AI Is Eating the Enterprise — But the Enterprise Is on the Menu Too. Seventy-two percent of organisations already embed AI, yet only 13 percent feel truly ready. Attackers know that gap and are rushing to weaponise it. Cisco’s latest report reads like a flight-recorder transcript from the future of ...
This week’s stories highlight the rapid emergence of new threats and defenses in the Agentic AI landscape. From OWASP’s DNS-inspired Agent Name Service (ANS) for verifying AI identities to real-world exploits like jailbreakable “dark LLMs” and prompt-injected assistants like GitLab Duo, the ecosystem is shifting toward identity-first architecture and layered ...
Prompt injection remains one of the most dangerous and poorly understood threats in AI security. To assess how today’s large language models (LLMs) handle Prompt Injection risks, we interviewed ChatGPT, Claude, Grok, and Deepseek. We asked each of them 11 expert-level questions covering real-world attacks, defense strategies, and future readiness. ...
Based on Microsoft AI Red Team’s white paper “Taxonomy of Failure Modes in Agentic AI Systems”. Why CISOs, Architects & Staff Engineers Must Read Microsoft’s Agentic AI Failure Mode Taxonomy Agentic AI is moving from proof-of-concept to production faster than most security teams can update their threat models. In response, ...
This week’s stories highlight a critical evolution in AI risk: the shift from isolated agent failures to system-level compromise in Agentic AI architectures and memory-based applications. From Princeton’s demonstration of cryptocurrency theft via false memory injection to Fortnite’s AI Darth Vader being manipulated into swearing within an hour of launch, ...
As AI systems rapidly integrate into critical infrastructure and enterprise workflows, their attack surfaces are expanding just as quickly. Consequently, traditional cybersecurity controls are no longer sufficient. To address this growing risk, the new ETSI TS 104 223 V1.1.1 (2025-04) — Securing Artificial Intelligence (SAI); Baseline Cyber Security Requirements for ...
As LLMs become embedded across enterprise applications, new red-teaming research shows jailbreak success rates surpassing 87% on models like GPT-4—even under safety-aligned settings. Techniques such as multi-turn roleplay, token-level obfuscation, and cross-model attacks continue to outpace current safeguards. Meanwhile, insider misuse and unfiltered GenAI outputs pose growing risks, prompting calls ...
MCP Security is a top concern for anyone building Agentic AI systems. The Model Context Protocol (MCP) connects tools, agents, and actions. It plays a role similar to TCP/IP—but for autonomous workflows. If MCP is compromised, the entire agent stack is at risk. Attackers can inject prompts, hijack tools, and ...
Enterprise use of generative AI is expanding, but so is the sophistication of attacks targeting these systems. New jailbreak methods are achieving nearly 100% success rates, even on well-aligned models like GPT-4 and Llama3, while recent research exposes vulnerabilities in memory, prompt interpretation, and cross-tool coordination protocols like MCP. At ...
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