Et Tu, RDP? Detecting Sticky Keys Backdoors with Brutus and WebAssembly
Everyone knows that one person on the team who’s inexplicably lucky, the one who stumbles upon a random vulnerability seemingly by chance. A few days ago, my coworker Michael Weber was telling me about a friend like this who, on a recent penetration test, pressed the shift key five times at an RDP login screen […]
Mapping the Unknown: Introducing Pius for Organizational Asset Discovery
Asset discovery is an essential part of Praetorian’s service delivery process. When we are engaged to carry out continuous external penetration testing, one key action is to build and maintain a thorough target asset inventory that goes beyond any lists or databases provided by the system owner. Pius is our open-source attack surface mapping tool […]
Building Bridges, Breaking Pipelines: Introducing Trajan
TL;DR: Trajan is an open-source CI/CD security tool from Praetorian that unifies vulnerability detection and attack validation across GitHub Actions, GitLab CI, Azure DevOps, and Jenkins in a single cross-platform engine. It ships with 32 detection plugins and 24 attack plugins covering poisoned pipeline execution, secrets exposure, self-hosted runner risks, and AI/LLM pipeline vulnerabilities. It […]
What’s Running on That Port? Introducing Nerva for Service Fingerprinting
Nerva is a high-performance, open-source CLI tool that identifies what services are running on open network ports. It fingerprints 120+ protocols across TCP, UDP, and SCTP, averaging 4x faster than nmap -sV with 99% detection accuracy. Written in Go as a single binary, Nerva helps security teams rapidly move from port discovery to service identification. […]
There’s Always Something: Secrets Detection at Engagement Scale with Titus
TL;DR: Titus is an open source secret scanner from Praetorian that detects and validates leaked credentials across source code, binary files, and HTTP traffic. It ships with 450+ detection rules and runs as a CLI, Go library, Burp Suite extension, or Chrome browser extension — putting secrets detection everywhere you already work during engagements. Say you find […]
MCP Server Security: The Hidden AI Attack Surface
TL;DR – MCP servers – the integration layer connecting AI assistants to external tools and data – are a significant and underexplored attack surface. Our research demonstrates that both locally hosted and third-party MCP servers can be exploited to execute arbitrary code, exfiltrate sensitive data, and manipulate user behavior, often with zero indication to the […]
Julius Update: From 17 to 33 Probes (and Now Detecting OpenClaw)
TL;DR: Julius v1.2.0 nearly doubles probe coverage from 17 to 33, adding detection for self-hosted inference servers, AI gateways, and RAG/orchestration platforms like Dify, Flowise, and KoboldCpp. The headline addition is OpenClaw, a fast-growing AI agent gateway where exposed instances leak API keys, grant filesystem access, and allow full user impersonation. Update Julius and run […]
Et Tu, Default Creds? Introducing Brutus for Modern Credential Testing
It’s day three of staring at a spreadsheet of 700,000 live hosts. Your port scans are done. Fingerprintx has identified thousands of SSH services, databases, admin panels, and file shares across a sprawling enterprise network. Now comes the part that every penetration tester hates: auditing and testing credentials at scale. You need to check for […]
Introducing Augustus: Open Source LLM Prompt Injection Tool
From LLM Fingerprinting to LLM Prompt Injection Last month we released Julius, a tool that answers the question: “what LLM service is running on this endpoint?” Julius identifies the infrastructure. But identification is only the first step. The natural follow-up: “now that I know what’s running, how do I test whether it’s secure?” That’s what […]
Deterministic AI Orchestration: A Platform Architecture for Autonomous Development
Executive Summary The primary bottleneck in autonomous software development is not model intelligence, but context management and architectural determinism. Current “Agentic” approaches fail at scale because they rely on probabilistic guidance (prompts) for deterministic engineering tasks (builds, security, state management). Furthermore, the linear cost of token consumption versus the non-linear degradation of model attention creates a “Context Trap” […]