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The open web is slowly but surely filling up with “traps” designed for LLM-powered AI agents. The technique, known as indirect prompt injection (IPI), involves hiding (more or less) covert instructions inside ordinary web pages, waiting for…
Enterprises running customer service bots, data analytics agents, and other AI-driven applications in production handle sensitive records and connect to core business systems every day. LangWatch has released Scenario, an open-source framework that run…
Penetration testers have long relied on collections of specialized tools, manual coordination, and documented runbooks to work through a target assessment. PentAGI, an open-source project from VXControl, attempts to automate that entire workflow using …
In this Help Net Security interview, Aqsa Taylor, Chief Security Evangelist, Exaforce, explains vibe hunting, an AI-driven approach to threat detection that inverts traditional hypothesis-driven methods. Instead of analysts defining attack vectors upfr…
Online platforms are running large language models at every stage of LLM content moderation, from generating training data to auditing their own systems for bias. Researchers at Google mapped how this is happening across what the authors call the Abuse…
Generative AI tools have brought the cost of deepfake production low enough that criminals and state-sponsored actors now use them routinely against financial institutions. A joint paper from the American Bankers Association, the Better Identity Coalit…
Container sandboxes are part of routine AI agent testing and deployment. Agents use them to run code, edit files, and interact with system resources without direct access to the host. The SandboxEscapeBench benchmark, developed by researchers at the Un…
Vendors selling AI-powered security operations platforms have built their pitches around a consistent set of promises: autonomous threat investigation, dramatic reductions in analyst workload, and an accelerating path toward humanless operations. Pract…
Prompt engineering has become a standard part of how large language models are deployed in production, and it introduces an attack surface most organizations have not yet addressed. Researchers have developed and tested a prompt-based backdoor attack m…
Large language models carry a persistent scaling problem. As context windows grow, the memory required to store key-value (KV) caches expands proportionally, consuming GPU memory and slowing inference. A team at Google Research has developed three comp…