Which versions of Pandasai are affected by CVE-2026-4997?

Organizations using Sinaptik AI PandasAI should be aware of moderate risk from CVE-2026-4997, a path traversal vulnerability rated CVSS 5.5. This could allow unauthorized file access.

Is there a public PoC exploit available for CVE-2026-4997?

Yes, a public proof-of-concept exploit is available for CVE-2026-4997. Prioritise patching immediately. EPSS: 0.1%.

How to fix or mitigate CVE-2026-4997?

Within 30 days: Identify affected systems running Sinaptik AI PandasAI and apply vendor patches as part of regular patch cycle. Review file handling controls.

Pandasai CVE-2026-4997

Q: What is the CVSS score of CVE-2026-4997?

CVE-2026-4997 has a CVSS 4.0 base score of 5.5 (Medium). CVSS vector: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X. EPSS exploitation probability: 0.1%.

EUVD-2026-16924 MEDIUM

Path Traversal (CWE-22)

2026-03-28 VulDB

Path Traversal Pandasai pandas

5.5

CVSS 4.0 · NVD

Severity by source

NVD PRIMARY

5.5 MEDIUM

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

Attack Vector

Network

Attack Complexity

Low

Privileges Required

None

User Interaction

None

Scope

Lifecycle Timeline

PoC Detected

Mar 30, 2026 - 13:26 vuln.today

Public exploit code

EUVD ID Assigned

Mar 28, 2026 - 12:45 euvd

EUVD-2026-16924

Analysis Generated

Mar 28, 2026 - 12:45 vuln.today

CVE Published

Mar 28, 2026 - 12:23 nvd

MEDIUM 5.5

DescriptionCVE.org

A security flaw has been discovered in Sinaptik AI PandasAI up to 3.0.0. This affects the function is_sql_query_safe of the file pandasai/helpers/sql_sanitizer.py. Performing a manipulation results in path traversal. The attack may be initiated remotely. The exploit has been released to the public and may be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.

AnalysisAI

Path traversal in Sinaptik AI PandasAI up to version 3.0.0 allows remote unauthenticated attackers to read arbitrary files by manipulating the is_sql_query_safe function in the SQL sanitizer module. The vulnerability has a CVSS score of 5.3 (low-to-medium severity) with public exploit code available, though active exploitation has not been confirmed by CISA. The vendor did not respond to early disclosure notification.

Technical ContextAI

The vulnerability resides in pandasai/helpers/sql_sanitizer.py, specifically in the is_sql_query_safe function which is responsible for validating and sanitizing SQL queries. The root cause is a path traversal flaw (CWE-22) in the input validation logic, where user-supplied input is not properly canonicalized or filtered before being used to access files or construct file paths. This allows attackers to use directory traversal sequences (e.g., ../) to escape intended directory boundaries and access files outside the restricted scope. The vulnerability affects all versions of Sinaptik AI PandasAI up to and including 3.0.0, as identified by the CPE cpe:2.3:a:sinaptik_ai:pandasai:*:*:*:*:*:*:*:*.

RemediationAI

Upgrade Sinaptik AI PandasAI to a version released after 3.0.0 that includes fixes for the path traversal vulnerability in the is_sql_query_safe function. Until patching is possible, implement input validation and path canonicalization at the application level to reject or sanitize directory traversal sequences (../, .., backslashes) before they reach the is_sql_query_safe function. Apply strict allowlisting of permitted file paths and disable symbolic link following if the application accesses the filesystem. Consult the vendor advisory at https://vuldb.com/vuln/353884 for release notes and timeline. Organizations unable to patch immediately should restrict network access to PandasAI services and monitor for suspicious file access patterns in application logs.