Uber Technologies Inc. has open-sourced its enterprise security system for AI agents, called Agentic AI Detection and Response (ADR), which tracks and blocks malicious agent actions. The software, use…
A developer has open-sourced a framework-agnostic testing methodology for AI agents, including a 61-source benchmark map and 58 universal test blocks across seven tiers, with full coverage of the OWAS…
A pre-deployment hardening pipeline that scans prompt templates and tool interfaces can eliminate basic data leakage entirely and reduce high-stress manipulation attacks by 91%, according to testing o…
Researchers propose Twin Agent, a privilege separation design pattern for LLM agents that uses two nearly symmetric agents—an Explore Agent inspecting untrusted information and a Safe Agent executing …
LLMbda, a new framework based on untyped call-by-value lambda calculus, introduces a provenance-based approach to defend AI agents against prompt injection attacks. In tests on the AgentDojo banking b…
An independent researcher found that existing indirect prompt injection benchmarks like BIPIA, InjecAgent, and AgentDojo may produce unreliable scores due to reliance on LLM-judges and evaluation of e…
Guardian, an open-source user-space firewall for AI agents, has released v0.1.0, intercepting and evaluating agent actions with a deterministic policy engine. In testing, it reduced prompt-injection a…
A new benchmark, dspy-security-bench, reveals that DSPy prompt optimization degrades adversarial robustness against harder prompt-injection attacks. Testing with AgentDojo's attack suite, optimizers l…