What is the CVSS score of EUVD-2026-58475?

EUVD-2026-58475 has a CVSS 3.1 base score of 9.1 (Critical). CVSS vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N. EPSS exploitation probability: 0.4%.

Which versions of IBM Langflow are affected by EUVD-2026-58475?

IBM Langflow OSS versions 1.0.0-1.9.6 lack brute-force protection on authentication, enabling attackers to compromise user accounts through repeated login attempts.. A patch is available.

How to fix or mitigate EUVD-2026-58475?

Within 24 hours, identify all IBM Langflow OSS deployments running versions 1.0.0 through 1.9.6 and isolate or disable internet-facing instances. Within 7 days, apply the vendor-released patch to all affected systems, prioritizing production deployments. Within 30 days, audit user passwords for compromise, implement account lockout policies, and deploy network-level rate limiting on authentication endpoints.

IBM Langflow EUVD-2026-58475

| CVE-2026-19297 CRITICAL

Improper Restriction of Excessive Authentication Attempts (CWE-307)

2026-08-13 ibm

GHSA-h6hj-8qx6-p2fm

Authentication Bypass IBM Langflow Oss

9.1

CVSS 3.1 · Vendor: ibm

Severity by source

Vendor (ibm) PRIMARY

9.1 CRITICAL

AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N

vuln.today AI

7.4 HIGH

Network, unauthenticated, no interaction, but success depends on guessing valid credentials so AC:H; account takeover yields C:H/I:H with no availability impact.

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

4.0 AV:N/AC:H/AT:N/PR:N/UI:N/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N

Primary rating from Vendor (ibm).

CVSS VectorVendor: ibm

Attack Vector

Network

Attack Complexity

Low

Privileges Required

None

User Interaction

None

Scope

Unchanged

Confidentiality

High

Integrity

High

Availability

None

Lifecycle Timeline

Analysis Generated

Aug 13, 2026 - 21:35 vuln.today

CVE Published

Aug 13, 2026 - 20:46 nvd

CRITICAL 9.1

DescriptionCVE.org

IBM Langflow OSS 1.0.0 through 1.9.6 could allow a remote attacker to obtain unauthorized access to user accounts due to improper restriction of excessive authentication attempts.

AnalysisAI

Account takeover in IBM Langflow OSS versions 1.0.0 through 1.9.6 is possible because the platform fails to limit repeated failed authentication attempts (CWE-307), letting remote attackers brute-force or credential-stuff their way into user accounts. IBM (the reporting vendor) rates it CVSS 9.1 with high confidentiality and integrity impact, reflecting full compromise of a targeted account. There is no public exploit identified at time of analysis and it is not listed in CISA KEV, but the missing lockout control is trivial to abuse against weak or reused credentials.

Technical ContextAI

Langflow is an open-source, Python-based low-code framework for building LLM/AI agent workflows, and its web application exposes an authentication endpoint for user accounts (CPE cpe:2.3:a:ibm:langflow_oss). The root cause is CWE-307, Improper Restriction of Excessive Authentication Attempts: the login flow does not enforce rate limiting, account lockout, exponential backoff, or CAPTCHA after repeated failures. This allows an attacker to submit an effectively unlimited number of username/password guesses, converting any weak, default, or previously-breached credential into a practical path to unauthorized access.

RemediationAI

Patch available per vendor advisory: upgrade to the fixed IBM Langflow OSS release referenced in IBM bulletin https://www.ibm.com/support/pages/node/7283558 (consult the bulletin for the exact patched version, as a specific fixed version number was not included in the provided data - do not rely on an assumed number). Until patched, apply compensating controls: place the Langflow login endpoint behind a reverse proxy or WAF that enforces per-IP and per-account rate limiting and temporary lockout after repeated failures; require strong, unique passwords and enable multi-factor authentication or SSO to blunt brute-force and credential-stuffing (trade-off: added login friction and configuration effort); and restrict network exposure of the Langflow UI/API to trusted networks or a VPN rather than the public internet (trade-off: reduces convenience of remote access). Monitor authentication logs for high-volume failed-login patterns as a detection layer.