Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-33020 is a high-severity Heap-based Buffer Overflow (CWE-122) vulnerability in Saitoha Libsixel. 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 10th 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 SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — 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.
CVE-2026-33020 is an integer overflow vulnerability in libsixel, an implementation of a SIXEL encoder/decoder derived from kmiya's sixel, affecting versions 1.8.7 and prior. The issue occurs in the sixel_frame_convert_to_rgb888() function within frame.c, where allocation size and pointer offset computations for palettised images (PAL1, PAL2, PAL4) use int arithmetic before casting to size_t. For images whose pixel count exceeds INT_MAX / 4, this results in an undersized heap allocation for the conversion buffer and a negative pointer offset for the normalization sub-buffer. Subsequent calls to sixel_helper_normalize_pixelformat() then write full image data from the invalid pointer, causing massive heap corruption, as confirmed by ASAN instrumentation. The vulnerability is classified under CWE-122 (Heap-based Buffer Overflow) and CWE-190 (Integer Overflow or Wraparound), with a CVSS v3.1 base score of 7.1.
An attacker can exploit this vulnerability locally by providing a specially crafted large palettised PNG image to a victim process using libsixel. Exploitation requires user interaction, such as opening the malicious image in a compatible application, but no special privileges are needed. Successful exploitation leads to reliable process crashes and heap corruption, enabling potential arbitrary code execution with high impact on integrity and availability, though no confidentiality impact.
The issue has been addressed in libsixel version 1.8.7-r1, as detailed in the project's GitHub release notes and security advisory GHSA-2xgm-4x47-2x2p, which recommend upgrading to the patched version for mitigation.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-22744
Vulnerability Data
libsixel is a SIXEL encoder/decoder implementation derived from kmiya's sixel. Versions 1.8.7 and prior contain an integer overflow which leads to a heap buffer overflow via sixel_frame_convert_to_rgb888() in frame.c, where allocation size and pointer offset computations for palettised images (PAL1,…
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PAL2, PAL4) are performed using int arithmetic before casting to size_t. For images whose pixel count exceeds INT_MAX / 4, the overflow produces an undersized heap allocation for the conversion buffer and a negative pointer offset for the normalization sub-buffer, after which sixel_helper_normalize_pixelformat() writes the full image data starting from the invalid pointer, causing massive heap corruption confirmed by ASAN. An attacker providing a specially crafted large palettised PNG can corrupt the heap of the victim process, resulting in a reliable crash and potential arbitrary code execution. This issue has been fixed in version 1.8.7-r1.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
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Affected Assets
Mitigating Controls
Control response
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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.