A Cisco evaluation of frontier LLMs found that no tested model consistently resisted multi-turn adversarial attacks, raising concerns about current AI safety assessments. The research suggests that many widely used AI safety benchmarks may underestimate real-world risk because they focus primarily on single-turn prompt evaluations rather than adaptive, iterative attacks. Key Takeaways from Cisco’s Research…
Tag: LLMs
AI, Global Security News
AI red teaming agents change how LLMs get tested
Adversarial probing of LLMs has piled up a sprawling toolkit over the past three years. Attack techniques with names like Tree of Attacks with Pruning, Crescendo, and Skeleton Key sit alongside hundreds of prompt transforms and scoring methods across open-source frameworks including Microsoft’s PyRIT, NVIDIA’s Garak, and Promptfoo. The catalog has grown faster than any…
AI, Global Security News
The AI backdoor your security stack is not built to see
Enterprises deploying LLMs have spent the past two years building defenses around a reasonable assumption: malicious behavior leaves a trace in the input. Scan for suspicious tokens, filter unusual characters, watch for prompt injection patterns. New research from Microsoft and the Institute of Science Tokyo demonstrates that this defensive posture has a blind spot, and…
AI, Compliance, Global Security News
AI is ready to take over Python programming, but not much else
Tests of how well 19 large language models (LLMs) complete and perform complicated multi-step tasks has shown that they are both error-prone and, in many cases, unreliable. The findings are contained a preprint paper, LLMs Corrupt Your Documents When You Delegate, written by Microsoft researchers Philippe Laban, Tobias Schnabel and Jennifer Neville based on a…
AI, Cybersecurity, Data Breaches, Endpoint, Global Security News, Risk Management
Poisoned truth: The quiet security threat inside enterprise AI
As enterprises rush to deploy internal LLMs, AI copilots, and autonomous agents, most security conversations focus on familiar threats: prompt injection, jailbreaks, model abuse, and data exfiltration. But some security leaders argue a quieter risk deserves far more attention: what happens when the model’s understanding of reality itself becomes corrupted. This problem is broadly described…
Cybersecurity, Global Security News
Parsing Agentic Offensive Security’s Existential Threat
Some fear frontier LLMs like Claude Mythos and Anthropic’s GPT-5.5 will lead to cybersecurity annihilation. Ari Herbert-Voss notes this could be an opportunity.
Exploits, Global Security News
LMDeploy CVE-2026-33626 Flaw Exploited Within 13 Hours of Disclosure
A high-severity security flaw in LMDeploy, an open-source toolkit for compressing, deploying, and serving LLMs, has come under active exploitation in the wild less than 13 hours after its public disclosure. The vulnerability, tracked as CVE-2026-33626 (CVSS score: 7.5), relates to a Server-Side Request Forgery (SSRF) vulnerability that could be exploited to access sensitive data.…
Apps, Endpoint, Global Security News, Risk Management
How Exposed Endpoints Increase Risk Across LLM Infrastructure
As more organizations run their own Large Language Models (LLMs), they are also deploying more internal services and Application Programming Interfaces (APIs) to support those models. Modern security risks are being introduced less from the models themselves and more from the infrastructure that serves, connects and automates the model. Each new LLM endpoint expands the…
AI, Apps, Compliance, Cybersecurity, Global Security News, Risk Management
AI FOMO: How Pressure to Adopt AI is Outpacing Understanding
AI – or large language models (LLMs) – is introducing new attack surfaces, despite the new capabilities that the technology promises. The new threats it is introducing, including prompt injection, deepfakes, and alignment risks, are huge security concerns at a strategic level. AI FOMO is driving enterprise adoption before risk mitigation At the Genetec Global…