CVE-2024-6563
July 8, 2024, 4:35 p.m.
7.5
High
Description
Buffer Copy without Checking Size of Input ('Classic Buffer Overflow') vulnerability in Renesas arm-trusted-firmware allows Local Execution of Code. This vulnerability is associated with program files https://github.Com/renesas-rcar/arm-trusted-firmware/blob/rcar_gen3_v2.5/drivers/renesas/common/io/i... https://github.Com/renesas-rcar/arm-trusted-firmware/blob/rcar_gen3_v2.5/drivers/renesas/common/io/io_rcar.C .
In line 313 "addr_loaded_cnt" is checked not to be "CHECK_IMAGE_AREA_CNT" (5) or larger, this check does not halt the function. Immediately after (line 317) there will be an overflow in the buffer and the value of "dst" will be written to the area immediately after the buffer, which is "addr_loaded_cnt". This will allow an attacker to freely control the value of "addr_loaded_cnt" and thus control the destination of the write immediately after (line 318). The write in line 318 will then be fully controlled by said attacker, with whichever address and whichever value ("len") they desire.
Product(s) Impacted
| Product | Versions |
|---|---|
| arm-trusted-firmware |
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-120
Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')
The product copies an input buffer to an output buffer without verifying that the size of the input buffer is less than the size of the output buffer, leading to a buffer overflow.
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: LOCAL
- Attack Complexity: HIGH
- Privileges Required: HIGH
- Scope: CHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: HIGH
- Availability Impact: HIGH
CVSS:3.1/AV:L/AC:H/PR:H/UI:N/S:C/C:H/I:H/A:H
Timeline
Published: July 8, 2024, 4:15 p.m.
Last Modified: July 8, 2024, 4:35 p.m.
Last Modified: July 8, 2024, 4:35 p.m.
Status : Undergoing Analysis
CVE has been marked for Analysis. Normally once in this state the CVE will be analyzed by NVD staff within 24 hours.
More infoSource
cve@asrg.io
*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.