc_message. A detailed stacktrace:
...
File "/Users/ori/Work/research/langchain/langflow/src/backend/base/langflow/api/build.py", line 466, in build_vertices
vertex_build_response: VertexBuildResponse = await _build_vertex(vertex_id, graph, event_manager)
File "/Users/ori/Work/research/langchain/langflow/src/backend/base/langflow/api/build.py", line 324, in _build_vertex
vertex_build_result = await graph.build_vertex(
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/graph/base.py", line 1563, in build_vertex
await vertex.build(
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/vertex/base.py", line 770, in build
await step(user_id=user_id, event_manager=event_manager, **kwargs)
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/events/observability/lifecycle_events.py", line 95, in wrapper
result = await observed_method(self, *args, **kwargs)
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/vertex/base.py", line 411, in _build
await self._build_results(
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/vertex/base.py", line 640, in _build_results
result = await initialize.loading.get_instance_results(
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/interface/initialize/loading.py", line 76, in get_instance_results
return await build_component(params=custom_params, custom_component=custom_component)
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/interface/initialize/loading.py", line 299, in build_component
build_results, artifacts = await custom_component.build_results()
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py", line 1136, in build_results
return await self._build_with_tracing()
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py", line 1118, in _build_with_tracing
results, artifacts = await self._build_results()
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py", line 1163, in _build_results
result = await self._get_output_result(output)
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py", line 1238, in _get_output_result
result = await method() if inspect.iscoroutinefunction(method) else await asyncio.to_thread(method)
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/base/models/model.py", line 88, in text_response
result = await self.get_chat_result(
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/base/models/model.py", line 180, in get_chat_result
return await self._get_chat_result(
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/base/models/model.py", line 232, in _get_chat_result
messages.append(input_value.to_lc_message(self.name))
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/schema/message.py", line 184, in to_lc_message
file_contents = self.get_file_content_dicts(model_name)
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/schema/message.py", line 256, in get_file_content_dicts
content_dicts.append(create_image_content_dict(file, None, model_name))
File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/utils/image.py", line 96, in create_image_content_dict
...
This triggers Langflow to feed the file into the LLM as an Image. Reading the files back depends on the specific LLM configuration.
PoC
Reproduction:
- Create a new flow and add a Chat Input node to it
- Share the flow ("Shareable Playground")
- Access the public link with the browser developers tools open and execute the flow.
- Find the
/api/v1/build_public_tmproute and copy as cURL - Edit the
filesJSON field to point to any file.
Impact
Potential file read (local or S3) if shareable playground feature is used.
Ori Lahav
Security Researcher @ Rubrik Inc.
CVE-2026-48520 has a CVSS score of 6.1 (Medium). The vector is network-reachable, no privileges required, and user interaction required. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (1.10.0); upgrading removes the vulnerable code path.
Affected versions
Security releases
Kodem intelligence
Severity tells you how bad this could be in the worst case. It does not tell you whether you are exposed. Exploitability and impact are functions of runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A vulnerable package can sit in your dependency tree and never run.
Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter. Kodem's runtime-powered SCA identifies whether this CVE is reachable in your applications.
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Frequently Asked Questions
- What is CVE-2026-48520? CVE-2026-48520 is a medium-severity security vulnerability in langflow (pip), affecting versions < 1.10.0. It is fixed in 1.10.0.
- How severe is CVE-2026-48520? CVE-2026-48520 has a CVSS score of 6.1 (Medium). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
- Which versions of langflow are affected by CVE-2026-48520? langflow (pip) versions < 1.10.0 is affected.
- Is there a fix for CVE-2026-48520? Yes. CVE-2026-48520 is fixed in 1.10.0. Upgrade to this version or later.
- Is CVE-2026-48520 exploitable, and should I be worried? Whether CVE-2026-48520 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
- What actually determines whether CVE-2026-48520 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
- How do I fix CVE-2026-48520? Upgrade
langflowto 1.10.0 or later.