Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Remove standing access before AI agents exploit it

AI has changed the calculus of a credential attack. Before, finding and exploiting credentials in an enterprise environment required time, patience, and human judgment. An attacker had to decide which accounts were worth testing and which systems were worth reaching. Many credentials never made the list.

AI Did Not Invent Social Engineering But It Did Industrialize It.

This year National Social Engineering Day falls on Aug. 6. This day is designed to give us an opportunity to remind people that cybercriminals do not always need sophisticated malware, an undisclosed vulnerability or a dark room filled with glowing monitors, sometimes, all they need is a good story. Social engineering existed long before computers. Confidence tricks, impersonation, false authority and appeals to greed or fear have been used for centuries.

From Connected Project Data to Construction Intelligence: Building the Foundation for AI-Powered Construction

Construction firms have invested heavily in technology to connect project information. Drawings, specifications, RFIs, submittals, BIM models, photos, and field reports are increasingly accessible from anywhere, helping office and field teams work from the same information. Connecting project information is a critical first step. It improves collaboration, reduces rework, and helps office and field teams work from the same information.

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.