ai · security · skills

ai security skills:
human craft for machine speed.

Pressure-test the function. Build the defender’s skills. Guided by Ace.

Autonomy rises. So does the bar.On track
12345GovernanceOrg managementIAMSecurity monitoringInfra security & resilienceModel securityApp securityData securityRisk & provider assessmentAI dev & supply chainPrivacy & complianceIncident responseFoundationalStructuralProcedural
Human bottleneck82%
Safety net needed22%

Manual: The human is the safety net. Low autonomy asks little of your controls.

Why this app

Security and risk lead every survey of AI concern.

Every fear has an owner in the model. Pressure-test the function it belongs to, and the read starts there.

Why now

Six open problems. No fitted owner yet.

Lines from real enterprise incident rooms and AI-security surveys. Not product features. Gaps your people already feel that no classic control alone closes.

The gap · Incident room

Agent and human shared one account. The record shows a single actor and accounts for nothing.

Source: Proofpoint, State of AI Security 2025 (survey of 275 enterprise security and business leaders). Quotes are what respondents report, not measured outcomes on this site.

Prefer the full urgency arc? Why now on /threats →

Ace's watch

What changed.And what to learn because of it.

Every item names the one thing worth learning next. If it cannot, it does not run.

From the field · 13 Sep 2026

HBR analysis warns that enterprise AI tool usage creates IP leakage risk through employee interaction feedback loops, synthetic data reuse, and shadow AI accounts that bypass corporate security controls

Standard DLP controls designed for email and document exfiltration do not cover the novel leakage vectors introduced by conversational AI interfaces and model training feedback loops

What to learn next

Implement AI-specific DLP controls that monitor employee interactions with external AI platforms for proprietary data exposure, enforce enterprise-tier contracts that block training on user data, and detect unauthorized shadow AI account usage

Source

From the practice · 13 Sep 2026

Forrester's AEGIS playbook and the Agent Airlock project both emphasize guardrails for intent, authority, and access when deploying AI agents at production scale

Agent authorization is emerging as a distinct security control domain separate from traditional IAM, requiring runtime policy enforcement that traditional access controls cannot provide

What to learn next

Deploy agent sandboxing with policy enforcement that constrains agent actions by intent, authority level, and data access scope, and integrate agent authorization gates into your CI/CD pipeline for AI deployments

Source

From the field · 13 Sep 2026

US lawmakers advance bipartisan kill-switch legislation requiring oversight mechanisms and shutdown capabilities for advanced AI systems, while Anthropic's CEO calls for industry-wide development coordination

Mandated shutdown capabilities for production AI systems are moving from policy discussion to legislative reality, creating a compliance obligation security teams will need to meet

What to learn next

Prepare documented shutdown procedures and oversight mechanisms for production AI systems, including kill-switch testing in incident response drills, ahead of expected regulatory mandates

Source

Every item on Ace’s record