Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:HSummary
CVE-2025-55733 is a critical-severity Code Injection (CWE-94) vulnerability in Thinkinai Deepchat. Its CVSS base score is 9.6 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked at the 49th percentile by exploit likelihood (below the median); 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 Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — 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.
CVE-2025-55733 is a one-click remote code execution vulnerability (CWE-94: Code Injection) in DeepChat, a smart assistant application that connects powerful AI to users' personal environments. The issue affects DeepChat versions prior to 0.3.1 and stems from insecure handling of custom deepchat: URLs by the application's URL scheme handler.
Attackers can exploit this vulnerability without privileges by embedding a specially crafted deepchat: URL on any website they control. When a victim visits the site or interacts with the link, their browser triggers the DeepChat app's custom URL handler, launching the application and processing the malicious URL, which leads to arbitrary remote code execution on the victim's machine. The CVSS v3.1 base score of 9.6 (AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H) reflects its high severity, requiring only network access and user interaction.
The vulnerability is fixed in DeepChat version 0.3.1, as detailed in the project's GitHub security advisory (GHSA-hqr4-4gfc-5p2j) and the patching commit (a0ff6f362e01ddceb7fd42d0af0b28b6184fb4d2). Users should update to 0.3.1 or later to mitigate the risk.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-25237
Vulnerability Data
DeepChat is a smart assistant that connects powerful AI to your personal world. DeepChat before 0.3.1 has a one-click remote code execution vulnerability. An attacker can exploit this vulnerability by embedding a specially crafted deepchat: URL on any website, including…
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a malicious one they control. When a victim visits such a site or clicks on the link, the browser triggers the app’s custom URL handler (deepchat:), causing the DeepChat application to launch and process the URL, leading to remote code execution on the victim’s machine. This vulnerability is fixed in 0.3.1.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: ai
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.1
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation finds code paths that accept and execute externally influenced strings.
Input validation directly stops untrusted data from being used to construct executable code without neutralization.
Least privilege limits the damage an injected code fragment can perform once executed.
Requiring documented secure development standards and tools enforces use of safe code-generation APIs and escaping.
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.
PR.PS-06's SDLC practices directly target injection flaws via secure coding and testing (mostly), yet as a single broad outcome it leaves many code-generation specifics unaddressed (partial).
PR.DS-10 protects runtime data confidentiality/integrity but has no bearing on neutralizing externally influenced input during code generation, so neither direction shows any preventive effect.
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.
Banning unapproved code samples and unauthenticated web services, combined with secure-coding standards and SAST, prevents the dynamic generation or inclusion of attacker-supplied code.
Controls that restrict unauthorized or malicious code from being introduced via external networks or removable media limit opportunities for an attacker to inject and execute arbitrary code.