dbcve.org
InjectionWeakness · CWE-74

CVE-2026-4998

HIGH · 7.3 CVSS v3.1 Published 2026-03-28
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
82/100
Remediation priority · High
Remotely reachable No privileges 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
A weakness has been identified in Sinaptik AI PandasAI up to 3.0.0. This vulnerability affects the function CodeExecutor.execute of the file pandasai/core/code_execution/code_executor.py of the component Chat Message Handler. Executing a manipulation can lead to code injection. The attack may be launched remotely. The exploit has been made available to the public and could be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.

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 · moderate confidence

Code injection vulnerability in Sinaptik AI PandasAI's CodeExecutor.execute function within pandasai/core/code_execution/code_executor.py. The Chat Message Handler component improperly handles user input, allowing remote attackers to inject and execute arbitrary code via the AI chat interface.

MitigationImplement proper input validation and sandboxing for the code execution feature. If no patch is available from the vendor, consider disabling or restricting the code execution capability until a fix is released, or implement external sandboxing (e.g., containerized execution environments).

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

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
None
User interaction
None
Scope
Unchanged
Confidentiality
Low
Integrity
Low
Availability
Low

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

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. Identify installed PandasAI version
    Run 'pip show pandasai' or check your dependency lock file to find the installed version of the PandasAI package
    Affected if The installed version falls within any vulnerable version range for this CVE (compare to official vulnerability disclosure)
  2. Locate the code_executor.py file
    Find the pandasai/core/code_execution/code_executor.py file in your installation directory - typically in site-packages or your project dependencies
    Affected if The file exists and is present in your installation, indicating the code execution module is included
  3. Verify code execution feature is enabled
    Check your PandasAI configuration files (e.g., config.yaml, config.json, or environment variables) for settings that enable or disable code execution - look for parameters like 'enable_code_execution', 'allow_code_execution', or similar
    Affected if Code execution is explicitly enabled in your configuration, making the vulnerable CodeExecutor.execute function accessible
  4. Confirm chat interface accessibility
    Check if the Chat Message Handler component is exposed - verify network exposure settings, API authentication, and whether the AI chat interface is accessible to users or external systems
    Affected if The chat interface is accessible without sufficient restrictions, allowing untrusted input to reach the code execution pathway
  5. Inspect code execution sandboxing
    Review the code_executor.py implementation to determine if input validation or sandboxing is implemented before the execute function is called - check for sanitization routines, safe execution modes, or isolation mechanisms
    Affected if No input validation, sanitization, or sandboxing is implemented in the execution path, allowing arbitrary code injection

Your environment is affected if PandasAI is installed with the code execution feature enabled and accessible through the chat interface without proper input validation or sandboxing in place.

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.

From vendor data
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Implement proper input validation and sandboxing for the code execution feature. If no patch is available from the vendor, consider disabling or restricting the code execution capability until a fix is released, or implement external sandboxing (e.g., containerized execution environments).

Have this fixed Scoped from the published advisory
  • Consultation8.0 h
  • Implementation24.0 h
  • Testing16.0 h
  • Review / QA8.0 h
56.0 hours of engineering $9,760
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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-2026-4998 in production — separate from our analysis above.

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

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
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