Risk Management | Breaking Cybersecurity News | The Hacker News

When I work on an incident, the first question I ask is almost never "what malware ran." It's "whose credentials did it use, and what was that account allowed to touch." Nine times out of ten, the interesting part of the story isn't the exploit. It's the access. The exploit gets you in the door. The privilege is what lets you walk through the building. For thirty years, that question had a human-shaped answer. A person clicked something, a person got phished, a person reused a password, an admin left a service account sitting on a domain controller with a password from 2014. The identity at the center of the incident belonged to somebody with a badge and a manager. That assumption is quietly dying, and most enterprises have not adjusted their controls to match. The actor on your network is increasingly not a person at all. It is a workload, a script, a bot, an API (application programming interface) client, and now an AI agent that can reason, plan...

Cybersecurity is entering a new phase. It's one where the gap between awareness and operational execution is becoming the industry's biggest challenge. That's what stood out to me most after reviewing the results of the 2026 Bitdefender Cybersecurity Assessment , which found that organizations have never had greater insight into the risks they face, yet turning that understanding into meaningful action remains a persistent challenge. Nowhere is that gap more visible, in my view, than in how organizations handle breach transparency. We surveyed 1,200 IT and cybersecurity professionals across six countries: France, Germany, Italy, Singapore, the United Kingdom, and the United States. Respondents ranged from frontline employees to IT managers to CISOs, all working within organizations with 500 or more employees. A Governance Problem, Not an Attacker Problem One of the most troubling findings in our report is not about attacker behavior. It's about internal respons...

The most important cybersecurity impact of artificial intelligence is not that attackers can write better phishing emails or automate parts of their workflow. It is that AI is changing the speed, scale, and decision-making dynamics of cyberattacks.  That creates a problem many organizations have not yet fully confronted: most cyber governance and incident response models were designed for human-speed attacks.  For years, security teams operated under a familiar sequence. Detect suspicious activity. Investigate. Validate the threat. Escalate to leadership. Decide on containment. Communicate with stakeholders. That model still has value, but it assumes defenders have enough time to build confidence before taking material action.  AI-enabled attacks challenge that assumption.  Adversaries can now use AI to accelerate reconnaissance, generate highly personalized social engineering, modify malware, test payloads, summarize stolen data, identify vulnerabilities, a...

The structural flaw in detection-only security postures runs deeper than tooling choices. Every hour a security team spends triaging runtime alerts is an hour not spent governing what entered the pipeline in the first place. And in modern CI/CD environments, that means the handful of alerts that represent genuine software supply chain compromise arrive only after the malicious dependency has already executed its payload, exfiltrated credentials, or established persistence inside the environment. The industry built an entire market category on that backwards logic, and enterprises are now paying for it in breach costs, developer burnout, and regulatory exposure that carries personal liability for the security leaders whose names appear on the program. The shift that actually reduces risk is not better monitoring at the end of the pipeline; it is governing the point of ingestion before code ever enters your lifecycle, which is a fundamentally different problem requiring a fundamental...

Most identity verification failures do not originate from flawless synthetic IDs or visually undetectable deepfakes. Instead, they stem from structural exposures and information loss between the point of data capture and the final automated decision. As remote identity systems evolve, trust becomes an architectural property. If a backend cannot verify the hardware provenance of an image or video, the rest of the security pipeline operates on degraded input. By the time a synthetic face reaches a visual liveness model, the most critical context may already be gone. This post examines why fragmented identity APIs drop vital signals, how identity supply chains dilute accountability, and why these gaps allow digital injection attacks to succeed. The Hidden Risk in Identity Supply Chains Modern identity verification often relies on a complex supply chain that distributes camera capture, document parsing, liveness checks, and risk scoring across multiple vendors. Rather than opera...

AI-driven vulnerability discovery is no longer a research project. Claude Mythos proved that. In a single sweep, it uncovered thousands of vulnerabilities in software we use every day, generated working exploits, and exposed bugs that had survived decades of human review. Other AI models are rapidly catching up, and we've entered into an entirely new operating environment for cybersecurity. The industry is treating this as a turning point, and it is. But not for the reason most people might think. The Real Problem Was Never Finding Vulnerabilities Most of the conversation around AI security focuses on discovery: AI can now identify vulnerabilities faster than human teams ever could. That is certainly true, but it also misses the larger operational reality organizations have been struggling with for years. Security teams were already overwhelmed long before AI entered the picture. Vulnerability scanners, fuzzers, and static analysis tools have consistently generated more...

Continuous Threat Exposure Management (CTEM) has moved well past buzzword status. We've talked about this before . It's true that in the past years, Gartner has been making these grand predictions about its benefits: organizations prioritizing CTEM investments will suffer two-thirds fewer breaches by 2026 … Well, we're now in 2026 and, in reality, SOC teams are still facing the same dilemma: more exposure data than they can act on, and no reliable way to decide what actually matters. 96% of security teams face challenges trying to validate whether their security risks are exploitable, while 2 in 3 state that they don't have a consolidated view of their cyber risk exposure. - Filigran-comissioned third-party market survey on exposure validation  It's pretty clear now that to actually benefit from CTEM, organizations needs to first utilize their cyber threat intelligence better. It is not just about better asset, vulnerability management or dealing with a single CTI provider, b...