Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:NSummary
CVE-2026-7754 is a high-severity SSRF (CWE-918) vulnerability in Langflow Langflow. Its CVSS base score is 7.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 10th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to AC-4 (Information Flow Enforcement) and SC-7 (Boundary Protection) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-45286
Vulnerability Data
IBM Langflow OSS 1.0.0 through 1.10.0 Langflow 1.9.0 could allow server-side request forgery (SSRF) due to insecure default configuration and incomplete enforcement of the SSRF protection mechanism.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
SSRF vulnerability in public-facing Langflow web application directly enables exploitation of the app for initial access.
Likely ATT&CK TechniquesAI
Techniques this vulnerability likely enables, inferred from its description, weakness type, and attributed-actor tradecraft. Confidence is per-technique.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Enforces information flow policies to block the application from initiating unauthorized outbound requests to internal or external resources, directly mitigating the SSRF weakness.
Implements boundary protection mechanisms that restrict server-initiated network connections, addressing the incomplete SSRF protection and insecure defaults allowing arbitrary requests.
Requires validation of URL and request inputs to reject malformed or internal-targeting values that enable SSRF exploitation in Langflow.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure development practices directly include input validation and destination allow-listing that prevent SSRF.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Network segmentation and egress controls can limit the damage from successful SSRF requests.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.