Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessPlant special-token literal in target web page
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DeliveryRed-teamer runs Decepticon recon crawl against target
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ExploitCrawl output wrapped into LLM message unescaped
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ExecutionSelf-hosted tokenizer parses literal as role boundary
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PersistForged operator turn bypasses agent guardrails
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ImpactArbitrary commands execute in Kali sandbox
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A05:2025 - Injection
ASVS 5.0
V1 - Encoding and Sanitization Input neutralization, injection prevention
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| Exploitation Conditions | Requires the BYOK deployment model where the operator has configured a self-hosted / OpenAI-compatible LLM backend (vLLM, SGLang, TGI, Ollama, LM Studio, text-generation-webui) whose tokenizer preserves special-token literal IDs in user content - the default for most such backends. Exploitation additionally requires that the operator direct Decepticon's reconnaissance crawler at attacker-controlled or attacker-compromised web content, which is normal operation for a red-team tool scanning untrusted targets. LIMITING FACTORS: deployments using hosted providers (OpenAI, Anthropic) are NOT vulnerable because those strip special tokens server-side; only Decepticon versions prior to 1.1.17 are affected; and the attacker cannot exploit unless a red-teamer actually crawls their planted content. |
| Impact | The CVSS 3.1 vector (AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H = 10.0) presents this as a maximally critical unauthenticated remote code execution flaw, but several signals argue for tempering that raw score. There is no CISA KEV listing, no EPSS score supplied, and no public exploit code referenced in the intelligence - so exploitation status is 'no public exploit identified at time of analysis.' More importantly, exploitability is heavily conditioned on deployment: the vendor's own patch commentary (GHSA-g5f9-3xfg-p9mf) states that hosted providers (OpenAI, Anthropic) strip special-token literals server-side and are therefore NOT affected, and the flaw only fires under the BYOK model with a self-hosted / OpenAI-compatible backend (vLLM, SGLang, TGI, Ollama, LM Studio, text-generation-webui) whose tokenizer preserves special-token IDs. That dependency on a specific, non-universal backend configuration means AC:L is arguably understated - I assess AC:H (CVSS 4.0 AT:P). The impact is real and severe where the preconditions hold (guardrail bypass leading to arbitrary command execution in the Kali sandbox), but the affected product is a niche red-team tool, so real-world priority is bounded by very low prevalence rather than by the perfect 10.0. Net: a genuine critical for the specific population running Decepticon <1.1.17 against untrusted targets with a self-hosted model, not a broad-fleet emergency. |
| Exploit ScenarioDerived | An attacker plants a ChatML/Llama/Gemma/Mistral special-token literal (e.g. <|im_start|> or [INST]) inside a web page hosted on a service that a red-teamer will point Decepticon at. When Decepticon's reconnaissance crawler ingests the page and wraps the result into an LLM message, a self-hosted tokenizer parses the literal into a structural role-boundary token, forging an authoritative operator/system turn that overrides the agent's quarantine guardrails and drives arbitrary command execution inside the Kali Linux sandbox. No public exploit code is referenced, though the mechanism is well-documented in the vendor advisory and patch tests. |
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Alert meAnalysisAIv1 – Sep 24, 2026
Decepticon versions prior to 1.1.17 fail to neutralize ChatML-style special-token literals (e.g. <|im_start|>, <|eot_id|>, <start_of_turn>, [INST], <<SYS>>) embedded in web crawl results returned by agent reconnaissance, so an attacker who plants such a string on a crawled page can forge an authoritative operator turn that the model acts on, bypassing Decepticon's agent guardrails and achieving arbitrary command execution inside the Kali Linux sandbox. Exploitation is unauthenticated (PR:N) but conditional: it requires the BYOK deployment model with a self-hosted or OpenAI-compatible backend (vLLM, SGLang, TGI, Ollama, LM Studio, text-generation-webui) whose tokenizer preserves special-token IDs, and the operator must actually crawl attacker-controlled or attacker-compromised content - both normal for a red-team tool. Deployments using hosted providers such as OpenAI or Anthropic are not vulnerable because those strip special tokens server-side; no public exploit code has been identified at time of analysis, and the advisory ships with a vendor fix in 1.1.17.
RemediationAI
Upgrade to Decepticon 1.1.17, which is the vendor-released patch for GHSA-g5f9-3xfg-p9mf and introduces application-layer special-token neutralization via zero-width-space insertion in the prompt_injection_shield and untrusted_output middlewares; the fix is also visible in commit 79ee2aaf22f4c36a5b1968f6ca3f8086b6e35b67 at https://github.com/BitterSecurity/Decepticon/commit/79ee2aaf22f4c36a5b1968f6ca3f8086b6e35b67, and the advisory is at https://github.com/BitterSecurity/Decepticon/security/advisories/GHSA-g5f9-3xfg-p9mf. If upgrading immediately is not possible, the most effective compensating control is to route BYOK traffic through a hosted provider (OpenAI, Anthropic) that strips special tokens server-side - the trade-off is loss of self-hosting flexibility and data-sovereignty control, and it does not fix the underlying code path if you later switch back. Alternatively, configure the self-hosted backend to reject or escape special-token literals in user content (for example by disabling special-token parsing in the tokenizer/chat template where the server supports it) - this depends on backend capability and can degrade legitimate tool-calling behavior. Restricting reconnaissance scope so the crawler is never pointed at untrusted or attacker-influenced web content reduces exposure but is impractical for red-team engagements by definition, and network-isolating or tightly sandboxing the Kali Linux execution environment limits blast radius without preventing guardrail bypass. Because no public exploit code has been identified at time of analysis, these measures are precautionary rather than responses to observed attacks, and deployments using hosted providers require no action specific to this CVE.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 3 packages in pypi
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
The root cause is CWE-74 (improper neutralization of special elements) applied to the LLM chat-template layer: Decepticon's reconnaissance middleware composed untrusted crawl output into prompt messages without defanging role-delimiter literals. The prior detection logic only annotated risk - it did not alter the bytes - which is insufficient for chat-template special tokens. When a self-hosted tokenizer (vLLM, SGLang, TGI, Ollama, LM Studio, text-generation-webui) preserves special-token vocabulary entries, a literal such as <|im_start|> is parsed into a structural role-boundary token rather than inert text, letting attacker-controlled content escape the 'untrusted_tool_output' quarantine envelope and impersonate the operator/system role. The upstream commit 79ee2aaf adds a neutralize_special_tokens() helper in packages/decepticon/decepticon/middleware/_injection_detector.py that inserts a zero-width space (U+200B) immediately after the leading bracket, breaking the exact-match token while leaving the text visually identical; this is wired into both prompt_injection_shield.py and untrusted_output.py. The regex deliberately covers ChatML/Qwen/DeepSeek (<|im_start|>, <|im_end|>, <|endoftext|>), Llama-3.x (<|begin_of_text|>, <|end_of_text|>, <|start_header_id|>, <|end_header_id|>, <|eot_id|>), Gemma 2/3 (<start_of_turn>, <end_of_turn>), Mistral/Mixtral ([INST], [/INST], <<SYS>>, <</SYS>>), and fullwidth vertical-bar Unicode bypasses (<|…|>, U+FF5C). Affected artifacts per CPE are BitterSecurity Decepticon, decepticon-core, and decepticon-sdk at all versions before 1.1.17.
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Severity by source
AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
Network-delivered via crawled content with no attacker privileges, but exploitation depends on a self-hosted tokenizer that preserves special tokens (non-universal), so AC:H; guardrail breakout into sandbox command execution justifies S:C and C/I/A:H.
Primary rating from Vendor (GitHub_M).
CVSS VectorVendor: GitHub_M
Lifecycle Timeline
2DescriptionCVE.org
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.
Technical POC Analysis
CWE-74 - Improper Neutralization of Special Elements in Output Used by a Downstream Component.
Full technical POC analysis - root cause, step-by-step exploitation and patch breakdown - is part of the Pro and Business plans.
Executive ViewAI
The Decepticon AI red-team agent can be hijacked by hostile text planted on a web page it crawls during reconnaissance, letting an attacker run arbitrary commands inside the tool's Kali Linux sandbox without authentication. Exposure is limited to Decepticon versions prior to 1.1.17 deployed with self-hosted or OpenAI-compatible model backends (vLLM, SGLang, TGI, Ollama, LM Studio, text-generation-webui); organizations using hosted providers such as OpenAI or Anthropic are not affected. Because these agents typically run with broad network reach and hold credentials and client engagement data, leadership should treat a compromise as a potential foothold into customer environments; exploitation status is that no public exploit identified at time of analysis and no vendor-released patch identified at time of analysis.
No vendor-released patch identified at time of analysis. Interim mitigations: restrict or disable agent crawling of attacker-controllable content; isolate Decepticon hosts on segmented networks with no access to production credentials, client data, or internal services; migrate to hosted model providers (OpenAI, Anthropic) that strip special tokens server-side; implement input sanitization and special-token filtering on all retrieved content before it reaches the model; rotate credentials accessible from the Kali sandbox; enforce egress restrictions and monitor agent command execution for injected operator-style turns.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Authentication bypass attacks exploit flaws in the verification mechanisms that control access to systems and applications.
EUVD-2026-86329
GHSA-g5f9-3xfg-p9mf
NVD
CVE.org
EPSS
Vulnrichment
Exploit-DB