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CVE-2026-41497 critical CVSS 9.8

Command Injection in praison (CVE-2026-41497)

Summary

command injection in praison (CVE-2026-41497). Successful exploitation can lead to full system takeover. Exploitable via ``bash``. Mitigation: upgrade to `>= 4.6.9` or later.

AI summary openai / gpt-4o

PraisonAI versions before 4.6.9 are vulnerable to a security flaw allowing attackers to execute unauthorized commands, due to insufficient command validation. The lack of input verification means your system could run harmful commands, leading to potential control loss. Similar vulnerabilities in the past have resulted in significant system breaches; therefore, updating to version 4.6.9 is strongly advised.
In PraisonAI, the 'MCPHandler.parse_mcp_command()' function lacks adequate validation for inputs, allowing arbitrary command execution. Affected are versions before 4.6.9, which addresses this issue by implementing appropriate checks. For example, commands that execute Python or Bash code inline are mishandled, putting the system at risk. The patch introduces validation and a command allowlist. It's recommended to monitor logs for abnormal executions to detect exploitation attempts.
❓ What is the problem
Insufficient validation in 'parse_mcp_command()' allows unauthorized command execution.
📍 Affected scope
PraisonAI system - 'MCPHandler.parse_mcp_command()' function
🔥 Severity
Critical severity (CVSS v3 score: 9.8) allowing remote, unauthenticated exploitation.
🔧 How to fix
Upgrade to PraisonAI version 4.6.9 which implements command and argument validation.
🛡️ Workaround
Information not provided in available resources.
🔍 Detection
Monitor log files for unusual command executions possibly indicating exploitation attempts.

Related past incidents Similar incidents extracted from past CVEs

Similar command injection vulnerability due to insufficient validation in PraisonAI.
Spring Cloud Function vulnerability allowing RCE via improper command handling.
Apache Struts improper input handling leading to RCE.

If this happens at your company Expected impact per business scenario

📌 For SaaS platforms relying on PraisonAI for coordination tasks across distributed teams.
Unauthorized command execution could result in data breaches and system compromise.
📌 In internal IT infrastructures using PraisonAI for automated workflows.
Compromised systems may lead to unauthorized access and persistent threats.
📌 For enterprises using AI models via PraisonAI for operational tasks.
Service disruptions and data integrity issues due to unauthorized system commands.
Recommended action
Companies should immediately upgrade PraisonAI to version 4.6.9, ensure command parsing is secure, and monitor system logs for signs of exploitation.

Response Actions (7 steps)

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

  1. 1
    Identify exposure identify
    grep -r 'praison' . | 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 `praison` 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
    Match against affected range verify
    Confirm if version satisfies `<= 4.6.8`

    Step 1 で見つかったバージョンが影響範囲 `<= 4.6.8` に該当するか照合。本番で稼働中ならインシデント扱い。

  3. 6
    Apply patch patch
    Upgrade praison to >= 4.6.9

    ステージング環境で >= 4.6.9 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。

  4. 7
    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 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。

References

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