Defend
Building a Hybrid Rule-Based and Machine Learning Framework to Detect and Defend Against Jailbreak Prompts in LLM Systems
In this tutorial, we introduce a Jailbreak Defense that we built step-by-step to detect and safely handle policy-evasion prompts. We generate realistic attack and benign examples, craft rule-based signals, and combine those with TF-IDF features into a compact, interpretable classifier so we can catch evasive prompts without blocking legitimate requests. We demonstrate evaluation metrics, explain…
Clément Domingo: “We are not using AI correctly to defend ourselves”
Following Kaspersky Horizon on 1 July in Madrid, Clément Domingo, ethical hacker and cybersecurity evangelist, explains the cybercrime landscape now looks like the legitimate startup world: structured organizations with affiliates and even team-building culture. How a criminal startup works “A cybercrime startup is similar to a classic startup, but dedicated to cybercrime in a very…
How cybersecurity leaders can defend against the spur of AI-driven NHI
Machine identities pose a big security risk for enterprises, and that risk will be magnified dramatically as AI agents are deployed. According to a report by cybersecurity vendor CyberArk, machine identities — also known as non-human identities (NHI) — now outnumber humans by 82 to 1, and their number is expected to increase exponentially. By…
Scattered Spider: Understanding Help Desk Scams and How to Defend Your Organization
In the wake of high-profile attacks on UK retailers Marks & Spencer and Co-op, Scattered Spider has been all over the media, with coverage spilling over into the mainstream news due to the severity of the disruption caused — currently looking like hundreds of millions in lost profits for M&S alone. This coverage is extremely…