Cyber Resilience

CVE-2026-26019

SSRF in Langchain Community ≤ 1.1.14

Published
11 February 2026
Modified
19 February 2026
Patch / advisory
CVSS Score v3.1 4.1
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:N/A:N
EPSS Score 0.0037 30th percentile
Risk Priority 33 floored blend · peak EPSS

Summary

CVE-2026-26019 is a medium-severity SSRF (CWE-918) vulnerability in Langchain Langchain Community. Its CVSS base score is 4.1 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 30th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as NLP and Transformers; in the Supply Chain and Deployment risk domain.

The strongest mitigations our analysis identified map to AC-4 (Information Flow Enforcement) and SI-10 (Information Input Validation) — see the control section below for these in your framework.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

LangChain is a framework for building LLM-powered applications. Prior to 1.1.14, the RecursiveUrlLoader class in @langchain/community is a web crawler that recursively follows links from a starting URL. Its preventOutside option (enabled by default) is intended to restrict crawling to…

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the same site as the base URL. The implementation used String.startsWith() to compare URLs, which does not perform semantic URL validation. An attacker who controls content on a crawled page could include links to domains that share a string prefix with the target, causing the crawler to follow links to attacker-controlled or internal infrastructure. Additionally, the crawler performed no validation against private or reserved IP addresses. A crawled page could include links targeting cloud metadata services, localhost, or RFC 1918 addresses, and the crawler would fetch them without restriction. This vulnerability is fixed in 1.1.14.

CWE(s)

AI Security AnalysisAI

AI Category
NLP and Transformers
Risk Domain
Supply Chain and Deployment
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Matched keywords: langchain, llm

Related Threats

MITRE ATT&CK Enterprise Techniques

T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2026-27795Same product: Langchain Langchain Community
CVE-2026-41481Same vendor: Langchain
CVE-2025-2828Same vendor: Langchain
CVE-2026-26013Same vendor: Langchain
CVE-2026-41488Same vendor: Langchain
CVE-2024-2057Same vendor: Langchain
CVE-2024-0243Same vendor: Langchain
CVE-2023-46229Same vendor: Langchain
CVE-2024-3095Same vendor: Langchain
CVE-2026-34070Same vendor: Langchain

Affected Assets

langchain
langchain community
≤ 1.1.14

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

Detect
Catch it (NIST detect / respond)

Harden
Shrink the surface (DISA STIG)

Validate
Prove the fix (OWASP ASVS)
  • V1.3.6
  • V1.5.3
  • V5.3.2
  • V10.4.7

Mitigating Controls (NIST 800-53 r5) AI

Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.

Input validation directly stops untrusted URLs from being accepted and fetched without destination checks.

Boundary protection limits the network reach of server-initiated requests even if SSRF occurs.

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.

PR.PS-06 mostly match
prevents

Secure development practices directly include input validation and destination allow-listing that prevent SSRF.

DE.CM-09 partial match
prevents

Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.

ID.RA-01 partial match
prevents

Vulnerability identification processes can discover and record SSRF flaws in web applications.

PR.IR-01 partial match
prevents

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.

prevents

Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.

References