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CVE-2026-15974

6.5 · MEDIUM

SGLang contains an SSRF and local file read in the multimodal generation endpoint /v1/chat/completions due to unsanitized image_url, allowing access to internal metadata, secrets, and services.

Published Jul 30, 2026CWE-918EPSS 0.36%

Overview

CVE-2026-15974 is a medium-severity vulnerability. It was published on July 30, 2026 and has a CVSS 3.1 base score of 6.5 (MEDIUM).

This vulnerability has a CVSS 3.1 base score of 6.5, rated MEDIUM. It can be exploited remotely over the network. Some level of privileges is required for exploitation.

Technical description

SGLang contains an SSRF and local file read in the multimodal generation endpoint /v1/chat/completions due to unsanitized image_url, allowing access to internal metadata, secrets, and services.

Remediation

Check the references section for vendor advisories, patches, and mitigation guidance. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.

References

GitHubgithub.com/sgl-project/sglang/security/advisories/GHSA-x7w5-h7rp-gfp9Refthoughts.apoorvdayal.com/posts/sglang-disclosures/Refthoughts.apoorvdayal.com/posts/sglang-disclosures/

How CyberStrike helps

Frequently asked questions

What is CVE-2026-15974?

CVE-2026-15974 is a medium-severity vulnerability. It was published on July 30, 2026 and has a CVSS 3.1 base score of 6.5 (MEDIUM).

How severe is CVE-2026-15974?

This vulnerability has a CVSS 3.1 base score of 6.5, rated MEDIUM. It can be exploited remotely over the network. Some level of privileges is required for exploitation.

How do I fix or remediate CVE-2026-15974?

Check the references section for vendor advisories, patches, and mitigation guidance. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.

How can CyberStrike help with CVE-2026-15974?

CyberStrike is an open-source, AI-augmented pentesting engine. Rather than flag a version number, it tests whether an issue like CVE-2026-15974 is actually reachable in your own applications and APIs, then verifies each finding before reporting it. That tells you if the weakness is a real, exploitable risk in your environment or a false positive you can safely deprioritize.

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