--- title: 1 unread message | daily.dev description: STRIDE, the classic Microsoft threat modeling framework from the 1990s, struggles with agentic AI because a single AI agent can simultaneously act as a... canonical: https://daily.dev/posts/1-unread-message-khukymmto twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: 1 unread message | daily.dev og:description: STRIDE, the classic Microsoft threat modeling framework from the 1990s, struggles with agentic AI because a single AI agent can simultaneously act as a... og:url: https://daily.dev/posts/1-unread-message-khukymmto og:image: https://api.daily.dev/og/posts/kHUKyMmto.png og:image:alt: 1 unread message og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # 1 unread message **[Sliver C2 Documentation](https://daily.dev/sources/bishopfox)** · 14 min read · 0 upvotes · 0 comments ## Summary STRIDE, the classic Microsoft threat modeling framework from the 1990s, struggles with agentic AI because a single AI agent can simultaneously act as a process, data store, dataflow, and actor, sometimes trusted and sometimes not. MAESTRO, introduced by Ken Huang, addresses this by modeling threats across seven architectural layers of autonomous AI systems: foundation models, data operations, agent frameworks, deployment/infrastructure, evaluation/observability, security/compliance, and the agent ecosystem/supply chain. Using a corporate flight-booking agent example, the piece walks through when STRIDE alone suffices (simple internal data retrieval), when MAESTRO becomes necessary (agent with external API and multi-system access), and how blending both frameworks with trust boundaries and actor types (valid internal actor, adversarial AI, malicious actor) gives fuller coverage. The recommendation is to treat AI agents as potential insider threats and combine frameworks rather than rigidly adhering to one. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Why does the STRIDE threat modeling framework fall short for agentic AI systems? STRIDE assumes systems have fixed, predictable roles, but an AI agent can simultaneously act as a process, data store, dataflow, and actor. It might be a trusted internal actor for one workflow and a potentially malicious external actor for another, which breaks STRIDE's core assumption of clearly defined component roles. _Teams securing agentic AI can follow ongoing threat-modeling frameworks and analysis on daily.dev._ ### What are the seven layers of the MAESTRO threat modeling framework for AI agents? MAESTRO models threats across seven layers: Foundation Models (L1), Data Operations (L2), Agent Frameworks (L3), Deployment and Infrastructure (L4), Evaluation and Observability (L5), Security and Compliance (L6, a vertical layer affecting all others), and Agent Ecosystem/Supply Chain (L7). Each layer surfaces distinct risks like memory poisoning, tool misuse, and prompt injection. _Developers building multi-layered AI agent defenses can track MAESTRO-style guidance on daily.dev._ ### Should AI agents be treated as insider threats in threat modeling? Yes, some organizations apply a zero-trust approach and start threat modeling internal agentic AI applications from the assumption that the agents themselves are insider threats. This is because an over-privileged agent with read/write access to systems like an approval database can be coerced into granting unauthorized approvals or altering policy, similar to a compromised employee account. _Security teams weighing zero-trust assumptions for AI agents can follow related analysis on daily.dev._ ## Similar posts on daily.dev - [Introducing MAESTRO: A framework for securing generative and agentic AI](https://daily.dev/posts/introducing-maestro-a-framework-for-securing-generative-and-agentic-ai-2rkaghzkq) · CSO Online · 1 upvotes · 0 comments - [Microsoft SQL Security Across the MAESTRO Stack: Building Secure Agentic AI with Defense-in-Depth](https://daily.dev/posts/microsoft-sql-security-across-the-maestro-stack-building-secure-agentic-ai-with-defense-in-depth-cfcprgyxn) · DevBlogs · 1 upvotes · 0 comments - [Trustworthy Productivity: Securing AI Accelerated Development](https://daily.dev/posts/trustworthy-productivity-securing-ai-accelerated-development-v8mtkdb7v) · InfoQ · 1 upvotes · 0 comments - [Agentic AI Security: Risks, Controls & Framework](https://daily.dev/posts/agentic-ai-security-risks-controls-framework-richrgmlz) · Orca Security Blog · 1 upvotes · 0 comments - [Building Trust in AI Agent Ecosystems](https://daily.dev/posts/building-trust-in-ai-agent-ecosystems-foe6ezl4c) · Cisco · 1 upvotes · 0 comments --- Tags: [#security](https://daily.dev/tags/security), [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#appsec](https://daily.dev/tags/appsec), [#prompt-injection](https://daily.dev/tags/prompt-injection) [View this post on daily.dev](https://daily.dev/posts/1-unread-message-khukymmto) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"1 unread message","url":"https://daily.dev/posts/1-unread-message-khukymmto","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/1-unread-message-khukymmto"},"datePublished":"2026-08-23T12:22:27.263Z","dateModified":"2026-08-23T12:50:15.712Z","description":"STRIDE, the classic Microsoft threat modeling framework from the 1990s, struggles with agentic AI because a single AI agent can simultaneously act as a...","image":"https://media.daily.dev/image/upload/s--foaA6JGU--/f_auto/v1722860399/public/Placeholder%2004","thumbnailUrl":"https://media.daily.dev/image/upload/s--foaA6JGU--/f_auto/v1722860399/public/Placeholder%2004","isAccessibleForFree":true,"articleSection":"Sliver C2 Documentation","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Sliver C2 Documentation","logo":"https://media.daily.dev/image/upload/logos/placeholder.jpg","url":"https://daily.dev/sources/bishopfox"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/1-unread-message-khukymmto","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"security,llm,ai-agents,appsec,prompt-injection","timeRequired":"PT14M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Sliver C2 Documentation","item":"https://daily.dev/sources/bishopfox"},{"@type":"ListItem","position":3,"name":"1 unread message"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/1-unread-message-khukymmto#faq","mainEntity":[{"@type":"Question","name":"Why does the STRIDE threat modeling framework fall short for agentic AI systems?","acceptedAnswer":{"@type":"Answer","text":"STRIDE assumes systems have fixed, predictable roles, but an AI agent can simultaneously act as a process, data store, dataflow, and actor. 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