CVE-2019-14085

Possible Integer underflow in WLAN function due to lack of check of data received from user side in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile in QCN7605, QCS605, SDA845, SDM670, SDM710,...

CVE-2018-11830

Improper input validation in QCPE create function may lead to integer overflow in Snapdragon Auto, Snapdragon Consumer Electronics Connectivity, Snapdragon Industrial IOT, Snapdragon Mobile in MDM9206, MDM9607, MDM9650, MDM9655, MSM8996AU, SD 410/12, SD 820A...

CVE-2018-14672

In ClickHouse before 18.12.13, functions for loading CatBoost models allowed path traversal and reading arbitrary files through error messages...

CVE-2018-13887

Untrusted header fields in GNSS XTRA3 function can lead to integer overflow in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Wearables in MDM9150, MDM9206, MDM9607, MDM9635M, MDM9650, MDM9655, MSM8909W, QCS605, Qualcomm 215,...

Mapping the Future of AI Security

AI security is one of the most pressing challenges facing the world today. Artificial intelligence is extraordinarily powerful, and, especially considering the advent of Agentic AI, growing more so by the day. But it is for this reason that securing it is so important. AI handles massive amounts ...

CVE-2017-18840

Certain NETGEAR devices are affected by denial of service. This affects M4300-28G before 12.0.2.15, M4300-52G before 12.0.2.15, M4300-28G-POE+ before 12.0.2.15, M4300-52G-POE+ before 12.0.2.15, M4300-8X8F before 12.0.2.15, M4300-12X12F before 12.0.2.15, M4300-24X24F before 12.0.2.15, M4300-24X...

CVE-2019-2346

Firmware is getting into loop of overwriting memory when scan command is given from host because of improper validation. in Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wired Infrastructure and Networking in IPQ807...

CVE-2019-2244

Possible integer underflow can happen when calculating length of elementary stream info from invalid section length which is later used to read from input buffer in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon IoT,...

CVE-2012-3290

Multiple unspecified vulnerabilities in Google Chrome before 20.0.1132.22 on the Acer AC700; Samsung Series 5, 5 550, and Chromebox 3; and Cr-48 Chromebook platforms have unknown impact and attack vectors...

CVE-2018-21229

Certain NETGEAR devices are affected by incorrect configuration of security settings. This affects R7500v2 before 1.0.3.20, R7800 before 1.0.2.38, WN3000RPv3 before 1.0.2.50, WNDR4300v2 before 1.0.0.50, and WNDR4500v3 before 1.0.0.50...

CVE-2018-21204

Certain NETGEAR devices are affected by a stack-based buffer overflow by an unauthenticated attacker. This affects D7800 before 1.0.1.30, R6100 before 1.0.1.20, R7500 before 1.0.0.118, R7500v2 before 1.0.3.24, R7800 before 1.0.2.40, R9000 before 1.0.2.52, WNDR3700v4 before 1.0.2.96, WNDR4300 befo...

CVE-2018-21219

Certain NETGEAR devices are affected by a buffer overflow by an unauthenticated attacker. This affects D3600 before 1.0.0.67, D6000 before 1.0.0.67, D6100 before 1.0.0.56, D7800 before 1.0.1.30, R6100 before 1.0.1.20, R7500 before 1.0.0.118, R7500v2 before 1.0.3.24, R9000 before 1.0.2.52,...

CVE-2018-11967

Signature verification of the skel library could potentially be disabled as the memory region on the remote subsystem in which the library is loaded is allocated from userspace currently in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industria...

CVE-2013-4829

HP LaserJet M4555, M525, and M725; LaserJet flow MFP M525c; LaserJet Enterprise color flow MFP M575c; Color LaserJet CM4540, M575, and M775; and ScanJet Enterprise 8500fn1 FutureSmart devices allow local users to read images of arbitrary scanned documents via unspecified vectors...

CVE-2017-18827

Certain NETGEAR devices are affected by stored XSS. This affects M4300-28G before 12.0.2.15, M4300-52G before 12.0.2.15, M4300-28G-POE+ before 12.0.2.15, M4300-52G-POE+ before 12.0.2.15, M4300-8X8F before 12.0.2.15, M4300-12X12F before 12.0.2.15, M4300-24X24F before 12.0.2.15, M4300-24X before...

Advancing Security with Digital Twins: a Comprehensive Survey

The proliferation of electronic devices has greatly transformed every aspect of human life, such as communication, healthcare, transportation, and energy. Unfortunately, the global electronics supply chain is vulnerable to various attacks, including piracy of intellectual properties, tampering,...

CAIN: Hijacking LLM-Humans Conversations Via a Two-Stage Malicious System Prompt Generation and Refining Framework

Large language models LLMs have advanced many applications, but are also known to be vulnerable to adversarial attacks. In this work, we introduce a novel security threat: hijacking AI-human conversations by manipulating LLMs' system prompts to produce malicious answers only to specific targeted...

When Safety Detectors Aren'T Enough: a Stealthy and Effective Jailbreak Attack on LLMs Via Steganographic Techniques

Jailbreak attacks pose a serious threat to large language models LLMs by bypassing built-in safety mechanisms and leading to harmful outputs. Studying these attacks is crucial for identifying vulnerabilities and improving model security. This paper presents a systematic survey of jailbreak method...

Mitigating Fine-Tuning Risks in LLMs Via Safety-Aware Probing Optimization

The significant progress of large language models LLMs has led to remarkable achievements across numerous applications. However, their ability to generate harmful content has sparked substantial safety concerns. Despite the implementation of safety alignment techniques during the pre-training...

CoTSRF: Utilize Chain of Thought As Stealthy and Robust Fingerprint of Large Language Models

Despite providing superior performance, open-source large language models LLMs are vulnerable to abusive usage. To address this issue, recent works propose LLM fingerprinting methods to identify the specific source LLMs behind suspect applications. However, these methods fail to provide stealthy...