Vulnerability in FastGPT (CVE-2026-54601)
Summary
Vulnerability in FastGPT (CVE-2026-54601). Risk of unauthorized operations or information disclosure. Exploitable via POST /api/core/dataset/collection/create/reTrainingCollection.
Original description
The description as published by the source.
FastGPT is an open source AI knowledge base platform. From 4.14.17 to before 4.15.0-beta4, FastGPT allows an authenticated tenant user to call POST /api/core/dataset/collection/create/reTrainingCollection in a way that persists a server-owned datasetId value from another tenant. This creates mixed dataset objects and downstream dataset, collection, and training endpoints then make authorization decisions from inconsistent ownership anchors, allowing cross-tenant read, update, and delete access when mixed object ids are known. This issue is fixed in version 4.15.0-beta4.
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-2026-54601 has been found in FastGPT.
Attackers can target a specific entry point like POST /api/core/dataset/collection/create/reTrainingCollection over the network to misuse the product.
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 "FastGPT CVE-2026-54601" on the vendor's site.
CVE-2026-54601 (FastGPT) — CWE-915 / CVSS v3 6.3
Attack vector: remote (network-reachable) / no user interaction
Attack surface: POST /api/core/dataset/collection/create/reTrainingCollection
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-915) exists in FastGPT. Attackers reach the vulnerable code path via POST /api/core/dataset/collection/create/reTrainingCollection.
Check the vendor advisory for the affected versions of FastGPT. Attack surface: POST /api/core/dataset/collection/create/reTrainingCollection.
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 POST /api/core/dataset/collection/create/reTrainingCollection requests with malformed payloads or SQL meta-characters. Run grep -r 'FastGPT' . 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
-
1Identify exposure identify
grep -r 'FastGPT' . | 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
FastGPTを grep し、稼働しているサービス・バージョンを把握する。 -
2Hunt for indicators of compromise detect
grep 'POST /api/core/dataset/collection/create/reTrainingCollection' /var/log/nginx/access.log | grep -E '(unusual_payload|sqli_pattern)'アクセスログで
POST /api/core/dataset/collection/create/reTrainingCollectionへの異常なリクエスト (不正な認証ヘッダ・SQLメタ文字)を過去 30〜90日分捜索。WAF/SIEM があれば該当パスのアラート発火履歴を確認。 -
3Post-deployment verification verify
Replay attack against POST /api/core/dataset/collection/create/reTrainingCollection on staging to confirm patch closes the vector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 Step 2 と同じログクエリでアラート再発が無いか継続監視。
References
- advisory github.com
- advisory github.com
- advisory nvd.nist.gov
- patch github.com
- patch github.com
- web github.com