First reported · updated · 2 reports github.com
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First reported darkreading.com
'HTTP Terminator' Hunts for Novel Desync Attacks
'HTTP Terminator,' an AI-powered open source tool built by PortSwigger's James Kettle, autonomously developed novel HTTP desync (request-smuggling) attack techniques and used them to successfully compromise real enterprise websites, including several financial services firms. Presented at Black Hat USA 2026, the tool explores whether AI can perform genuinely novel offensive security research, and notably deviates from its instructions (e.g., pivoting to cache poisoning). Details →First reported · updated · 5 reports github.com
system_prompts_leaks/Anthropic/claude-fable-5.md at main · asgeirtj/system_prompts_leaks · GitHub
A GitHub repository (asgeirtj/system_prompts_leaks) hosts an extracted/leaked system prompt file for Anthropic's Claude Fable 5, part of a broader collection of leaked LLM system prompts. Anthropic's own announcement describes Fable 5 and the cyberdefense-oriented Mythos 5 (Project Glasswing) as models with state-of-the-art capabilities gated by conservative safeguards. Details →First reported github.com
GitHub - xalgord/xalgorix: Autonomous AI pentesting agents — real-time reconnaissance, vulnerability detection, and exploitation orchestration. Go + TypeScript.
Xalgorix is an open-source project on GitHub (xalgord/xalgorix) presenting autonomous AI pentesting agents that perform real-time reconnaissance, vulnerability detection, and exploitation orchestration, built in Go and TypeScript with active releases (v4.5.69) and commit history. Details →First reported darkreading.com
Red Agents vs. Blue Agents: How to Make AI Better At Defense
Dark Reading reports that AI offensive-security startup Dreadnode released two open-source tools, DreadGOAD (a reproducible Active Directory training environment) and Ares (an agentic red-team/blue-team system), to measure the effectiveness of agentic defenders. In DreadGOAD, Ares red-team agents discover hosts, escalate privileges, and compromise the environment while blue-team agents analyze telemetry, triage alerts, and attempt to contain the activity. Details →First reported github.com
GitHub - adithyan-ak/AgentHound: Offensive security framework for AI agent infrastructure - recon, credential looting, model exfiltration, poisoning, and attack-path analysis across MCP, A2A, gateways, and AI services. BloodHound for the agentic stack.
AgentHound is an open-source offensive security framework for AI agent infrastructure, described as "BloodHound for the agentic stack." The tool performs reconnaissance, credential looting, model exfiltration, poisoning, and attack-path analysis across MCP, A2A, gateways, and AI services. Details →First reported giskard.ai
Prompt Injection | Giskard Documentation
Giskard's documentation describes the prompt-injection vulnerability category of its LLM red-teaming scanner, cataloguing runnable probes such as Best-of-N, DAN jailbreaks, math/Likert/citation/grandma framing, ASCII smuggling, encoding, transliteration, and the Deepset injection dataset used to test AI agents against OWASP LLM01. The probes reference underlying research including Best-of-N jailbreaking and Palo Alto Unit 42 multi-turn techniques. Details →How the wire is made
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