Vulnerability-Lookup

CNVD-2025-21546

Vulnerability from cnvd - Published: 2025-09-18

Title

Langflow远程代码执行漏洞

Description

Langflow是Langflow开源的一个用于构建多代理和 RAG 应用程序的可视化框架。 Langflow存在远程代码执行漏洞，攻击者可利用该漏洞发送精心编制的HTTP请求来执行任意代码。

Severity

高

Patch Name

Langflow远程代码执行漏洞的补丁

Patch Description

Langflow是Langflow开源的一个用于构建多代理和 RAG 应用程序的可视化框架。 Langflow存在远程代码执行漏洞，攻击者可利用该漏洞发送精心编制的HTTP请求来执行任意代码。目前，供应商发布了安全公告及相关补丁信息，修复了此漏洞。

Formal description

目前厂商已发布升级补丁以修复漏洞。补丁获取链接： https://github.com/langflow-ai/langflow/releases/tag/1.3.0

Reference

https://nvd.nist.gov/vuln/detail/CVE-2025-3248

Impacted products

Name
langflow langflow <1.3.0

Show details on source website

JSON

To clipboard

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    "cve": {
      "cveNumber": "CVE-2025-3248",
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  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2025-21546",
  "openTime": "2025-09-18",
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  "patchName": "Langflow\u8fdc\u7a0b\u4ee3\u7801\u6267\u884c\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "langflow langflow \u003c1.3.0"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2025-3248",
  "serverity": "\u9ad8",
  "submitTime": "2025-04-14",
  "title": "Langflow\u8fdc\u7a0b\u4ee3\u7801\u6267\u884c\u6f0f\u6d1e"
}

CVE-2025-3248 (GCVE-0-2025-3248)

Vulnerability from cvelistv5 – Published: 2025-04-07 14:22 – Updated: 2026-07-14 22:25

Title

Langflow < 1.3.0 Unauthenticated RCE via /api/v1/validate/code

Summary

Langflow versions prior to 1.3.0 are susceptible to code injection in the /api/v1/validate/code endpoint. A remote and unauthenticated attacker can send crafted HTTP requests to execute arbitrary code.

Severity

9.8 (Critical)


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

SSVC

Exploitation: active Automatable: yes Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-08-15 19:50 UTC

CWE

CWE-306 - Missing Authentication for Critical Function

Assigner

VulnCheck mitre root

References

5 references

URL	Tags
https://github.com/langflow-ai/langflow/pull/6911	issue-tracking
https://github.com/langflow-ai/langflow/releases/…	release-notes
https://www.horizon3.ai/attack-research/disclosur…	exploit
https://www.vulncheck.com/advisories/langflow-una…	third-party-advisory
https://www.cisa.gov/known-exploited-vulnerabilit…	government-resource

Impacted products

1 product

Vendor	Product	Version
langflow-ai	langflow	Affected: 0 , < 1.3.0 (semver) cpe:2.3:a:langflow:langflow::::::::

Credits

Naveen Sunkavally of Horizon3.ai

Show details on NVD website

JSON

To clipboard

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Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.