Ensure Kernel SMEP is Enabled

Supervisor Mode Execution Prevention SMEP can be enabled to prevent the user-space code execution on the kernel. If SMEP is not enabled, attackers can execute the user-space code through kernel-mode code redirection, which increases the attack surface and reduces system security. SMEP is enabled ...

OET: Optimization-Based Prompt Injection Evaluation Toolkit

Large Language Models LLMs have demonstrated remarkable capabilities in natural language understanding and generation, enabling their widespread adoption across various domains. However, their susceptibility to prompt injection attacks poses significant security risks, as adversarial inputs can...

An Empirical Study on the Effectiveness of Large Language Models for Binary Code Understanding

Binary code analysis plays a pivotal role in the field of software security and is widely used in tasks such as software maintenance, malware detection, software vulnerability discovery, patch analysis, etc. However, unlike source code, reverse engineers face significant challenges in understandi...

Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report

As transformer-based large language models LLMs increasingly permeate society, they have revolutionized domains such as software engineering, creative writing, and digital arts. However, their adoption in cybersecurity remains limited due to challenges like scarcity of specialized training data a...

CipherBank: Exploring the Boundary of LLM Reasoning Capabilities through Cryptography Challenges

Large language models LLMs have demonstrated remarkable capabilities, especially the recent advancements in reasoning, such as o1 and o3, pushing the boundaries of AI. Despite these impressive achievements in mathematics and coding, the reasoning abilities of LLMs in domains requiring cryptograph...

Breaking the Flow and the Bank: Stealthy Cyberattacks on Water Network Hydraulics

As water distribution networks WDNs become increasingly connected with digital infrastructures, they face greater exposure to cyberattacks that threaten their operational integrity. Stealthy False Data Injection Attacks SFDIAs are particularly concerning, as they manipulate sensor data to...

Private Federated Learning Using Preference-Optimized Synthetic Data

In practical settings, differentially private Federated learning DP-FL is the dominant method for training models from private, on-device client data. Recent work has suggested that DP-FL may be enhanced or outperformed by methods that use DP synthetic data Wu et al., 2024; Hou et al., 2024. The...

Secure Transfer Learning: Training Clean Models against Backdoor in (Both) Pre-Trained Encoders and Downstream Datasets

Transfer learning from pre-trained encoders has become essential in modern machine learning, enabling efficient model adaptation across diverse tasks. However, this combination of pre-training and downstream adaptation creates an expanded attack surface, exposing models to sophisticated backdoor...

Malicious code in search-benchmark-frontend (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 83090fc7978d15e4a0ee6c1d633d8998d6b7ce00f6c0ec85ec1e6297d679517e Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

MAL-2025-3164 Malicious code in search-benchmark-frontend (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 83090fc7978d15e4a0ee6c1d633d8998d6b7ce00f6c0ec85ec1e6297d679517e Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

Malware in search-benchmark-frontend

Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be rotated immediately from a different computer. The package should be removed, but as full control of the computer may have been given to an outsid...

dataset-format-benchmark (0.0.10) potentially affected by CVE-2024-8020 via pytorch-lightning (1.9.2)

pytorch-lightning PYPI version 1.9.2 is affected by a known vulnerability. The following packages have a transitive dependency on pytorch-lightning and may be impacted: - dataset-format-benchmark 0.0.10 Source cves: CVE-2024-8020 Source advisory: OSV:GHSA-98FP-7V67-4V3Q...

dataset-format-benchmark (>=0.0.11, <=0.0.12), hybrid-graph (>=0.2.0, <=0.61.0) +2 more potentially affected by CVE-2024-8019 via pytorch-lightning (1.9.3)

pytorch-lightning PYPI version 1.9.3 is affected by a known vulnerability. The following packages have a transitive dependency on pytorch-lightning and may be impacted: - dataset-format-benchmark =0.0.11, =0.2.0, =0.1.0, =0.1.1 Source cves: CVE-2024-8019 Source advisory: OSV:GHSA-4CV3-V7PV-RFHF...

dataset-format-benchmark (0.0.10) potentially affected by CVE-2024-8019 via pytorch-lightning (1.9.2)

pytorch-lightning PYPI version 1.9.2 is affected by a known vulnerability. The following packages have a transitive dependency on pytorch-lightning and may be impacted: - dataset-format-benchmark 0.0.10 Source cves: CVE-2024-8019 Source advisory: OSV:GHSA-4CV3-V7PV-RFHF...

Malicious code in alchemy-asset-transfers-benchmark (npm)

The package communicates with a domain associated with malicious activity. --- -= Per source details. Do not edit below this line.=-...

Malware in spliffy-benchmark

Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be rotated immediately from a different computer. The package should be removed, but as full control of the computer may have been given to an outsid...

io.jboot:jboot (>=1.0-alpha2, <=1.0-alpha4.2), io.mangoo:mangooio-benchmark (>=4.4.0-beta1, <=4.4.0-beta3) +42 more potentially affected by CVE-2023-4639 via io.undertow:undertow-core (1.4.12.final)

io.undertow:undertow-core MAVEN version 1.4.12.final is affected by a known vulnerability. The following packages have a transitive dependency on io.undertow:undertow-core and may be impacted: - io.jboot:jboot =1.0-alpha2, =4.4.0-beta1, =3.12.0, =3.12.0, =3.12.0, =3.12.0, =0.2.8, =0.2.8, =0.2.8,...

Malicious code in spliffy-benchmark (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 8ead6b661fb169fc63b0a65eb514024ee59694c0b4e6031a27afc765d0089b5d Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

MAL-2024-10570 Malicious code in spliffy-benchmark (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 8ead6b661fb169fc63b0a65eb514024ee59694c0b4e6031a27afc765d0089b5d Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

Linux do_map_benchmark Heap Buffer Overflow

The vulnerability of the domapbenchmark function in the kernel/dma/mapbenchmark.c module of the Linux operating system is related to reading memory beyond the allocated buffer. Exploiting this vulnerability could allow an attacker to compromise the confidentiality, integrity, and accessibility of...