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CVE-2026-18618 high CVSS 7.5

Vulnerability in ml-metadata (CVE-2026-18618)

Summary

Vulnerability in ml-metadata (CVE-2026-18618). Risk of unauthorized operations or information disclosure.

Original description

The description as published by the source.

A flaw was found in ml-metadata. The statically-linked gRPC stack in ml-metadata is outdated, making it vulnerable to known HTTP/2 denial of service (DoS) issues. An in-cluster attacker, with network access to the MLMD pod, could exploit these vulnerabilities by sending specially crafted HTTP/2 requests. This could lead to a denial of service by crashing the MLMD pod, disrupting all pipeline runs in the affected namespace.

Source: GitHub Security Advisories (Global) NVD GitHub Advisory

Auto-generated summary

Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.

A vulnerability tracked as CVE-2026-18618 has been found in ml-metadata.
Risk of unauthorized operations or information disclosure. CVSS score: 7.5/10.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "ml-metadata CVE-2026-18618" on the vendor's site.

CVE-2026-18618 (ml-metadata) — CWE-770 / CVSS v3 7.5
Attack vector: remote (network-reachable) / unauthenticated / no user interaction
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.

❓ What is the problem

A vulnerability (CWE-770) exists in ml-metadata.

📍 Affected scope

Check the vendor advisory for the affected versions of ml-metadata.

🔥 Severity

Severity: High (CVSS 7.5/10). Risk of unauthorized operations or information disclosure.

🔧 How to fix

Update to the patched release per vendor advisory.

🛡️ Workaround

Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.

🔍 Detection

Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'ml-metadata' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.

Response actions

Concrete steps and command examples for SOC/SRE teams to execute in order

  1. 1
    Identify exposure identify 
    grep -r 'ml-metadata' . | grep -v node_modules

    リポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で ml-metadata を grep し、稼働しているサービス・バージョンを把握する。

  2. 2
    Post-deployment verification verify 
    Confirm patched version is live in production

    パッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。

References

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