Vulnerability-Lookup

FKIE_CVE-2024-23752

Vulnerability from fkie_nvd - Published: 2024-01-22 01:15 - Updated: 2026-06-17 07:13

Severity

9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Summary

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.

References

	URL	Tags
	cve@mitre.org	https://github.com/gventuri/pandas-ai/issues/868	Exploit, Mailing List, Vendor Advisory
	af854a3a-2127-422b-91ae-364da2661108	https://github.com/gventuri/pandas-ai/issues/868	Exploit, Mailing List, Vendor Advisory

Impacted products

	Vendor	Product	Version
	gabrieleventuri	pandasai	*

JSON

To clipboard

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "n/a",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "n/a"
            }
          ]
        }
      ],
      "source": "cve@mitre.org"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:gabrieleventuri:pandasai:*:*:*:*:*:python:*:*",
              "matchCriteriaId": "14CBB3DD-8C76-4489-9ED7-97DF5E46B561",
              "versionEndIncluding": "1.5.17",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "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."
    },
    {
      "lang": "es",
      "value": "GenerateSDFPipeline en Synthetic_dataframe en PandasAI (tambi\u00e9n conocido como pandas-ai) hasta 1.5.17 permite a los atacantes activar la generaci\u00f3n de c\u00f3digo Python arbitrario que es ejecutado por SDFCodeExecutor. Un atacante puede crear un marco de datos que proporcione una especificaci\u00f3n en ingl\u00e9s de este c\u00f3digo Python. NOTA: el proveedor intent\u00f3 anteriormente restringir la ejecuci\u00f3n del c\u00f3digo en respuesta a un problema separado, CVE-2023-39660."
    }
  ],
  "id": "CVE-2024-23752",
  "lastModified": "2026-06-17T07:13:31.787",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 9.8,
          "baseSeverity": "CRITICAL",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 5.9,
        "source": "nvd@nist.gov",
        "type": "Primary"
      },
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 9.8,
          "baseSeverity": "CRITICAL",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 5.9,
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2024-23752",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "yes"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2025-05-08T15:59:19.996196Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2024-01-22T01:15:08.607",
  "references": [
    {
      "source": "cve@mitre.org",
      "tags": [
        "Exploit",
        "Mailing List",
        "Vendor Advisory"
      ],
      "url": "https://github.com/gventuri/pandas-ai/issues/868"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Exploit",
        "Mailing List",
        "Vendor Advisory"
      ],
      "url": "https://github.com/gventuri/pandas-ai/issues/868"
    }
  ],
  "sourceIdentifier": "cve@mitre.org",
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-862"
        }
      ],
      "source": "nvd@nist.gov",
      "type": "Primary"
    },
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-862"
        }
      ],
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "type": "Secondary"
    }
  ]
}

CVE-2024-23752 (GCVE-0-2024-23752)

Vulnerability from cvelistv5 – Published: 2024-01-22 00:00 – Updated: 2025-05-30 14:23

Summary

Severity

9.8 (Critical)


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

SSVC

Exploitation: poc Automatable: yes Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-05-08 15:59 UTC

CWE

n/a
CWE-862 - Missing Authorization

Assigner

mitre CNA under the mitre root

CNA scorecard E 29/100 over 2132 records in the last 180 days details

References

1 reference

URL	Tags
https://github.com/gventuri/pandas-ai/issues/868

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "providerMetadata": {
          "dateUpdated": "2024-08-01T23:13:07.389Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
          "shortName": "CVE"
        },
        "references": [
          {
            "tags": [
              "x_transferred"
            ],
            "url": "https://github.com/gventuri/pandas-ai/issues/868"
          }
        ],
        "title": "CVE Program Container"
      },
      {
        "metrics": [
          {
            "cvssV3_1": {
              "attackComplexity": "LOW",
              "attackVector": "NETWORK",
              "availabilityImpact": "HIGH",
              "baseScore": 9.8,
              "baseSeverity": "CRITICAL",
              "confidentialityImpact": "HIGH",
              "integrityImpact": "HIGH",
              "privilegesRequired": "NONE",
              "scope": "UNCHANGED",
              "userInteraction": "NONE",
              "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
              "version": "3.1"
            }
          },
          {
            "other": {
              "content": {
                "id": "CVE-2024-23752",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "yes"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-05-08T15:59:19.996196Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "problemTypes": [
          {
            "descriptions": [
              {
                "cweId": "CWE-862",
                "description": "CWE-862 Missing Authorization",
                "lang": "en",
                "type": "CWE"
              }
            ]
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-05-30T14:23:33.821Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "n/a",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "n/a"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "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."
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "description": "n/a",
              "lang": "en",
              "type": "text"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2024-01-22T00:53:21.268Z",
        "orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
        "shortName": "mitre"
      },
      "references": [
        {
          "url": "https://github.com/gventuri/pandas-ai/issues/868"
        }
      ]
    }
  },
  "cveMetadata": {
    "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
    "assignerShortName": "mitre",
    "cveId": "CVE-2024-23752",
    "datePublished": "2024-01-22T00:00:00.000Z",
    "dateReserved": "2024-01-22T00:00:00.000Z",
    "dateUpdated": "2025-05-30T14:23:33.821Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

Order JSON

How durations are calculated

Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.

Each result shows its source dates. A negative interval means the end event came first; when date-only inputs leave the order open, the result says so. Date-only inputs are approximate. The earliest evidence wins: KEV report dates and sightings are labelled as such. Records describing another vulnerability are listed but never calculated from, and a PoC alone does not establish exploitation. Missing patch evidence does not prove that no patch exists. Filters below change the event list only.

Publication & reservation Sightings KEV catalogs Other timestamps

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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.

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