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  <updated>2026-09-29T18:02:13.929989+00:00</updated>
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  <entry>
    <id>https://vulnerability.circl.lu/vuln/cve-2026-61732</id>
    <title>CVE-2026-61732 — Decepticon: Role-boundary forgery via ChatML special-token literals in web crawl output composed into LLM context</title>
    <updated>2026-09-29T18:02:15.464058+00:00</updated>
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      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> BitterSecurity Decepticon, BitterSecurity decepticon-core, BitterSecurity decepticon-sdk</p>
<p>Decepticon is an autonomous hacking agent for red teams. Versions prior to 1.1.17 wrap web crawl results — the output of agent reconnaissance against target services — into LLM messages without neutralizing ChatML special-token literals. Under the BYOK (Bring Your Own Key) deployment model, users configure their own LLM credentials to any OpenAI-compatible endpoint. Most open-source and self-deployed model providers (vLLM, SGLang, Ollama, LM Studio, text-generation-webui, etc.) do not filter special-token literals from user content in their default configurations. Those literals are parsed into structural role-boundary token IDs, meaning an attacker string planted in a target web page forges a new operator turn the model treats as authoritative, bypassing Decepticon's agent guardrails and resulting in arbitrary command execution inside the Kali Linux sandbox. Version 1.1.17 patches the issue.</p></div>
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    <link href="https://vulnerability.circl.lu/vuln/cve-2026-61732"/>
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