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{"bugzilla": {"description": "lupa: Lupa: Arbitrary Code Execution due to inconsistent attribute filtering", "id": "2455413", "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2455413"}, "csaw": false, "cvss3": {"cvss3_base_score": "8.1", "cvss3_scoring_vector": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H", "status": "draft"}, "cwe": "CWE-914", "details": ["A flaw was found in Lupa, a tool that integrates Lua or LuaJIT2 runtimes into CPython. An attacker can exploit this vulnerability by bypassing attribute filtering mechanisms when accessing attributes through built-in functions like `getattr` and `setattr`. This inconsistency in applying security restrictions can allow an attacker to execute arbitrary code, potentially compromising the system."], "mitigation": {"lang": "en:us", "value": "Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability."}, "name": "CVE-2026-34444", "package_state": [{"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-codeserver-datascience-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-minimal-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:satellite:6", "fix_state": "Affected", "package_name": "satellite/foreman-mcp-server-rhel9", "product_name": "Red Hat Satellite 6"}], "public_date": "2026-04-06T15:30:30Z", "references": ["https://www.cve.org/CVERecord?id=CVE-2026-34444\nhttps://nvd.nist.gov/vuln/detail/CVE-2026-34444\nhttps://github.com/scoder/lupa/security/advisories/GHSA-69v7-xpr6-6gjm"], "threat_severity": "Important"}

{"affected": [{"configurations": [{"platform": null, "status": "affected", "versions": {"scheme": "generic", "value": "[0,2.6]"}}], "enrichment": {"confidence": 100.0, "confidence_source": "cna", "scores": [{"score": 100.0, "source": "cna"}]}, "original": {"product": "lupa", "source": "cna", "vendor": "scoder"}, "product": "lupa", "vendor": "scoder"}], "analysis": {"en": {"generated_at": "2026-04-06T20:35:39.530846+00:00", "value": {"mitigation_remediation": ["Review the GitHub security advisory for scoder:lupa and apply a newer release that corrects the attribute_filter enforcement if one is available.", "Verify that the updated package correctly blocks privileged attribute access through unit tests or debugging tools.", "If a patched release is not yet released, limit the use of Lupa in untrusted or externally supplied code, or remove Lupa from the application entirely until a fix is provided.", "Continuously monitor vendor advisories and security bulletins to apply patches as soon as they are released."], "summary": {"action": "Immediate Patch", "impact": "Remote Code Execution"}, "threat_synthesis": {"affected_systems": "The flaw affects the scoder:lupa package, specifically installations that rely on version 2.6 or older. Any Python application that imports or utilizes these earlier Lupa releases, especially when executing untrusted code that employs built\u2011in attribute access functions, is at risk.", "description_and_impact": "Lupa integrates the Lua or LuaJIT2 runtime into CPython, enabling Lua scripts to run inside a Python process. The vulnerability stems from incomplete application of the attribute_filter\u2014 a mechanism intended to restrict access to privileged internal members. When CPython processes built\u2011in operations such as getattr and setattr, the filter is not consistently enforced, allowing an attacker to read or modify restricted attributes. This bypass ultimately permits execution of arbitrary code within the host Python interpreter, exposing the entire process to attack.", "risk_and_exploitability": "The CVSS base score of 7.9 classifies this as a high\u2011severity remote code execution flaw. No public EPSS score is available and the vulnerability is not currently listed in the CISA KEV catalog, implying limited known exploitation. Exploitation requires an attacker to influence attribute access within a CPython process that has loaded the vulnerable Lupa extension, such as by executing or importing untrusted Python modules that invoke getattr or setattr on Lua objects. Successful exploitation would grant full control over the Python process and, by extension, the host system."}}}}, "created": "2026-04-06T20:14:03.788311+00:00", "updated": "2026-04-06T21:32:15.003531+00:00", "vendors": ["scoder", "scoder$PRODUCT$lupa"]}