Raw vector
CVSS:4.0/AV:A/AC:H/AT:N/PR:L/UI:N/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-7846 is a low-severity Race Condition (CWE-362) vulnerability. Its CVSS base score is 1.2 (Low).
Operationally, exploitation aligns with the MITRE ATT&CK technique Path Interception (T1034); ranked at the 6th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as NLP and Transformers; in the Data-Related Vulnerabilities risk domain.
The strongest mitigations our analysis identified map to AC-25 (Reference Monitor) and AC-3 (Access Enforcement) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-27392
Vulnerability Data
A vulnerability has been found in chatchat-space Langchain-Chatchat up to 0.3.1.3. Impacted is the function files of the file libs/chatchat-server/chatchat/server/api_server/openai_routes.py of the component OpenAI-Compatible File Upload API. Such manipulation of the argument file.filename leads to time-of-check time-of-use. Access to the…
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local network is required for this attack to succeed. The attack requires a high level of complexity. The exploitability is considered difficult. The exploit has been disclosed to the public and may be used. The project was informed of the problem early through an issue report but has not responded yet.
- CWE(s)
AI Security AnalysisAI
- AI Category
- NLP and Transformers
- Risk Domain
- Data-Related Vulnerabilities
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: langchain, openai
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V10.4.2V10.4.5V15.1.3V15.4.1
Mitigating Controls (NIST 800-53 r5) AI
A reference monitor that is always invoked and analyzable structurally eliminates the non-atomic check-then-use pattern underlying TOCTOU.
Access enforcement that performs an atomic check-and-use decision directly stops the window in which a TOCTOU race can be exploited.
Maintaining separate execution domains for each process structurally eliminates unintended concurrent access to the same shared resources.
Preventing unintended information transfer through shared system resources directly addresses the improper concurrent modification that defines a race condition.
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.
Secure SDLC practices directly require proper synchronization primitives and concurrency testing that prevent race conditions.
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.
Security testing can detect race conditions, but does not prevent them at design or coding time.
Secure SDLC mandates concurrency controls and synchronization primitives that directly prevent race conditions.
Application security requirements can specify thread-safety and locking rules, but do not prescribe implementation details.
Secure architecture principles require proper synchronization and resource isolation, addressing the root cause of CWE-362.
Secure coding standards explicitly forbid unsafe concurrent access patterns and mandate atomic operations or locks.
Reliable, synchronized time across systems narrows the exploitable window in which a resource state can change between a security check and its use.