https://db.gcve.eu/sightings/feed 2026-07-15T18:36:26.508415+00:00 Vulnerability-Lookup info@gcve.eu python-feedgen Contains only the most 10 recent sightings. https://db.gcve.eu/sighting/1a67e8b1-e2eb-408a-8bbb-e4301081f96c/export 2026-07-15T18:36:26.521684+00:00 cedric https://db.gcve.eu/user/cedric {"uuid": "1a67e8b1-e2eb-408a-8bbb-e4301081f96c", "vulnerability_lookup_origin": "1a89b78e-f703-45f3-bb86-59eb712668bd", "author": "2a075640-a300-48a4-bb44-bc6130783b9b", "vulnerability": "GHSA-7rxv-5jhh-j6xx", "type": "seen", "source": "https://infosec.exchange/users/cR0w/statuses/114774063698653725", "content": "", "creation_timestamp": "2025-06-30T19:53:48.623669Z"} 2025-06-30T19:53:48.623669+00:00 https://db.gcve.eu/sighting/c7348f38-d856-4c88-852d-bdbef074f154/export 2026-07-15T18:36:26.524048+00:00 cedric https://db.gcve.eu/user/cedric {"uuid": "c7348f38-d856-4c88-852d-bdbef074f154", "vulnerability_lookup_origin": "1a89b78e-f703-45f3-bb86-59eb712668bd", "author": "2a075640-a300-48a4-bb44-bc6130783b9b", "vulnerability": "GHSA-7RXV-5JHH-J6XX", "type": "published-proof-of-concept", "source": "Telegram/xYRYp9RnMrs6asvPZWHHQ0msOulfM9P8474m_eOJ4G31k98", "content": "", "creation_timestamp": "2025-06-24T04:32:30.000000Z"} 2025-06-24T04:32:30+00:00 https://db.gcve.eu/sighting/0395774d-37b9-491a-9493-845341ee3241/export 2026-07-15T18:36:26.524252+00:00 cedric https://db.gcve.eu/user/cedric {"uuid": "0395774d-37b9-491a-9493-845341ee3241", "vulnerability_lookup_origin": "1a89b78e-f703-45f3-bb86-59eb712668bd", "author": "2a075640-a300-48a4-bb44-bc6130783b9b", "vulnerability": "GHSA-7RXV-5JHH-J6XX", "type": "published-proof-of-concept", "source": "https://t.me/DarkWebInformer_CVEAlerts/19297", "content": "\ud83d\udd17 DarkWebInformer.com - Cyber Threat Intelligence\n\ud83d\udccc CVE ID: CVE-2025-52566\n\ud83d\udd25 CVSS Score: 8.6 (cvssV3_1, Vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H)\n\ud83d\udd39 Description: llama.cpp is an inference of several LLM models in C/C++. Prior to version b5721, there is a signed vs. unsigned integer overflow in llama.cpp's tokenizer implementation (llama_vocab::tokenize) (src/llama-vocab.cpp:3036) resulting in unintended behavior in tokens copying size comparison. Allowing heap-overflowing llama.cpp inferencing engine with carefully manipulated text input during tokenization process. This issue has been patched in version b5721.\n\ud83d\udccf Published: 2025-06-24T03:21:19.009Z\n\ud83d\udccf Modified: 2025-06-24T03:21:19.009Z\n\ud83d\udd17 References:\n1. https://github.com/ggml-org/llama.cpp/security/advisories/GHSA-7rxv-5jhh-j6xx\n2. https://github.com/ggml-org/llama.cpp/commit/dd6e6d0b6a4bbe3ebfc931d1eb14db2f2b1d70af", "creation_timestamp": "2025-06-24T03:48:12.000000Z"} 2025-06-24T03:48:12+00:00