CVE-2026-61732 PUBLISHED

Decepticon: Role-boundary forgery via ChatML special-token literals in web crawl output composed into LLM context

Assigner: GitHub_M
Reserved: 10.07.2026 Published: 24.09.2026 Updated: 24.09.2026

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.

Metrics

CVSS Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
CVSS Score: 10

Product Status

Vendor BitterSecurity
Product Decepticon
Versions
  • Version < 1.1.17 is affected
Vendor BitterSecurity
Product decepticon-core
Versions
  • Version < 1.1.17 is affected
Vendor BitterSecurity
Product decepticon-sdk
Versions
  • Version < 1.1.17 is affected

References

Problem Types

  • CWE-74: Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection') CWE