cmark-gfm <0.29.0.gfm.7 OOBR in validate_protocol
CVE-2023-22485 Published on January 24, 2023
cmark-gfm out-of-bounds read in validate_protocol
cmark-gfm is GitHub's fork of cmark, a CommonMark parsing and rendering library and program in C. In versions prior 0.29.0.gfm.7, a crafted markdown document can trigger an out-of-bounds read in the `validate_protocol` function. We believe this bug is harmless in practice, because the out-of-bounds read accesses `malloc` metadata without causing any visible damage.This vulnerability has been patched in 0.29.0.gfm.7.
Vulnerability Analysis
CVE-2023-22485 can be exploited with network access, and does not require authorization privileges or user interaction. This vulnerability is considered to have a low attack complexity. An automatable proof of concept (POC) exploit exists. The potential impact of an exploit of this vulnerability is considered to have a small impact on confidentiality, a small impact on integrity and availability.
Weakness Type
Out-of-bounds Read
The software reads data past the end, or before the beginning, of the intended buffer. Typically, this can allow attackers to read sensitive information from other memory locations or cause a crash. A crash can occur when the code reads a variable amount of data and assumes that a sentinel exists to stop the read operation, such as a NUL in a string. The expected sentinel might not be located in the out-of-bounds memory, causing excessive data to be read, leading to a segmentation fault or a buffer overflow. The software may modify an index or perform pointer arithmetic that references a memory location that is outside of the boundaries of the buffer. A subsequent read operation then produces undefined or unexpected results.
Products Associated with CVE-2023-22485
Want to know whenever a new CVE is published for github Cmark Gfm? stack.watch will email you.
Affected Versions
github cmark-gfm Version < 0.29.0.gfm.7 is affected by CVE-2023-22485Exploit Probability
EPSS (Exploit Prediction Scoring System) scores estimate the probability that a vulnerability will be exploited in the wild within the next 30 days. The percentile shows you how this score compares to all other vulnerabilities.