CVE-2026-41481: CWE-918: Server-Side Request Forgery (SSRF) in langchain-ai langchain-text-splitters
LangChain is a framework for building agents and LLM-powered applications. Prior to langchain-text-splitters 1.1.2, HTMLHeaderTextSplitter.split_text_from_url() validated the initial URL using validate_safe_url() but then performed the fetch with requests.get() with redirects enabled (the default). Because redirect targets were not revalidated, a URL pointing to an attacker-controlled server could redirect to internal, localhost, or cloud metadata endpoints, bypassing SSRF protections. The response body is parsed and returned as Document objects to the calling application code. Whether this constitutes a data exfiltration path depends on the application: if it exposes Document contents (or derivatives) back to the requester who supplied the URL, sensitive data from internal endpoints could be leaked. Applications that store or process Documents internally without returning raw content to the requester are not directly exposed to data exfiltration through this issue. This vulnerability is fixed in 1.1.2.
AI Analysis
Technical Summary
The vulnerability (CVE-2026-41481) affects langchain-text-splitters before version 1.1.2. The function HTMLHeaderTextSplitter.split_text_from_url() uses validate_safe_url() to check the initial URL but performs the HTTP fetch with requests.get() with redirects enabled by default. Redirect targets are not revalidated, enabling an attacker to supply a URL that redirects to internal, localhost, or cloud metadata endpoints, bypassing SSRF protections. The fetched response body is parsed into Document objects and returned to the application. If the application exposes these Document contents back to the requester, sensitive internal data could be leaked. Applications that do not expose Document contents to the requester are not directly impacted. The vulnerability is fixed in version 1.1.2.
Potential Impact
An attacker can exploit this SSRF vulnerability to cause the application to fetch data from internal or cloud metadata endpoints by supplying a malicious URL that redirects to these endpoints. This can lead to unauthorized disclosure of sensitive internal information if the application returns the fetched Document contents to the requester. There is no indication of integrity or availability impact. The severity is rated medium with a CVSS score of 6.5.
Mitigation Recommendations
This vulnerability is fixed in langchain-text-splitters version 1.1.2. Users should upgrade to version 1.1.2 or later to remediate the issue. There is no official remediation level stated beyond the fix. No additional mitigations are specified by the vendor advisory. Patch status is confirmed by the vendor advisory.
CVE-2026-41481: CWE-918: Server-Side Request Forgery (SSRF) in langchain-ai langchain-text-splitters
Description
LangChain is a framework for building agents and LLM-powered applications. Prior to langchain-text-splitters 1.1.2, HTMLHeaderTextSplitter.split_text_from_url() validated the initial URL using validate_safe_url() but then performed the fetch with requests.get() with redirects enabled (the default). Because redirect targets were not revalidated, a URL pointing to an attacker-controlled server could redirect to internal, localhost, or cloud metadata endpoints, bypassing SSRF protections. The response body is parsed and returned as Document objects to the calling application code. Whether this constitutes a data exfiltration path depends on the application: if it exposes Document contents (or derivatives) back to the requester who supplied the URL, sensitive data from internal endpoints could be leaked. Applications that store or process Documents internally without returning raw content to the requester are not directly exposed to data exfiltration through this issue. This vulnerability is fixed in 1.1.2.
CVSS v3.1
Score 6.5medium
Affected software
pkg:pypi/langchain-text-splittersRun on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
Weaknesses
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The vulnerability (CVE-2026-41481) affects langchain-text-splitters before version 1.1.2. The function HTMLHeaderTextSplitter.split_text_from_url() uses validate_safe_url() to check the initial URL but performs the HTTP fetch with requests.get() with redirects enabled by default. Redirect targets are not revalidated, enabling an attacker to supply a URL that redirects to internal, localhost, or cloud metadata endpoints, bypassing SSRF protections. The fetched response body is parsed into Document objects and returned to the application. If the application exposes these Document contents back to the requester, sensitive internal data could be leaked. Applications that do not expose Document contents to the requester are not directly impacted. The vulnerability is fixed in version 1.1.2.
Potential Impact
An attacker can exploit this SSRF vulnerability to cause the application to fetch data from internal or cloud metadata endpoints by supplying a malicious URL that redirects to these endpoints. This can lead to unauthorized disclosure of sensitive internal information if the application returns the fetched Document contents to the requester. There is no indication of integrity or availability impact. The severity is rated medium with a CVSS score of 6.5.
Mitigation Recommendations
This vulnerability is fixed in langchain-text-splitters version 1.1.2. Users should upgrade to version 1.1.2 or later to remediate the issue. There is no official remediation level stated beyond the fix. No additional mitigations are specified by the vendor advisory. Patch status is confirmed by the vendor advisory.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-04-20T16:14:19.006Z
- Cvss Version
- 3.1
- State
- PUBLISHED
- Remediation Level
- null
- Vendor Advisory Urls
- [{"url":"https://access.redhat.com/security/cve/CVE-2026-41481","vendor":"Red Hat"}]
Threat ID: 69ebdedf87115cfb68748361
Added to database: 04/24/2026, 21:21:35 UTC
Last enriched: 07/15/2026, 09:14:41 UTC
Last updated: 07/31/2026, 19:22:58 UTC
Views: 336
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