{"dataType": "CVE_RECORD", "dataVersion": "5.1", "cveMetadata": {"cveId": "CVE-2025-46725", "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "state": "PUBLISHED", "assignerShortName": "GitHub_M", "dateReserved": "2025-04-28T20:56:09.084Z", "datePublished": "2025-05-20T17:24:31.618Z", "dateUpdated": "2025-05-20T17:53:02.636Z"}, "containers": {"cna": {"title": "Langroid has a Code Injection vulnerability in LanceDocChatAgent through vector_store", "problemTypes": [{"descriptions": [{"cweId": "CWE-94", "lang": "en", "description": "CWE-94: Improper Control of Generation of Code ('Code Injection')", "type": "CWE"}]}], "metrics": [{"cvssV4_0": {"attackVector": "NETWORK", "attackComplexity": "LOW", "attackRequirements": "NONE", "privilegesRequired": "NONE", "userInteraction": "NONE", "vulnConfidentialityImpact": "HIGH", "vulnIntegrityImpact": "HIGH", "vulnAvailabilityImpact": "HIGH", "subConfidentialityImpact": "NONE", "subIntegrityImpact": "NONE", "subAvailabilityImpact": "NONE", "baseScore": 8.1, "baseSeverity": "HIGH", "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"}}], "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"}], "affected": [{"vendor": "langroid", "product": "langroid", "versions": [{"version": "< 0.53.15", "status": "affected"}]}], "providerMetadata": {"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M", "dateUpdated": "2025-05-20T17:24:31.618Z"}, "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."}], "source": {"advisory": "GHSA-22c2-9gwg-mj59", "discovery": "UNKNOWN"}}, "adp": [{"metrics": [{"other": {"type": "ssvc", "content": {"timestamp": "2025-05-20T17:52:58.111561Z", "id": "CVE-2025-46725", "options": [{"Exploitation": "none"}, {"Automatable": "yes"}, {"Technical Impact": "total"}], "role": "CISA Coordinator", "version": "2.0.3"}}}], "title": "CISA ADP Vulnrichment", "providerMetadata": {"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "shortName": "CISA-ADP", "dateUpdated": "2025-05-20T17:53:02.636Z"}}]}}

{"dataType": "CVE_RECORD", "containers": {"adp": [{"title": "CISA ADP Vulnrichment", "metrics": [{"other": {"type": "ssvc", "content": {"id": "CVE-2025-46725", "role": "CISA Coordinator", "options": [{"Exploitation": "none"}, {"Automatable": "yes"}, {"Technical Impact": "total"}], "version": "2.0.3", "timestamp": "2025-05-20T17:52:58.111561Z"}}}], "providerMetadata": {"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "shortName": "CISA-ADP", "dateUpdated": "2025-05-20T17:52:59.906Z"}}], "cna": {"title": "Langroid has a Code Injection vulnerability in LanceDocChatAgent through vector_store", "source": {"advisory": "GHSA-22c2-9gwg-mj59", "discovery": "UNKNOWN"}, "metrics": [{"cvssV4_0": {"version": "4.0", "baseScore": 8.1, "attackVector": "NETWORK", "baseSeverity": "HIGH", "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", "userInteraction": "NONE", "attackComplexity": "LOW", "attackRequirements": "NONE", "privilegesRequired": "NONE", "subIntegrityImpact": "NONE", "vulnIntegrityImpact": "HIGH", "subAvailabilityImpact": "NONE", "vulnAvailabilityImpact": "HIGH", "subConfidentialityImpact": "NONE", "vulnConfidentialityImpact": "HIGH"}}], "affected": [{"vendor": "langroid", "product": "langroid", "versions": [{"status": "affected", "version": "< 0.53.15"}]}], "references": [{"url": "https://github.com/langroid/langroid/security/advisories/GHSA-22c2-9gwg-mj59", "name": "https://github.com/langroid/langroid/security/advisories/GHSA-22c2-9gwg-mj59", "tags": ["x_refsource_CONFIRM"]}, {"url": "https://github.com/langroid/langroid/commit/0d9e4a7bb3ae2eef8d38f2e970ff916599a2b2a6", "name": "https://github.com/langroid/langroid/commit/0d9e4a7bb3ae2eef8d38f2e970ff916599a2b2a6", "tags": ["x_refsource_MISC"]}], "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."}], "problemTypes": [{"descriptions": [{"lang": "en", "type": "CWE", "cweId": "CWE-94", "description": "CWE-94: Improper Control of Generation of Code ('Code Injection')"}]}], "providerMetadata": {"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M", "dateUpdated": "2025-05-20T17:24:31.618Z"}}}, "cveMetadata": {"cveId": "CVE-2025-46725", "state": "PUBLISHED", "dateUpdated": "2025-05-20T17:53:02.636Z", "dateReserved": "2025-04-28T20:56:09.084Z", "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "datePublished": "2025-05-20T17:24:31.618Z", "assignerShortName": "GitHub_M"}, "dataVersion": "5.1"}

{"configurations": [{"nodes": [{"cpeMatch": [{"criteria": "cpe:2.3:a:langroid:langroid:*:*:*:*:*:*:*:*", "matchCriteriaId": "FBE9F987-C1AA-4EB5-A30A-935D89DB9EA7", "versionEndExcluding": "0.53.15", "vulnerable": true}], "negate": false, "operator": "OR"}]}], "cveTags": [], "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."}, {"lang": "es", "value": "Langroid es un framework de Python para crear aplicaciones basadas en modelos de lenguaje grandes (LLM). Antes de la versi\u00f3n 0.53.15, `LanceDocChatAgent` utilizaba la funci\u00f3n eval() de Pandas mediante `compute_from_docs()`. Como resultado, un atacante podr\u00eda hacer que el agente ejecute comandos maliciosos a trav\u00e9s de `QueryPlan.dataframe_calc]`, comprometiendo as\u00ed el sistema host. Langroid 0.53.15 depura la entrada a la funci\u00f3n afectada de forma predeterminada para abordar los vectores de ataque m\u00e1s comunes y a\u00f1adi\u00f3 varias advertencias sobre este comportamiento riesgoso en la documentaci\u00f3n del proyecto."}], "id": "CVE-2025-46725", "lastModified": "2025-08-13T16:37:02.567", "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"}], "cvssMetricV40": [{"cvssData": {"Automatable": "NOT_DEFINED", "Recovery": "NOT_DEFINED", "Safety": "NOT_DEFINED", "attackComplexity": "LOW", "attackRequirements": "NONE", "attackVector": "NETWORK", "availabilityRequirement": "NOT_DEFINED", "baseScore": 8.1, "baseSeverity": "HIGH", "confidentialityRequirement": "NOT_DEFINED", "exploitMaturity": "UNREPORTED", "integrityRequirement": "NOT_DEFINED", "modifiedAttackComplexity": "NOT_DEFINED", "modifiedAttackRequirements": "NOT_DEFINED", "modifiedAttackVector": "NOT_DEFINED", "modifiedPrivilegesRequired": "NOT_DEFINED", "modifiedSubAvailabilityImpact": "NOT_DEFINED", "modifiedSubConfidentialityImpact": "NOT_DEFINED", "modifiedSubIntegrityImpact": "NOT_DEFINED", "modifiedUserInteraction": "NOT_DEFINED", "modifiedVulnAvailabilityImpact": "NOT_DEFINED", "modifiedVulnConfidentialityImpact": "NOT_DEFINED", "modifiedVulnIntegrityImpact": "NOT_DEFINED", "privilegesRequired": "NONE", "providerUrgency": "NOT_DEFINED", "subAvailabilityImpact": "NONE", "subConfidentialityImpact": "NONE", "subIntegrityImpact": "NONE", "userInteraction": "NONE", "valueDensity": "NOT_DEFINED", "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/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", "version": "4.0", "vulnAvailabilityImpact": "HIGH", "vulnConfidentialityImpact": "HIGH", "vulnIntegrityImpact": "HIGH", "vulnerabilityResponseEffort": "NOT_DEFINED"}, "source": "security-advisories@github.com", "type": "Secondary"}]}, "published": "2025-05-20T18:15:46.580", "references": [{"source": "security-advisories@github.com", "tags": ["Patch"], "url": "https://github.com/langroid/langroid/commit/0d9e4a7bb3ae2eef8d38f2e970ff916599a2b2a6"}, {"source": "security-advisories@github.com", "tags": ["Vendor Advisory"], "url": "https://github.com/langroid/langroid/security/advisories/GHSA-22c2-9gwg-mj59"}], "sourceIdentifier": "security-advisories@github.com", "vulnStatus": "Analyzed", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-94"}], "source": "security-advisories@github.com", "type": "Primary"}]}

{}

{"created": "2025-07-12T22:01:16.942456+00:00", "updated": "2025-07-12T22:01:16.942527+00:00", "vendors": ["langroid", "langroid$PRODUCT$langroid"]}