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.
Published: 2026-09-24
Score: 10 Critical
EPSS: 1.2% Low
KEV: No
Impact: Remote Code Execution
Action: Patch
AI Analysis

Impact

Decepticon, an autonomous hacking agent for red teams, is vulnerable when earlier versions wrap web crawl results into large language model messages without removing special-token literals specific to ChatML. These literals are interpreted as role‑boundary tokens, allowing attacker‑inserted strings on a target web page to forge a new operator turn that the model treats as authoritative. This bypasses Decepticon’s guardrails and permits the attacker to execute arbitrary commands inside the Kali Linux sandbox, resulting in full compromise of the sandbox environment.

Affected Systems

The affected products are BitterSecurity’s Decepticon, Decepticon‑core and Decepticon‑sdk. Vulnerable releases are all versions prior to v1.1.17; the fix is included in v1.1.17 and later.

Risk and Exploitability

The CVSS score of 10 signals a critical vulnerability. Although the EPSS score is not available and the issue is not listed in CISA’s KEV catalog, the likely attack vector requires that the user has deployed Decepticon with a Bring‑Your‑Own‑Key LLM endpoint that does not strip ChatML special‑token literals. Based on the description, an attacker can inject malicious content into a target web page, which is then re‑interpreted by the LLM and executed in the sandbox with full privileges. With no known mitigated status and a critical severity, the risk is high for any environment running the vulnerable Decepticon components.

Generated by OpenCVE AI on September 25, 2026 at 06:14 UTC.

Remediation

No vendor fix or workaround currently provided.

OpenCVE Recommended Actions

  • Apply the official patch to Decepticon version 1.1.17 or later.
  • Reconfigure the OpenAI‑compatible LLM endpoint to filter or reject ChatML special‑token literals in user content.
  • Validate target web pages for embedded malicious strings before the agent performs reconnaissance and limit automatic crawling to trusted domains.

Generated by OpenCVE AI on September 25, 2026 at 06:14 UTC.

Tracking

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

Fri, 25 Sep 2026 14:45:00 +0000

Type Values Removed Values Added
First Time appeared Bittersecurity
Bittersecurity decepticon
Bittersecurity decepticon-core
Bittersecurity decepticon-sdk
Vendors & Products Bittersecurity
Bittersecurity decepticon
Bittersecurity decepticon-core
Bittersecurity decepticon-sdk

Thu, 24 Sep 2026 17:45:00 +0000

Type Values Removed Values Added
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.
Title Decepticon: Role-boundary forgery via ChatML special-token literals in web crawl output composed into LLM context
Weaknesses CWE-74
References
Metrics cvssV3_1

{'score': 10, 'vector': 'CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H'}


Subscriptions

Bittersecurity Decepticon Decepticon-core Decepticon-sdk
cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published:

Updated: 2026-09-24T18:00:43.383Z

Reserved: 2026-07-10T18:59:00.046Z

Link: CVE-2026-61732

cve-icon Vulnrichment

No data.

cve-icon NVD

Status : Received

Published: 2026-09-24T18:17:15.860

Modified: 2026-09-24T19:17:14.910

Link: CVE-2026-61732

cve-icon Redhat

No data.

cve-icon OpenCVE Enrichment

Updated: 2026-09-25T14:16:28Z

Weaknesses
  • CWE-74

    Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')