CVE-2024-42358
Aug. 6, 2024, 5:15 p.m.
6.2
Medium
Description
PDFio is a simple C library for reading and writing PDF files. There is a denial of service (DOS) vulnerability in the TTF parser. Maliciously crafted TTF files can cause the program to utilize 100% of the Memory and enter an infinite loop. This can also lead to a heap-buffer-overflow vulnerability. An infinite loop occurs in the read_camp function by nGroups value. The ttf.h library is vulnerable. A value called nGroups is extracted from the file, and by changing that value, you can cause the program to utilize 100% of the Memory and enter an infinite loop. If the value of nGroups in the file is small, an infinite loop will not occur. This library, whether used as a standalone binary or as part of another application, is vulnerable to DOS attacks when parsing certain types of files. Automated systems, including web servers that use this code to convert PDF submissions into plaintext, can be DOSed if an attacker uploads a malicious TTF file. This issue has been addressed in release version 1.3.1. All users are advised to upgrade. There are no known workarounds for this vulnerability.
Product(s) Impacted
| Product | Versions |
|---|---|
| PDFio |
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-835
Loop with Unreachable Exit Condition ('Infinite Loop')
The product contains an iteration or loop with an exit condition that cannot be reached, i.e., an infinite loop.
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: LOCAL
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: UNCHANGED
- Confidentiality Impact: NONE
- Integrity Impact: NONE
- Availability Impact: HIGH
CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Timeline
Published: Aug. 6, 2024, 5:15 p.m.
Last Modified: Aug. 6, 2024, 5:15 p.m.
Last Modified: Aug. 6, 2024, 5:15 p.m.
Status : Received
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
security-advisories@github.com
*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.