Every non-human identity audit asks the same question: what is this agent allowed to do? Wrong question. Permissions are static — agentic behavior isn't. An agent can hold the exact same scope today it held yesterday and still act completely differently, because its next move is generated, not configured. Approving access once was never going to catch that; only watching behavior continuously will. That's the shift CSAI's control framework is built around. https://t.co/sS6QedIMYL #AgenticAI
Do you actually know what data your AI agents can touch, or are you just assuming the permissions someone set six months ago still make sense? Most teams haven't checked. TAISE is built for exactly that blind spot: https://t.co/kkg6NL1y5d
Vendor risk teams send out the same cloud security questionnaire hundreds of times a year, get inconsistent answers, then redo it all at renewal. STAR Registry breaks that cycle: providers publish verified assessments once, publicly, and any customer can pull them up instantly. It's the largest cloudassurance registry in the world, and it's free to search. https://t.co/3ruhLAH4J9 #CloudSecurity
Nobody asks security before connecting an agent to Salesforce, then Jira, then the billing API. Business teams ask if it works, not what it can now touch. Capability grows one integration at a time until an agent's reach is wider than any single team mapped or approved. That's the agentic control plane gap — and it's exactly what CSAI Foundation is building governance for. https://t.co/sS6QedIMYL #AgenticAI #CloudSecurity
Think about how a hotel issues master keycards to housekeeping. Every card opens every room, but nobody logs which staffer used which card on which floor. That's fine until something goes missing, and then there's no way to know who was even in the room. That's how most companies are rolling out AI agents right now. TAISE is where you learn to build the access model and audit trail before that becomes your problem: https://t.co/rZNoyh0BoC
AICM just won the 2026 CSO Award — but the trophy isn't the point. The point is most orgs are still grading AI risk with a checklist someone threw together last quarter. AICM gives you 243 control objectives across 18 domains, built for how AI systems actually fail. https://t.co/4xQxvDvtFp #AIsecurity
When an employee leaves, IT has a checklist: revoke badge, kill SSO, wipe the laptop, reassign their files. When an agent gets retired, forked into three new agents, or quietly re-permissioned overnight — what's the checklist? For most orgs, there isn't one, because agent identity was never treated as something with a lifecycle: provisioning, scoped authorization, rotation, deprovisioning. CSAI is building that framework so "who is this agent, and what can it still do" has an answer. https://t.co/sS6QedIMYL #AgenticAI
"We're secure, we passed our SOC 2 audit" is one of the most common lines in cloud security, and one of the least reliable. A clean audit means controls existed on paper at a point in time, not that your config is airtight today. CCSK teaches you to evaluate the actual architecture, not just the paperwork: https://t.co/d9kwHN8smX
Every vendor security questionnaire looks different, but they're all trying to answer the same questions. That's why teams burn weeks reinventing assessments instead of reusing what already works. CCM v4.1 gives you 207 controls across 17 domains, vendor-neutral and free, so you stop starting from scratch. https://t.co/qsxWxrz2df #CloudSecurity
Pull up your incident response runbook. There's a playbook for "compromised employee account" and one for "phishing click." Is there one for "agent chained three individually-approved permissions into an outcome nobody approved"? Most runbooks stop at human actors — which means when an agent causes the incident, remediation has no owner, just a debate. That's the gap CSAI is building governance for: https://t.co/sS6QedIMYL #AgenticAI #CyberSecurity
How much of your architecture is trusted today only because nobody has gotten around to questioning it yet?
CCZT is where you go to actually answer that: https://t.co/LsOMrUQo60
Most teams secure the LLM's front door — auth, rate limits, logging — and call it done. But the bigger risk is what happens after a prompt gets in: the model calling internal APIs, reading files, triggering downstream actions with zero verification at each step. Zero Trust for LLMs means treating every model output as untrusted input to the next system, not just gatekeeping the input. CSA's guidance breaks down where to put those checkpoints. https://t.co/3w93oo29WO #ZeroTrust
CISO Daily Briefing: AI agents keep breaching sandboxes. Tech: 3 Diffusers CVEs (up to CVSS 8.8) patched in 0.38.0, older builds stay exposed; a no-CVE bug lets hidden PR comments hijack reviewer AI agents; 5 Android agent frameworks fail screen-injection checks, no disclosure channel. Gov: EU AI Act's GPAI grace period expired Aug 2 — fines now reach €15M or 3% of turnover. Strategic: no coordinated fix exists across them — a governance gap, not just technical.
https://t.co/tlopU6jOaq
Zero Trust assumes an identity stable enough to attach policy to — a user, a device, a service account with a fixed scope. Agents don't hold still: one spins up sub-agents, inherits permissions, acts on credentials it never directly requested. By the time it takes an action, the "identity" you verified may already be a different actor. Least privilege and continuous verification have to be rebuilt for actors that mutate mid-task — that's the rethink CSAI is doing now. https://t.co/sS6QedIMYL #ZeroTrust #AgenticAI
This week's theme in my feed: vendors slapping a "Zero Trust" sticker on what's basically a fancier VPN, and buyers not having the framework to call it out. The term's gotten stretched so thin it barely means anything on its own anymore. CCZT gives you the actual architecture underneath the marketing: https://t.co/FQ0RKRE1Y3
Quick question: when you threat modeled your last agentic AI project, did "memory poisoning" or "cascading hallucination between agents" even make the list? Most checklists were written for static apps, not systems that reason, delegate, and remember. MAESTRO was built specifically for that gap — a threat modeling framework for agentic AI. Worth a look before your next build review. https://t.co/3w93oo29WO #AgenticAI
Three agents — pricing, fraud-check, inventory — each cleared a security review on their own. Nobody reviewed what happens when they start calling each other in a loop under load. The decision that comes out the other end wasn't "made" by any single agent, and it doesn't map to any single team's job description. That gap between org charts is where multi-agent risk actually lives. CSAI's cross-domain approach to agentic AI security starts there. https://t.co/sS6QedIMYL #AgenticAI #CyberSecurity
It's 4:45 on a Friday and someone just asked in Slack whether patching the OS is on us or the cloud provider. That question always shows up at the worst possible time, and it's usually a sign the shared responsibility model was assumed rather than actually understood. CCSK settles it before it becomes Monday's incident: https://t.co/d9kwHN8smX
Every quarter, some team somewhere is writing a cloud security policy from a blank doc — pulling bits from old audits, a competitor's whitepaper, whatever a consultant left behind. That's reinventing a wheel that already has years of scrutiny behind it.
CSA's Security Guidance v5 is the comprehensive reference for cloud security: architecture, controls, and practices, already vetted. Start there instead of from zero.
https://t.co/BNHaB086pX
#CloudSecurity
We spent five years hardening the software supply chain — SBOMs, signed commits, provenance for every dependency. Then we plugged agents into production and skipped that discipline for the one artifact actually making decisions: the model itself. Where did its weights come from? Who fine-tuned it since? You'd never run unsigned code in prod. Why run an unverified model? CSAI Foundation is building the chain-of-custody standard agentic AI is missing: https://t.co/sS6QedIMYL #AgenticAI #AISupplyChain