Flounder 0.1.2

Flounder turns modern coding agents into an end-to-end security audit system. Give it an authorized target boundary - a repository, source tree, package, deployed clue, or prior run - and the agent can prepare the workspace, read the code and supporting material, map the attack surface, dig into...

RedAmon 5.1.0

An autonomous AI framework that chains reconnaissance, exploitation, and post-exploitation into a single pipeline, then goes further by triaging every finding, implementing code fixes, and opening pull requests on your repository. From first packet to merged patch, with human oversight at every...

Formal Security Analysis of Agent Protocol Composition

AI agent protocols define how agents use tools, delegate work, and coordinate across software systems, but their security requirements remain incomplete and inconsistently enforced across deployments. We present AgentThread, a source-linked framework for security assurance analysis of agent...

Flounder 0.1.0

Flounder turns modern coding agents into an end-to-end security audit system. Give it an authorized target boundary - a repository, source tree, package, deployed clue, or prior run - and the agent can prepare the workspace, read the code and supporting material, map the attack surface, dig into...

CNAPP’s New Normal: Hyper-Prioritization and Autonomous Remediation at Cloud Scale

AI-powered detection has crossed a threshold. Security teams can now surface vulnerabilities, misconfigurations, and active attack paths at a speed and scale that was unimaginable a few years ago. The problem is no longer finding or knowing risk; it’s closing it fast enough to matter. Cloud...

elevate-kit

elevate-kit Local privilege escalation enumeration scripts fo...

PT-2026-51189

A vulnerability was found in AOMEI Dynamic Disk Manager up to 10.10.1. This issue affects some unknown processing in the library ddmdrv.sys of the component Kernel Driver. Performing a manipulation results in improper access controls. The attack must be initiated from a local position. The exploi...

Snyk VulnBench JS 1.0: Can LLMs Find the Same Bugs Twice?

We ran 300 repeated vulnerability-finding scans to measure how repeatable agentic large language model LLM security review is on the same JavaScript code, prompt, and benchmark harness. The headline result is that LLM security findings were unevenly repeatable: reference-matched findings were...

The Audit Gap in Blockchain Security: A Four-Year Empirical Study of Public Audit Findings and Real-World Exploit Incidents

This paper presents an empirical analysis of the Web3 security landscape over the four-year and three-month period from 1 January 2022 to 27 March 2026. The dataset combines 23,818 public audit findings produced by 22 independent security firms with 218 real-world exploit incidents documented by...

Anthropic’s Project Glasswing Update

In April, Anthropic initated Project Glasswing. The idea was to let companies use their new model to find and fix vulnerabilities in their own software. It was a fantastic PR move, and so many press outlets have uncritically parroted Anthropic's claims that it's now common wisdom that Mythos is...

Updating the taxonomy of failure modes in agentic AI systems: What a year of red teaming taught us

In this article 1. Why the Taxonomy Needed Updating 2. Seven new failure modes 3. Operational findings: What red teaming showed 4. New mitigations 5. What to do this quarter When the Microsoft AI Red Team published the Taxonomy of Failure Modes in Agentic AI Systems in April 2025, the goal was a...

Updating the taxonomy of failure modes in agentic AI systems: What a year of red teaming taught us

In this article 1. Why the Taxonomy Needed Updating 2. Seven new failure modes 3. Operational findings: What red teaming showed 4. New mitigations 5. What to do this quarter When the Microsoft AI Red Team published the Taxonomy of Failure Modes in Agentic AI Systems in April 2025, the goal was a...

Bastet: A Fine-Grained Expert-Labeled Dataset for DeFi Smart Contract Vulnerability Detection

Smart contract vulnerabilities in Decentralized Finance DeFi protocols resulted in over 1.49 billion USD in confirmed losses in 2024 alone, across 192 incidents 1. As LLM-based vulnerability detection emerges as a promising approach to address these threats, the quality of evaluation datasets has...

snyk-agentic-appsec-poc

Snyk Agentic AppSec POC Proof of concept demonstrating autono...

Quality and Security Signals in AI-Generated Python Refactoring Pull Requests

As AI agents increasingly contribute to code development and maintenance, there is still limited empirical evidence on the quality and risk characteristics of their changes in real-world projects, particularly for refactoring-oriented contributions. It remains unclear how agent-authored refactori...

eip-mcp

Exploit Intel Platform MCP Server Package/command: eip-mcp...

offsec-skills

offsec-exploit-research Elite adaptive whitebox exploit resea...

Windows-pentest-lab

Windows-pentest-lab Penetration testing and vulnerability asse...

PickleFuzzer: A Case Study in Fuzzing for Discrepancies between Python Pickle Implementations

Python's native serialization protocol, pickle, is a powerful but insecure format for transferring untrusted data. It is frequently used, especially for saving machine learning models, despite known security challenges. While developers sometimes mitigate this risk by restricting imports during...

Microsoft's MDASH AI System Finds 16 Windows Flaws Fixed in Patch Tuesday

Microsoft has unveiled a new multi-model artificial intelligence AI-driven system called MDASH to facilitate vulnerability discovery and remediation at scale, adding that it's being tested by some customers as part of a limited private preview. MDASH, short for m ulti-mod el a gentic s canning h...