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CVE-2026-18904 – Sensitive Information Disclosure / Message Injection – Langflow OSS 1.0.0–1.11.1

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Summary

CVE-2026-18904 is an authorization bypass vulnerability (CWE-639, Authorization Bypass Through User-Controlled Key) affecting IBM Langflow OSS versions 1.0.0 through 1.11.1. A namespace collision between user identifiers in flow metadata allows a remote, unauthenticated attacker to read another user’s public-playground chat history and inject unauthorized messages into it. The flaw carries a CVSS v3.1 base score of 8.2 (High).

Technical details

  • Root cause: Flow metadata exposes owner user IDs, and a namespace collision between user identifiers allows one user’s identifier to be conflated with another’s within the public-playground chat mechanism.
  • Trigger conditions: An attacker interacts with a Langflow public-playground chat associated with a flow whose metadata leaks the owning user’s identifier.
  • Attack vector: Network-based, requires no authentication and no user interaction (AV:N/AC:L/PR:N/UI:N).
  • Impact: High confidentiality impact (attacker can read another user’s private chat history) and low integrity impact (attacker can inject unauthorized messages into that chat history); no availability impact.

Affected software

  • IBM Langflow OSS versions 1.0.0 through 1.11.1

Severity

  • CVSS v3.1 Base Score: 8.2 (High)
  • Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:N

Mitigation and recommended actions

  • Immediate: Upgrade Langflow OSS to version 1.11.2 or later, available via PyPI.
  • If immediate patching is not possible: No vendor-documented workaround exists for this issue; restrict network exposure of Langflow instances (particularly public-playground endpoints) until the upgrade can be applied, and review chat history logs for signs of unauthorized access.

How IONIX identifies potentially affected assets

IONIX matches the following signals against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Raw response body: <title>Langflow</title> followed by a <script src="./assets/index-*.js"> tag.

References

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How IONIX’s External Exposure Management Platform Detects and Validates
Zero-Days to Shrink MTTR

1

Map your entire attack surface (continously)

IONIX uses multi-factor discovery methods, including DNS analysis, certificate mapping, metadata inspection, and more, to automatically map every internet-facing asset across your environment. This includes cloud instances, third-party platforms, shadow IT, and even forgotten infrastructure that traditional tools miss.

2

Monitor for new CVEs

Dozens of threat intel feeds using agentic technology are continuously analyzed to detect the appearance of proof-of-concept code, exploit kits, and indicators of active targeting. IONIX goes further by applying AI to proactively evaluate whether emerging vulnerabilities are likely to be exploited, even before PoCs go public.

3

Identify Potential External Exposures

Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

Execute Exploit Validations

By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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  • Identification of potentially exposed assets to this CVE
  • Confirmation of verified exploitable assets
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