Vulnerability in FedML-AI FedML (CVE-2026-90614)
Summary
Vulnerability in FedML-AI FedML (CVE-2026-90614). Risk of unauthorized operations or information disclosure.
Original description
The description as published by the source.
A weakness has been identified in FedML-AI FedML up to 0.9.6. Affected by this issue is the function S3Storage.read_model of the file fedml/core/distributed/communication/s3/remote_storage.py of the component MQTT+S3 Communication Backend. This manipulation of the argument s3_key_str causes deserialization. Remote exploitation of the attack is possible. The project was informed of the problem early through an issue report but has not responded yet.
Source: NIST National Vulnerability Database 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-2026-90614 has been found in FedML-AI FedML.
Risk of unauthorized operations or information disclosure. CVSS score: 6.3/10.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "FedML-AI FedML CVE-2026-90614" on the vendor's site.
CVE-2026-90614 (FedML-AI FedML) — CWE-20 / CVSS v3 6.3
Attack vector: remote (network-reachable) / 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.
A vulnerability (CWE-20) exists in FedML-AI FedML.
Check the vendor advisory for the affected versions of FedML-AI FedML.
Severity: Medium (CVSS 6.3/10). Risk of unauthorized operations or information disclosure.
Update to the patched release per vendor advisory.
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Audit SBOM/dependencies to find affected services.
Response actions
Concrete steps and command examples for SOC/SRE teams to execute in order
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1Identify exposure identify
Audit SBOM/dependencies for affected components.資産台帳・SBOM・依存マニフェストで FedML-AI FedML を使っているサービスとバージョンを洗い出す。
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2Post-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
- web cna@vuldb.com
- web github.com
- web vuldb.com
- web vuldb.com
- web vuldb.com
- web vuldb.com
- web nvd.nist.gov
- web github.com
- web github.com