{"id":"CVE-2026-61732","state":"PUBLISHED","title":"Decepticon: Role-boundary forgery via ChatML special-token literals in web crawl output composed into LLM context","description":"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.","publishedAt":"2026-09-24T17:40:51.248Z","updatedAt":"2026-09-24T18:00:43.383Z","severity":{"score":10,"label":"Critical","version":"3.1","vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H","source":"GitHub_M"},"assigner":"GitHub_M","products":["BitterSecurity Decepticon","BitterSecurity decepticon-core","BitterSecurity decepticon-sdk"],"affected":[{"vendor":"BitterSecurity","product":"Decepticon","versions":[{"version":"< 1.1.17","status":"affected"}]},{"vendor":"BitterSecurity","product":"decepticon-core","versions":[{"version":"< 1.1.17","status":"affected"}]},{"vendor":"BitterSecurity","product":"decepticon-sdk","versions":[{"version":"< 1.1.17","status":"affected"}]}],"references":["https://github.com/BitterSecurity/Decepticon/security/advisories/GHSA-g5f9-3xfg-p9mf","https://github.com/BitterSecurity/Decepticon/commit/79ee2aaf22f4c36a5b1968f6ca3f8086b6e35b67"],"weaknesses":["CWE-74"],"ingestedAt":"2026-10-29T20:12:32.778Z","source":{"repository":"CVEProject/cvelistV5","path":"cves/2026/61xxx/CVE-2026-61732.json","commit":"556c9d3a8cd17e218bb8e452ba7cd619a384ff47"},"raw":{"dataType":"CVE_RECORD","dataVersion":"5.2","cveMetadata":{"cveId":"CVE-2026-61732","state":"PUBLISHED","datePublished":"2026-09-24T17:40:51.248Z","dateUpdated":"2026-09-24T18:00:43.383Z","assignerShortName":"GitHub_M","assignerOrgId":"a0819718-46f1-4df5-94e2-005712e83aaa","dateReserved":"2026-07-10T18:59:00.046Z"},"containers":{"cna":{"title":"Decepticon: Role-boundary forgery via ChatML special-token literals in web crawl output composed into LLM context","descriptions":[{"lang":"en","value":"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."}],"affected":[{"vendor":"BitterSecurity","product":"Decepticon","versions":[{"version":"< 1.1.17","status":"affected"}]},{"vendor":"BitterSecurity","product":"decepticon-core","versions":[{"version":"< 1.1.17","status":"affected"}]},{"vendor":"BitterSecurity","product":"decepticon-sdk","versions":[{"version":"< 1.1.17","status":"affected"}]}],"references":[{"url":"https://github.com/BitterSecurity/Decepticon/security/advisories/GHSA-g5f9-3xfg-p9mf","name":"https://github.com/BitterSecurity/Decepticon/security/advisories/GHSA-g5f9-3xfg-p9mf","tags":["x_refsource_CONFIRM"]},{"url":"https://github.com/BitterSecurity/Decepticon/commit/79ee2aaf22f4c36a5b1968f6ca3f8086b6e35b67","name":"https://github.com/BitterSecurity/Decepticon/commit/79ee2aaf22f4c36a5b1968f6ca3f8086b6e35b67","tags":["x_refsource_MISC"]}],"metrics":[{"cvssV3_1":{"attackComplexity":"LOW","attackVector":"NETWORK","availabilityImpact":"HIGH","baseScore":10,"baseSeverity":"CRITICAL","confidentialityImpact":"HIGH","integrityImpact":"HIGH","privilegesRequired":"NONE","scope":"CHANGED","userInteraction":"NONE","vectorString":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H","version":"3.1"}}],"problemTypes":[{"descriptions":[{"cweId":"CWE-74","lang":"en","description":"CWE-74: Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')","type":"CWE"}]}],"providerMetadata":{"shortName":"GitHub_M","orgId":"a0819718-46f1-4df5-94e2-005712e83aaa","dateUpdated":"2026-09-24T17:40:51.248Z"},"source":{"advisory":"GHSA-g5f9-3xfg-p9mf","discovery":"UNKNOWN"}},"adp":[{"title":"CISA ADP Vulnrichment","references":[{"url":"https://github.com/BitterSecurity/Decepticon/security/advisories/GHSA-g5f9-3xfg-p9mf","tags":["exploit"]}],"metrics":[{"other":{"type":"ssvc","content":{"timestamp":"2026-09-24T17:59:08.643777Z","id":"CVE-2026-61732","options":[{"Exploitation":"poc"},{"Automatable":"yes"},{"Technical Impact":"total"}],"role":"CISA Coordinator","version":"2.0.3"}}}],"providerMetadata":{"shortName":"CISA-ADP","orgId":"134c704f-9b21-4f2e-91b3-4a467353bcc0","dateUpdated":"2026-09-24T18:00:43.383Z"}}]}}}