CVE-2024-23752: PandasAI · Missing Authorization
Source CVE Database V5
Mentioned vulnerabilities
Not known to be exploited · CVSS 9.8 Critical.
Data as of 26 Oct 2026, 10:12 UTC
- EPSS
- 1.0% chance of exploitation in 30 days – higher than 63% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HExploitation evidence
Disclosed: evidence found.
CVE published 22 Jan 2024
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.
What to do
AI-suggested
To mitigate this vulnerability, European organizations should immediately audit their use of PandasAI and identify any deployments of the affected synthetic_dataframe module, particularly the GenerateSDFPipeline function. Until official patches are released, organizations should consider disabling or restricting the use of this functionality in their environments. Implement strict input validation and sanitization on any dataframes or inputs that could be processed by PandasAI to prevent malicious English language specifications from being interpreted. Employ runtime application self-protection (RASP) or sandboxing techniques to limit the execution context of Python code generated by PandasAI, minimizing potential damage from exploitation. Monitor network and system logs for unusual activity related to PandasAI processes, including unexpected code execution or data pipeline anomalies. Additionally, update incident response plans to include detection and containment strategies for this vulnerability. Engage with the vendor or open-source community to track patch releases and apply updates promptly once available. Finally, consider isolating AI and data science workloads from critical production systems to reduce attack surface exposure.
Description
GenerateSDFPipeline in synthetic_dataframe in PandasAI (aka pandas-ai) through 1.5.17 allows attackers to trigger the generation of arbitrary Python code that is executed by SDFCodeExecutor. An attacker can create a dataframe that provides an English language specification of this Python code. NOTE: the vendor previously attempted to restrict code execution in response to a separate issue, CVE-2023-39660.