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Read the latest insights on AI security technologies, industry trends, and prompt engineering from the AIM Intelligence research and engineering teams.
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AI Security Digest — June 2026
DIGEST • JUL 21, 2026

AI Security Digest — June 2026

June 2026 was the month the guardrail became a platform feature. OpenAI shipped in-model activation classifiers, AWS, Google, and Microsoft productized runtime checks within four days of each other, and F5 bundled AI testing with AI runtime defense. Meanwhile the Shai-Hulud/Miasma worm turned 13 AI coding agents into propagation vectors, the US Commerce Department shut down two frontier models over a single jailbreak, and academia converged on structural execution control over blocking. Six stories that defined the month.

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"Vetted, Self-Contained Sources": What We Found Inside a NASA Mission's Public Chatbot
SECURITY • JUL 1, 2026

"Vetted, Self-Contained Sources": What We Found Inside a NASA Mission's Public Chatbot

A public chatbot on NASA's Parker Solar Probe mission page promised users its answers came only from "vetted, self-contained sources." We red-teamed it into fabricating leaked memos, fake election audits, and climate denial citing the mission's own data — then disclosed it through proper channels and saw the endpoint taken offline.

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The Helpfulness Trap: Claude Opus 4.8 and the CBRN Breach Hidden in Plain Sight
RESEARCH • JUN 24, 2026

The Helpfulness Trap: Claude Opus 4.8 and the CBRN Breach Hidden in Plain Sight

No jailbreak, no tricks — just professionally framed requests. Using our Stinger red-teaming engine, we collected 83 confirmed CBRN breaches from Claude Opus 4.8.

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Why AI Security Is Moving Toward Continuous Monitoring
RESEARCH • JUN 19, 2026

Why AI Security Is Moving Toward Continuous Monitoring

A recent NIST publication argues that no finite set of AI safety rules can protect against all future attacks. As AI agents gain access to tools and enterprise systems, security is shifting from static guardrails toward continuous monitoring and adaptation.

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AI Security Digest — May 2026
DIGEST • JUN 12, 2026

AI Security Digest — May 2026

May 2026 was a watershed month for AI security. From the first AI-authored zero-day exploit confirmed in the wild, to a self-propagating npm worm that reached OpenAI's code-signing pipeline, to prompt injection flaws enabling full RCE in Microsoft's Semantic Kernel — the attack surface around AI systems expanded on every front. This digest covers seven stories that defined the month, including the release of XL-SafetyBench from AIM Intelligence and collaborators.

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

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

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How ELITE Reveals Dangerous Weaknesses in Vision-Language AI
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.

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

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