AIM BLOG

Latest Insights.

HomeBlog
Read the latest insights on AI security technologies, industry trends, and prompt engineering from the AIM Intelligence research and engineering teams.
Article list
RESEARCH • NOV 30, 2025

Tool-Mediated Belief Injection: How Tool Outputs Can Cascade Into Model Misalignment

When we deploy language models with access to external tools, we dramatically expand their capabilities. However, tool access also introduces new attack surfaces that differ fundamentally from traditional prompt injection. We document how adversarially crafted tool outputs can establish false premises that persist and compound across a conversation.

Read Post →
RESEARCH • AUG 14, 2025

MisalignmentBench: How We Social Engineered LLMs Into Breaking Their Own Alignment

We got frontier models to lie, manipulate, and self-preserve. Not through prompt injection or jailbreaks. We deployed them in contextually rich scenarios with specific roles and guidelines. The models broke their own alignment trying to navigate the situations we created.

Read Post →
RESEARCH • MAY 29, 2025

How ELITE Reveals Dangerous Weaknesses in Vision-Language AI

As AI systems evolve to process images and text together, the risks grow exponentially. ELITE doesn't just measure whether a model is 'safe' — it evaluates how dangerous its outputs could be with precision that rivals human reviewers.

Read Post →
RESEARCH • MAY 26, 2025

Pressure Point: How One Bad Metric Can Push AI Toward a Fatal Choice

In a simulated earthquake response scenario, Claude 4 Opus was given conflicting rules. When pressured by authority, it reversed its ethical decision and recommended letting a critical patient die to optimize an efficiency score.

Read Post →
SECURITY • MAY 21, 2025

Exploiting MCP: Emerging Security Threats in Large Language Models (LLMs)

Discover how attackers exploit vulnerabilities in the Model Context Protocol (MCP) to manipulate Large Language Models (LLMs), steal data, and disrupt operations. Learn real-world attack scenarios and defense strategies.

Read Post →
RESEARCH • NOV 27, 2024

Making AI Safer with SPA-VL: A New Dataset for Ethical Vision-Language Models

SPA-VL is a meticulously designed dataset that sets a new standard for safety alignment in VLMs, incorporating diversity, feedback, and real-world relevance to ensure AI systems are both powerful and ethical.

Read Post →
SECURITY • NOV 25, 2024

The Hidden Threat: Understanding Indirect Prompt Injection in LLMs

Indirect Prompt Injection (IPI) is a sophisticated attack that manipulates how LLM-integrated applications process external data, causing them to misinterpret maliciously crafted inputs as commands.

Read Post →
RESEARCH • NOV 18, 2024

Introducing AI Safety Benchmark v0.5: MLCommons' Initiative

AI Safety Benchmark v0.5 is a proof-of-concept benchmark designed to evaluate the safety of text-based generative language models, providing a structured approach to assess potential risks.

Read Post →
RESEARCH • NOV 15, 2024

AIM Red Team: Leveraging Psychological Personas for Advanced LLM Jailbreaking Strategies

Explore how psychological persona-based approaches can be used to test LLM vulnerabilities through single-turn and multi-turn jailbreaking scenarios based on Big Five personality traits.

Read Post →
12Next →
aim

Ready to secure your AI?

Consult with AIM Intelligence's security experts and request a free red teaming demo optimized for your system.

EXPLORE PLATFORM