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      <title>bdu:2025-12549</title>
      <link>https://cve.radiocsirt.org/vuln/bdu:2025-12549</link>
      <description>bdu:2025-12549</description>
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      <title>certfr-2025-avi-0969 — De multiples vulnérabilités ont été découvertes dans les produits VMware. Elles permettent à un attaquant de provoquer…</title>
      <link>https://cve.radiocsirt.org/vuln/certfr-2025-avi-0969</link>
      <description>certfr-2025-avi-0969</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/certfr-2025-avi-0969</guid>
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      <title>EUVD-2026-252677</title>
      <link>https://cve.radiocsirt.org/vuln/euvd-2026-252677</link>
      <description>EUVD-2026-252677</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/euvd-2026-252677</guid>
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      <title>fkie_cve-2025-6051</title>
      <link>https://cve.radiocsirt.org/vuln/fkie_cve-2025-6051</link>
      <description>&lt;p&gt;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&amp;#39;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.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;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&amp;#39;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.&lt;/p&gt;</content:encoded>
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      <title>GHSA-rcv9-qm8p-9p6j — Hugging Face Transformers library has Regular Expression Denial of Service</title>
      <link>https://cve.radiocsirt.org/vuln/ghsa-rcv9-qm8p-9p6j</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: transformers&lt;/p&gt;
&lt;p&gt;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&amp;#39;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.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: transformers&lt;/p&gt;
&lt;p&gt;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&amp;#39;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.&lt;/p&gt;</content:encoded>
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      <title>PYSEC-2026-1988 — Hugging Face Transformers library has Regular Expression Denial of Service</title>
      <link>https://cve.radiocsirt.org/vuln/pysec-2026-1988</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: transformers&lt;/p&gt;
&lt;p&gt;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&amp;#39;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.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: transformers&lt;/p&gt;
&lt;p&gt;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&amp;#39;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.&lt;/p&gt;</content:encoded>
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