Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:HSummary
CVE-2024-49749 is a high-severity Out-of-bounds Write (CWE-787) vulnerability in Google Android. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 16th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SA-15 (Development Process, Standards, and Tools) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
The vulnerability is an out-of-bounds write caused by an integer overflow in the DGifSlurp function within dgif_lib.c. This affects the GIF image parsing component referenced in the Android security bulletin for January 2025 and is tracked under CWE-787. The flaw carries a CVSS 3.1 score of 8.8.
Remote attackers can trigger the issue over a network connection to achieve arbitrary code execution. No additional execution privileges or user interaction are required for successful exploitation.
The referenced Android security bulletin provides the official advisory and patch information for affected builds.
EPSS for the CVE rose from a low baseline to a peak of 0.0509 on 2026-03-07 before receding to the current value of 0.0269, indicating a period of increased exploitation interest after disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-43650
Vulnerability Data
In DGifSlurp of dgif_lib.c, there is a possible out of bounds write due to an integer overflow. This could lead to remote code execution with no additional execution privileges needed. User interaction is not needed for exploitation.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation (including fuzzing and bounds checks) finds out-of-bounds write flaws before deployment.
Requiring documented secure-development standards and tools can mandate bounds-checked coding practices that avoid the weakness.
Input validation can structurally reject or sanitize data that would otherwise trigger an out-of-bounds write.
Memory-protection mechanisms limit the exploitability and blast radius of a successful out-of-bounds write.
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 (static analysis, bounds checking, code review) are the primary means of preventing out-of-bounds writes.
Vulnerability scanning and recording can discover out-of-bounds write flaws so they can be remediated.
Patching or replacing vulnerable software directly eliminates known instances of this coding weakness.
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 can detect and prevent out-of-bounds write defects.
Secure development life cycle mandates practices that prevent out-of-bounds writes.
Application security requirements can specify bounds-checking and safe memory handling.
Secure architecture and engineering principles reduce the likelihood of buffer overflows.
Secure coding directly addresses out-of-bounds writes through language choice and coding standards.
Change management can enforce review gates that catch unsafe memory operations before deployment.