2901 matches found
reposherlock
RepoSherlock Englisch | Türkçe Gib eine GitHub-Repository-URL oder einen lokalen Pfad ein und erhalte Architektur, Ausführungshinweise, Risiken und umsetzbare Probleme. Live-CLI-Vorschau Warum RepoSherlock Bevor du ausführst: Verstehe die Architektur. Bevor du vertraust: Sieh dir Sicherheits- und...
bearer
Scansiona il tuo codice sorgente contro i principali rischi di sicurezza e privacy. Bearer è uno strumento di test statico della sicurezza delle applicazioni SAST progettato per scansionare il tuo codice sorgente e analizzare i flussi di dati per identificare, filtrare e dare priorità ai rischi d...
cicd-goat
Deliberately vulnerable CI/CD environment. Hack CI/CD pipelines, capture the flags. 🚩 Created by Cider Security Acquired by Palo Alto Networks. Table of Contents...
xmap
XMap: The Internet Scanner XMap is a fast network scanner designed for performing Internet-wide IPv6 & IPv4 network research scanning. XMap is reimplemented and improved thoroughly from ZMap and is fully compatible with ZMap, armed with the "5 minutes" probing speed and novel scanning techniques...
packj
Packj flags malicious/risky open-source packages Packj pronounced package is a tool to help to mitigate software supply chain attacks. It can detect malicious, vulnerable, abandoned, typo-squatting, and other "risky" packages from popular open-source package registries, such as NPM, RubyGems, and...
CVE-2026-21762
HCL DevOps Loop is affected by missing HTTP security headers. Missing security headers may reduce browser protections against common web-based attacks such as clickjacking, MIME-type sniffing, and cross-site scripting...
Description-Code Inconsistency in Real-World MCP Servers: Measurement, Detection, and Security Implications
The Model Context Protocol MCP has emerged as a critical standard empowering Large Language Models LLMs to utilize external tools. In this ecosystem, LLMs rely on natural language descriptions provided by MCP servers to select and execute functions. This interaction implicitly assumes that tool...
Security, Privacy, and Ethical Risks in OpenClaw
This paper systematically investigates the security, privacy, and ethical risks, as well as the traceability challenges of OpenClaw, a locally executable AI agent system for natural language interaction and real-world task completion. While OpenClaw shows strong potential for personal assistance,...
Security of LLM-Generated Code: A Comparative Analysis
The majority of software developers use or are planning to use Artificial Intelligence AI tools in their development processes. Their top reasons include improving productivity and faster learning. In fact, Large Language Model LLM-generated code is currently in production, including in major tec...
Astra Linux – Vulnerability in edk2
The example of an encrypted private key in EDK2, located in the IpSecDxe.efi, may pose potential security risks...
From AI-Generated Content to Agentic Action: Security and Safety Threats in Generative AI
Generative AI systems are increasingly used not only to produce content but also to retrieve data, invoke tools, and execute actions. This work examines the security and safety implications of that shift across content-level, model-level, and agentic threats. We analyze how attacker access...
CVE-2025-62316
Technical details are not publicly available in the provided documents. Monitor for updates on CVE-2025-62316 from the linked sources; no affected products, vectors, or remediation are stated.
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...
Security Risks in Tool-Enabled AI Agents: A Systematic Analysis of Privileged Execution Environments
Tool-enabled AI agents are increasingly deployed in cloud-hosted environments and offered as services, where they perform side-effecting operations through privileged tools within execution environments. While such agents enable powerful automation, the security implications of hosting autonomous...
Heimdallr: Characterizing and Detecting LLM-Induced Security Risks in GitHub CI Workflows
GitHub Continuous Integration CI workflows increasingly integrate Large Language Models LLMs to automate review, triage, content generation, and repository maintenance. This creates a new attack surface: externally controllable workflow inputs can shape LLM prompts and outputs, which may in turn...
A week in security (April 27 – May 3)
Last week on Malwarebytes Labs: 3 easy-to-miss cybersecurity risks for small businesses Actively exploited cPanel bug exposes millions of websites to takeover More PayPal emails hijacked to deliver tech support scams Hackers stole hundreds of thousands of Roblox accounts: Here’s what to do...
Security Attack and Defense Strategies for Autonomous Agent Frameworks: A Layered Review with OpenClaw As a Case Study
Autonomous agent frameworks built upon large language models LLMs are evolving into complex, tool-integrated, and continuously operating systems, introducing security risks beyond traditional prompt-level vulnerabilities. As this paradigm is still at an early stage of development, a timely and...
The AI Threat Multiplier: Why Architectural Flaws Are the New Frontier
AI has put an end to the era of evaluating CVEs in isolation. The most critical risks now emerge when legacy state machines meet asynchronous execution...
Why Your Deprecated Endpoints Are an Attacker’s Best Friend: The Rise of Ghost APIs
Ghost APIs are deprecated endpoints left active, exposing systems to attack. Learn how they differ from shadow APIs and why they create hidden security risks...