[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-0aec124c9827ed5d-shadow-ai-outruns-enterprise-policies-in-2026-summary":3,"summaries-facets-categories":224,"summary-related-0aec124c9827ed5d-shadow-ai-outruns-enterprise-policies-in-2026-summary":3819},{"id":4,"title":5,"ai":6,"body":13,"categories":142,"created_at":144,"date_modified":144,"description":134,"extension":145,"faq":144,"featured":146,"kicker_label":144,"meta":147,"navigation":205,"path":206,"published_at":207,"question":144,"scraped_at":208,"seo":209,"sitemap":210,"source_id":211,"source_name":212,"source_type":213,"source_url":214,"stem":215,"tags":216,"thumbnail_url":144,"tldr":221,"tweet":144,"unknown_tags":222,"__hash__":223},"summaries\u002Fsummaries\u002F0aec124c9827ed5d-shadow-ai-outruns-enterprise-policies-in-2026-summary.md","Shadow AI Outruns Enterprise Policies in 2026",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","x-ai\u002Fgrok-4.1-fast",8228,3205,46870,0.00322545,{"type":14,"value":15,"toc":133},"minimark",[16,21,25,28,31,35,38,41,44,47,50,54,57,60,63,66,70,73,80,86,89,92,95,99],[17,18,20],"h2",{"id":19},"shadow-ais-scale-dwarfs-policy-efforts","Shadow AI's Scale Dwarfs Policy Efforts",[22,23,24],"p",{},"Employees adopt AI tools faster than governance can respond: 40-65% use unapproved AI per IBM and Netskope surveys, with 47% accessing via personal accounts and over half inputting sensitive data like source code, financials, and PII. Fewer than 20% see this as wrong—it's driven by productivity needs, not malice. Even when policies exist, 38% misunderstand them and 56% lack guidance; comprehension doesn't stop circumvention.",[22,26,27],{},"\"By the time a company’s legal team finishes drafting its generative AI acceptable use policy, a meaningful percentage of its engineers, analysts, and product managers have already moved past it. Not deliberately. Not maliciously. Just practically.\" This opening quote captures why shadow AI is the 2026 norm: tools like ChatGPT for debugging code or summarizing meetings deliver immediate wins policies can't match.",[22,29,30],{},"Samsung's 2023 incidents previewed this—engineers leaked semiconductor data in three cases post-ban lift, using a memo-based policy with no enforcement. Banning one tool just shifts to others, eroding visibility.",[17,32,34],{"id":33},"breach-costs-and-data-flows-reveal-hidden-risks","Breach Costs and Data Flows Reveal Hidden Risks",[22,36,37],{},"Shadow AI inflates breaches: IBM's 2025 report shows $670k extra costs per incident, averaging $4.63M vs $3.96M standard, factoring in 1\u002F5 breaches with 65% PII compromise (vs 53% avg) and 40% IP theft (vs 33%). Netskope logs 223 GenAI violations\u002Fmonth avg, 2,100 for top quartile, with prompts up 500% to 18k\u002Fmonth.",[22,39,40],{},"Data leaked spans code, projections, PII, HR data, M&A intel. Law firms exposed privileged info; hospitals misapplied de-identification (HHS clarifies it fails HIPAA sans agreements). Competitive intel is routine: engineers summarize internal analyses, sales paste pricing models.",[22,42,43],{},"Agentic AI escalates: Gartner predicts 40% of apps with task-specific agents by 2026 (from \u003C5%), built via Copilot Studio or APIs without IT review. These chain CRM\u002Femail access, vulnerable to prompt injection (OWASP #1 risk).",[22,45,46],{},"\"A policy employees understand but routinely ignore is not a governance framework. It is a liability disclaimer.\" This underscores why 63% lack policies, 66% skip audits—AI enters via browsers\u002Fextensions, not procurement.",[22,48,49],{},"EU AI Act enforcement (Aug 2026 for high-risk) demands inventories shadow AI evades, risking 3% turnover fines.",[17,51,53],{"id":52},"bans-backfire-provide-alternatives-to-win-compliance","Bans Backfire; Provide Alternatives to Win Compliance",[22,55,56],{},"90% block some AI, but substitution persists—personal data, mobiles bypass. 27% prefer unauthorized for better functionality; new hires factor AI access in job choice.",[22,58,59],{},"Procurement models fail; NIST's Govern\u002FMap\u002FMeasure\u002FManage assumes visibility most lack (108 known cloud services, 10x shadow). Effective orgs reframe to \"managed enablement\": tier tools (approved\u002Flimited\u002Fprohibited), classify data first, use real-time coaching over blocks.",[22,61,62],{},"CSA's discover\u002Fclassify\u002Fassess\u002Fcontrols\u002Fmonitor loop demands live inventories. When alternatives exist, shadow use drops sharply.",[22,64,65],{},"\"The goal is not to eliminate shadow AI through policy force. It is to make governed AI use easier than ungoverned AI use — so that the path of least resistance runs through the approved channel.\" This pivot prioritizes friction: warnings like \"PII detected, use enterprise tool\" guide at decision point.",[17,67,69],{"id":68},"layered-tools-bridge-visibility-prevention-governance","Layered Tools Bridge Visibility, Prevention, Governance",[22,71,72],{},"Combine layers for coverage:",[22,74,75,79],{},[76,77,78],"strong",{},"Discovery\u002FVisibility:"," Netskope (network traffic, 65k apps); Nudge Security (OAuth\u002Femail maps, 200k apps, behavioral nudges); Microsoft Purview (M365\u002FAzure DSPM, browser DLP).",[22,81,82,85],{},[76,83,84],{},"DLP for AI:"," Nightfall (ML detectors for prompts\u002Fsessions, redaction); Cyberhaven (endpoint lineage); Lakera Guard (LLM guardrails vs injections).",[22,87,88],{},"Governance platforms (truncated) build atop these. Tradeoff: no single tool suffices; Microsoft excels in-ecosystem but needs supplements.",[22,90,91],{},"Only 37% have policies, per IBM—stack these for inventories, enforcement, coaching.",[22,93,94],{},"\"Employees running semiconductor source code through ChatGPT to debug errors... are acting exactly in company interests — trying to close tickets faster... The productivity pressure that drives shadow AI adoption is not a bug in the system. It is the system.\"",[17,96,98],{"id":97},"key-takeaways","Key Takeaways",[100,101,102,106,109,112,115,118,121,124,127,130],"ul",{},[103,104,105],"li",{},"Inventory shadow AI first: Use Netskope\u002FNudge for real-time discovery; assume 10x unknown services.",[103,107,108],{},"Classify data rigorously: Define \"sensitive\" for AI contexts; prerequisite for tiered tools.",[103,110,111],{},"Tier approvals: Approved (no limits), limited (rules), prohibited—migrate shadow to governed paths.",[103,113,114],{},"Deploy real-time DLP\u002Fcoaching: Nightfall\u002FPurview warn\u002Fblock PII at paste, not post-breach.",[103,116,117],{},"Monitor agents: Gartner 40% trajectory demands OAuth\u002FAPI sprawl controls vs human-only models.",[103,119,120],{},"Measure costs: Shadow AI adds $670k\u002Fbreach; track violations (223+\u002Fmonth baseline).",[103,122,123],{},"Avoid bans: Provide superior enterprise alternatives; drops unauthorized use dramatically.",[103,125,126],{},"Comply proactively: EU AI Act needs inventories by Aug 2026; 73% gaps in discovery.",[103,128,129],{},"Quarterly reviews: Governance as ops, not docs—CSA continuous monitor.",[103,131,132],{},"Stack layers: Visibility + DLP + platforms for full stack.",{"title":134,"searchDepth":135,"depth":135,"links":136},"",2,[137,138,139,140,141],{"id":19,"depth":135,"text":20},{"id":33,"depth":135,"text":34},{"id":52,"depth":135,"text":53},{"id":68,"depth":135,"text":69},{"id":97,"depth":135,"text":98},[143],"DevOps & Cloud",null,"md",false,{"content_references":148,"triage":200},[149,155,159,163,167,170,174,178,181,185,188,191,194,197],{"type":150,"title":151,"author":152,"publisher":152,"url":153,"context":154},"report","2025 Cost of a Data Breach Report","IBM","https:\u002F\u002Fnewsroom.ibm.com\u002F2025-07-30-ibm-report-13-of-organizations-reported-breaches-of-ai-models-or-applications,-97-of-which-reported-lacking-proper-ai-access-controls","cited",{"type":150,"title":156,"author":157,"publisher":157,"url":158,"context":154},"Cloud and Threat Report 2026","Netskope","https:\u002F\u002Fwww.netskope.com\u002Fresources\u002Fcloud-and-threat-reports\u002Fcloud-and-threat-report-2026",{"type":160,"title":161,"url":162,"context":154},"other","Samsung semiconductor data leak","https:\u002F\u002Fwww.darkreading.com\u002Fvulnerabilities-threats\u002Fsamsung-engineers-sensitive-data-chatgpt-warnings-ai-use-workplace",{"type":150,"title":164,"publisher":165,"url":166,"context":154},"AI Risk Management Framework","NIST","https:\u002F\u002Fwww.nist.gov\u002Fitl\u002Fai-risk-management-framework",{"type":150,"title":168,"publisher":165,"url":169,"context":154},"2024 Generative AI Profile (NIST AI 600-1)","https:\u002F\u002Fnvlpubs.nist.gov\u002Fnistpubs\u002Fai\u002FNIST.AI.600-1.pdf",{"type":160,"title":171,"publisher":172,"url":173,"context":154},"EU AI Act","European Commission","https:\u002F\u002Fdigital-strategy.ec.europa.eu\u002Fen\u002Fpolicies\u002Fregulatory-framework-ai",{"type":150,"title":175,"publisher":176,"url":177,"context":154},"OWASP Top 10 for LLMs (2025 edition)","OWASP","https:\u002F\u002Fowasp.org\u002Fwww-project-top-10-for-large-language-model-applications\u002F",{"type":160,"title":179,"url":180,"context":154},"Gartner forecasts on AI agents","https:\u002F\u002Fwww.gartner.com\u002Fen\u002Fnewsroom\u002Fpress-releases\u002F2025-08-26-gartner-predicts-40-percent-of-enterprise-apps-will-feature-task-specific-ai-agents-by-2026-up-from-less-than-5-percent-in-2025",{"type":182,"title":157,"url":183,"context":184},"tool","https:\u002F\u002Fwww.netskope.com\u002F","recommended",{"type":182,"title":186,"url":187,"context":184},"Nudge Security","https:\u002F\u002Fwww.nudgesecurity.com\u002F",{"type":182,"title":189,"url":190,"context":184},"Microsoft Purview","https:\u002F\u002Fwww.microsoft.com\u002Fen-us\u002Fsecurity\u002Fbusiness\u002Fmicrosoft-purview",{"type":182,"title":192,"url":193,"context":184},"Nightfall AI","https:\u002F\u002Fwww.nightfall.ai\u002F",{"type":182,"title":195,"url":196,"context":184},"Cyberhaven","https:\u002F\u002Fwww.cyberhaven.com\u002F",{"type":182,"title":198,"url":199,"context":184},"Lakera Guard","https:\u002F\u002Fwww.lakera.ai\u002F",{"relevance":201,"novelty":201,"quality":202,"actionability":135,"composite":203,"reasoning":204},3,4,3.05,"Category: Business & SaaS. The article discusses the challenges of shadow AI in enterprises, highlighting the gap between employee tool adoption and governance policies, which is relevant to product builders concerned with compliance and risk management. However, while it presents useful statistics and insights, it lacks specific actionable steps for addressing these issues.",true,"\u002Fsummaries\u002F0aec124c9827ed5d-shadow-ai-outruns-enterprise-policies-in-2026-summary","2026-05-13 21:44:37","2026-05-13 23:00:23",{"title":5,"description":134},{"loc":206},"0aec124c9827ed5d","MarkTechPost","article","https:\u002F\u002Fwww.marktechpost.com\u002F2026\u002F05\u002F13\u002Fenterprise-ai-governance-in-2026-why-the-tools-employees-use-are-ahead-of-the-policies-that-cover-them\u002F","summaries\u002F0aec124c9827ed5d-shadow-ai-outruns-enterprise-policies-in-2026-summary",[217,218,219,220],"ai-tools","devops","cloud","saas","40-65% of employees use unapproved AI tools for productivity, exposing sensitive data; bans fail, so shift to tiered approvals and real-time DLP to channel usage into governed 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Archon v3 on Hetzner VPS with Docker",{"provider":7,"model":8,"input_tokens":3824,"output_tokens":3825,"processing_time_ms":3826,"cost_usd":3827},7846,1531,13348,0.0023122,{"type":14,"value":3829,"toc":4001},[3830,3834,3854,3864,3868,3875,3908,3923,3927,3938,3947,3962,3965,3969,3972,3994],[17,3831,3833],{"id":3832},"automate-vps-provisioning-for-one-click-archon-deployment","Automate VPS Provisioning for One-Click Archon Deployment",[22,3835,3836,3837,3841,3842,3845,3846,3849,3850,3853],{},"Hetzner VPS (CX11 at €2.50\u002Fmonth, pay-per-hour) handles Archon v3 basics: Caddy for HTTPS\u002FLet's Encrypt, Postgres DB, Docker stack. Create firewall opening ports 22 (SSH), 80 (HTTP), 443 (HTTPS). Use pre-built cloud-init.yaml from tasklist.smartcode.diy\u002Flist\u002Farchon-v3-cloud-setup—it runs apt upgrade, installs Docker\u002FCompose, clones Archon repo (github.com\u002Fcoleam00\u002FArchon), copies .env.example and Caddyfile.example, creates 'archon' user. Paste YAML into Hetzner server create dialog (Ubuntu 22.04, SSH keys, Nuremberg location). Server boots in minutes; monitor with ",[3838,3839,3840],"code",{},"cloud-init status --long"," or ",[3838,3843,3844],{},"watch cloud-init status",". SSH as root (e.g., via MobaXterm with Pageant keys), ",[3838,3847,3848],{},"su - archon",", verify ",[3838,3851,3852],{},"\u002Fopt\u002Farchon"," exists. Trade-off: Basic setup, not production-hardened—add WAF (Hetzner), IP whitelisting, or VPN.",[22,3855,3856,3857,3841,3860,3863],{},"Point subdomain (e.g., archon.yourdomain.com) A record to VPS public IP. Verify propagation: ",[3838,3858,3859],{},"dig archon.yourdomain.com",[3838,3861,3862],{},"nslookup",". DNS resolves in seconds on United Domains.",[17,3865,3867],{"id":3866},"secure-env-with-tokens-and-domain-for-production-access","Secure .env with Tokens and Domain for Production Access",[22,3869,3870,3871,3874],{},"Edit ",[3838,3872,3873],{},"\u002Fopt\u002Farchon\u002F.env"," minimally:",[100,3876,3877,3883,3893,3902],{},[103,3878,3879,3882],{},[3838,3880,3881],{},"GLOBAL_AUTH=false"," (initially; enable later).",[103,3884,3885,3888,3889,3892],{},[3838,3886,3887],{},"CLOUD_OAUTH_TOKEN",": Run ",[3838,3890,3891],{},"npx @11ty\u002Feleventy@latest --cloud-token"," on local machine.",[103,3894,3895,3841,3898,3901],{},[3838,3896,3897],{},"GH_TOKEN",[3838,3899,3900],{},"GITHUB_TOKEN",": GitHub Settings > Developer Settings > Personal Access Tokens (Classic) > Generate new (repo scope, no expiration for testing).",[103,3903,3904,3907],{},[3838,3905,3906],{},"DOMAIN=archon.yourdomain.com"," (line ~126).",[22,3909,3910,3911,3914,3915,3918,3919,3922],{},"Optional integrations (Telegram\u002FSlack): Rasmus's video covers. Start stack: ",[3838,3912,3913],{},"docker compose --profile db,cloud,auth up -d",". Check: ",[3838,3916,3917],{},"docker compose ps"," (all healthy), ",[3838,3920,3921],{},"curl https:\u002F\u002Farchon.yourdomain.com\u002Fhealth"," (returns OK), browser loads Web UI with auto-SSL. Exposes endpoints 24\u002F7.",[17,3924,3926],{"id":3925},"add-form-based-auth-and-lock-down-access","Add Form-Based Auth and Lock Down Access",[22,3928,3929,3930,3933,3934,3937],{},"Generate bcrypt hash: ",[3838,3931,3932],{},"htpasswd -bnBC 10 \"\" yourpass | tr -d ':\\n'"," (e.g., username 'archon', pass 'archon'). Hex secret: ",[3838,3935,3936],{},"openssl rand -hex 32",". Add to .env (line ~145):",[3939,3940,3945],"pre",{"className":3941,"code":3943,"language":3944},[3942],"language-text","AUTH_USER=archon\nAUTH_PASS=$2y$10$92ixRDXWuX[hash]\nAUTH_COOKIE_SECRET=yourhexsecret\n","text",[3838,3946,3943],{"__ignoreMap":134},[22,3948,3949,3950,3953,3954,3957,3958,3961],{},"Replace Caddyfile with tasklist version (uncomments form auth reverse_proxy). Restart: ",[3838,3951,3952],{},"docker compose --profile db,cloud,auth up -d --force-recreate auth"," (first-time) or ",[3838,3955,3956],{},"--force-recreate caddy"," later. Logs: ",[3838,3959,3960],{},"docker compose logs caddy",". Test incognito: Login screen blocks unauth access.",[22,3963,3964],{},"Extra security: Hetzner WAF + static IP\u002FVPN whitelist. Blocks public access effectively.",[17,3966,3968],{"id":3967},"update-restart-and-stop-without-downtime","Update, Restart, and Stop Without Downtime",[22,3970,3971],{},"Maintenance via archon user:",[100,3973,3974,3981,3987],{},[103,3975,3976,3977,3980],{},"Update: ",[3838,3978,3979],{},"git pull && docker compose --profile db,cloud,auth down && docker compose --profile db,cloud,auth up --build -d",".",[103,3982,3983,3984,3980],{},"Restart: ",[3838,3985,3986],{},"docker compose --profile db,cloud,auth restart",[103,3988,3989,3990,3993],{},"Stop: ",[3838,3991,3992],{},"docker compose --profile db,cloud,auth down"," (includes DB\u002FCaddy).",[22,3995,3996,3997,4000],{},"Cloud-init skips manual steps (Option B in tasklist). External DB (Supabase\u002FNeon): Set ",[3838,3998,3999],{},"DATABASE_URL"," in .env, omit 'db' profile. Full docs: archon.diy\u002Fbook. Scales for testing; monitor costs (delete VPS post-test saves €€€).",{"title":134,"searchDepth":135,"depth":135,"links":4002},[4003,4004,4005,4006],{"id":3832,"depth":135,"text":3833},{"id":3866,"depth":135,"text":3867},{"id":3925,"depth":135,"text":3926},{"id":3967,"depth":135,"text":3968},[143],"This video shows you how to install Archon v3 on your own server, making it accessible 24\u002F7 via a subdomain and its Web UI and other Endpoints. We'll walk through the process on a Hetzner VPS server, following a prepared Task List to ensure a straightforward setup for your server, which you can also use to follow the video. The goal is to get you up and running with Archon v3, covering all the essential steps for server management.\n\nHetzner Referral (Support the Channel): https:\u002F\u002Fhetzner.cloud\u002F?ref=nAOvh4nkSWmQ\nRasmus: https:\u002F\u002Fwww.youtube.com\u002F@UCbJSc2NyTZgz3Qu21kDId5Q \nCole: https:\u002F\u002Fwww.youtube.com\u002F@UCMwVTLZIRRUyyVrkjDpn4pA \n\n*Tasklist:* http:\u002F\u002Ftasklist.smartcode.diy\u002Flist\u002Farchon-v3-cloud-setup\n\n----\n🚀 Want to learn agentic coding with live daily events and workshops?\nCheck out Dynamous AI: https:\u002F\u002Fdynamous.ai\u002F?code=646a60\nGet 10% off here 👉 https:\u002F\u002Fshorturl.smartcode.diy\u002Fdynamous_ai_10_percent_discount\n----\n\nChapters\n0:00 Archon - How to set up Archon a a VPS Server?\n2:31 VPS Hetzner - Initial Server Configuration\n3:56 Cloud-Init Configuration for Server Start\n8:06 Domain Setup and DNS Records\n10:43 Configure .env (Environment Settings: Secrets, Tokens, ...)\n13:47 Github Access Token \n18:40 Form-Based Auth for Archon (Login)\n\nResources\n\n⭐ Archon on GitHub: https:\u002F\u002Fgithub.com\u002Fcoleam00\u002FArchon\n📖 The Archon Book: https:\u002F\u002Farchon.diy\u002Fbook\n🎓 Dynamous AI Community: https:\u002F\u002Fdynamous.ai\u002F?code=646a60\n💰 10% OFF Dynamous: https:\u002F\u002Fshorturl.smartcode.diy\u002Fdynamous_ai_10_percent_discount",{},"\u002Fsummaries\u002Fe5968758c24688f8-self-host-archon-v3-on-hetzner-vps-with-docker-summary","2026-04-09 03:00:05","2026-04-10 03:09:03",{"title":3822,"description":4008},{"loc":4010},"e5968758c24688f8","DIY Smart Code","video","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=5CYG0SrpW0Q","summaries\u002Fe5968758c24688f8-self-host-archon-v3-on-hetzner-vps-with-docker-summary",[218,219,217,4021],"docker","Provision Hetzner VPS, apply cloud-init YAML for auto-setup of Archon v3 with Caddy HTTPS reverse proxy, Postgres DB, then configure .env secrets and optional form auth for secure 24\u002F7 access via subdomain.",[4021],"1AcL7qEopcAf0EBWNfrdu7IaGhfwIpLhhlC3lEWhkmY",{"id":4026,"title":4027,"ai":4028,"body":4033,"categories":4247,"created_at":144,"date_modified":144,"description":134,"extension":145,"faq":144,"featured":146,"kicker_label":144,"meta":4248,"navigation":205,"path":4249,"published_at":4250,"question":144,"scraped_at":144,"seo":4251,"sitemap":4252,"source_id":4253,"source_name":4254,"source_type":213,"source_url":4255,"stem":4256,"tags":4257,"thumbnail_url":144,"tldr":4259,"tweet":144,"unknown_tags":4260,"__hash__":4261},"summaries\u002Fsummaries\u002Fcut-snowflake-cortex-code-costs-with-prompts-and-l-summary.md","Cut Snowflake Cortex Code Costs with Prompts and Limits",{"provider":7,"model":8,"input_tokens":4029,"output_tokens":4030,"processing_time_ms":4031,"cost_usd":4032},4776,1640,9737,0.0017527,{"type":14,"value":4034,"toc":4241},[4035,4039,4042,4045,4062,4065,4069,4072,4084,4087,4159,4162,4177,4180,4184,4187,4190,4205,4208,4223,4230,4234,4237],[17,4036,4038],{"id":4037},"craft-precise-prompts-to-slash-token-consumption","Craft Precise Prompts to Slash Token Consumption",[22,4040,4041],{},"Cortex Code (CoCo) bills by tokens from both input prompts and outputs, so vague prompts trigger extra tool calls and higher costs. Bad example: \"Help me with my data.\" Good: \"Create staging model for RAW.SALES.ORDERS with not_null on ORDER_ID.\"",[22,4043,4044],{},"Follow these practices to minimize tokens:",[100,4046,4047,4050,4053,4056,4059],{},[103,4048,4049],{},"Use full table names (e.g., RAW.SALES.ORDERS).",[103,4051,4052],{},"Specify exact output format.",[103,4054,4055],{},"Keep prompts concise.",[103,4057,4058],{},"Include business logic upfront.",[103,4060,4061],{},"Reference AGENTS.md for consistent agent behavior.",[22,4063,4064],{},"This approach directly cuts credits since CoCo is serverless and doesn't use warehouses.",[17,4066,4068],{"id":4067},"query-usage-history-and-set-proactive-alerts","Query Usage History and Set Proactive Alerts",[22,4070,4071],{},"Track daily credits, per-user usage, and request counts with these ACCOUNT_USAGE tables (data lags 45 mins to 2 hours):",[100,4073,4074,4079],{},[103,4075,4076],{},[3838,4077,4078],{},"SNOWFLAKE.ACCOUNT_USAGE.CORTEX_CODE_SNOWSIGHT_USAGE_HISTORY",[103,4080,4081],{},[3838,4082,4083],{},"SNOWFLAKE.ACCOUNT_USAGE.CORTEX_CODE_CLI_USAGE_HISTORY",[22,4085,4086],{},"Example query for last 30 days:",[3939,4088,4092],{"className":4089,"code":4090,"language":4091,"meta":134,"style":134},"language-sql shiki shiki-themes github-light github-dark","SELECT\n  DATE(u.USAGE_TIME) AS usage_date,\n  us.NAME AS user_name,\n  ROUND(SUM(u.TOKEN_CREDITS), 4) AS daily_credits,\n  SUM(u.TOKENS) AS total_tokens,\n  COUNT(*) AS request_count\nFROM SNOWFLAKE.ACCOUNT_USAGE.CORTEX_CODE_SNOWSIGHT_USAGE_HISTORY u\nLEFT JOIN SNOWFLAKE.ACCOUNT_USAGE.USERS us ON u.USER_ID = us.USER_ID\nWHERE u.USAGE_TIME >= DATEADD('day', -30, CURRENT_TIMESTAMP())\nGROUP BY DATE(u.USAGE_TIME), us.NAME\nORDER BY usage_date DESC, daily_credits DESC;\n","sql",[3838,4093,4094,4102,4107,4112,4117,4123,4129,4135,4141,4147,4153],{"__ignoreMap":134},[4095,4096,4099],"span",{"class":4097,"line":4098},"line",1,[4095,4100,4101],{},"SELECT\n",[4095,4103,4104],{"class":4097,"line":135},[4095,4105,4106],{},"  DATE(u.USAGE_TIME) AS usage_date,\n",[4095,4108,4109],{"class":4097,"line":201},[4095,4110,4111],{},"  us.NAME AS user_name,\n",[4095,4113,4114],{"class":4097,"line":202},[4095,4115,4116],{},"  ROUND(SUM(u.TOKEN_CREDITS), 4) AS daily_credits,\n",[4095,4118,4120],{"class":4097,"line":4119},5,[4095,4121,4122],{},"  SUM(u.TOKENS) AS total_tokens,\n",[4095,4124,4126],{"class":4097,"line":4125},6,[4095,4127,4128],{},"  COUNT(*) AS request_count\n",[4095,4130,4132],{"class":4097,"line":4131},7,[4095,4133,4134],{},"FROM SNOWFLAKE.ACCOUNT_USAGE.CORTEX_CODE_SNOWSIGHT_USAGE_HISTORY u\n",[4095,4136,4138],{"class":4097,"line":4137},8,[4095,4139,4140],{},"LEFT JOIN SNOWFLAKE.ACCOUNT_USAGE.USERS us ON u.USER_ID = us.USER_ID\n",[4095,4142,4144],{"class":4097,"line":4143},9,[4095,4145,4146],{},"WHERE u.USAGE_TIME >= DATEADD('day', -30, CURRENT_TIMESTAMP())\n",[4095,4148,4150],{"class":4097,"line":4149},10,[4095,4151,4152],{},"GROUP BY DATE(u.USAGE_TIME), us.NAME\n",[4095,4154,4156],{"class":4097,"line":4155},11,[4095,4157,4158],{},"ORDER BY usage_date DESC, daily_credits DESC;\n",[22,4160,4161],{},"For notifications:",[100,4163,4164,4171],{},[103,4165,4166,4167,4170],{},"Activate account budgets: ",[3838,4168,4169],{},"CALL SNOWFLAKE.LOCAL.ACCOUNT_ROOT_BUDGET!ACTIVATE();"," then set limits (e.g., 7 credits monthly) and emails.",[103,4172,4173,4174,3980],{},"Build custom alerts, like firing if Snowsight exceeds 2 credits in 24 hours via CRON '* * * * * UTC', using ",[3838,4175,4176],{},"SYSTEM$SEND_EMAIL",[22,4178,4179],{},"Budgets alert but don't hard-stop usage.",[17,4181,4183],{"id":4182},"enforce-rolling-24-hour-credit-limits-per-user","Enforce Rolling 24-Hour Credit Limits Per User",[22,4185,4186],{},"Set daily estimated credit limits on a rolling 24-hour window—access blocks when hit until usage drops below:",[22,4188,4189],{},"Account-wide:",[3939,4191,4193],{"className":4089,"code":4192,"language":4091,"meta":134,"style":134},"ALTER ACCOUNT SET CORTEX_CODE_SNOWSIGHT_DAILY_EST_CREDIT_LIMIT_PER_USER = 5;\nALTER ACCOUNT SET CORTEX_CODE_CLI_DAILY_EST_CREDIT_LIMIT_PER_USER = 10;\n",[3838,4194,4195,4200],{"__ignoreMap":134},[4095,4196,4197],{"class":4097,"line":4098},[4095,4198,4199],{},"ALTER ACCOUNT SET CORTEX_CODE_SNOWSIGHT_DAILY_EST_CREDIT_LIMIT_PER_USER = 5;\n",[4095,4201,4202],{"class":4097,"line":135},[4095,4203,4204],{},"ALTER ACCOUNT SET CORTEX_CODE_CLI_DAILY_EST_CREDIT_LIMIT_PER_USER = 10;\n",[22,4206,4207],{},"Per-user overrides:",[3939,4209,4211],{"className":4089,"code":4210,"language":4091,"meta":134,"style":134},"ALTER USER power_user SET CORTEX_CODE_SNOWSIGHT_DAILY_EST_CREDIT_LIMIT_PER_USER = 20;\nALTER USER intern_user SET CORTEX_CODE_SNOWSIGHT_DAILY_EST_CREDIT_LIMIT_PER_USER = 0;\n",[3838,4212,4213,4218],{"__ignoreMap":134},[4095,4214,4215],{"class":4097,"line":4098},[4095,4216,4217],{},"ALTER USER power_user SET CORTEX_CODE_SNOWSIGHT_DAILY_EST_CREDIT_LIMIT_PER_USER = 20;\n",[4095,4219,4220],{"class":4097,"line":135},[4095,4221,4222],{},"ALTER USER intern_user SET CORTEX_CODE_SNOWSIGHT_DAILY_EST_CREDIT_LIMIT_PER_USER = 0;\n",[22,4224,4225,4226,4229],{},"Unset with ",[3838,4227,4228],{},"ALTER ACCOUNT UNSET ..."," or per user. This prevents runaway costs from heavy users.",[17,4231,4233],{"id":4232},"work-around-key-limitations","Work Around Key Limitations",[22,4235,4236],{},"CoCo lacks file uploads (use stages), external API calls (use external functions), background jobs, multi-session memory (use AGENTS.md), full large-context handling, and free tier support. These constraints avoid misuse but require planning to stay efficient without extra credits.",[4238,4239,4240],"style",{},"html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"title":134,"searchDepth":135,"depth":135,"links":4242},[4243,4244,4245,4246],{"id":4037,"depth":135,"text":4038},{"id":4067,"depth":135,"text":4068},{"id":4182,"depth":135,"text":4183},{"id":4232,"depth":135,"text":4233},[143],{},"\u002Fsummaries\u002Fcut-snowflake-cortex-code-costs-with-prompts-and-l-summary","2026-04-08 21:21:18",{"title":4027,"description":134},{"loc":4249},"60d79e4bf9e7f868","Towards AI","https:\u002F\u002Funknown","summaries\u002Fcut-snowflake-cortex-code-costs-with-prompts-and-l-summary",[217,4258,218,219],"prompt-engineering","Precise prompts reduce token usage; monitor via ACCOUNT_USAGE tables, set alerts, and enforce per-user daily credit limits like 5 for Snowsight to prevent surprise bills.",[],"K4mwWAXotaxJkbSIlKQ2dhzH9-4pliO4Lkr9uneMcq8",{"id":4263,"title":4264,"ai":4265,"body":4270,"categories":4374,"created_at":144,"date_modified":144,"description":4375,"extension":145,"faq":144,"featured":146,"kicker_label":144,"meta":4376,"navigation":205,"path":4377,"published_at":4378,"question":144,"scraped_at":4379,"seo":4380,"sitemap":4381,"source_id":4382,"source_name":4383,"source_type":4017,"source_url":4384,"stem":4385,"tags":4386,"thumbnail_url":144,"tldr":4388,"tweet":144,"unknown_tags":4389,"__hash__":4390},"summaries\u002Fsummaries\u002F6efb045ed12647b6-claude-code-leak-reveals-ai-supply-chain-perils-summary.md","Claude Code Leak Reveals AI Supply Chain Perils",{"provider":7,"model":8,"input_tokens":4266,"output_tokens":4267,"processing_time_ms":4268,"cost_usd":4269},8229,2225,19837,0.00246745,{"type":14,"value":4271,"toc":4367},[4272,4276,4279,4282,4285,4289,4292,4295,4298,4302,4305,4308,4311,4315,4318,4321,4323,4346,4349],[17,4273,4275],{"id":4274},"ai-coding-tools-expose-broader-supply-chain-weaknesses","AI Coding Tools Expose Broader Supply Chain Weaknesses",[22,4277,4278],{},"Panelists agree the Claude Code source leak isn't isolated to Anthropic but signals systemic flaws in AI-era supply chains, particularly npm's history of typosquatting and dependency confusion attacks. JR Rao frames it as a shift from traditional vulnerabilities to subverted trust chains: attackers exploit package managers to infiltrate workflows, with blame often falling on end-users like Claude adopters. Visibility into Claude Code's internals—via npm maps linking to source artifacts—lowers attack research costs, revealing upcoming features like offline mode and dream mode that could inspire targeted exploits.",[22,4280,4281],{},"Dave Bales highlights npm hash subversion tactics, rendering verification unreliable. Short-term fallout includes malware-laden fake GitHub repos (e.g., Vidar infostealer disguised as forks). Long-term, leaked code lets adversaries bypass guardrails, enabling unrestricted AI coding. Nick Bradley downplays immediate doom for Anthropic, likening it to pirated software, but notes excitement in novel threats beyond XSS or SQLi.",[22,4283,4284],{},"\"This is really a AI era supply chain security problem and it is a problem with npm,\" says JR, emphasizing lookalike packages targeting agentic systems, API key abuses, and embedded logic patterns.",[17,4286,4288],{"id":4287},"removing-ai-guardrails-fuels-malicious-automation","Removing AI Guardrails Fuels Malicious Automation",[22,4290,4291],{},"Leaked AI coding tools like Claude Code pose amplified risks in CI\u002FCD pipelines due to features like proactive mode, which automates 24\u002F7 code generation without human oversight. Dave warns this empowers attackers to build malicious repositories effortlessly: \"Proactive mode being enabled in this source code is a big deal... They're going to have code written for them while they sleep.\"",[22,4293,4294],{},"Panelists diverge on severity—Nick sees it as inevitable abuse of any tool (\"any tool that you think you're going to use for something good, someone else is going to use it for something bad\"), while Dave predicts weaponized bad-actor repos. JR ties it to agent limitations: AI lacks human adeptness at spotting typosquatting or shell executions. Consensus: Test updates in isolated labs before deployment, lag one version behind (N-1 strategy) for stability, and scrutinize supply chains holistically.",[22,4296,4297],{},"Quote from external report cited by host: \"The attack surface exposed by the Clawed Code leak... What changed on March 31st is that the attack research cost collapsed.\"",[17,4299,4301],{"id":4300},"one-credential-suffices-in-brazen-supply-chain-attacks","One Credential Suffices in Brazen Supply Chain Attacks",[22,4303,4304],{},"TeamPCP's spree—starting with a single privileged GitHub Actions token in Trivy Security Scanner—cascades into compromises like Light LLM, Telnyx, and a European Commission cloud exposing 29 entities' data. Dave calls them \"brazen,\" prioritizing speed over stealth: one credential unlocks vast access. Despite rotations, Trivy's miss of one instance enabled entry.",[22,4306,4307],{},"JR positions identity as the \"new perimeter\": attackers race to harvest credentials before short-lived ones expire, targeting code-embedded secrets. Nick attributes failures to overcomplication—too many credentials without airtight procedures—admitting bad guys win via speed, sans QA or ethics: \"Sometimes the bad guys just going to win... They don't have the same practices we do.\"",[22,4309,4310],{},"Murky attribution with ShinyHunters and Lapsus$ claiming overlaps matters little to defenders (per JR), though it informs TTPs. Overlaps via affiliates blur lines, but victims must assume breach, audit soup-to-nuts.",[17,4312,4314],{"id":4313},"sharing-close-calls-and-cybercrime-ai-lessons","Sharing Close Calls and Cybercrime AI Lessons",[22,4316,4317],{},"Beyond breaches, panelists advocate \"close-call\" databases for unexploited threats, shifting threat intel from post-mortems to prevention. Reactive mode dominates, but proactive sharing could reveal patterns.",[22,4319,4320],{},"Cybercriminals model mature AI adoption: unburdened by ethics, they deploy tools like Claude Code aggressively. Businesses lag due to guardrails, but lessons include rapid iteration and testing. Nick urges full-compromise assumptions post-exposure; Dave stresses lab validation to counter fast patches.",[17,4322,98],{"id":97},[100,4324,4325,4328,4331,4334,4337,4340,4343],{},[103,4326,4327],{},"Audit npm packages for lookalikes, typosquatting, and dependency confusion; verify trust chains beyond hashes.",[103,4329,4330],{},"Test AI tool updates (e.g., Claude Code) in isolated labs; adopt N-1 versioning to avoid unvetted latest releases.",[103,4332,4333],{},"Treat identity as primary perimeter: rotate credentials exhaustively, use short-lived\u002FJIT access, avoid embedding in code.",[103,4335,4336],{},"Assume breach after supply chain incidents like TeamPCP; scan environments end-to-end for indicators.",[103,4338,4339],{},"Build close-call sharing mechanisms and study cybercriminals' unhindered AI use for faster, bolder adoption.",[103,4341,4342],{},"Prioritize agentic AI security: monitor for API key leaks, proactive mode abuses, and shell executions in pipelines.",[103,4344,4345],{},"Ignore attribution noise; focus on TTPs from any actor for detection rules.",[22,4347,4348],{},"Notable quotes:",[4350,4351,4352,4355,4358,4361,4364],"ol",{},[103,4353,4354],{},"Nick Bradley: \"Any tool that you think you're going to use for something good, someone else is going to use it for something bad.\" (On inevitable AI tool abuse.)",[103,4356,4357],{},"Dave Bales: \"Proactive mode being enabled... allows the engine to code for you 24\u002F7.\" (Highlighting malicious automation risk.)",[103,4359,4360],{},"JR Rao: \"We are moving from an era where we had vulnerabilities to where trust chains are being subverted.\" (Framing supply chain evolution.)",[103,4362,4363],{},"Nick Bradley: \"Sometimes the bad guys just going to win, right? Because they're just going to be faster.\" (On defender challenges vs. threat speed.)",[103,4365,4366],{},"Dave Bales: \"They're brazen... if they can get a credential, it seems like they're going to use it.\" (Describing TeamPCP tactics.)",{"title":134,"searchDepth":135,"depth":135,"links":4368},[4369,4370,4371,4372,4373],{"id":4274,"depth":135,"text":4275},{"id":4287,"depth":135,"text":4288},{"id":4300,"depth":135,"text":4301},{"id":4313,"depth":135,"text":4314},{"id":97,"depth":135,"text":98},[143],"Visit the Security Intelligence the podcast page → https:\u002F\u002Fibm.biz\u002FBdpmAn\n\nWhat happens when one of the world’s most popular AI coding tools falls into the wrong hands? \n\nOn this episode of Security Intelligence, Nick Bradley, Dave Bales and JR Rao discuss the Claude Code source code leak. Attackers are already using the opportunity to spread malware through fake repos, but the real question is how threat actors might use their newfound knowledge of Claude Code’s internals to wreak havoc on AI agents and the CI\u002FCD pipeline. \n\nThen, we follow up on our old friends TeamPCP, Shiny Hunters and Lapsus$, whose overlapping data breach claims are causing no small amount of confusion and consternation among security pros. We examine the credential rotation problem and the uneven security surface of modern supply chains that helped get us in this mess. \n\nPlus: Threat intelligence usually focuses on attacks that did happen. But what if we started talking about the ones that didn’t? And do cybercriminals have anything to teach us about “mature” AI adoption? Some big names seem to think so. \n\nAll that and more on Security Intelligence. \n\nSegments: \n\n00:00 – Introduction\n1:12 -- The Claude Code leak \n11:19 -- TeamPCP’s breach spree \n21:21 -- “Close-call” databases  \n29:28 -- Cybercrime and AI adoption \n\nThe opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. \n\nExplore to securely deploy and operate agentic AI workloads at runtime → https:\u002F\u002Fibm.biz\u002FBdpmAb\n#ClaudeAI #ThreatIntelligence #DataBreach",{},"\u002Fsummaries\u002F6efb045ed12647b6-claude-code-leak-reveals-ai-supply-chain-perils-summary","2026-04-08 10:16:24","2026-04-08 14:47:42",{"title":4264,"description":4375},{"loc":4377},"6efb045ed12647b6","IBM Technology","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=qtFtECYOzZE","summaries\u002F6efb045ed12647b6-claude-code-leak-reveals-ai-supply-chain-perils-summary",[218,219,217,4387],"agents","Leaked Claude Code source exposes npm vulnerabilities and AI agent risks in CI\u002FCD, urging defenders to harden supply chains, rotate credentials rigorously, and test updates in labs amid brazen threat actor speed.",[],"rYHeHb79Rw2biSTzKaB6ZPctw8GE0Ra2h3D9INxtA3c",{"id":4392,"title":4393,"ai":4394,"body":4399,"categories":4436,"created_at":144,"date_modified":144,"description":134,"extension":145,"faq":144,"featured":146,"kicker_label":144,"meta":4437,"navigation":205,"path":4446,"published_at":144,"question":144,"scraped_at":4447,"seo":4448,"sitemap":4449,"source_id":4450,"source_name":4451,"source_type":213,"source_url":4452,"stem":4453,"tags":4454,"thumbnail_url":144,"tldr":4455,"tweet":144,"unknown_tags":4456,"__hash__":4457},"summaries\u002Fsummaries\u002F3393634cd1348cbf-secretless-iam-secures-agentic-ai-workloads-summary.md","Secretless IAM Secures Agentic AI Workloads",{"provider":7,"model":8,"input_tokens":4395,"output_tokens":4396,"processing_time_ms":4397,"cost_usd":4398},5292,1832,13966,0.00146755,{"type":14,"value":4400,"toc":4431},[4401,4405,4408,4411,4415,4418,4421,4425,4428],[17,4402,4404],{"id":4403},"eliminate-secrets-for-ai-agents-with-identity-based-access","Eliminate Secrets for AI Agents with Identity-Based Access",[22,4406,4407],{},"Traditional human IAM fails for AI agents and workloads because agents aren't humans—they need continuous verification, runtime policies, and context-aware controls without stored secrets. Use secretless authentication: grant short-lived, just-in-time credentials based on unique agent identities (delegated, autonomous, or chained). This avoids bootstrap secrets, rotations, and leakage risks. Aembit brokers access across AWS, Azure, GCP, on-prem, and SaaS using standards like OAuth, OIDC, SPIFFE, Kerberos. Result: developers skip auth coding, security enables access confidently, and agents act autonomously without compromising environments.",[22,4409,4410],{},"Enforce per-task access dynamically—no scripts or manual workflows. Combine agent+user into blended identities for MCP servers, adding MFA-strength conditions like security posture, geography, or time windows. This delivers operational visibility: audit logs per agent identity (not hidden in user sessions) and a one-click kill switch to revoke access instantly.",[17,4412,4414],{"id":4413},"policy-driven-controls-accelerate-secure-ai-adoption","Policy-Driven Controls Accelerate Secure AI Adoption",[22,4416,4417],{},"Define granular policies for what AI agents access, enforced in real-time at the gateway with token exchange and credential isolation. Supports billions of transactions in complex enterprises, SOC2\u002FISO27001 compliant, SaaS-delivered without add-ons. For agentic AI hitting LLMs (OpenAI, Claude, Gemini), APIs, or tools, centralize control in one data plane—verify, monitor, revoke per agent.",[22,4419,4420],{},"Offload secret provisioning, rotations, and audits to cut developer overhead. Works for all workloads: multi-cloud, SaaS, on-prem. Gain audit-ready logs as a single intelligence source, preventing hidden AI actions via user delegation.",[17,4422,4424],{"id":4423},"case-studies-prove-fte-savings-and-speed-gains","Case Studies Prove FTE Savings and Speed Gains",[22,4426,4427],{},"Snowflake secured agentic workloads: saved 2 FTEs, cut 85% of credential issuance\u002Frotation\u002Faudits, added conditional policies and identity logging. Large retailer replaced HashiCorp Vault DIY: saved 3-5 FTEs, delivered 6 months early, streamlined management. Property firm hit 7-month ROI: no-code multi-cloud setup, no stored credentials, better troubleshooting logs. Red Cup IT deployed AI agents in customer envs: short-lived access reduced manual handling, extended controls to cloud\u002Fdesktop without disruption.",[22,4429,4430],{},"Testimonials confirm: Snowflake saved 5-10 hours\u002Fday automating processes; scales to enterprise zero trust for non-humans across clouds\u002Fcontainers\u002FAPIs\u002FSaaS.",{"title":134,"searchDepth":135,"depth":135,"links":4432},[4433,4434,4435],{"id":4403,"depth":135,"text":4404},{"id":4413,"depth":135,"text":4414},{"id":4423,"depth":135,"text":4424},[143],{"content_references":4438,"triage":4443},[4439],{"type":160,"title":4440,"url":4441,"context":4442},"Emerging Agentic Identity Access","https:\u002F\u002Fsoftwareanalyst.substack.com\u002Fp\u002Femerging-agentic-identity-access","mentioned",{"relevance":4119,"novelty":202,"quality":202,"actionability":202,"composite":4444,"reasoning":4445},4.35,"Category: AI Automation. The article provides a detailed approach to implementing secretless IAM for AI agents, addressing a specific pain point of managing credentials in AI workloads. It offers actionable insights on policy enforcement and real-time audits, which can be directly applied by developers and technical founders looking to enhance security in their AI products.","\u002Fsummaries\u002F3393634cd1348cbf-secretless-iam-secures-agentic-ai-workloads-summary","2026-04-15 15:28:19",{"title":4393,"description":134},{"loc":4446},"3393634cd1348cbf","__oneoff__","https:\u002F\u002Faembit.io","summaries\u002F3393634cd1348cbf-secretless-iam-secures-agentic-ai-workloads-summary",[4387,218,219,220],"Replace long-lived secrets with identity-based, short-lived access for AI agents using policy enforcement and real-time audits, saving 2-5 FTEs and cutting 85% of credential tasks per case studies.",[],"cUfPDwKWNEn5zYFJq89XFEoSGGHqqrSCpWWZhz-i6Iw"]