Vulnerability-Lookup

CVE-2026-48520 (GCVE-0-2026-48520)

Vulnerability from cvelistv5 – Published: 2026-06-23 16:31 – Updated: 2026-06-24 14:19

Title

Langflow: Unauthenticated Shareable Playground arbitrary local or S3 file read

Summary

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.10.0, 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 This vulnerability is fixed in 1.10.0.

Severity

6.1 (Medium)


                        
                          CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:H/I:N/A:N

SSVC

Exploitation: poc Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-06-24 14:18 UTC

CWE

CWE-73 - External Control of File Name or Path

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7926 records in the last 180 days details

References

1 reference

URL	Tags
https://github.com/langflow-ai/langflow/security/…	x_refsource_CONFIRM

Impacted products

1 product

Vendor	Product	Version	CPE status
langflow-ai	langflow	Affected: < 1.10.0	guessed

Show details on NVD website

JSON

To clipboard

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FKIE_CVE-2026-48520

Vulnerability from fkie_nvd - Published: 2026-06-23 17:17 - Updated: 2026-10-26 11:10

Severity

6.1 (Medium) - CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:H/I:N/A:N

Summary

References

	URL	Tags
	security-advisories@github.com	https://github.com/langflow-ai/langflow/security/advisories/GHSA-rcjh-r59h-gq37	Exploit, Vendor Advisory
	134c704f-9b21-4f2e-91b3-4a467353bcc0	https://github.com/langflow-ai/langflow/security/advisories/GHSA-rcjh-r59h-gq37	Exploit, Vendor Advisory

Impacted products

	Vendor	Product	Version
	langflow	langflow	*

JSON

To clipboard

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          "product": "langflow",
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GHSA-RCJH-R59H-GQ37

Vulnerability from github – Published: 2026-06-16 17:36 – Updated: 2026-07-20 13:42

Summary

Langflow: Unauthenticated Shareable Playground arbitrary local or S3 file read

Details

Summary

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: 1. Create a new flow and add a Chat Input node to it 2. Share the flow ("Shareable Playground") 3. Access the public link with the browser developers tools open and execute the flow. 4. Find the /api/v1/build_public_tmp route and copy as cURL 5. Edit the files JSON 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.

Severity

6.1 (Medium)


                  
                    CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:H/I:N/A:N

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "langflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.10.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-48520"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-73"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-06-16T17:36:00Z",
    "nvd_published_at": "2026-06-23T17:17:01Z",
    "severity": "MODERATE"
  },
  "details": "### Summary\nThe \"Shareable Playground\" (or \"Public Flows\" in code) contains a potential arbitrary file-read vulnerability, depending on the exact flow configuration used.\n\nBy 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.\nThe 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\n\n### Details\nShareable Playground feature works by enabling the execution of workflows by unauthenticated users, by accessing a link.\nSpecifically, it enables the route `/api/v1/build_public_tmp` to execute any public flow, given a public flow ID.\nThis 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:\n```\n...\n  File \"/Users/ori/Work/research/langchain/langflow/src/backend/base/langflow/api/build.py\", line 466, in build_vertices\n    vertex_build_response: VertexBuildResponse = await _build_vertex(vertex_id, graph, event_manager)\n  File \"/Users/ori/Work/research/langchain/langflow/src/backend/base/langflow/api/build.py\", line 324, in _build_vertex\n    vertex_build_result = await graph.build_vertex(\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/graph/base.py\", line 1563, in build_vertex\n    await vertex.build(\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/vertex/base.py\", line 770, in build\n    await step(user_id=user_id, event_manager=event_manager, **kwargs)\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/events/observability/lifecycle_events.py\", line 95, in wrapper\n    result = await observed_method(self, *args, **kwargs)\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/vertex/base.py\", line 411, in _build\n    await self._build_results(\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/vertex/base.py\", line 640, in _build_results\n    result = await initialize.loading.get_instance_results(\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/interface/initialize/loading.py\", line 76, in get_instance_results\n    return await build_component(params=custom_params, custom_component=custom_component)\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/interface/initialize/loading.py\", line 299, in build_component\n    build_results, artifacts = await custom_component.build_results()\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py\", line 1136, in build_results\n    return await self._build_with_tracing()\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py\", line 1118, in _build_with_tracing\n    results, artifacts = await self._build_results()\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py\", line 1163, in _build_results\n    result = await self._get_output_result(output)\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py\", line 1238, in _get_output_result\n    result = await method() if inspect.iscoroutinefunction(method) else await asyncio.to_thread(method)\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/base/models/model.py\", line 88, in text_response\n    result = await self.get_chat_result(\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/base/models/model.py\", line 180, in get_chat_result\n    return await self._get_chat_result(\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/base/models/model.py\", line 232, in _get_chat_result\n    messages.append(input_value.to_lc_message(self.name))\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/schema/message.py\", line 184, in to_lc_message\n    file_contents = self.get_file_content_dicts(model_name)\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/schema/message.py\", line 256, in get_file_content_dicts\n    content_dicts.append(create_image_content_dict(file, None, model_name))\n  File \"/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/utils/image.py\", line 96, in create_image_content_dict\n    ...\n```\n\nThis triggers Langflow to feed the file into the LLM as an Image. Reading the files back depends on the specific LLM configuration.\n\n### PoC\nReproduction:\n1. Create a new flow and add a Chat Input node to it\n2. Share the flow (\"Shareable Playground\")\n3. Access the public link with the browser developers tools open and execute the flow.\n4. Find the `/api/v1/build_public_tmp` route and copy as cURL\n5. Edit the `files` JSON field to point to any file.\n\n### Impact\nPotential file read (local or S3) if shareable playground feature is used.\n\n\n\nOri Lahav\nSecurity Researcher @ Rubrik Inc.",
  "id": "GHSA-rcjh-r59h-gq37",
  "modified": "2026-07-20T13:42:32Z",
  "published": "2026-06-16T17:36:00Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/langflow-ai/langflow/security/advisories/GHSA-rcjh-r59h-gq37"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-48520"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/langflow-ai/langflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/langflow/PYSEC-2026-244.yaml"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Langflow: Unauthenticated Shareable Playground arbitrary local or S3 file read"
}

PYSEC-2026-244

Vulnerability from pysec - Published: 2026-06-23 17:17 - Updated: 2026-06-27 10:28

Details

Severity

6.1 (Medium)


                  
                    CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:H/I:N/A:N

Impacted products

Name	purl
langflow	pkg:pypi/langflow

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "ecosystem_specific": {},
      "package": {
        "ecosystem": "PyPI",
        "name": "langflow",
        "purl": "pkg:pypi/langflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.10.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "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",
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        "0.0.61",
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        "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",
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        "0.2.11",
        "0.2.12",
        "0.2.13",
        "0.2.2",
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        "0.2.4",
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        "1.8.3",
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      ]
    }
  ],
  "aliases": [
    "CVE-2026-48520",
    "GHSA-rcjh-r59h-gq37"
  ],
  "details": "Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.10.0, 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 This vulnerability is fixed in 1.10.0.",
  "id": "PYSEC-2026-244",
  "modified": "2026-06-27T10:28:49.331820Z",
  "published": "2026-06-23T17:17:01.367Z",
  "references": [
    {
      "type": "EVIDENCE",
      "url": "https://github.com/langflow-ai/langflow/security/advisories/GHSA-rcjh-r59h-gq37"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

WID-SEC-W-2026-1865

Vulnerability from csaf_certbund - Published: 2026-06-09 22:00 - Updated: 2026-06-09 22:00

Summary

Langflow: Schwachstelle ermöglicht Offenlegung von Informationen

Severity

Mittel

Scope

1 vulnerability in this advisory, including CVE-2026-48520.

CVE-2026-48520

Known affected: 1 product

Open the full advisory

Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.

Action not permitted

CVE-2026-48520 (GCVE-0-2026-48520)

FKIE_CVE-2026-48520

GHSA-RCJH-R59H-GQ37

Summary

Details

PoC

Impact

PYSEC-2026-244

WID-SEC-W-2026-1865

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Nomenclature

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