--- title: Four ways AI has fundamentally changed the threat... description: The Sysdig Threat Research Team documents four structural shifts in the 2026 threat landscape driven by agentic AI. First, autonomous AI agents (ATAs) are now... canonical: https://daily.dev/posts/four-ways-ai-has-fundamentally-changed-the-threat-landscape-in-2026-0qwofii9p twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Four ways AI has fundamentally changed the threat landscape in 2026 | daily.dev og:description: The Sysdig Threat Research Team documents four structural shifts in the 2026 threat landscape driven by agentic AI. First, autonomous AI agents (ATAs) are now... og:url: https://daily.dev/posts/four-ways-ai-has-fundamentally-changed-the-threat-landscape-in-2026-0qwofii9p og:image: https://api.daily.dev/og/posts/0QWofII9p.png og:image:alt: Four ways AI has fundamentally changed the threat landscape in 2026 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. # Four ways AI has fundamentally changed the threat landscape in 2026 **[Sysdig Blog](https://daily.dev/sources/sysdig-blog)** · 12 min read · 1 upvotes · 0 comments ## Summary The Sysdig Threat Research Team documents four structural shifts in the 2026 threat landscape driven by agentic AI. First, autonomous AI agents (ATAs) are now conducting end-to-end attacks without human intervention — moving from initial access to database exfiltration in under an hour, escaping containers to steal Kubernetes secrets, and running full ransomware operations (JADEPUFFER). Second, AI infrastructure (Langflow, LMDeploy, Marimo, LiteLLM, Ollama) has become a prime target because it stores high-value credentials and API keys. Third, exploitation timelines have collapsed — several AI framework CVEs were exploited within 4–36 hours of disclosure, sometimes before a CVE was even assigned. Fourth, attackers are manipulating models via CTF-framing jailbreaks and deploying 'abliterated' (guardrail-stripped) open-source models. The post argues that runtime visibility, AI asset inventories (AIBOMs), and detection tuned to LLM behavioral artifacts are now essential defensive controls. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What is JADEPUFFER and how does agentic ransomware work? JADEPUFFER is the first documented case of agentic ransomware, a complete extortion operation run end-to-end by an AI agent rather than a human operator. It exploited a year-old vulnerability in an internet-facing Langflow instance, harvested LLM, cloud, and cryptocurrency credentials, then encrypted over 1,300 configuration entries on a production MySQL and Alibaba Nacos server, leaving an LLM-generated ransom note with a Bitcoin address. _Teams tracking ransomware evolution can follow agentic threat research like this through daily.dev._ ### How fast are attackers exploiting new AI infrastructure CVEs after disclosure? Recent AI infrastructure vulnerabilities have been exploited within hours of disclosure: a PraisonAI authentication bypass in under 4 hours, a Marimo RCE in under 10 hours, an LMDeploy SSRF in 12 hours, a Langflow RCE in 20 hours, and a LiteLLM SQL injection in 36 hours. Several attacks began from a GitHub Security Advisory before a CVE was even assigned, since disclosures effectively hand attackers a ready proof of concept. _Developers patching AI pipeline tools can follow disclosure-to-exploit timelines like these on daily.dev._ ### How many Ollama instances are publicly exposed to the internet and why does that matter? An estimated 175,000 Ollama instances were found publicly exposed across more than 130 countries. Attackers have used exposed, unauthenticated Ollama servers as the reasoning engine for autonomous offensive tools, meaning locally hosted models create the same stolen-compute risk as cloud LLM API credential theft, a technique known as LLMjacking. _Anyone securing self-hosted LLM deployments can track exposure findings like this via daily.dev._ --- Tags: [#security](https://daily.dev/tags/security), [#llm](https://daily.dev/tags/llm), [#ai-security](https://daily.dev/tags/ai-security), [#agentic-ai](https://daily.dev/tags/agentic-ai) [View this post on daily.dev](https://daily.dev/posts/four-ways-ai-has-fundamentally-changed-the-threat-landscape-in-2026-0qwofii9p) ```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":"Four ways AI has fundamentally changed the threat landscape in 2026","url":"https://daily.dev/posts/four-ways-ai-has-fundamentally-changed-the-threat-landscape-in-2026-0qwofii9p","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/four-ways-ai-has-fundamentally-changed-the-threat-landscape-in-2026-0qwofii9p"},"datePublished":"2026-07-21T13:50:10.252Z","dateModified":"2026-09-14T07:39:10.976Z","description":"The Sysdig Threat Research Team documents four structural shifts in the 2026 threat landscape driven by agentic AI. First, autonomous AI agents (ATAs) are now...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/8f2a92c74e0786549983353bf8c2cf41?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/8f2a92c74e0786549983353bf8c2cf41?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Sysdig Blog","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":"Sysdig Blog","logo":"https://media.daily.dev/image/upload/s--1S2uMy2c--/f_auto,q_auto/v1780213305/logos/sysdig-blog?_a=BAMAMiWQ0","url":"https://daily.dev/sources/sysdig-blog"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/four-ways-ai-has-fundamentally-changed-the-threat-landscape-in-2026-0qwofii9p","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"security,llm,ai-security,agentic-ai","timeRequired":"PT12M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Sysdig Blog","item":"https://daily.dev/sources/sysdig-blog"},{"@type":"ListItem","position":3,"name":"Four ways AI has fundamentally changed the threat landscape in 2026"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/four-ways-ai-has-fundamentally-changed-the-threat-landscape-in-2026-0qwofii9p#faq","mainEntity":[{"@type":"Question","name":"What is JADEPUFFER and how does agentic ransomware work?","acceptedAnswer":{"@type":"Answer","text":"JADEPUFFER is the first documented case of agentic ransomware, a complete extortion operation run end-to-end by an AI agent rather than a human operator. It exploited a year-old vulnerability in an internet-facing Langflow instance, harvested LLM, cloud, and cryptocurrency credentials, then encrypted over 1,300 configuration entries on a production MySQL and Alibaba Nacos server, leaving an LLM-generated ransom note with a Bitcoin address. Teams tracking ransomware evolution can follow agentic threat research like this through daily.dev."}},{"@type":"Question","name":"How fast are attackers exploiting new AI infrastructure CVEs after disclosure?","acceptedAnswer":{"@type":"Answer","text":"Recent AI infrastructure vulnerabilities have been exploited within hours of disclosure: a PraisonAI authentication bypass in under 4 hours, a Marimo RCE in under 10 hours, an LMDeploy SSRF in 12 hours, a Langflow RCE in 20 hours, and a LiteLLM SQL injection in 36 hours. Several attacks began from a GitHub Security Advisory before a CVE was even assigned, since disclosures effectively hand attackers a ready proof of concept. Developers patching AI pipeline tools can follow disclosure-to-exploit timelines like these on daily.dev."}},{"@type":"Question","name":"How many Ollama instances are publicly exposed to the internet and why does that matter?","acceptedAnswer":{"@type":"Answer","text":"An estimated 175,000 Ollama instances were found publicly exposed across more than 130 countries. Attackers have used exposed, unauthenticated Ollama servers as the reasoning engine for autonomous offensive tools, meaning locally hosted models create the same stolen-compute risk as cloud LLM API credential theft, a technique known as LLMjacking. Anyone securing self-hosted LLM deployments can track exposure findings like this via daily.dev."}}]} ```