Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How to survive the AI spend hangover

It's 6:30am and you hear the door of the nightclub you've spent the last 8 hours inside shriek as it closes behind you. You watch bleary-eyed as an overly bright sunrise illuminates the business-suited people as they glide effortlessly along the sidewalk, their obnoxiously well-rested faces talking about work on their fully charged phones. You wonder, "Where did all the fun people go? And what happened to my wallet?".

Off-by-1 Labs: Why AI-generated vulnerability patches still require expert human review

We studied what happens when Large Language Models (LLMs) generate vulnerability patches for recently disclosed, complex vulnerabilities. Our data shows that LLMs produce Fix-Like Artifacts with Embedded Defects (FLAWED) 53.9% of the time when complex patches are required.

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.

Open-source AI Needs Security: Why Cyberhaven Is Joining the Open Secure AI Alliance

Today, Cyberhaven is joining the Open Secure AI Alliance to help advance a future in which enterprises can adopt open-source AI without compromising security, compliance, or control over their data. Cyberhaven is betting on a world where companies are free to choose from many models, agent frameworks, and open harnesses, as well as run them on infrastructure they control. That choice matters. Enterprises will not standardize on a single model or AI platform.

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.