CVE-2026-61732: Decepticon: Role-boundary forgery via ChatML special-token literals in web crawl output composed into LLM context
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.
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CWE-74: Exact CWE lookup
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1CVSS vectors
3Timeline events
1ADP providers
3Source links
SSVC decision data
CISA-ADPCISA Coordinator
Timestamp
Version
2.0.3
Exploitation: pocAutomatable: yesTechnical Impact: total
CVSS vector scores
1 official score
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CWE-74 · source CWE mapping
Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')
Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection') represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.