codeql-workshop-cve-2021-21380

CodeQL workshop for Java: Finding a SQL injection In this workshop we will use syntactical and semantic reasoning to find a SQL injection in the XWiki platform's rating component documented by CVE-2021-21380 Contents CodeQL workshop for Java: Finding a SQL injection Contents Prerequisites and set...

deleting-the-trace

Control-token injection attacks on tool-using agents Code and logged measurements for a study of two input-level attacks on tool-using language model agents. The first attack appends a short string of a model's own channel-control tokens to untrusted input; the tokenizer reads it as an...

vulnhawk

AI-powered code security scanner that finds vulnerabilities Semgrep and CodeQL miss. Quick Start • GitHub Action • Comparison • Languages • FAQ The Problem Traditional SAST tools rely on pattern matching and AST rules. They excel at catching known vulnerability patterns, but they fundamentally...

aixcc-afc-atlantis

Atlantis This repository contains Atlantis , Team Atlanta's Cyber Reasoning System CRS submitted to the AIxCC Final Competition AFC. Atlantis is designed to automatically discover and analyze vulnerabilities in software systems. The main system implementation is located in the...

VulnLLM-R

VulnLLM-R: Specialized Reasoning LLM for Vulnerability Detection Paper: arXiv:2512.07533 Code & Data: GitHub Demo: Web demo Model: 7B Model Environment and dataset 🛠️ Create environment Install Git LFS and clone the repository LFS files are fetched automatically during clone git lfs install...

llm-circuit-finder

llm-circuit-finder I replicated Ng's RYS method and found that duplicating 3 specific layers in Qwen2.5-32B boosts reasoning by 17% and duplicating layers 12-14 in Devstral-24B improves logical deduction from 0.22→0.76 on BBH — no training, no weight changes, just routing hidden states through th...

AutoRAN-public

🧠 AutoRAN: Automated Hijacking of Safety Reasoning in Large Reasoning Models AutoRAN is an automated Hijacking of Safety Reasoning that leverages less-aligned secondary auxiliary models to simulate reasoning traces, generate narrative prompts, and iteratively refine those prompts to bypass safety...

GuardReasoner-VL

GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning Yue Liu, Shengfang Zhai, Mingzhe Du Yulin Chen, Tri Cao, Hongcheng Gao, Cheng Wang Xinfeng Li, Kun Wang, Junfeng Fang, Jiaheng Zhang, Bryan Hooi 1National University of Singapore, 2Nanyang Technological University To enhance the safety ...

Sentinel-GPT

Sentinel-GPT: Agentic AI for Threat Hunting 🛡️ An automated cybersecurity pipeline that transforms raw Azure logs into actionable intelligence using LLM-based reasoning. 📖 Overview Sentinel-GPT is an AI Agent specialised for threat hunting in cybersecurity. It is integrated with Azure Log Analytic...

claude-XML-injection

Claude Sonnet 4.6 — Credential Fabrication via XML Tag Injection Reported: June 14, 2026 | Patched: June 20, 2026 | Anthropic Response: None 56 days Researcher: X1NON Affected Model: Claude Sonnet 4.6 and other non-Haiku Claude models Severity: High CVSS 8.7 Status: Patched — No bounty awarded, n...

Agentic-SOC-Simulation

🛡️ Agentic SOC Parallel Simulation ASPS: Autonomous Security Operations Parallel Simulation Center Redefining the Future of Security Operations: Full-Stack SOC Parallel Simulation, Multi-Agent Collaboration, and Data-Driven Autonomous Defense 🇨🇳 中文文档 Chinese Version This project is a cutting-edge...

KidnapRAG

KidnapRAG: A Black-Box Attack for Hijacking Reasoning in Agentic Retrieval-Augmented Generation Systems 🎓 Paper | 📄 Datasets | 🚀 Quick Start Quick Start Run the following commands from the parent directory of the cloned KidnapRAG repository. cd KidnapRAG conda create -n KidnapRAG python=3.10 cond...

OdTM

OWASP Ontology-driven threat modelling OdTM framework Ontology-driven Threat Modelling OdTM framework is a set of means for implementation of an ontological approach into automatic threat modelling of computer systems. It is an OWASP Incubator Project. The ontological approach, provided by the Od...

sgxray

SGXRay: Automating Vulnerability Detection for SGX Apps Intel SGX protects isolated application logic and sensitive data inside an enclave with hardware-based memory encryption. To use such hardware-based security mechanism requires a strict programming model on memory usage， with complex APIs in...

SecFlow

SecFlow Fully Automated Multi-Vector Threat Analysis Pipeline Drop in any file, URL, IP, domain, or image. SecFlow routes it through specialized analyzers, reasons about findings with AI, and produces a professional security report with YARA rules, SIGMA rules, and exportable PDF — automatically...

NetLogic

NetLogic Cloud-Native Attack Surface Mapper & Vulnerability Correlator — v3.0 NetLogic is a network security platform combining active port scanning, CVE correlation live NVD API, SSL/TLS analysis, HTTP security auditing, DNS/email security assessment, subdomain takeover detection, passive OSINT,...

Spring AI 2.1 Message Parts: Reasoning That Survives the Round Trip

Spring AI: Message Parts Doc | Upgrade Notes | OpenAI Responses Doc | Session Doc Reasoning models do more than think before they answer. They hand part of that thinking back to you and expect to get it back on the next request. Claude signs its thinking blocks. Gemini attaches thought signatures...

OpenAI Compaction Flaw Let Researchers Bypass Hidden Reasoning Protections

OpenAI's compaction feature, which shrinks a long conversation to save space, could be turned into a way to copy a model's hidden reasoning out in plain text, security firm Xint has shown. OpenAI's reasoning models work through a problem before answering, and the service normally returns only the...

SoK: Timestamps Are Not a Time Model: Rethinking Temporal Reasoning in Host-Based Intrusion Detection

Host-based intrusion detectors order events, window audit streams and sequence attack stages by their timestamps. Every conclusion they draw therefore rests on assumptions about clocks, delivery, entity identity and the integrity of the evidence, and most of these assumptions go unstated. This...

SecLog-Bench: A Scalable Benchmark for Cybersecurity Log Reasoning with Scaffolded Evidence

Large language models LLMs have shown strong potential for cybersecurity, leading to growing interest in LLM-based automated cybersecurity log analysis. However, current datasets 1 are limited in scale; 2 rely mainly on single-source evidence; and 3 have only binary or multi-class attack labels,...