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CVE-2026-47392
critical
CVSS 9.9
Vulnerability in praisonaiagents (CVE-2026-47392)
Summary
vulnerability in praisonaiagents (CVE-2026-47392). Successful exploitation can lead to full system takeover. Exploitable via ``print.__self__``. Mitigation: upgrade to `1.6.40` or later.
AI summary snake-internal / snake-material-v2
A vulnerability tracked as **CVE-2026-47392** has been found in praisonaiagents.
Attackers can target a specific entry point like ``print.__self__`` over the network to misuse the product.
Successful exploitation can lead to full system takeover. CVSS score: 9.9/10.
What to do: upgrade praisonaiagents to **1.6.40** or later.
If unsure, ask your IT team or search "praisonaiagents CVE-2026-47392" on the vendor's site.
CVE-2026-47392 (praisonaiagents) — CWE-184 / CVSS v3 9.9
Attack vector: remote (network-reachable) / no user interaction
Attack surface: `print.__self__` / `builtins` / `__import__` / `type.__getattribute__`
Patched: `1.6.40` — 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.
❓ What is the problem
**A vulnerability** (CWE-184) exists in praisonaiagents. Attackers reach the vulnerable code path via ``print.__self__`` without authentication.
📍 Affected scope
praisonaiagents — . Attack surface: `print.__self__` / `builtins` / `__import__` / `type.__getattribute__`.
🔥 Severity
Severity: Critical (CVSS 9.9/10). Successful exploitation can lead to full system takeover
🔧 How to fix
Update to **1.6.40**.
🛡️ 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 'praisonaiagents' .` against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response Actions (7 steps)
Concrete steps and command examples for SOC/SRE teams to execute in order
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1Identify exposure identify
grep -r 'praisonaiagents' . | 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 `praisonaiagents` を grep し、稼働しているサービス・バージョンを把握する。
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6Apply patch patch
Upgrade praisonaiagents to 1.6.40ステージング環境で 1.6.40 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と、Step 3 で見つけた異常検知の続報チェックを含めること。
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7Post-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 Step 3 と同じログクエリでアラート再発が無いか継続監視。
Affected packages
pip
praisonaiagents
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.6.40"}]}]
pip
PraisonAI
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"4.6.40"}]}]
PyPI
praisonaiagents
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.6.40"}]}]
PyPI
praisonai
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"4.6.40"}]}]