Recent disclosures highlight security flaws in AI application frameworks such as Chainlit, alongside growing use of AI by defenders to prioritize exploitable vulnerabilities. Strategic reporting also underscores executive misalignment on AI risk and the need for stronger governance and semantic-aware defenses as AI adoption accelerates.
Red teaming AI isn’t about tricking models, it’s about breaking systems. Learn how to test AI deployments the way attackers actually will.
Anthropic patched critical prompt-injection-related vulnerabilities in its Git MCP server, and follow-up reporting added detail on the Google Gemini calendar data flaw. Strategic commentary from Davos emphasizes AI security infrastructure gaps as prompt injection and semantic threat vectors remain primary risks in 2026.
AI systems can be attacked through cost and compute abuse without ever breaking a rule. Learn how to treat AI resource consumption as a security-controlled asset.
New reporting shows how AI assistants can be manipulated through trusted enterprise workflows such as calendar invites and health data integrations, increasing the risk of indirect prompt injection and sensitive data exposure. Adjacent cybersecurity developments reinforce that email infrastructure weaknesses, public exploit code, and geopolitical pressures remain key pathways into AI-enabled environments.
When AI gets access to cloud APIs and SaaS platforms, trust becomes risk. Learn how to secure AI as a non-human identity before automation turns into exposure.
New reporting detailed an indirect prompt-activation technique against Microsoft Copilot and highlighted a critical ServiceNow AI Platform impersonation flaw, underscoring how assistant security failures often mirror classic SaaS and phishing attack paths. Adjacent coverage reinforced the ongoing risk of browser-extension data exfiltration and rising policy focus on securing AI agents.
Data poisoning doesn’t attack models directly, it attacks trust. Learn how poisoned training and RAG data reshape AI behavior and how to defend against it.
January security reporting highlights growing concern over AI agent memory and post-holiday discovery of shadow AI integrations, while adjacent cyber trends show identity abuse and SaaS compromise continuing to drive enterprise risk.
AI threats aren’t mysterious, they’re familiar risks in new places. Learn how to apply STRIDE threat modeling to AI systems and design stronger defenses.
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