今日共收录 1854 条安全情报，包含 1458 个 CVE，156 篇安全通告，以及 125 篇研究论文。
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A authorization bypass vulnerability exists in the /api/runscript functionality of FUXA (version(s): 1.3.2-2809). A spec
CVE-2026-118689
OvenMediaEngine through 0.21.0 contains a denial of service vulnerability in OvtPacket::LoadHeader() that allows unauthe
CVE-2026-83831
Double free in Microsoft Edge (Chromium-based) allows an unauthorized attacker to execute code over a network.
CVE-2026-23705
An Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') vulnerability [CWE-89] vulnerabi
CVE-2026-20942
Improper restriction of rendered ui layers or frames in Microsoft Edge (Chromium-based) allows an unauthorized attacker
CVE-2026-116071
rotki before 1.44.2 contains a weak key derivation vulnerability that allows attackers to brute-force backups because th
CVE-2026-100132
Acrobat for Edge is affected by an out-of-bounds read vulnerability that could lead to disclosure of sensitive memory. A
CVE-2026-113691
Stored cross-site scripting in the SmartIT knowledge-article feature of BMC IT Service Management Suite versions 25.3.01
CVE-2026-97860
YMS-VPN8 and YMS-VPN8-CP provided by Yamaha Corporation register Windows services with unquoted file paths. A user who h
CVE-2026-109822
Yamaha wireless LAN router NWR100 provided by Yamaha Corporation contains an issue with insecure storage of sensitive in
Cryptocurrency giant Binance said on Thursday that a "security incident" on its platform has impacted about $6.3 billion
Palo Alto Networks on Wednesday warned that threat actors are exploiting the recently patched PHP2Shell vulnerabilities
We present TextSeal2, a distortion-free watermark for large language models that keeps its signal under speculative deco
Despite growing capabilities, LLMs remain susceptible to prompt injections: malicious inputs that can manipulate or hija
Indirect prompt injection threatens local LLM agents through untrusted tool outputs, motivating defenses that suppress a
Large language models (LLMs) deployed in safety-critical settings must resist adversarial inputs designed to elicit harm
Cyber threat intelligence (CTI) reports describe adversary behavior in natural language, but converting them into struct
Large language model (LLM) agents have demonstrated strong capabilities in automating complex information-seeking and tr
Large language model (LLM) agents often receive access to more files, accounts, and services than a task requires. Promp
Large Language Model (LLM) agents are increasingly acting through Web interfaces and external tools. They produce trajec