On the Evaluation of Spiking Neural Network Configurations for Network Intrusion Detection

Network intrusion detection is a core component of modern cybersecurity infrastructure, yet the deep learning models that dominate the field are computationally demanding, motivating interest in lightweight alternatives suited to edge and neuromorphic deployment. Spiking Neural Networks SNNs are...

Orthanc Explorer 2 代码注入漏洞

Orthanc Explorer 2 is a user interface plugin for the Orthanc Server’s open-source medical imaging management system. Versions of Orthanc Explorer 2 prior to 1.12.0 contained a code injection vulnerability. This vulnerability stemmed from the param operation in the File...

How to Compare the Security of Code Written by Humans to LLM-Generated Code

Large language models LLMs are rapidly transforming how software is created and maintained. Comparing LLM-generated code against human-written standards is essential to determine whether these new tools uphold or erode the security baselines established by professional developers. Yet, we lack a...

Dissecting the Black Box: Circuit-Level Analysis of LLM Vulnerability Detection

Large language models LLMs can detect software vulnerabilities, but how do they actually identify vulnerable code? We address this question using mechanistic interpretability; analyzing the internal computations of a neural network to understand its reasoning process.Using Circuit Tracer on...

SUSE CVE-2026-8376

Perl versions before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.11 have a heap buffer overflow when compiling regular expressions with a repeated fixed string on 32-bit builds. Perlstudychunk in regcompstudy.c checked the size of the joined substring buffer in characters...

Towards Cybersecurity SuperIntelligence (CSI): What'S the Best Harness for Cybersecurity?

What is the best harness for cybersecurity AI? Cybersecurity systems are converging on a single execution scaffold per agent, an iterative shell loop driven by a Large Language Model LLM. However, scaffolds are not interchangeable, rarely interoperable, and no single scaffold dominates across all...

CVE-2026-8376

Perl versions before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.11 have a heap buffer overflow when compiling regular expressions with a repeated fixed string on 32-bit builds. Perlstudychunk in regcompstudy.c checked the size of the joined substring buffer in characters...

UBUNTU-CVE-2026-8376

Perl versions before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.11 have a heap buffer overflow when compiling regular expressions with a repeated fixed string on 32-bit builds. Perlstudychunk in regcompstudy.c checked the size of the joined substring buffer in characters...

The Fault in Our Drafts: Vulnerabilities in RPKI Specification and Software

The Resource Public Key Infrastructure RPKI secures the Internet's routing system by defining a complex trust and validation framework for certificates, Route Origin Authorizations ROAs, manifests, and Certificate Revocation Lists CRLs. These mechanisms are specified across dozens of RFCs. This...

Silent Consent, Persistent Risk: Android Permission Groups and Custom Permissions

Android's permission system is designed to balance usability with informed consent, yet two legacy mechanisms still undermine that balance in Android 16: i permission groups that silently auto-grant new permissions within a group after a user's initial approval, and ii normal-level custom...

CVE-2026-8376

Perl versions before 5.40.5-RC1, from 5.41.0 before 5.42.3-RC1, from 5.43.0 before 5.43.11 have a heap buffer overflow when compiling regular expressions with a repeated fixed string on 32-bit builds. Perlstudychunk in regcompstudy.c checked the size of the joined substring buffer in characters...

CALIBURN: A Regime-Sensitivity Study of Operationally Calibrated Streaming Intrusion Detection

Streaming network intrusion detection systems must process flows continuously while keeping memory bounded, but most current methods leave alerting threshold selection as a post-hoc tuning problem poorly suited to production. Operators need alerting behaviour specifiable before deployment using...

MAL-2026-4753 Malicious code in gt-tester-exp-profiler-exp-00000017 (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector f1490f970bd52c80c89f33029f9e875f1fb595014621d50e0ce87a167d1cd348 setup.py installs a site-wide.pth file gttesterexpprofilerexp00000017probe.pth into site-packages that imports the package's probe module and calls...

Exploit for CVE-2026-9082

⚠️ Security Research & Legal Disclaimer 📌 Purpose of This...

Data Brokers’ and AI Firms’ Opt-Out Forms Are Built to Fail, Report Finds

A new study finds AI companies, defense firms, and dating apps are among 38 data collectors allegedly using manipulative design to confuse users while collecting their data...

Domijn: The Security of Domain Registrars and the Risk of a Domain Name Takeover

Domain names are key assets for organisation. They anchor an organisation's online presence and reputation, and serve as linking pin for web services and, e.g., email. Consequently, a malicious takeover of a domain can lead to significant damages. Organisations register domain names through...

Exploit for Improper Handling of Exceptional Conditions in Apache Struts

apache-struts-cve-2017-56...

How AI Hallucinations Are Creating Real Security Risks

AI hallucinations are introducing serious security risks into critical infrastructure decision-making by exploiting human trust through highly confident yet incorrect outputs. When an AI model lacks certainty, it doesn’t have a mechanism to recognize that. Instead, it generates the most probable...

Toward Securing AI Agents like Operating Systems

Autonomous agents based on large language models LLMs are rapidly emerging as a general-purpose technology, with recent systems such as OpenClaw extending their capabilities through broad tool use, third-party skills, and deeper integration into user environments. At the same time, these agentic...

Security Incentivization: An Empirical Study of How Micropayments Impact Code Security

Security often receives insufficient developer attention because it does not directly generate visible value, leading to underinvestment in practice. We evaluate a countermeasure by team-level incentives tied to measurable security improvements over time. Our semi-automated mechanism aggregates...