Path Traversal in PraisonAI (CVE-2026-47397)
Summary
Path traversal in PraisonAI (CVE-2026-47397). Risk of unauthorized operations or information disclosure. Exploitable via write_file. Mitigation: upgrade to 4.6.40 or later.
Original description
The description as published by the source.
PraisonAI is a multi-agent teams system. Prior to version 4.6.40, hidden metadata in a webpage causes PraisonAI agents to write attacker-controlled content to arbitrary paths. write_file skips path validation when workspace=None (always None in production). Version 4.6.40 fixes the issue.
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-2026-47397 has been found in PraisonAI.
Attackers can target a specific entry point like write_file over the network to misuse the product.
Risk of unauthorized operations or information disclosure.
What to do: upgrade PraisonAI to 4.6.40 or later.
If unsure, ask your IT team or search "PraisonAI CVE-2026-47397" on the vendor's site.
CVE-2026-47397 (PraisonAI) — CWE-22
Attack surface: write_file / None
Patched: 4.6.40 — apply immediately
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.
Path traversal (CWE-22) exists in PraisonAI. Attackers reach the vulnerable code path via write_file.
Check the vendor advisory for the affected versions of PraisonAI. Attack surface: write_file / None.
Severity: ?. Risk of unauthorized operations or information disclosure.
Update to 4.6.40.
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. Run grep -r 'PraisonAI' . 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
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1Identify exposure identify
grep -r 'PraisonAI' . | 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
PraisonAIを grep し、稼働しているサービス・バージョンを把握する。 -
2Apply patch patch
Upgrade PraisonAI to 4.6.40ステージング環境で 4.6.40 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスを含めること。
-
3Post-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。
Affected packages
References
- advisory github.com
- advisory github.com
- advisory nvd.nist.gov
- package github.com
- patch github.com
- patch github.com
- web github.com