CVE-2024-5171
Published: 05 June 2024
Summary
CVE-2024-5171 is a critical-severity Improper Input Validation (CWE-20) vulnerability in Aomedia Libaom. Its CVSS base score is 10.0 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Client Execution (T1203); ranked at the 41.8th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-46420
Vulnerability details
Integer overflow in libaom internal function img_alloc_helper can lead to heap buffer overflow. This function can be reached via 3 callers: * Calling aom_img_alloc() with a large value of the d_w, d_h, or align parameter may result in integer overflows…
more
in the calculations of buffer sizes and offsets and some fields of the returned aom_image_t struct may be invalid. * Calling aom_img_wrap() with a large value of the d_w, d_h, or align parameter may result in integer overflows in the calculations of buffer sizes and offsets and some fields of the returned aom_image_t struct may be invalid. * Calling aom_img_alloc_with_border() with a large value of the d_w, d_h, align, size_align, or border parameter may result in integer overflows in the calculations of buffer sizes and offsets and some fields of the returned aom_image_t struct may be invalid.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Integer overflow in libaom image allocation functions leads to heap buffer overflow, exploitable for arbitrary code execution in client applications processing crafted AV1 inputs.
MITRE ATLAS TechniquesAI
MITRE ATLAS techniques
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.