HighVulnerabilityLLM-specific

CVE-2026-19306: IBM Langflow OSS arbitrary file read through authenticated build request

Source: NVD(opens in a new tab)
Identifier: CVE-2026-19306
Published: September 4, 2026
Record updated: October 9, 2026

Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.5%

Summary

IBM Langflow OSS versions 1.0.0 through 1.11.2 let an authenticated attacker read arbitrary files from the server filesystem. The attacker supplies absolute paths or traversal sequences in the files parameter of a build request, and the file contents are embedded in the language model prompt and sent to the configured model endpoint. The LANGFLOW_RESTRICT_LOCAL_FILE_ACCESS=true setting was not enforced in the Chat Input to Message attachment pipeline, though it applied to other file-reading components.

Mitigation

The source does not state a fix yet. Check the original advisory for updates.

Details

Scores and exploitation

CVSS score: 7.7(high)
CVSS vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N
Attack vector: network
Attack complexity: low
Privileges required: low
User interaction: none
EPSS: 0.5%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 4, 2026.
Disclosure date: September 4, 2026

Weaknesses and techniques

Weakness (CWE): CWE-22
Attack pattern (CAPEC): CAPEC-126

Classification

Attack type: Data extraction,
Other
Attack sophistication: Trivial
AI component targeted: Plugin
Impact: Confidentiality
Labels: security,
privacy

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative. The source gives this advisory a description and no title, so the title above is a headline generated from the source text.

Original source: https://nvd.nist.gov/vuln/detail/CVE-2026-19306

First tracked: September 4, 2026 at 02:08 PM ET, from NVD/CVE Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 93% (self-assessed)

Summary

Mitigation

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