CVE-2026-35093
Freedesktop Libinput ≤ 1.30.3
Raw vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:HSummary
CVE-2026-35093 is a high-severity Code Injection (CWE-94) vulnerability in Freedesktop Libinput. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked at the 8th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
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-2026-35093 is a code injection vulnerability (CWE-94) in libinput, a library used for handling input devices in Linux graphical environments. The flaw allows a local attacker to place a specially crafted Lua bytecode file in certain system or user configuration directories, bypassing security restrictions. This enables the execution of unauthorized code with the same permissions as the affected program, such as a graphical compositor that relies on libinput. The vulnerability carries a CVSS v3.1 base score of 8.8 (AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H), indicating high severity due to its potential for privilege escalation and broad impact.
A local attacker with low privileges (PR:L) can exploit this vulnerability with low complexity and no user interaction required. By placing the malicious Lua bytecode in accessible configuration paths, the attacker achieves remote code execution in the context of the libinput-using process, such as a compositor. This grants the ability to monitor keyboard input and transmit it to an external location, effectively enabling keylogging and data exfiltration with high confidentiality, integrity, and availability impacts, compounded by the changed scope (S:C).
Red Hat advisories detail the issue at https://access.redhat.com/security/cve/CVE-2026-35093 and https://bugzilla.redhat.com/show_bug.cgi?id=2453839, while the libinput project tracks it via https://gitlab.freedesktop.org/libinput/libinput/-/work_items/1271. These resources provide guidance on patches and mitigation steps for affected systems.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-17907
Vulnerability Data
A flaw was found in libinput. A local attacker who can place a specially crafted Lua bytecode file in certain system or user configuration directories can bypass security restrictions. This allows the attacker to run unauthorized code with the same…
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permissions as the program using libinput, such as a graphical compositor. This could lead to the attacker monitoring keyboard input and sending that information to an external location.
- CWE(s)
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.