Vulnerability-Lookup

GHSA-MHRG-94VW-45C5

Vulnerability from github – Published: 2026-03-27 06:31 – Updated: 2026-03-29 15:33

Summary

Spring AI: Insufficient Validation causes SSRF when processing multimodal messages with user-supplied URLs

Details

Spring AI's spring-ai-bedrock-converse contains a Server-Side Request Forgery (SSRF) vulnerability in BedrockProxyChatModel when processing multimodal messages that include user-supplied media URLs. Insufficient validation of those URLs allows an attacker to induce the server to issue HTTP requests to unintended internal or external destinations.

This issue affects Spring AI: from 1.0.0 before 1.0.5, from 1.1.0 before 1.1.4.

Severity

8.6 (High)


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

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{
  "affected": [
    {
      "package": {
        "ecosystem": "Maven",
        "name": "org.springframework.ai:spring-ai-bedrock-converse"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "1.0.0-M5"
            },
            {
              "fixed": "1.0.5"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "Maven",
        "name": "org.springframework.ai:spring-ai-bedrock-converse"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "1.1.0-M1"
            },
            {
              "fixed": "1.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-22742"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-918"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-03-29T15:33:25Z",
    "nvd_published_at": "2026-03-27T06:16:37Z",
    "severity": "HIGH"
  },
  "details": "Spring AI\u0027s spring-ai-bedrock-converse\u00a0contains a Server-Side Request Forgery (SSRF) vulnerability in\u00a0BedrockProxyChatModel\u00a0when processing multimodal messages that include user-supplied media URLs. Insufficient validation of those URLs allows an attacker to induce the server to issue HTTP requests to unintended internal or external destinations.\n\nThis issue affects Spring AI: from 1.0.0 before 1.0.5, from 1.1.0 before 1.1.4.",
  "id": "GHSA-mhrg-94vw-45c5",
  "modified": "2026-03-29T15:33:25Z",
  "published": "2026-03-27T06:31:43Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22742"
    },
    {
      "type": "WEB",
      "url": "https://github.com/spring-projects/spring-ai/commit/a7d3223bc11a010b93fbc40a17fa9b68c52a8118"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/spring-projects/spring-ai"
    },
    {
      "type": "WEB",
      "url": "https://github.com/spring-projects/spring-ai/releases/tag/v1.0.5"
    },
    {
      "type": "WEB",
      "url": "https://github.com/spring-projects/spring-ai/releases/tag/v1.1.4"
    },
    {
      "type": "WEB",
      "url": "https://spring.io/security/cve-2026-22742"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Spring AI: Insufficient Validation causes SSRF when processing multimodal messages with user-supplied URLs"
}

CVE-2026-22742 (GCVE-0-2026-22742)

Vulnerability from cvelistv5 – Published: 2026-03-27 05:27 – Updated: 2026-05-10 13:03

Title

Server-Side Request Forgery in BedrockProxyChatModel via Unvalidated Media URL Fetching

Summary

Severity

8.6 (High)


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

SSVC

Exploitation: none Automatable: yes Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-03-27 19:24 UTC

CWE

CWE-918 - Server-Side Request Forgery (SSRF)

Assigner

vmware mitre root

References

1 reference

URL	Tags
https://spring.io/security/cve-2026-22742

Impacted products

1 product

Vendor	Product	Version
Spring	Spring AI	Affected: 1.0.0 , < 1.0.5 (custom) Affected: 1.1.0 , < 1.1.4 (custom)

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JSON

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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.