Vulnerability-Lookup

GHSA-7G3F-Q846-Q9HX

Vulnerability from github – Published: 2025-03-20 12:32 – Updated: 2025-03-20 12:32

Details

Vanna-ai v0.6.2 is vulnerable to SQL Injection due to insufficient protection against injecting additional SQL commands from user requests. The vulnerability occurs when the generate_sql function calls extract_sql with the LLM response. An attacker can include a semi-colon between a search data field and their own command, causing the extract_sql function to remove all LLM generated SQL and execute the attacker's command if it passes the is_sql_valid function. This allows the execution of user-defined SQL beyond the expected boundaries, notably the trained schema.

Severity

8.1 (High)


                  
                    CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N

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{
  "affected": [],
  "aliases": [
    "CVE-2024-7764"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-89"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-03-20T10:15:36Z",
    "severity": "HIGH"
  },
  "details": "Vanna-ai v0.6.2 is vulnerable to SQL Injection due to insufficient protection against injecting additional SQL commands from user requests. The vulnerability occurs when the `generate_sql` function calls `extract_sql` with the LLM response. An attacker can include a semi-colon between a search data field and their own command, causing the `extract_sql` function to remove all LLM generated SQL and execute the attacker\u0027s command if it passes the `is_sql_valid` function. This allows the execution of user-defined SQL beyond the expected boundaries, notably the trained schema.",
  "id": "GHSA-7g3f-q846-q9hx",
  "modified": "2025-03-20T12:32:46Z",
  "published": "2025-03-20T12:32:46Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-7764"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/85d403b1-fbed-42e9-9ec1-2f79abf6eb0f"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2024-7764 (GCVE-0-2024-7764)

Vulnerability from cvelistv5 – Published: 2025-03-20 10:11 – Updated: 2025-03-20 13:43

Title

SQL Injection in vanna-ai/vanna

Summary

Vanna-ai v0.6.2 is vulnerable to SQL Injection due to insufficient protection against injecting additional SQL commands from user requests. The vulnerability occurs when the `generate_sql` function calls `extract_sql` with the LLM response. An attacker can include a semi-colon between a search data field and their own command, causing the `extract_sql` function to remove all LLM generated SQL and execute the attacker's command if it passes the `is_sql_valid` function. This allows the execution of user-defined SQL beyond the expected boundaries, notably the trained schema.

Severity

8.1 (High)


                        
                          CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N

SSVC

Exploitation: poc Automatable: no Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-03-20 13:43 UTC

CWE

CWE-89 - Improper Neutralization of Special Elements used in an SQL Command

Assigner

@huntr_ai mitre root Scorecard

References

1 reference

URL	Tags
https://huntr.com/bounties/85d403b1-fbed-42e9-9ec…

Impacted products

1 product

Vendor	Product	Version
vanna-ai	vanna-ai/vanna	Affected: unspecified , ≤ latest (custom)

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JSON

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  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2024-7764",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-03-20T13:43:19.044296Z",
                "version": "2.0.3"
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          "dateUpdated": "2025-03-20T13:43:43.656Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
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          "vendor": "vanna-ai",
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          "value": "Vanna-ai v0.6.2 is vulnerable to SQL Injection due to insufficient protection against injecting additional SQL commands from user requests. The vulnerability occurs when the `generate_sql` function calls `extract_sql` with the LLM response. An attacker can include a semi-colon between a search data field and their own command, causing the `extract_sql` function to remove all LLM generated SQL and execute the attacker\u0027s command if it passes the `is_sql_valid` function. This allows the execution of user-defined SQL beyond the expected boundaries, notably the trained schema."
        }
      ],
      "metrics": [
        {
          "cvssV3_0": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "NONE",
            "baseScore": 8.1,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N",
            "version": "3.0"
          }
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        "advisory": "85d403b1-fbed-42e9-9ec1-2f79abf6eb0f",
        "discovery": "EXTERNAL"
      },
      "title": "SQL Injection in vanna-ai/vanna"
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  "cveMetadata": {
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    "dateReserved": "2024-08-13T18:24:14.074Z",
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    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
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Sightings

Author	Source	Type	Date	Other

Nomenclature

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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.

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.

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GHSA-7G3F-Q846-Q9HX

CVE-2024-7764 (GCVE-0-2024-7764)

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