Vulnerability-Lookup

PYSEC-2026-1531

Vulnerability from pysec - Published: 2026-07-07 16:02 - Updated: 2026-07-07 17:24

Details

Summary

LanceDocChatAgent uses pandas eval() through compute_from_docs(): https://github.com/langroid/langroid/blob/18667ec7e971efc242505196f6518eb19a0abc1c/langroid/vector_store/base.py#L136-L150

As a result, an attacker may be able to make the agent run malicious commands through QueryPlan.dataframe_calc compromising the host system.

Fix

Langroid 0.53.15 sanitizes input to the affected function by default to tackle the most common attack vectors, and added several warnings about the risky behavior in the project documentation.

Severity

8.1 (High)


                  
                    CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:U

Impacted products

Name	purl
langroid	pkg:pypi/langroid

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "langroid",
        "purl": "pkg:pypi/langroid"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.53.15"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
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      ]
    }
  ],
  "aliases": [
    "CVE-2025-46725",
    "GHSA-22c2-9gwg-mj59"
  ],
  "details": "### Summary\n[LanceDocChatAgent](https://github.com/langroid/langroid/blob/main/langroid/agent/special/lance_doc_chat_agent.py#L158) uses pandas eval() through `compute_from_docs()`:\nhttps://github.com/langroid/langroid/blob/18667ec7e971efc242505196f6518eb19a0abc1c/langroid/vector_store/base.py#L136-L150\n\nAs a result, an attacker may be able to make the agent run malicious commands through [QueryPlan.dataframe_calc](https://github.com/langroid/langroid/blob/main/langroid/agent/special/lance_tools.py#L16) compromising the host system.\n\n### Fix \nLangroid 0.53.15 sanitizes input to the affected function by default to tackle the most common attack vectors, and added several warnings about the risky behavior in the project documentation.",
  "id": "PYSEC-2026-1531",
  "modified": "2026-07-07T17:24:29.745678Z",
  "published": "2026-07-07T16:02:52.788656Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/langroid/langroid/security/advisories/GHSA-22c2-9gwg-mj59"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-46725"
    },
    {
      "type": "WEB",
      "url": "https://github.com/langroid/langroid/commit/0d9e4a7bb3ae2eef8d38f2e970ff916599a2b2a6"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/langroid/langroid"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/langroid"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-22c2-9gwg-mj59"
    }
  ],
  "severity": [
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:U",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Langroid has a Code Injection vulnerability in LanceDocChatAgent through vector_store"
}

CVE-2025-46725 (GCVE-0-2025-46725)

Vulnerability from cvelistv5 – Published: 2025-05-20 17:24 – Updated: 2025-05-20 17:53

Title

Langroid has a Code Injection vulnerability in LanceDocChatAgent through vector_store

Summary

Langroid is a Python framework to build large language model (LLM)-powered applications. Prior to version 0.53.15, `LanceDocChatAgent` uses pandas eval() through `compute_from_docs()`. As a result, an attacker may be able to make the agent run malicious commands through `QueryPlan.dataframe_calc]`) compromising the host system. Langroid 0.53.15 sanitizes input to the affected function by default to tackle the most common attack vectors, and added several warnings about the risky behavior in the project documentation.

Severity

8.1 (High)


                        
                          CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:U

SSVC

Exploitation: none Automatable: yes Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-05-20 17:52 UTC

CWE

CWE-94 - Improper Control of Generation of Code ('Code Injection')

Assigner

GitHub_M mitre root Scorecard

References

2 references

URL	Tags
https://github.com/langroid/langroid/security/adv…	x_refsource_CONFIRM
https://github.com/langroid/langroid/commit/0d9e4…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
langroid	langroid	Affected: < 0.53.15

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2025-46725",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "yes"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-05-20T17:52:58.111561Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-05-20T17:53:02.636Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "langroid",
          "vendor": "langroid",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c 0.53.15"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "Langroid is a Python framework to build large language model (LLM)-powered applications. Prior to version 0.53.15, `LanceDocChatAgent` uses pandas eval() through `compute_from_docs()`. As a result, an attacker may be able to make the agent run malicious commands through `QueryPlan.dataframe_calc]`) compromising the host system. Langroid 0.53.15 sanitizes input to the affected function by default to tackle the most common attack vectors, and added several warnings about the risky behavior in the project documentation."
        }
      ],
      "metrics": [
        {
          "cvssV4_0": {
            "attackComplexity": "LOW",
            "attackRequirements": "NONE",
            "attackVector": "NETWORK",
            "baseScore": 8.1,
            "baseSeverity": "HIGH",
            "privilegesRequired": "NONE",
            "subAvailabilityImpact": "NONE",
            "subConfidentialityImpact": "NONE",
            "subIntegrityImpact": "NONE",
            "userInteraction": "NONE",
            "vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:U",
            "version": "4.0",
            "vulnAvailabilityImpact": "HIGH",
            "vulnConfidentialityImpact": "HIGH",
            "vulnIntegrityImpact": "HIGH"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-94",
              "description": "CWE-94: Improper Control of Generation of Code (\u0027Code Injection\u0027)",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-05-20T17:24:31.618Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/langroid/langroid/security/advisories/GHSA-22c2-9gwg-mj59",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/langroid/langroid/security/advisories/GHSA-22c2-9gwg-mj59"
        },
        {
          "name": "https://github.com/langroid/langroid/commit/0d9e4a7bb3ae2eef8d38f2e970ff916599a2b2a6",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/langroid/langroid/commit/0d9e4a7bb3ae2eef8d38f2e970ff916599a2b2a6"
        }
      ],
      "source": {
        "advisory": "GHSA-22c2-9gwg-mj59",
        "discovery": "UNKNOWN"
      },
      "title": "Langroid has a Code Injection vulnerability in LanceDocChatAgent through vector_store"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2025-46725",
    "datePublished": "2025-05-20T17:24:31.618Z",
    "dateReserved": "2025-04-28T20:56:09.084Z",
    "dateUpdated": "2025-05-20T17:53:02.636Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

GHSA-22C2-9GWG-MJ59

Vulnerability from github – Published: 2025-05-20 18:01 – Updated: 2025-05-20 20:56

Summary

Langroid has a Code Injection vulnerability in LanceDocChatAgent through vector_store

Details

Summary

LanceDocChatAgent uses pandas eval() through compute_from_docs(): https://github.com/langroid/langroid/blob/18667ec7e971efc242505196f6518eb19a0abc1c/langroid/vector_store/base.py#L136-L150

As a result, an attacker may be able to make the agent run malicious commands through QueryPlan.dataframe_calc compromising the host system.

Fix

Langroid 0.53.15 sanitizes input to the affected function by default to tackle the most common attack vectors, and added several warnings about the risky behavior in the project documentation.

Severity

8.1 (High)


                  
                    CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:U

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "langroid"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.53.15"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-46725"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-94"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2025-05-20T18:01:52Z",
    "nvd_published_at": "2025-05-20T18:15:46Z",
    "severity": "HIGH"
  },
  "details": "### Summary\n[LanceDocChatAgent](https://github.com/langroid/langroid/blob/main/langroid/agent/special/lance_doc_chat_agent.py#L158) uses pandas eval() through `compute_from_docs()`:\nhttps://github.com/langroid/langroid/blob/18667ec7e971efc242505196f6518eb19a0abc1c/langroid/vector_store/base.py#L136-L150\n\nAs a result, an attacker may be able to make the agent run malicious commands through [QueryPlan.dataframe_calc](https://github.com/langroid/langroid/blob/main/langroid/agent/special/lance_tools.py#L16) compromising the host system.\n\n### Fix \nLangroid 0.53.15 sanitizes input to the affected function by default to tackle the most common attack vectors, and added several warnings about the risky behavior in the project documentation.",
  "id": "GHSA-22c2-9gwg-mj59",
  "modified": "2025-05-20T20:56:51Z",
  "published": "2025-05-20T18:01:52Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/langroid/langroid/security/advisories/GHSA-22c2-9gwg-mj59"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-46725"
    },
    {
      "type": "WEB",
      "url": "https://github.com/langroid/langroid/commit/0d9e4a7bb3ae2eef8d38f2e970ff916599a2b2a6"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/langroid/langroid"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:U",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Langroid has a Code Injection vulnerability in LanceDocChatAgent through vector_store"
}

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.

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.

Action not permitted

PYSEC-2026-1531

Summary

Fix

CVE-2025-46725 (GCVE-0-2025-46725)

GHSA-22C2-9GWG-MJ59

Summary

Fix

Tags

Sightings

Nomenclature

Related by attack behaviour