CVE-2024-6036
DoS in Gaizhenbiao Chuanhuchatgpt 20240410
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:HSummary
CVE-2024-6036 is a critical-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Gaizhenbiao Chuanhuchatgpt. Its CVSS base score is 9.1 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique OS Exhaustion Flood (T1499.001); ranked in the top 5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Other ATLAS/OWASP Terms risk domain.
The strongest mitigations our analysis identified map to SC-5 (Denial-of-service Protection) and SC-6 (Resource Availability) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
A vulnerability in gaizhenbiao/chuanhuchatgpt version 20240410 permits any remote user to trigger an unrestricted server restart by issuing a request to the /queue/join? endpoint containing the parameter "fn_index":66. The flaw is tracked as CVE-2024-6036 with a CVSS 3.1 score of 9.1 and is associated with CWE-400. The restart capability can interrupt service availability, lead to data loss or corruption, and affect overall system integrity.
Any unauthenticated attacker with network access can exploit the issue without user interaction, achieving denial-of-service conditions or integrity impacts through repeated or targeted restarts. The current and peak EPSS scores are both 0.0687, indicating no material increase in exploitation interest after disclosure. Public references point to a huntr.com bounty report but contain no details on patches or mitigation steps.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-47194
Vulnerability Data
A vulnerability in gaizhenbiao/chuanhuchatgpt version 20240410 allows any user to restart the server at will by sending a specific request to the `/queue/join?` endpoint with `"fn_index":66`. This unrestricted server restart capability can severely disrupt service availability, cause data loss or…
more
corruption, and potentially compromise system integrity.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- ChuanHuChatGPT (gaizhenbiao/chuanhuchatgpt) is a self-hosted web UI for ChatGPT-like AI chat assistants, supporting LLMs via APIs like OpenAI or Ollama. It uses Gradio-style endpoints (/queue/join), common in AI/ML demos, and is listed on an AI/ML bug bounty platform (huntr.com), confirming AI relevance.
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
SC-5 directly limits the effects of resource-exhaustion events that constitute uncontrolled consumption.
SC-6 enforces explicit allocation limits on resources, structurally preventing the weakness from occurring.
Process isolation confines resource consumption to separate domains, reducing blast radius without stopping the root flaw.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Explicitly requires monitoring and maintaining resource capacity, directly addressing uncontrolled consumption to preserve availability.
Continuous monitoring of computing resources can detect resource exhaustion but does not itself enforce allocation limits.
Resilience mechanisms such as avoiding single points of failure indirectly reduce impact of resource exhaustion.
Hardened configuration baselines can include resource quotas and limits that constrain consumption.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Resource-utilization monitoring and alerting on bottlenecks or overloads limits the impact of denial-of-service or resource-exhaustion attacks.
By continuously monitoring utilization, stress-testing peak loads, and maintaining documented plans to scale or throttle resources, the control directly limits an attacker’s ability to drive a system into uncontrolled resource exhaustion.
Pre-agreed severity-based prioritization and resource allocation during incident triage reduce the likelihood that an attacker-induced resource exhaustion will overwhelm the organization before corrective action is taken.
Business-continuity plans that include resource-management controls reduce the likelihood that an attacker can trigger uncontrolled resource consumption by forcing the system into a degraded or fallback state.
Defining RTOs and capacity requirements for ICT services during business-impact analysis forces organizations to provision sufficient resources and throttling mechanisms, reducing the likelihood that an attacker can induce denial-of-service through uncontrolled resource consumption.
Early notification of anomalous resource consumption or system malfunctions enables throttling or isolation before availability is lost.