{"kind": "product", "path": "vulns/pypi/transformers", "name": "transformers", "product": "transformers", "ecosystem": "PyPI", "items": [{"id": "CVE-2026-80047", "noindex": false, "published": "2026-09-01T13:40:05.952Z", "modified": "2026-09-23T17:24:14.772Z", "cvss": 7.8, "cvss_vector": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.00099, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-80047", "title": "Hugging Face Transformers library writes remote code to disk prior to consent check", "description": "A vulnerability in Hugging Face Transformers (versions 4.57.0 to 5.16.1) allows remote Python files to be written to local disk without user consent when using GenerativePreTrainedModel.load_custom_generate(). The function fetches and caches a remote module file before performing the required trust_remote_code consent check, inverting the security model enforced by other code-loading paths (such as AutoConfig, AutoModel, and AutoTokenizer). As a result, attacker‑controlled Python code from custom_generate/generate.py is copied into the user’s ~/.cache/huggingface/modules directory even if the user declines the trust prompt. Although execution", "references": ["https://github.com/huggingface/transformers", "https://kb.cert.org/vuls/id/456290", "https://www.kb.cert.org/vuls/id/456290"], "fixes": [], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-9856", "noindex": false, "published": "2026-08-02T15:10:53.809Z", "modified": "2026-08-03T14:57:43.370Z", "cvss": 7.1, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:L", "severity": "high", "epss": 0.0046, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-9856", "title": "Path Traversal in huggingface/transformers", "description": "A vulnerability in huggingface/transformers versions <=5.8.0.dev0 allows an attacker to perform arbitrary file writes via path traversal. The issue resides in the `save_pretrained()` methods of `PreTrainedTokenizerBase` and `ProcessorMixin`, where keys from the `chat_template` dictionary are used directly as filenames without proper validation. An attacker can exploit this by publishing a malicious Hugging Face Hub repository with a crafted `tokenizer_config.json` file. When a victim downloads and saves the tokenizer or processor, the attacker-controlled keys can escape the intended save directory, enabling arbitrary file writes with attacker", "references": ["https://huntr.com/bounties/362824d5-fe18-40e8-a6cf-62277f97a170", "https://github.com/huggingface/transformers/commit/eaaaf8494dd5386634ae37d1d122212fdc315be5", "https://nvd.nist.gov/vuln/detail/CVE-2026-9856"], "fixes": ["5.10.0"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-5241", "noindex": false, "published": "2026-06-03T12:33:10.227Z", "modified": "2026-09-01T12:04:56.842Z", "cvss": 7.7, "cvss_vector": "CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:C/C:H/I:H/A:N", "severity": "high", "epss": 0.00597, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-5241", "title": "Policy Bypass in LightGlue Nested Config Resolution in huggingface/transformers", "description": "A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The issue arises because the `trust_remote_code` parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `LightGlueConfig` reads the `trust_remote_code` value from the untrusted `config.json` file and propagates it into nested `AutoConfig.from_pretrained()` c", "references": ["https://huntr.com/bounties/ceb3ce1a-4c45-497a-b25e-cb9a7685e619", "https://github.com/huggingface/transformers/commit/676559d5022b74aaa0cee1cee0842b7f27c5320e", "https://access.redhat.com/security/cve/CVE-2026-5241"], "fixes": ["5.5.0"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}, {"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-4372", "noindex": false, "published": "2026-05-24T13:40:40.995Z", "modified": "2026-05-26T15:21:02.376Z", "cvss": 7.8, "cvss_vector": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.00696, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-4372", "title": "Arbitrary Remote Code Execution via `_attn_implementation_internal` Config Injection in huggingface/transformers", "description": "A critical remote code execution vulnerability exists in all versions of the HuggingFace transformers library prior to version 5.3.0. The vulnerability allows an attacker to craft a malicious `config.json` file containing the `_attn_implementation_internal` field set to an attacker-controlled HuggingFace Hub repository ID. When a victim loads this model using the standard `AutoModelForCausalLM.from_pretrained()` API, the library downloads and executes arbitrary Python code from the attacker's repository with the victim's full OS privileges. This issue arises due to unfiltered deserialization of configuration attributes, insufficient sanitizat", "references": ["https://huntr.com/bounties/1f693a6e-6836-4b8b-a0bd-ca036fba8884", "https://github.com/huggingface/transformers/commit/a7f8e7ff37d87d1a1a0c8cf607971c607741452f", "https://nvd.nist.gov/vuln/detail/CVE-2026-4372"], "fixes": ["5.3.0"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-1839", "noindex": false, "published": "2026-04-07T05:22:00.959Z", "modified": "2026-04-07T13:27:41.789Z", "cvss": 6.5, "cvss_vector": "CVSS:3.0/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:L/A:H", "severity": "medium", "epss": 0.00382, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-1839", "title": "Arbitrary Code Execution via Unsafe torch.load() in Trainer Checkpoint Loading in huggingface/transformers", "description": "A vulnerability in the HuggingFace Transformers library, specifically in the `Trainer` class, allows for arbitrary code execution. The `_load_rng_state()` method in `src/transformers/trainer.py` at line 3059 calls `torch.load()` without the `weights_only=True` parameter. This issue affects all versions of the library supporting `torch>=2.2` when used with PyTorch versions below 2.6, as the `safe_globals()` context manager provides no protection in these versions. An attacker can exploit this vulnerability by supplying a malicious checkpoint file, such as `rng_state.pth`, which can execute arbitrary code when loaded. The issue is resolved in v", "references": ["https://huntr.com/bounties/3c77bb97-e493-493d-9a88-c57f5c536485", "https://github.com/huggingface/transformers/commit/03c8082ba4594c9b8d6fe190ca9bed0e5f8ca396", "https://nvd.nist.gov/vuln/detail/CVE-2026-1839"], "fixes": ["5.0.0", "5.0.0rc3"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}, {"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-14930", "noindex": false, "published": "2025-12-23T21:04:52.512Z", "modified": "2025-12-26T14:32:13.294Z", "cvss": 7.8, "cvss_vector": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.00329, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-14930", "title": "Hugging Face Transformers GLM4 Deserialization of Untrusted Data Remote Code Execution Vulnerability", "description": "Hugging Face Transformers GLM4 Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.\n\nThe specific flaw exists within the parsing of weights. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ", "references": ["https://www.zerodayinitiative.com/advisories/ZDI-25-1145/", "https://nvd.nist.gov/vuln/detail/CVE-2025-14930"], "fixes": [], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-14928", "noindex": false, "published": "2025-12-23T21:04:48.438Z", "modified": "2025-12-26T14:31:29.167Z", "cvss": 7.8, "cvss_vector": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.00342, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-14928", "title": "Hugging Face Transformers HuBERT convert_config Code Injection Remote Code Execution Vulnerability", "description": "Hugging Face Transformers HuBERT convert_config Code Injection Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must convert a malicious checkpoint.\n\nThe specific flaw exists within the convert_config function. The issue results from the lack of proper validation of a user-supplied string before using it to execute Python code. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-28253.", "references": ["https://www.zerodayinitiative.com/advisories/ZDI-25-1146/", "https://nvd.nist.gov/vuln/detail/CVE-2025-14928"], "fixes": [], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-14924", "noindex": false, "published": "2025-12-23T21:04:40.830Z", "modified": "2025-12-26T14:22:34.996Z", "cvss": 7.8, "cvss_vector": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.00329, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-14924", "title": "Hugging Face Transformers megatron_gpt2 Deserialization of Untrusted Data Remote Code Execution Vulnerability", "description": "Hugging Face Transformers megatron_gpt2 Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.\n\nThe specific flaw exists within the parsing of checkpoints. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current ", "references": ["https://www.zerodayinitiative.com/advisories/ZDI-25-1141/", "https://nvd.nist.gov/vuln/detail/CVE-2025-14924"], "fixes": [], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-14920", "noindex": false, "published": "2025-12-23T21:04:36.809Z", "modified": "2025-12-24T16:29:05.697Z", "cvss": 7.8, "cvss_vector": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.0036, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-14920", "title": "Hugging Face Transformers Perceiver Model Deserialization of Untrusted Data Remote Code Execution Vulnerability", "description": "Hugging Face Transformers Perceiver Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.\n\nThe specific flaw exists within the parsing of model files. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the curren", "references": ["https://www.zerodayinitiative.com/advisories/ZDI-25-1150/", "https://nvd.nist.gov/vuln/detail/CVE-2025-14920"], "fixes": [], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-14926", "noindex": false, "published": "2025-12-23T21:04:32.162Z", "modified": "2025-12-24T16:26:53.253Z", "cvss": 7.8, "cvss_vector": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.00342, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-14926", "title": "Hugging Face Transformers SEW convert_config Code Injection Remote Code Execution Vulnerability", "description": "Hugging Face Transformers SEW convert_config Code Injection Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must convert a malicious checkpoint.\n\nThe specific flaw exists within the convert_config function. The issue results from the lack of proper validation of a user-supplied string before using it to execute Python code. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-28251.", "references": ["https://www.zerodayinitiative.com/advisories/ZDI-25-1147/", "https://nvd.nist.gov/vuln/detail/CVE-2025-14926"], "fixes": [], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-14927", "noindex": false, "published": "2025-12-23T21:04:28.008Z", "modified": "2025-12-24T16:26:02.865Z", "cvss": 7.8, "cvss_vector": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.00342, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-14927", "title": "Hugging Face Transformers SEW-D convert_config Code Injection Remote Code Execution Vulnerability", "description": "Hugging Face Transformers SEW-D convert_config Code Injection Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must convert a malicious checkpoint.\n\nThe specific flaw exists within the convert_config function. The issue results from the lack of proper validation of a user-supplied string before using it to execute Python code. An attacker can leverage this vulnerability to execute code in the context of the current user.\n\n. Was ZDI-CAN-28252.", "references": ["https://www.zerodayinitiative.com/advisories/ZDI-25-1148/", "https://nvd.nist.gov/vuln/detail/CVE-2025-14927"], "fixes": [], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-14921", "noindex": false, "published": "2025-12-23T21:04:23.187Z", "modified": "2025-12-24T16:25:13.340Z", "cvss": 7.8, "cvss_vector": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.00329, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-14921", "title": "Hugging Face Transformers Transformer-XL Model Deserialization of Untrusted Data Remote Code Execution Vulnerability", "description": "Hugging Face Transformers Transformer-XL Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.\n\nThe specific flaw exists within the parsing of model files. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the c", "references": ["https://www.zerodayinitiative.com/advisories/ZDI-25-1149/", "https://nvd.nist.gov/vuln/detail/CVE-2025-14921"], "fixes": [], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-14929", "noindex": false, "published": "2025-12-23T21:04:15.474Z", "modified": "2025-12-24T16:24:34.136Z", "cvss": 7.8, "cvss_vector": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.00369, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-14929", "title": "Hugging Face Transformers X-CLIP Checkpoint Conversion Deserialization of Untrusted Data Remote Code Execution Vulnerability", "description": "Hugging Face Transformers X-CLIP Checkpoint Conversion Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.\n\nThe specific flaw exists within the parsing of checkpoints. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context ", "references": ["https://www.zerodayinitiative.com/advisories/ZDI-25-1144/", "https://nvd.nist.gov/vuln/detail/CVE-2025-14929"], "fixes": [], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-6921", "noindex": false, "published": "2025-09-23T13:56:15.636Z", "modified": "2025-09-23T14:56:29.038Z", "cvss": 5.3, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L", "severity": "medium", "epss": 0.00511, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-6921", "title": "Regular Expression Denial of Service (ReDoS) in huggingface/transformers", "description": "The huggingface/transformers library, versions prior to 4.53.0, is vulnerable to Regular Expression Denial of Service (ReDoS) in the AdamWeightDecay optimizer. The vulnerability arises from the _do_use_weight_decay method, which processes user-controlled regular expressions in the include_in_weight_decay and exclude_from_weight_decay lists. Malicious regular expressions can cause catastrophic backtracking during the re.search call, leading to 100% CPU utilization and a denial of service. This issue can be exploited by attackers who can control the patterns in these lists, potentially causing the machine learning task to hang and rendering ser", "references": ["https://huntr.com/bounties/287d15a7-6e7c-45d2-8c05-11e305776f1f", "https://github.com/huggingface/transformers/commit/47c34fba5c303576560cb29767efb452ff12b8be", "https://nvd.nist.gov/vuln/detail/CVE-2025-6921"], "fixes": ["4.53.0"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-6051", "noindex": false, "published": "2025-09-14T17:03:02.953Z", "modified": "2025-09-15T15:59:54.371Z", "cvss": 5.3, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L", "severity": "medium", "epss": 0.00382, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-6051", "title": "Regular Expression Denial of Service (ReDoS) in huggingface/transformers", "description": "A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically within the `normalize_numbers()` method of the `EnglishNormalizer` class. This vulnerability affects versions up to 4.52.4 and is fixed in version 4.53.0. The issue arises from the method's handling of numeric strings, which can be exploited using crafted input strings containing long sequences of digits, leading to excessive CPU consumption. This vulnerability impacts text-to-speech and number normalization tasks, potentially causing service disruption, resource exhaustion, and API vulnerabilities.", "references": ["https://huntr.com/bounties/af929523-7b59-418a-bf55-301830b2ac9d", "https://github.com/huggingface/transformers/commit/ba8eaba9865618253f997784aa565b96206426f0", "https://nvd.nist.gov/vuln/detail/CVE-2025-6051"], "fixes": ["4.53.0"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-6638", "noindex": false, "published": "2025-09-12T10:46:07.934Z", "modified": "2025-09-12T11:52:53.854Z", "cvss": 5.3, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L", "severity": "medium", "epss": 0.00555, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-6638", "title": "Regular Expression Denial of Service (ReDoS) in huggingface/transformers", "description": "A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically affecting the MarianTokenizer's `remove_language_code()` method. This vulnerability is present in version 4.52.4 and has been fixed in version 4.53.0. The issue arises from inefficient regex processing, which can be exploited by crafted input strings containing malformed language code patterns, leading to excessive CPU consumption and potential denial of service.", "references": ["https://huntr.com/bounties/6a6c933f-9ce8-4ded-8b3b-2c1444c61f36", "https://github.com/huggingface/transformers/commit/47c34fba5c303576560cb29767efb452ff12b8be", "https://nvd.nist.gov/vuln/detail/CVE-2025-6638"], "fixes": ["4.53.0"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-5197", "noindex": false, "published": "2025-08-06T11:53:37.232Z", "modified": "2025-08-06T13:03:10.518Z", "cvss": 5.3, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L", "severity": "medium", "epss": 0.00419, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-5197", "title": "Regular Expression Denial of Service (ReDoS) in huggingface/transformers", "description": "A Regular Expression Denial of Service (ReDoS) vulnerability exists in the Hugging Face Transformers library, specifically in the `convert_tf_weight_name_to_pt_weight_name()` function. This function, responsible for converting TensorFlow weight names to PyTorch format, uses a regex pattern `/[^/]*___([^/]*)/` that can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. The vulnerability affects versions up to 4.51.3 and is fixed in version 4.53.0. This issue can lead to service disruption, resource exhaustion, and potential API service vulnerabilities, impacting model conversion proc", "references": ["https://huntr.com/bounties/3f8b3fd0-166b-46e7-b60f-60dd9d2678bf", "https://github.com/huggingface/transformers/commit/944b56000be5e9b61af8301aa340838770ad8a0b", "https://nvd.nist.gov/vuln/detail/CVE-2025-5197"], "fixes": ["4.53.0"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-3933", "noindex": false, "published": "2025-07-11T09:22:27.103Z", "modified": "2025-07-11T15:07:34.839Z", "cvss": 5.3, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L", "severity": "medium", "epss": 0.00496, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-3933", "title": "Regular Expression Denial of Service (ReDoS) in huggingface/transformers", "description": "A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically within the DonutProcessor class's `token2json()` method. This vulnerability affects versions 4.50.3 and earlier, and is fixed in version 4.52.1. The issue arises from the regex pattern `<s_(.*?)>` which can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. This vulnerability can lead to service disruption, resource exhaustion, and potential API service vulnerabilities, impacting document processing tasks using the Donut model.", "references": ["https://huntr.com/bounties/25282953-5827-4384-bb6f-5790d275721b", "https://github.com/huggingface/transformers/commit/ebbe9b12dd75b69f92100d684c47f923ee262a93", "https://nvd.nist.gov/vuln/detail/CVE-2025-3933"], "fixes": ["4.52.1"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-3777", "noindex": false, "published": "2025-07-07T09:55:38.190Z", "modified": "2025-07-07T12:26:15.099Z", "cvss": 3.5, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:N/A:N", "severity": "low", "epss": 0.00406, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-3777", "title": "Improper Input Validation in huggingface/transformers", "description": "Hugging Face Transformers versions up to 4.49.0 are affected by an improper input validation vulnerability in the `image_utils.py` file. The vulnerability arises from insecure URL validation using the `startswith()` method, which can be bypassed through URL username injection. This allows attackers to craft URLs that appear to be from YouTube but resolve to malicious domains, potentially leading to phishing attacks, malware distribution, or data exfiltration. The issue is fixed in version 4.52.1.", "references": ["https://huntr.com/bounties/ccba0730-9248-4853-b7ff-5c20e6364f09", "https://github.com/huggingface/transformers/commit/4dda5f71b35fb70cf602187eef84bb17a50b9082", "https://nvd.nist.gov/vuln/detail/CVE-2025-3777"], "fixes": ["4.52.1"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}, {"id": "CVE-2025-3264", "noindex": false, "published": "2025-07-07T09:55:11.030Z", "modified": "2025-07-07T14:40:12.531Z", "cvss": 5.3, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L", "severity": "medium", "epss": 0.00496, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2025-3264", "title": "Regular Expression Denial of Service (ReDoS) in huggingface/transformers", "description": "A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically in the `get_imports()` function within `dynamic_module_utils.py`. This vulnerability affects versions 4.49.0 and is fixed in version 4.51.0. The issue arises from a regular expression pattern `\\s*try\\s*:.*?except.*?:` used to filter out try/except blocks from Python code, which can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. This vulnerability can lead to remote code loading disruption, resource exhaustion in model serving, supply chain attack vec", "references": ["https://huntr.com/bounties/3c6f7822-9992-476d-8cf0-b0b1623427df", "https://github.com/huggingface/transformers/commit/0720e206c6ba28887e4d60ef60a6a089f6c1cc76", "https://nvd.nist.gov/vuln/detail/CVE-2025-3264"], "fixes": ["4.51.0"], "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}]}], "total": 32, "unknown_count": 0, "release_unconfirmed": false, "page": 1, "pages": 2, "filtered": false, "noindex": false, "filters": {}, "page_size": 20, "products": [{"name": "transformers", "path": "vulns/pypi/transformers", "ecosystem": "PyPI"}], "stacks": [{"name": "system", "path": "vulns/stack/system", "slug": "system"}, {"name": "web", "path": "vulns/stack/web", "slug": "web"}, {"name": "php", "path": "vulns/stack/php", "slug": "php"}, {"name": "python", "path": "vulns/stack/python", "slug": "python"}, {"name": "node", "path": "vulns/stack/node", "slug": "node"}, {"name": "database", "path": "vulns/stack/database", "slug": "database"}, {"name": "containers", "path": "vulns/stack/containers", "slug": "containers"}, {"name": "network", "path": "vulns/stack/network", "slug": "network"}, {"name": "applications", "path": "vulns/stack/applications", "slug": "applications"}], "versions": ["5.9.0", "5.8.1", "5.8.0", "5.7.0", "5.6.2", "5.6.1", "5.6.0", "5.5.4", "5.5.3", "5.5.2", "5.5.1", "5.5.0"], "stats": {"recent": 0, "kev": 0}, "lastmod": "2026-09-23T17:24:14.772Z", "early_advisories": [], "license": "You may freely use the PatchFirst selection and our additions (priorities, early warnings, texts, summaries and aggregates) for your own purposes, including internal business use. Resale, commercial distribution and bulk mirroring of this selection or these additions require a written agreement with the operator. Whenever you use or publish the selection or our additions, credit PatchFirst (https://patchfirst.dev/vulns/) with this link to the regional feed page. Original records from open sources remain subject to their respective licenses and terms. These conditions do not restrict your rights to the original data, which you can obtain directly from those sources.", "terms_url": "https://patchfirst.dev/vulns/#feed-terms", "attribution": {"name": "PatchFirst", "url": "https://patchfirst.dev/vulns/"}, "source_changes": "Records are selected, normalized and combined by PatchFirst; summaries and translations may be added. News is credited with a link to the original source in each entry.", "sources": [{"id": "cve", "name": "CVE List / CVE.org", "url": "https://www.cve.org/", "license": "CVE Terms of Use", "terms_url": "https://www.cve.org/Legal/TermsOfUse", "notice": "Copyright © 1999–2021, The MITRE Corporation. LICENSE Submissions : For all materials you submit to the Common Vulnerabilities and Exposures (CVE™), you hereby grant to The MITRE Corporation (MITRE) and all CVE Numbering Authorities (CNAs) a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare derivative works of, publicly display, publicly perform, sublicense, and distribute such materials and derivative works. Unless required by applicable law or agreed to in writing, you provide such materials on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. CVE Usage : MITRE hereby grants you a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare derivative works of, publicly display, publicly perform, sublicense, and distribute Common Vulnerabilities and Exposures (CVE™). Any copy you make for such purposes is authorized provided that you reproduce MITRE's copyright designation and this license in any such copy. DISCLAIMERS ALL DOCUMENTS AND THE INFORMATION CONTAINED THEREIN PROVIDED BY MITRE ARE PROVIDED ON AN \"AS IS\" BASIS AND THE CONTRIBUTOR, THE ORGANIZATION HE/SHE REPRESENTS OR IS SPONSORED BY (IF ANY), THE MITRE CORPORATION, ITS BOARD OF TRUSTEES, OFFICERS, AGENTS, AND EMPLOYEES, DISCLAIM ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE INFORMATION THEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE."}, {"id": "osv", "name": "OSV", "url": "https://osv.dev/", "terms_url": "https://google.github.io/osv.dev/data/", "terms": "Upstream licenses vary; see the source catalog."}, {"id": "kev", "name": "CISA KEV", "url": "https://www.cisa.gov/known-exploited-vulnerabilities-catalog", "license": "CC0-1.0", "terms_url": "https://github.com/cisagov/kev-data/blob/develop/LICENSE"}, {"id": "epss", "name": "FIRST EPSS", "url": "https://www.first.org/epss/", "terms_url": "https://www.first.org/epss/faq", "terms": "Free public scores; attribution requested (FIRST EPSS, scores generated by Empirical Security)."}, {"id": "github-advisory", "name": "GitHub Advisory Database", "url": "https://github.com/advisories", "license": "CC-BY-4.0", "terms_url": "https://github.com/github/advisory-database/blob/main/LICENSE.md"}, {"id": "exploitdb", "name": "Exploit-DB", "url": "https://www.exploit-db.com/", "license": "GPL-2.0", "terms_url": "https://gitlab.com/exploit-database/exploitdb/-/blob/main/LICENSE.md"}, {"id": "metasploit", "name": "Metasploit", "url": "https://github.com/rapid7/metasploit-framework", "license": "BSD-3-Clause", "terms_url": "https://github.com/rapid7/metasploit-framework/blob/master/LICENSE", "notice": "Copyright (c) 2006-2026, Rapid7, Inc.\nLicense: BSD-3-clause\n Redistribution and use in source and binary forms, with or without modification,\n are permitted provided that the following conditions are met:\n .\n * Redistributions of source code must retain the above copyright notice,\n this list of conditions and the following disclaimer.\n .\n * Redistributions in binary form must reproduce the above copyright notice,\n this list of conditions and the following disclaimer in the documentation\n and/or other materials provided with the distribution.\n .\n * Neither the name of Rapid7, Inc. nor the names of its contributors\n may be used to endorse or promote products derived from this software\n without specific prior written permission.\n .\n THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" AND\n ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\n WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\n DISCLAIMED. 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