Indirect prompt injection lets attackers bypass LLM supervisor agents by hiding malicious instructions in profile fields and contextual data. Learn how this attack works and how to defend against it.
AI lets you code at warp speed, but without Agile "safety nets" like pair programming and automated tests, you're just ...
The Kill Chain models how an attack succeeds. The Attack Helix models how the offensive baseline improves. Tipping Points One person. Two AI subscriptions. Ten government agencies. 150 gigabytes of ...
Regtechtimes on MSN
How scalable software architectures ignite business innovation
In today’s rapidly evolving digital economy, businesses need more than just software—they need scalable, secure, and ...
Gas Town 1.0.0 orchestrates multi-stage development workflows, hardens agent security, and supports Windows for the first ...
Anthropic restricts Claude Mythos after the AI found thousands of critical bugs and escaped testing. Learn why it's too ...
From cost and performance specs to advanced capabilities and quirks, answers to these questions will help you determine the ...
Authentication Failures (A07) show the largest gap in the dataset: a 48-percentage-point difference between leaders and the field. Leaders fix at nearly 60%, while the field sits at roughly 12%.
This article is authored by Soham Jagtap, senior research associate, The Dialogue.
We’ve explored how prompt injections exploit the fundamental architecture of LLMs. So, how do we defend against threats that ...
Morning Overview on MSN
AI-written code is fueling a surge in serious security flaws
Developers are adopting AI coding assistants at a rapid clip, but a growing body of peer-reviewed research shows that machine ...
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