Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-22688 is a critical-severity Command Injection (CWE-77) vulnerability in Tencent Weknora. Its CVSS base score is 9.9 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked in the top 23% 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 AI Agent Protocols and Integrations; in the Protocol-Specific Risks 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-2026-22688 is a command injection vulnerability (CWE-77) affecting WeKnora, an LLM-powered framework for deep document understanding and semantic retrieval. In versions prior to 0.2.5, the vulnerability enables authenticated users to inject malicious values into the stdio_config.command/args fields within MCP stdio settings. This injection causes the server to execute arbitrary subprocesses using the attacker-supplied values. The issue carries a CVSS v3.1 base score of 9.9 (AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H), indicating critical severity due to its potential for complete system compromise.
An attacker with authenticated access to the WeKnora server can exploit this vulnerability remotely over the network with low complexity and no user interaction required. By manipulating the stdio_config parameters, the attacker can execute arbitrary commands as the server process, achieving high-impact confidentiality, integrity, and availability violations. The changed scope (S:C) amplifies the risk, as successful exploitation allows control over subprocesses that could lead to full server takeover, data exfiltration, or further lateral movement.
The vulnerability has been addressed in WeKnora version 0.2.5, as detailed in the project's GitHub security advisory (GHSA-78h3-63c4-5fqc) and corresponding patch commit (f7900a5e9a18c99d25cec9589ead9e4e59ce04bb). Security practitioners should prioritize upgrading to the patched version and review access controls for authenticated users interacting with MCP stdio configurations.
As an LLM-powered framework, this vulnerability highlights risks in AI/ML pipelines where untrusted inputs can propagate to system-level execution, though no evidence of real-world exploitation is reported in available sources.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-1695
Vulnerability Data
WeKnora is an LLM-powered framework designed for deep document understanding and semantic retrieval. Prior to version 0.2.5, there is a command injection vulnerability that allows authenticated users to inject stdio_config.command/args into MCP stdio settings, causing the server to execute subprocesses…
more
using these injected values. This issue has been patched in version 0.2.5.
- CWE(s)
AI Security AnalysisAI
- AI Category
- AI Agent Protocols and Integrations
- Risk Domain
- Protocol-Specific Risks
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: llm, mcp
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.3V1.2.5V1.2.8V1.2.9
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover command-construction flaws before deployment.
Input validation directly stops construction of commands from untrusted data containing special elements.
Secure engineering principles include proper neutralization and safe command construction practices.
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 input validation and neutralization that prevent command injection.
Runtime monitoring of software and data can detect anomalous command execution resulting from injection.
Identifying recorded vulnerabilities enables remediation of command-injection flaws before exploitation.
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.
Secure coding standards require proper escaping and parameterization of commands, directly eliminating CWE-77.
Security testing in development catches command-injection vulnerabilities before release.
Secure development life cycle mandates input validation and command construction practices that directly prevent command injection.
Application security requirements explicitly call for controls against injection flaws including command injection.
Secure architecture principles reduce the attack surface but do not prescribe the specific neutralization techniques needed.