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PraisonaiApplication · Praison

CVE-2026-39888

CRITICAL · 9.9 CVSS v3.1 Published 2026-04-08
Fix available
A fix is available. Upgrade to 1.5.115 or later.
See remediation →
100/100
Remediation priority · Urgent
Remotely reachable Zero-click

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
PraisonAI is a multi-agent teams system. Prior to 1.5.115, execute_code() in praisonaiagents.tools.python_tools defaults to sandbox_mode="sandbox", which runs user code in a subprocess wrapped with a restricted __builtins__ dict and an AST-based blocklist. The AST blocklist embedded inside the subprocess wrapper (blocked_attrs of python_tools.py) contains only 11 attribute names — a strict subset of the 30+ names blocked in the direct-execution path. The four attributes that form a frame-traversal chain out of the sandbox are all absent from the subprocess list (__traceback__, tb_frame, f_back, and f_builtins). Chaining these attributes through a caught exception exposes the real Python builtins dict of the subprocess wrapper frame, from which exec can be retrieved and called under a non-blocked variable name — bypassing every remaining security layer. This vulnerability is fixed in 1.5.115.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · high confidence

In PraisonAI versions prior to 1.5.115, the execute_code() function's subprocess sandbox mode uses an incomplete AST blocklist containing only 11 attribute names, missing four critical frame-traversal attributes (__traceback__, tb_frame, f_back, f_builtins). Attackers can chain these missing attributes through exception handling to access the real Python builtins dict and obtain exec, achieving arbitrary code execution and bypassing all security layers.

MitigationUpgrade to PraisonAI version 1.5.115 or later, which includes the complete attribute blocklist in the subprocess sandbox mode.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.

NVD · CPE data
PraisonaiApplication
Affected:< 1.5.115

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Network
Complexity
Low
Privileges
Low
User interaction
None
Scope
Changed
Confidentiality
High
Integrity
High
Availability
High

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Check installed PraisonAI version
    Run 'pip show praisonai' or 'pip list' to retrieve the installed version number
    Affected if Version is below 1.5.115
  2. Verify execute_code function exists
    Attempt to import the function with 'python -c "from praisonai import execute_code; print(execute_code)"'
    Affected if Function exists and PraisonAI version is below 1.5.115
  3. Check if subprocess sandbox is in use
    Inspect code or configuration where execute_code is called, looking for subprocess=True or sandbox-related parameters in the function call
    Affected if Subprocess sandbox mode is enabled and version is below 1.5.115

Environment is affected if PraisonAI version is below 1.5.115 and the execute_code function with subprocess sandbox is being used to process untrusted code

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

dbcve · scoped
Upgrade available Upgrade to 1.5.115 or later
Fixed in 1.5.115
Interim mitigation

Upgrade to PraisonAI version 1.5.115 or later, which includes the complete attribute blocklist in the subprocess sandbox mode.

Recommended fix High confidence

1.5.115

  1. Upgrade PraisonAI to version 1.5.115 or later using your package manager (e.g., pip install praisonai==1.5.115 or pip install --upgrade praisonai)
  2. After upgrading, verify the installation by checking the version: pip show praisonai or import praisonai; print(praisonai.__version__)
  3. If using in a project, ensure your dependency configuration (requirements.txt, pyproject.toml, etc.) pins the minimum version to 1.5.115 or later

Generated from the published advisory — verify against the referenced sources before acting.

Fix this in Praisonai Scoped from the published advisory
  • Consultation3.0 h
  • Implementation6.0 h
  • Testing8.0 h
  • Review / QA4.0 h
21.0 hours of engineering $3,600
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2026-39888 in production — separate from our analysis above.

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What this is

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What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
  • No weaponised exploit code, or anything meant to cause harm
  • No spam, self-promotion, credentials, or personal data