CVE-2025-6051

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{"bugzilla": {"description": "transformers: Regular Expression Denial of Service (ReDoS) in huggingface/transformers", "id": "2395072", "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2395072"}, "csaw": false, "cvss3": {"cvss3_base_score": "5.3", "cvss3_scoring_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L", "status": "draft"}, "cwe": "CWE-1333", "details": ["A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library\u2019s EnglishNormalizer.normalize_numbers method of the CLVP model. Maliciously crafted long numeric strings cause excessive CPU usage due to inefficient regex processing, leading to potential service disruption."], "mitigation": {"lang": "en:us", "value": "For mitigation, it\u2019s recommended to implement input validation to limit the length and complexity of numeric strings processed by the EnglishNormalizer. Applying rate limiting and monitoring CPU usage can also help detect and prevent potential abuse. For services exposed to untrusted inputs, consider adding sandboxing or timeouts to avoid prolonged processing caused by malicious payloads."}, "name": "CVE-2025-6051", "package_state": [{"cpe": "cpe:/a:redhat:openshift_lightspeed", "fix_state": "Fix deferred", "package_name": "openshift-lightspeed/lightspeed-service-api-rhel9", "product_name": "OpenShift Lightspeed"}, {"cpe": "cpe:/a:redhat:openshift_lightspeed", "fix_state": "Fix deferred", "package_name": "openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9", "product_name": "OpenShift Lightspeed"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Fix deferred", "package_name": "rhaiis/vllm-cuda-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Fix deferred", "package_name": "rhaiis/vllm-rocm-rhel9", "product_name": "Red Hat AI Inference Server"}, {"cpe": "cpe:/a:redhat:ai_inference_server:3", "fix_state": "Fix deferred", "package_name": 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"product_name": "Red Hat Enterprise Linux AI (RHEL AI)"}, {"cpe": "cpe:/a:redhat:enterprise_linux_ai:1", "fix_state": "Fix deferred", "package_name": "rhelai1/instructlab-amd-rhel9", "product_name": "Red Hat Enterprise Linux AI (RHEL AI)"}, {"cpe": "cpe:/a:redhat:enterprise_linux_ai:1", "fix_state": "Fix deferred", "package_name": "rhelai1/instructlab-intel-rhel9", "product_name": "Red Hat Enterprise Linux AI (RHEL AI)"}, {"cpe": "cpe:/a:redhat:enterprise_linux_ai:1", "fix_state": "Fix deferred", "package_name": "rhelai1/instructlab-nvidia-rhel9", "product_name": "Red Hat Enterprise Linux AI (RHEL AI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Fix deferred", "package_name": "rhoai/odh-feature-server-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Fix deferred", "package_name": "rhoai/odh-llama-stack-core-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Fix deferred", "package_name": "rhoai/odh-training-operator-rhel8", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Fix deferred", "package_name": "rhoai/odh-training-operator-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}], "public_date": "2025-09-14T17:03:02Z", "references": ["https://www.cve.org/CVERecord?id=CVE-2025-6051\nhttps://nvd.nist.gov/vuln/detail/CVE-2025-6051\nhttps://github.com/huggingface/transformers/commit/ba8eaba9865618253f997784aa565b96206426f0\nhttps://huntr.com/bounties/af929523-7b59-418a-bf55-301830b2ac9d"], "statement": "This ReDoS vulnerability is classified as a Moderate issue because, while it does not compromise confidentiality or integrity, it can significantly impact the availability of services using the affected component. Attackers can exploit this flaw by sending specially crafted long numeric inputs that cause excessive CPU consumption, potentially slowing down or crashing text processing pipelines, such as text-to-speech systems. Although it requires no special privileges or user interaction, the impact is limited to resource exhaustion rather than data theft or system takeover.", "threat_severity": "Moderate"}

{"created": "2025-09-15T10:43:26.222956+00:00", "updated": "2025-09-15T10:43:26.223007+00:00", "vendors": ["huggingface", "huggingface$PRODUCT$transformers"]}