Week of October 26–30, 2026

Dormant AI agents are an open door no one locked.

Arrakis Security's 2026 Autonomous Agents Threat Report found that 76% of enabled AI agents had not run in 60 days — yet retained live credentials and active connections to sensitive company systems. Agents get deployed, go idle, and nobody revokes their access. Each dormant agent is a standing invitation for an attacker who finds it first, with no expiry and no owner watching.

Every agent needs a declared identity from day one, with credentials scoped to the minimum required and a clear lifecycle policy. RuntimeAI's agent identity layer continuously monitors active and dormant agents, revokes credentials automatically when an agent violates its defined scope or exceeds an inactivity threshold, and keeps a tamper-evident record of every access event to satisfy the next audit.

RuntimeAI governs this at runtime, where the agent actually acts.

#AIAgents #NonHumanIdentity #ZeroTrust #AIGovernance #RuntimeAI

AI coding agents follow instructions they were never meant to trust.

Forever Security found that a plain text file silently saved to the Downloads folder — named AGENTS.md — can redirect AI coding agents into installing malicious npm packages or handing over a user's login token the next time the agent opens that directory. No user click required after the file lands. The attack exploits the same instruction-following behavior that makes these agents productive.

Runtime enforcement has to sit between the agent and the action. Every tool call an agent makes — package installs, file reads, credential access — needs to be evaluated against declared policy before it executes. RuntimeAI intercepts those calls at the runtime layer, blocks the ones that deviate from the agent's authorized scope, and logs every enforcement decision for post-incident forensics.

See how RuntimeAI turns this from an incident into a blocked action.

#AgentSecurity #SupplyChain #ToolCallEnforcement #AIAgents #RuntimeAI

The biggest AI threat in most organizations is wearing an ID badge.

An O'Reilly survey of 209 security professionals found that employees pasting sensitive company data into AI tools ranked as the top AI security concern — above AI-powered attacks and above AI-generated phishing. The risk is structural: when staff route proprietary data through consumer AI tools outside IT visibility, there is no policy to enforce and no record of where that data went.

Fixing it requires seeing it first. RuntimeAI continuously discovers unsanctioned AI tool connections across the enterprise and intercepts outbound data flows that carry sensitive fields — tokenizing PII and confidential content before it reaches any external model, so enforcement happens at the point of transmission rather than in the post-breach debrief.

RuntimeAI closes this gap at the runtime layer, before it lands.

#ShadowAI #InsiderRisk #DataPrivacy #PIIProtection #RuntimeAI

A rogue agent can do real damage in the seconds before anyone knows it has gone wrong.

On October 16, NIST, CISA, and the NSA published a joint guide treating runaway AI agents as incidents to rehearse — not just risks to acknowledge. The guide surfaces the hardest question in AI incident response: whose authority was the agent operating under, and was that authority ever formally granted? Without a pre-existing identity record, responders spend the critical window reconstructing chain of custody instead of stopping the bleeding.

The answer has to exist before the incident fires. RuntimeAI assigns every agent a declared identity and operating scope at deployment, enforces a sub-50ms kill switch to halt any agent that deviates from that scope, and maintains a tamper-evident identity record that incident responders can query the moment an alert fires — no reconstruction required.

This is exactly the control RuntimeAI enforces in real time.

#IncidentResponse #NonHumanIdentity #AIAgentSecurity #NIST #RuntimeAI

Nearly 3,900 State Bank of India customer records surfaced on the dark web this month.

SBI is still investigating how the records escaped. The pattern is familiar: sensitive customer data concentrated in a system, extracted without adequate access controls, and sold. As AI agents gain direct access to banking databases — for fraud detection, personalization, and loan processing — the extraction surface expands. An agent that can query customer records can also, if misconfigured or compromised, exfiltrate them in bulk.

Runtime policy enforcement has to govern what data any agent can access, how much it can retrieve in a single operation, and where that data is permitted to flow. RuntimeAI enforces those boundaries at the point of execution, blocks bulk extraction that exceeds a declared data scope, and generates a tamper-evident access log that supports breach investigation and satisfies the regulator on the other end of the notification deadline.

Check out how RuntimeAI solves this at the runtime layer.

#DataBreach #FinancialSecurity #AIAgents #DataGovernance #RuntimeAI