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    <title>MCP on GMO Flatt Security Research</title>
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      <title>Securing LLM Function-Calling: Risks &amp; Mitigations for AI Agents</title>
      <link>https://flatt.tech/research/posts/securing-llm-function-calling/</link>
      <pubDate>Wed, 29 Oct 2025 00:00:00 +0000</pubDate>
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      <description>&lt;h2 id=&#34;introduction&#34;&gt;Introduction&lt;/h2&gt;&#xA;&lt;p&gt;Hello. I’m Yamakawa (&lt;a href=&#34;https://x.com/dai_shopper3&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;@dai_shopper3&lt;/a&gt;&#xA;), a security engineer at GMO Flatt Security, Inc.&lt;/p&gt;&#xA;&lt;p&gt;LLMs exhibit high capabilities in various applications such as text generation, summarization, and question answering, but they have several limitations when used alone. Fundamentally, a standalone model only has the function of generating strings in response to input natural language. Therefore, to create an autonomous AI based on an LLM, a means to exchange information with the outside and execute concrete actions is necessary.&lt;/p&gt;</description>
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