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GitHub0xblackash/cve-2026-55450

CVE-2026-55450

Advisory documenting CVE-2026-55450, an unauthenticated file upload flaw in Langflow, with impact analysis, detection references, and remediation guidance.

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CVE-2026-55450 — Langflow Security Advisory

ChatGPT Image Oct 8, 2026, 10_47_35 PM

Unauthenticated File Upload Vulnerability

CVE ID Research Platform


Overview

CVE-2026-55450 concerns a reported file-upload vulnerability affecting Langflow, an open-source platform for building AI-powered workflows.

An exposed upload endpoint may permit unauthenticated file uploads, potentially resulting in excessive disk consumption and disclosure of internal filesystem paths.

This repository documents the vulnerability, its potential impact, detection references, and recommended mitigation measures.


Vulnerability Details

AttributeDetails
CVE IDCVE-2026-55450
ProductLangflow
Affected versionsEarlier than 1.9.1, according to the referenced advisory
Fixed version1.9.1 or later
Attack vectorNetwork
AuthenticationNot required for the reported vulnerable endpoint
Potential impactDenial of service and information disclosure
Related weaknessesCWE-306, CWE-400, CWE-200

For authoritative information, consult the official GitHub Security Advisory.


Technical Details

The reported vulnerability involves the following API endpoint:

POST /api/v1/upload/{flow_id}

Insufficient authentication and upload restrictions may expose a deployment to unauthorized file uploads.

The potential consequences include:

  • Excessive disk consumption and service disruption.
  • Disclosure of internal filesystem paths through application responses.
  • Unauthorized access to functionality intended for authenticated users.

The existence of this endpoint alone does not confirm that a deployment is vulnerable. Version, configuration, and patch status must be verified.


Demo

CVE-2026-55450

Potential Impact

Denial of Service

Excessive file uploads can consume available storage resources and affect application availability.

Information Disclosure

Responses that expose internal filesystem paths may reveal implementation details useful for further security assessment.

Access Control Failure

An upload endpoint that does not enforce the required authentication and authorization controls may allow unauthorized operations.


Detection and Validation

Security teams should validate their Langflow deployments using authorized, non-destructive methods.

Recommended checks:

  1. Identify Langflow instances in the authorized asset inventory.
  2. Determine the installed software version.
  3. Compare the version and configuration against the official advisory.
  4. Review authentication, authorization, and upload-size restrictions.
  5. Confirm whether the vendor-recommended patch has been applied.

Detection References

  • Official GitHub Security Advisory
  • ProjectDiscovery Nuclei Detection Template
  • Langflow Source Repository

Automated detection results should be treated as indicators rather than definitive proof of vulnerability. Active testing must be restricted to systems for which explicit authorization has been granted.


Remediation

Recommended defensive measures:

  • Upgrade to Langflow 1.9.1 or a later supported release containing the applicable security fix.
  • Restrict public exposure of Langflow services and API endpoints.
  • Enforce authentication and authorization on upload operations.
  • Configure appropriate upload-size limits and storage quotas.
  • Review application logs for suspicious upload activity.
  • Monitor disk utilization and unexpected filesystem growth.
  • Ensure error responses do not disclose sensitive internal paths.

Where supported, review the max_file_size_upload setting and verify its effective value against the documentation for the deployed release.


References

  • GitHub Security Advisory
  • Langflow GitHub Repository
  • Nuclei Templates
  • CVE Program

Disclaimer

This repository is intended for defensive security research, vulnerability awareness, and authorized testing.

Do not test systems without permission. The author assumes no responsibility for damage or misuse resulting from unauthorized activity.


Security Research | Vulnerability Analysis | Defensive Validation

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