Agentic AI: From Model Risk to Enterprise Risk
The organizations that thrive in 2030 will be those that treat governance as the foundational architecture for innovations in autonomy.
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Continuous Offensive Security & AI Pentesting: 20 FAQs
Applications can change several times between scheduled security assessments. New features, APIs, and integrations may introduce risk long before the next annual penetration test begins. That gap is pushing offensive testing beyond a single tool or a single point-in-time engagement. Teams are increasingly combining Dynamic Application Security Testing (DAST), AI penetration testing, and AI red teaming to evaluate different layers of application risk.
How to Present AI Risks to the Board of Directors
A board meeting agenda gives the CISO ten minutes to talk about AI. Walking in with a shadow AI tool count or a list of blocked prompts does not answer the question directors probably have: what happens if this goes wrong, and who is accountable when it does? Boards increasingly carry direct exposure for AI oversight failures, from regulatory scrutiny to shareholder litigation.
The Identity Surface You're Not Watching: Three Layers of Coding Agent Risk
There's a widespread assumption in enterprise security that identity is a problem IAM programs know how to solve. Provision the right access, enforce least privilege, audit the credential chain, and you've addressed the identity risk. For human users and traditional service accounts, that's approximately correct. For coding agents, it misses two-thirds of the problem. Coding agents don't have a single identity. They operate across a layered identity surface, and each layer carries its own risk profile.
Defense at Machine Speed: How Arctic Wolf Built the Aurora Agentic SOC on AWS
Avni Wala, Principal Developer – Arctic Wolf Laura Ellis, SVP Artificial Intelligence – Arctic Wolf Merin Eralil, Security Partner Solutions Architect – AWS Tim Sitze, Solutions Architect – AWS AI didn’t just make defenders faster. It made attackers faster too. The moment both sides got access to the same speed, speed stopped being the advantage. With speed no longer separating attackers from defenders, the deciding factor moved somewhere else.
How to Connect Claude to Jira Securely Without Giving AI Unrestricted Access
Teams are connecting Claude to Jira to summarize issues, draft tickets, and answer sprint questions in seconds. The productivity gains are real, but so is the security risk. The problem is simple: a direct connection gives Claude the same permissions as the person who set it up. If that user can view confidential projects or delete issues, so can Claude. There's no business logic in between deciding what AI should and shouldn't touch. Most organizations don't want to ban AI.
Ep. 72 - The File That Lies: One CLAUDE.md Walks Off With Your Agent's Credentials
A poisoned CLAUDE.md file inside a cloned repository quietly tells a coding agent to send its test logs to an outside endpoint, and the agent complies, shipping environment details, internal system information, and API keys to a server the developer never controlled. The model was not broken. It was obedient. In this episode of The Cyber Resilience Brief (a SafeBreach podcast), host Tova Dvorin and SafeBreach senior sales engineer Adrian Culley break down why building agentic AI controls is not the same as proving they hold under attack.
MCP Security Risks: Trusting Tool Descriptions Without Standards
Are we trusting AI tools too much? Right now, agents trust tool descriptions without verification. This could lead to serious security risks! What happens when a major server gets compromised? It's time to rethink our standards for AI tool security. What do you think about AI trust issues?
The AI Inventory Problem Nobody Solved
By now, most organizations have invested in AI governance. Far fewer have solved the problem that makes governance possible in the first place: knowing what AI they are actually running — and with 57% of employees using AI tools at work without telling their manager, the gap is wider than most inventories admit. In this video, Kovrr breaks down what an AI asset inventory actually is, why traditional asset management never catches shadow AI, and what it takes to keep the record accurate.
Shadow AI Is the New Shadow IT: Getting Visibility Into the Models Your Teams Already Use
Security teams spent a decade wrestling shadow IT - the unsanctioned SaaS accounts, personal Dropboxes, and rogue cloud instances that employees adopted faster than governance could follow. That battle produced hard-won playbooks: discover, broker, monitor. Now the same movie is replaying with AI, at higher speed and with higher stakes. Developers embed model APIs into services over a lunch break, marketing teams paste customer data into chatbots, and product features quietly ship with third-party inference behind them. Most organizations today cannot answer a basic question.