<?xml version='1.0' encoding='UTF-8'?>
<?xml-stylesheet href="/static/style.xsl" type="text/xsl"?>
<rss xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/" version="2.0">
  <channel>
    <title>Most recent entries from all</title>
    <link>https://cve.radiocsirt.org</link>
    <description>Contains only the most 10 recent entries.</description>
    <docs>http://www.rssboard.org/rss-specification</docs>
    <generator>python-feedgen</generator>
    <language>en</language>
    <lastBuildDate>Sun, 04 Oct 2026 13:20:35 +0000</lastBuildDate>
    <item>
      <title>bdu:2025-14680</title>
      <link>https://cve.radiocsirt.org/vuln/bdu:2025-14680</link>
      <description>bdu:2025-14680</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/bdu:2025-14680</guid>
    </item>
    <item>
      <title>certfr-2025-avi-1057 — 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-1057</link>
      <description>certfr-2025-avi-1057</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/certfr-2025-avi-1057</guid>
    </item>
    <item>
      <title>EUVD-2026-261777</title>
      <link>https://cve.radiocsirt.org/vuln/euvd-2026-261777</link>
      <description>EUVD-2026-261777</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/euvd-2026-261777</guid>
    </item>
    <item>
      <title>fkie_cve-2025-62426</title>
      <link>https://cve.radiocsirt.org/vuln/fkie_cve-2025-62426</link>
      <description>&lt;p&gt;vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before 0.11.1, the /v1/chat/completions and /tokenize endpoints allow a chat_template_kwargs request parameter that is used in the code before it is properly validated against the chat template. With the right chat_template_kwargs parameters, it is possible to block processing of the API server for long periods of time, delaying all other requests. This issue has been patched in version 0.11.1.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before 0.11.1, the /v1/chat/completions and /tokenize endpoints allow a chat_template_kwargs request parameter that is used in the code before it is properly validated against the chat template. With the right chat_template_kwargs parameters, it is possible to block processing of the API server for long periods of time, delaying all other requests. This issue has been patched in version 0.11.1.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/fkie_cve-2025-62426</guid>
    </item>
    <item>
      <title>GHSA-69j4-grxj-j64p — vLLM vulnerable to DoS via large Chat Completion or Tokenization requests with specially crafted `chat_template_kwargs`</title>
      <link>https://cve.radiocsirt.org/vuln/ghsa-69j4-grxj-j64p</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: vllm&lt;/p&gt;
&lt;p&gt;### Summary
The /v1/chat/completions and /tokenize endpoints allow a `chat_template_kwargs` request parameter that is used in the code before it is properly validated against the chat template. With the right `chat_template_kwargs` parameters, it is possible to block processing of the API server for long periods of time, delaying all other requests&lt;/p&gt;
&lt;p&gt;### Details
In serving_engine.py, the chat_template_kwargs are unpacked into kwargs passed to chat_utils.py `apply_hf_chat_template` with no validation on the keys or values in that chat_template_kwargs dict. This means they can be used to override optional parameters in the `apply_hf_chat_template` method, such as `tokenize`, changing its default from False to True.&lt;/p&gt;
&lt;p&gt;https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/openai/serving_engine.py#L809-L814&lt;/p&gt;
&lt;p&gt;https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/chat_utils.py#L1602-L1610&lt;/p&gt;
&lt;p&gt;Both serving_chat.py and serving_tokenization.py call into this `_preprocess_chat` method of `serving_engine.py` and they both pass in `chat_template_kwargs`.&lt;/p&gt;
&lt;p&gt;So, a `chat_template_kwargs` like `{&amp;#34;tokenize&amp;#34;: True}` makes tokenization happen as part of applying the chat template, even though that is not expected. Tokenization is a blocking operation, and with sufficiently large input can block the API server&amp;#39;s event loop, which blocks handling of all other requests until this tokenization is complete.&lt;/p&gt;
&lt;p&gt;This…&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: vllm&lt;/p&gt;
&lt;p&gt;### Summary
The /v1/chat/completions and /tokenize endpoints allow a `chat_template_kwargs` request parameter that is used in the code before it is properly validated against the chat template. With the right `chat_template_kwargs` parameters, it is possible to block processing of the API server for long periods of time, delaying all other requests&lt;/p&gt;
&lt;p&gt;### Details
In serving_engine.py, the chat_template_kwargs are unpacked into kwargs passed to chat_utils.py `apply_hf_chat_template` with no validation on the keys or values in that chat_template_kwargs dict. This means they can be used to override optional parameters in the `apply_hf_chat_template` method, such as `tokenize`, changing its default from False to True.&lt;/p&gt;
&lt;p&gt;https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/openai/serving_engine.py#L809-L814&lt;/p&gt;
&lt;p&gt;https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/chat_utils.py#L1602-L1610&lt;/p&gt;
&lt;p&gt;Both serving_chat.py and serving_tokenization.py call into this `_preprocess_chat` method of `serving_engine.py` and they both pass in `chat_template_kwargs`.&lt;/p&gt;
&lt;p&gt;So, a `chat_template_kwargs` like `{&amp;#34;tokenize&amp;#34;: True}` makes tokenization happen as part of applying the chat template, even though that is not expected. Tokenization is a blocking operation, and with sufficiently large input can block the API server&amp;#39;s event loop, which blocks handling of all other requests until this tokenization is complete.&lt;/p&gt;
&lt;p&gt;This…&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/ghsa-69j4-grxj-j64p</guid>
    </item>
    <item>
      <title>PYSEC-2026-2012 — vLLM vulnerable to DoS via large Chat Completion or Tokenization requests with specially crafted `chat_template_kwargs`</title>
      <link>https://cve.radiocsirt.org/vuln/pysec-2026-2012</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: vllm&lt;/p&gt;
&lt;p&gt;### Summary
The /v1/chat/completions and /tokenize endpoints allow a `chat_template_kwargs` request parameter that is used in the code before it is properly validated against the chat template. With the right `chat_template_kwargs` parameters, it is possible to block processing of the API server for long periods of time, delaying all other requests&lt;/p&gt;
&lt;p&gt;### Details
In serving_engine.py, the chat_template_kwargs are unpacked into kwargs passed to chat_utils.py `apply_hf_chat_template` with no validation on the keys or values in that chat_template_kwargs dict. This means they can be used to override optional parameters in the `apply_hf_chat_template` method, such as `tokenize`, changing its default from False to True.&lt;/p&gt;
&lt;p&gt;https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/openai/serving_engine.py#L809-L814&lt;/p&gt;
&lt;p&gt;https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/chat_utils.py#L1602-L1610&lt;/p&gt;
&lt;p&gt;Both serving_chat.py and serving_tokenization.py call into this `_preprocess_chat` method of `serving_engine.py` and they both pass in `chat_template_kwargs`.&lt;/p&gt;
&lt;p&gt;So, a `chat_template_kwargs` like `{&amp;#34;tokenize&amp;#34;: True}` makes tokenization happen as part of applying the chat template, even though that is not expected. Tokenization is a blocking operation, and with sufficiently large input can block the API server&amp;#39;s event loop, which blocks handling of all other requests until this tokenization is complete.&lt;/p&gt;
&lt;p&gt;This…&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: vllm&lt;/p&gt;
&lt;p&gt;### Summary
The /v1/chat/completions and /tokenize endpoints allow a `chat_template_kwargs` request parameter that is used in the code before it is properly validated against the chat template. With the right `chat_template_kwargs` parameters, it is possible to block processing of the API server for long periods of time, delaying all other requests&lt;/p&gt;
&lt;p&gt;### Details
In serving_engine.py, the chat_template_kwargs are unpacked into kwargs passed to chat_utils.py `apply_hf_chat_template` with no validation on the keys or values in that chat_template_kwargs dict. This means they can be used to override optional parameters in the `apply_hf_chat_template` method, such as `tokenize`, changing its default from False to True.&lt;/p&gt;
&lt;p&gt;https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/openai/serving_engine.py#L809-L814&lt;/p&gt;
&lt;p&gt;https://github.com/vllm-project/vllm/blob/2a6dc67eb520ddb9c4138d8b35ed6fe6226997fb/vllm/entrypoints/chat_utils.py#L1602-L1610&lt;/p&gt;
&lt;p&gt;Both serving_chat.py and serving_tokenization.py call into this `_preprocess_chat` method of `serving_engine.py` and they both pass in `chat_template_kwargs`.&lt;/p&gt;
&lt;p&gt;So, a `chat_template_kwargs` like `{&amp;#34;tokenize&amp;#34;: True}` makes tokenization happen as part of applying the chat template, even though that is not expected. Tokenization is a blocking operation, and with sufficiently large input can block the API server&amp;#39;s event loop, which blocks handling of all other requests until this tokenization is complete.&lt;/p&gt;
&lt;p&gt;This…&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/pysec-2026-2012</guid>
    </item>
    <item>
      <title>RHSA-2026:3461 — Red Hat Security Advisory: Red Hat AI Inference Server 3.2.2 (CUDA)</title>
      <link>https://cve.radiocsirt.org/vuln/rhsa-2026:3461</link>
      <description>&lt;p&gt;ray: Ray Job Submission Arbitrary Code Execution libtiff: TIFFRasterScanlineSize64 produce too-big size and could cause OOM libtiff: Segment fault in libtiff  in TIFFReadRGBATileExt() leading to denial of service shadow-utils: Default subordinate ID configuration in /etc/login.defs could lead to compromise libssh: out-of-bounds read in sftp_handle() vllm: Server Side request forgery (SSRF) in MediaConnector sqlite: Integer Truncation in SQLite libtiff: LibTIFF Use-After-Free Vulnerability openssl: Out-of-bounds read &amp;amp; write in RFC 3211 KEK Unwrap libxslt: libxml2: Inifinite recursion at exsltDynMapFunction function in libexslt/dynamic.c libtiff: Libtiff Write-What-Where openssl: OpenSSL: Remote code execution or Denial of Service via oversized Initialization Vector in CMS parsing golang.org/x/oauth2/jws: Unexpected memory consumption during token parsing in golang.org/x/oauth2/jws golang.org/x/crypto/ssh: Denial of Service in the Key Exchange of golang.org/x/crypto/ssh os/exec: Unexpected paths returned from LookPath in os/exec runc: container escape with malicious config due to /dev/console mount and related races vim: Vim path traversial vim: Vim path traversal firefox: thunderbird: expat: libexpat in Expat allows attackers to trigger large dynamic memory allocations via a small document that is submitted for parsing vllm: Timing Attack in vLLM API Token Verification Leading to Authentication Bypass vllm: vLLM OpenAI-Compatible Server Resource Exhaustion via chat_template…&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;ray: Ray Job Submission Arbitrary Code Execution libtiff: TIFFRasterScanlineSize64 produce too-big size and could cause OOM libtiff: Segment fault in libtiff  in TIFFReadRGBATileExt() leading to denial of service shadow-utils: Default subordinate ID configuration in /etc/login.defs could lead to compromise libssh: out-of-bounds read in sftp_handle() vllm: Server Side request forgery (SSRF) in MediaConnector sqlite: Integer Truncation in SQLite libtiff: LibTIFF Use-After-Free Vulnerability openssl: Out-of-bounds read &amp;amp; write in RFC 3211 KEK Unwrap libxslt: libxml2: Inifinite recursion at exsltDynMapFunction function in libexslt/dynamic.c libtiff: Libtiff Write-What-Where openssl: OpenSSL: Remote code execution or Denial of Service via oversized Initialization Vector in CMS parsing golang.org/x/oauth2/jws: Unexpected memory consumption during token parsing in golang.org/x/oauth2/jws golang.org/x/crypto/ssh: Denial of Service in the Key Exchange of golang.org/x/crypto/ssh os/exec: Unexpected paths returned from LookPath in os/exec runc: container escape with malicious config due to /dev/console mount and related races vim: Vim path traversial vim: Vim path traversal firefox: thunderbird: expat: libexpat in Expat allows attackers to trigger large dynamic memory allocations via a small document that is submitted for parsing vllm: Timing Attack in vLLM API Token Verification Leading to Authentication Bypass vllm: vLLM OpenAI-Compatible Server Resource Exhaustion via chat_template…&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/rhsa-2026:3461</guid>
    </item>
  </channel>
</rss>
