Raw vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:HSummary
CVE-2025-48379 is a high-severity Heap-based Buffer Overflow (CWE-122) vulnerability in Python Pillow. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 19th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as Computer Vision; in the Data-Related Vulnerabilities risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-19662
Vulnerability Data
Pillow is a Python imaging library. In versions 11.2.0 to before 11.3.0, there is a heap buffer overflow when writing a sufficiently large (>64k encoded with default settings) image in the DDS format due to writing into a buffer without…
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checking for available space. This only affects users who save untrusted data as a compressed DDS image. This issue has been patched in version 11.3.0.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Computer Vision
- Risk Domain
- Data-Related Vulnerabilities
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: pillow
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.4.1
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation (including fuzzing and memory-error detectors) can discover heap overflows after they have been coded.
Input validation enforces bounds checking on data written to heap buffers, directly stopping the overflow condition from being introduced.
Security engineering principles require use of memory-safe constructs and bounds-checked allocation routines that avoid introducing heap overflows.
Memory-protection mechanisms limit the ability of a heap overflow to execute attacker-controlled code or corrupt adjacent structures.
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 directly require bounds checking and safe memory handling that prevent heap overflows.
Vulnerability scanning and recording can discover heap-overflow flaws but does not prevent their introduction in code.
Timely patching removes known heap-overflow instances after they exist.
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 heap overflows before release.
Secure development lifecycle mandates practices that reduce the likelihood of introducing heap overflows.
Application security requirements can specify bounds-checking and safe memory APIs that mitigate heap overflows.
Secure architecture and engineering principles include memory-safety and input-validation controls that address heap overflows.
Secure coding standards directly prescribe techniques (safe functions, bounds checks) that prevent heap-based buffer overflows.
Change management ensures controlled deployment of fixes for discovered heap-overflow vulnerabilities.