CVE-2026-33317

April 24, 2026, 2:50 p.m.

8.7
High

Description

OP-TEE is a Trusted Execution Environment (TEE) designed as companion to a non-secure Linux kernel running on Arm; Cortex-A cores using the TrustZone technology. In versions 3.13.0 through 4.10.0, missing checks in `entry_get_attribute_value()` in `ta/pkcs11/src/object.c` can lead to out-of-bounds read from the PKCS#11 TA heap or a crash. When chained with the OOB read, the PKCS#11 TA function `PKCS11_CMD_GET_ATTRIBUTE_VALUE` or `entry_get_attribute_value()` can, with a bad template parameter, be tricked into reading at most 7 bytes beyond the end of the template buffer and writing beyond the end of the template buffer with the content of an attribute value of a PKCS#11 object. Commits e031c4e562023fd9f199e39fd2e85797e4cbdca9, 16926d5a46934c46e6656246b4fc18385a246900, and 149e8d7ecc4ef8bb00ab4a37fd2ccede6d79e1ca contain patches and are anticipated to be part of version 4.11.0.

Product(s) Impacted

Vendor Product Versions
Op-tee
  • Op-tee
  • 3.13.0-4.10.0

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-125
Out-of-bounds Read
The product reads data past the end, or before the beginning, of the intended buffer.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a op-tee op-tee 3.13.0-4.10.0 / / / / / / /

CVSS Score

8.7 / 10

CVSS Data - 3.1

  • Attack Vector: LOCAL
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: CHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: LOW
  • CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:L

    View Vector String

Timeline

Published: April 24, 2026, 3:16 a.m.
Last Modified: April 24, 2026, 2:50 p.m.

Status : Awaiting Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.