libtheora AVI Parser OOB Read
CVE-2026-5673 Published on April 6, 2026
Libtheora: libtheora: denial of service or information disclosure via malformed avi file processing
A flaw was found in libtheora. This heap-based out-of-bounds read vulnerability exists within the AVI (Audio Video Interleave) parser, specifically in the avi_parse_input_file() function. A local attacker could exploit this by tricking a user into opening a specially crafted AVI file containing a truncated header sub-chunk. This could lead to a denial-of-service (application crash) or potentially leak sensitive information from the heap.
Vulnerability Analysis
CVE-2026-5673 can be exploited with local system access, requires user interaction and a small amount of user privileges. This vulnerability is considered to have a low attack complexity. The potential impact of an exploit of this vulnerability is considered to have a small impact on confidentiality, a small impact on integrity, and a high impact on availability.
Timeline
Reported to Red Hat.
Made public.
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-2026-5673
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Affected Versions
Red Hat Enterprise Linux 10: Red Hat Enterprise Linux 6: Red Hat Enterprise Linux 7: Red Hat Enterprise Linux 8: Red Hat Enterprise Linux 9:Exploit 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.