Decepticon: Role-boundary forgery via ChatML special-token literals in web crawl output composed into LLM context
- Published
- Last modified
- Where the record stands: published, rejected by its publisher, or superseded by another id.What do these mean? →
- published
- Whether CISA lists it in its Known Exploited Vulnerabilities catalog: proof that attackers are using it.What do these mean? →
- Not listed in CISA KEV
- Fix
- Fixed in 1.1.17
- Whether working attack code is public (Exploit-DB, Metasploit, Nuclei or GitHub). Public code makes attacks easier.What do these mean? →
- None on Exploit-DB, Metasploit or GitHub
- Exploitation: poc
- Automatable: yes
- Technical impact: total
Summary
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.
Timeline
- CVE published
- CISA SSVC assessment
Exploitation: poc · Automatable: yes · Technical impact: total
- Record last updated
Affected versions
- BitterSecurity Decepticon
fixed in 1.1.17
- BitterSecurity decepticon-core
fixed in 1.1.17
- BitterSecurity decepticon-sdk
fixed in 1.1.17
- decepticon-corePyPI
fixed in 1.1.17
- decepticonPyPI
fixed in 1.1.17
- decepticon-sdkPyPI
fixed in 1.1.17