Machine Identity | Breaking Cybersecurity News | The Hacker News

AI agent security is moving through a familiar maturity curve: adoption, then visibility, and finally, control. But what we've collectively discovered is that enforcing least privilege for AI agents is harder than we ever imagined. This is why there are so many approaches, from prompt filtering to identity-layer access controls. Where we've collectively landed is that understanding the intent of AI agents is essential to securing them. It's not easy, but it's the only path forward. Organizations approach this challenge with different levels of sophistication. For many, the current goal is simply to find the AI agents already operating across the business. That is a necessary first step. AI agents are appearing in SaaS platforms, developer environments, cloud workflows, customer support systems, productivity tools, and internal applications. Some are sanctioned, and others are not. But discovery alone isn't useful. AI agents are not passive; they reason, plan, c...

Most people understand identity theft as an attacker stealing a real person's sensitive information and impersonating them. Synthetic identity fraud is much harder to catch. Instead of stealing a real identity, the attacker manufactures a new one, frankensteining together several real data points with fabricated ones to create a person who doesn't exist. Since no real victim monitors misuse, a fake identity can silently accumulate permissions and credibility over time before it's ever detected. This same principle has a largely unexplored parallel with Non-Human Identities (NHIs). Security teams are spending significant effort to protect NHIs from being stolen. Still, the machine-side equivalent of synthetic identity fraud is rarely discussed: identities that were never legitimately provisioned from the start. Following this approach, an attacker doesn't hijack an existing service account but instead fabricates one, blending real environmental attributes with fake o...

If an autonomous AI agent interacts with your company's core intellectual property today, can your security team instantly name the person who authorized it? For most enterprises, the answer is a simple no . The rush to adopt internal AI tools has left a massive trail of administrative debt: orphaned agents (AI tools left running after their creator leaves the company) and standing privileges (AI that retains permanent, unrestricted access it no longer needs). When an employee moves on, the automated tools they built stay active—often keeping unmonitored access to sensitive databases and source code long after the human’s credentials are revoked. To help security teams bridge this line of accountability, The Hacker News is hosting a technical briefing. Secure your spot today for the live webinar: Orphaned Agents & Standing Privileges: The Hidden Access Risks of Internal AI . Why Existing Security Tools Miss the Signal Traditional access tools treat AI like stand...

Human identities management and control is pretty well done with its set of dedicated tools, frameworks, and best practices. This is a very different world when it comes to Non-human identities also referred to as machine identities. GitGuardian’s end-to-end NHI security platform is here to close the gap. Enterprises are Losing Track of Their Machine Identities Machine identities–service accounts, API keys, bots, automation, and workload identities–that now outnumber humans by up to 100:1 are in fact a massive blind spot in companies' security landscape: Without robust governance, NHIs become a prime target for attackers. Orphaned credentials, over-privileged accounts, and “zombie” secrets are proliferating—especially as organizations accelerate cloud adoption, integrate AI-powered agents, and automate their infrastructure . Secrets Sprawl: The New Attack Surface GitGuardian’s research shows that 70% of valid secrets detected in public repositories in 2022 remained active in ...

It wasn't ransomware headlines or zero-day exploits that stood out most in this year's Verizon 2025 Data Breach Investigations Report (DBIR) — it was what fueled them. Quietly, yet consistently, two underlying factors played a role in some of the worst breaches: third-party exposure and machine credential abuse . According to the 2025 DBIR, third-party involvement in breaches doubled year-over-year, jumping from 15% to 30% . In parallel, attackers increasingly exploited machine credentials and ungoverned machine accounts to gain access, escalate privileges, and exfiltrate sensitive data. The message is clear: it's no longer enough to protect your employee users alone. To truly defend against modern threats, organizations must govern all identities — human, non-employee, and machine — within a unified security strategy. Third-Party Risk: Expanding Faster Than Organizations Can Control Today’s enterprise is a patchwork of partnerships: contractors, vendors, business p...

When we talk about identity in cybersecurity, most people think of usernames, passwords, and the occasional MFA prompt. But lurking beneath the surface is a growing threat that does not involve human credentials at all, as we witness the exponential growth of Non-Human Identities (NHIs).  At the top of mind when NHIs are mentioned, most security teams immediately think of Service Accounts . But NHIs go far beyond that. You’ve got Service Principals , Snowflake Roles , IAM Roles , and platform-specific constructs from AWS, Azure, GCP, and more. The truth is, NHIs can vary just as widely as the services and environments in your modern tech stack, and managing them means understanding this diversity. The real danger lies in how these identities authenticate. Secrets: The Currency of Machines Non-Human Identities, for the most part, authenticate using secrets : API keys, tokens, certificates, and other credentials that grant access to systems, data, and critical infrastructure. Th...