Raw vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:U/C:L/I:N/A:HSummary
CVE-2026-1764 is a medium-severity Out-of-bounds Read (CWE-125) vulnerability in Redhat Enterprise Linux. Its CVSS base score is 5.6 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Malicious File (T1204.002); ranked at the 11th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and SI-16 (Memory Protection) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-37025
Vulnerability Data
A flaw was found in GNOME localsearch (previously known as tracker-miners) MP3 Extractor. When processing specially crafted MP3 files containing ID3v2.4 tags, a missing bounds check in the `extract_performers_tags` function can lead to a heap buffer overflow. This vulnerability allows…
more
a remote attacker to cause a Denial of Service (DoS) by triggering a read of unmapped memory. In some cases, it could also lead to information disclosure by reading visible heap data.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Out-of-bounds read in MP3 file parser directly enables execution via a malicious file (user opens crafted MP3).
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces bounds checking and validation on untrusted MP3/ID3 input to block the out-of-bounds read in extract_performers_tags.
Applies memory-protection techniques that can contain or block exploitation of the heap buffer over-read during MP3 tag processing.
Verifies integrity of media-processing components and can detect anomalous behavior or corruption resulting from the crafted MP3 files.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure-development practices such as bounds checking and memory-safe languages directly prevent out-of-bounds reads.
Vulnerability scanning and recording can discover instances of out-of-bounds reads after code is deployed.
Routine patching replaces vulnerable code containing out-of-bounds read flaws.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing in development and acceptance includes fuzzing and static analysis that detect out-of-bounds read defects before release.
Logging can record evidence of an out-of-bounds read but does not prevent the weakness itself.
Secure development life cycle mandates input validation and bounds checking that directly prevent out-of-bounds reads.
Application security requirements include explicit bounds and memory-safety specifications that mitigate buffer over-reads.
Secure system architecture and engineering principles require memory-safe design patterns and runtime protections against out-of-bounds access.
Secure coding standards explicitly forbid unsafe pointer arithmetic and mandate bounds-checked reads, eliminating CWE-125.