Cyber Resilience

CVE-2023-41782

Zte Zxcloud Irai ≤ 7.23.30

Published
05 January 2024
Modified
28 January 2025
Patch / advisory
CVSS Score v3.1 3.9
Click a component to see what it means
Raw vectorCVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:U/C:L/I:N/A:L
EPSS Score 0.0020 10th percentile
Risk Priority 22 floored blend · peak EPSS

Summary

CVE-2023-41782 is a low-severity Improper Input Validation (CWE-20) vulnerability in Zte Zxcloud Irai. Its CVSS base score is 3.9 (Low).

Operationally, ranked at the 10th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

There is a DLL hijacking vulnerability in ZTE ZXCLOUD iRAI, an attacker could place a fake DLL file in a specific directory and successfully exploit this vulnerability to execute malicious code.

CWE(s)

Related Threats

CVEs Like This One

CVE-2026-40004Same product: Zte Zxcloud Irai
CVE-2023-25650Same product: Zte Zxcloud Irai
CVE-2026-44406Same product: Zte Zxcloud Irai
CVE-2023-41780Same product: Zte Zxcloud Irai
CVE-2024-22062Same product: Zte Zxcloud Irai
CVE-2023-41776Same product: Zte Zxcloud Irai
CVE-2023-41779Same product: Zte Zxcloud Irai
CVE-2023-41783Same product: Zte Zxcloud Irai
CVE-2023-25648Same product: Zte Zxcloud Irai
CVE-2026-44407Same product: Zte Zxcloud Irai

Affected Assets

zte
zxcloud irai
≤ 7.23.30

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

Detect
Catch it (NIST detect / respond)

Harden
Shrink the surface (DISA STIG)
  • 8 hardening rules · 3 OS baselines
Validate
Prove the fix (OWASP ASVS)

Likely Mitigating Controls AI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

addresses: CWE-20

Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.

addresses: CWE-20

Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.

addresses: CWE-20

Directly implements checks on information inputs to reject invalid data before processing.

addresses: CWE-20

Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.

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 mostly match
prevents

Secure SDLC practices directly require and enforce input validation during development.

PR.PS-01 partial match
prevents

Hardened configuration baselines can enforce safe search-path settings and reduce exposure.

PR.PS-05 partial match
prevents

Execution allow-listing can block malicious binaries placed in hijackable search locations.

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.

detects

Testing against a defined set of requirements and using code review plus vulnerability scanning forces validation of inputs and handling of unanticipated conditions, reducing the chance that malformed data will be accepted.

mitigates

Restricting software installation reduces the chance that an attacker-controlled path element is introduced into the search path.

prevents

Secure-coding guidelines and mandatory security testing (including code scans) compel developers to validate and sanitize inputs at design and implementation time, lowering the incidence of malformed or malicious data reaching downstream components.

prevents

Mandating input controls that include integrity checks and input validation ensures that untrusted data is examined before use, blocking the root cause of many injection and malformed-data weaknesses.

prevents

Security-by-design principles explicitly call for data validation and sanitization at every layer, reducing the chance that malformed or malicious input will be processed without scrutiny.

prevents

Requiring language-specific secure coding standards, peer review, SAST and documented mitigation of common programming errors forces validation of all inputs before they are trusted.

References