GHSA-g5f9-3xfg-p9mf: Decepticon: Role-boundary forgery via ChatML special-token literals in web crawl output composed into LLM context

Decepticon is vulnerable to role-boundary forgery when web crawl results containing ChatML special-token literals (special symbols that mark conversation roles in LLM message formatting) are inserted into LLM messages without being neutralized. Attackers can plant malicious tokens in target web pages; when the recon agent scrapes these pages and feeds them to the LLM, the tokens trick the model into treating attacker input as a legitimate new instruction, bypassing security guardrails and enabling arbitrary command execution. The vulnerability affects all 16 specialist agents in Decepticon when using self-hosted or open-source LLM backends (like vLLM or SGLang) that don't filter these literals, though hosted services like OpenAI and Anthropic are currently immune because they strip the literals server-side.