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Search Results (5 CVEs found)
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2026-96280 | 2 Flatpak, Redhat | 8 Flatpak, Enterprise Linux, Enterprise Linux Eus and 5 more | 2026-11-06 | 7.5 High |
| The OCI delta stream parser read sizes as guint64 but passed them to GLib I/O and allocation functions expecting gsize (32 bits on 32-bit systems), causing undersized allocations while subsequent operations use the original 64-bit size, leading to heap buffer overflows. An attacker controlling an OCI registry can craft a delta stream that triggers this during flatpak install/update, potentially achieving code execution on 32-bit systems. | ||||
| CVE-2026-77014 | 1 Redhat | 4 Enterprise Linux, Openshift, Openshift Container Platform and 1 more | 2026-11-06 | 5.3 Medium |
| A flaw was found in libsoup's SoupServer HTTP Range header processing. The sort_ranges() comparator in soup-message-headers.c truncates a 64-bit subtraction result to 32-bit int, flipping the sign for range offsets differing by more than INT_MAX. This causes silent omission of requested byte ranges from HTTP 206 Partial Content responses on resources larger than approximately 2 GB. | ||||
| CVE-2026-116012 | 2 Nationalsecurityagency, Nsa | 2 Ghidra, Ghidra | 2026-11-05 | 3.6 Low |
| Ghidra before 12.2 contains a numeric truncation vulnerability in PackedDecode::skipAttribute and skipAttributeRemaining in marshal.cc that stores 64-bit string lengths in 32-bit variables. Attackers can supply a crafted packed stream, such as a malicious .sla file, to inject attributes into the decompiler's input or crash the decompiler process. | ||||
| CVE-2026-107479 | 1 Qt | 3 Qt, Qt5compat, Qtbase | 2026-11-04 | 5.5 Medium |
| An integer truncation vulnerability in the QTextCodec conversion functions of the Qt 5 Core Compatibility APIs module impacts the Qt Framework. An application using the affected functionality could crash. | ||||
| CVE-2020-15202 | 2 Google, Opensuse | 2 Tensorflow, Leap | 2024-11-21 | 9 Critical |
| In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | ||||
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