Incident Response | Breaking Cybersecurity News | The Hacker News

More than half of IT & cybersecurity professionals who experienced a breach in the past 12 months say they were told to keep it confidential, even when it was reportable. That finding comes from the 2026 Bitdefender Cybersecurity Assessment , a study Bitdefender has run for several years running. Disclosure rules have expanded significantly since the question was first asked in 2023, but the pressure to hide breaches continues. How Many Organizations Hide Breaches? Roughly half of 1,200 IT and security professionals surveyed reported a breach or security incident in the last 12 months. Of that group, 55.2% said they had been asked to keep a breach confidential even when it should have been disclosed. That's a snapshot. Here's the trendline: In 2023, 42.0% of respondents said they'd been asked to keep a breach quiet. By 2025 that number had climbed to 57.6%. In 2026 it settled back to 55.2%, which appears to be a plateau, not a reversal. IT & security pr...

Most security teams know that dwell time matters. The harder question is what to do about it. Dwell time is the period between an attacker gaining access and the security team containing the threat. During that window, a threat actor has time to learn the environment, steal credentials, move between systems, and reach sensitive data. For years, security teams have tried to reduce this window by adding more detection tools. The problem is that more alerts do not necessarily mean faster detection.  A recent industry incident response report puts the global median dwell time at 14 days, up from 11 the year before, quietly reversing a run of steady improvement that had held for close to a decade. The better way to think about it is as an operational problem. Two numbers matter most. Mean time to detect (MTTD) tells you how quickly the team recognizes a real threat, while mean time to respond (MTTR) tells you how quickly the team investigates and contains it. An AI native SIEM...

Many AI systems depend on input signals that teams cannot fully inspect or explain. These opaque sources reduce visibility into the data paths that influence model behavior. Engineers lose provenance records, limiting the diagnosis of abnormal outputs. This complicates the work of security teams that need clear records of what influenced a model at any point in time. Verifiable search data offers a stable alternative. It gives teams an input they can examine, store, and reproduce in controlled conditions. Engineers can compare model behavior against information that was publicly accessible at the time a result was produced, rather than depend on hidden internal signals. This article outlines why verifiable search data gives AI and security teams the clarity required to maintain operational control. Why Traceability Matters in AI Systems Traceability lets teams follow an input from its origin through each processing step. When every stage can be inspected, engineers can review...

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...

Launching a ransomware attack used to take real effort. Now, thanks to AI, almost anyone can launch a sophisticated attack, which changes the game for everyone responsible for protecting businesses. Reconnaissance that once took hours now takes minutes. Phishing emails that used to require careful crafting can now be generated at scale and sent to hundreds of targets simultaneously. IBM's 2025 Cost of a Data Breach Report found that AI reduced the time required to create phishing emails from 16 hours to just 5 minutes. For MSPs managing dozens or hundreds of clients, and for internal IT teams holding the line across an entire organization, understanding how AI is changing ransomware is key to staying ahead of the threat and minimizing disruption when attacks occur. The attack that starts in the inbox Before attackers can encrypt files or demand a ransom, they first need a way into the organization. One of the easiest ways to get that access is by tricking someone into cli...

BEC accounted for over $3 billion in reported losses last year alone. Most organizations don't realize they're exposed until it's too late. Here's how to tell if your defenses have gaps. Business email compromise doesn't announce itself. There's no ransomware splash screen, no locked files, no dramatic system outage. Instead, a finance team member processes what looks like a routine vendor payment update. A controller wires funds based on what appears to be a CFO's direct request. By the time anyone notices, the money is gone. The FBI IC3's 2024 Internet Crime Report documented $55 billion in cumulative BEC losses over the past decade, with $3 billion in 2024 alone — making it the most financially destructive enterprise-targeted cyber threat in the country. The challenge with BEC is that it exploits trust, not technology. These attacks carry no malicious payload for a gateway to catch — just carefully crafted messages designed to manipulate human judgment. That makes traditional de...

The conversation around Anthropic's Claude Mythos Preview has understandably centered on zero-days. If AI systems can identify and exploit vulnerabilities across every operating system and browser at scale, defenders have to assume that exploit timelines will keep compressing. But for CISOs, the harder question is how long exposed access credentials remain valid after defenders discover the exposure. Credentials determine how far an attacker can move, how long they can persist, and how difficult containment becomes. A vulnerability just gets them in the door. That gap between time-to-exploit and time-to-revoke is where many organizations are most exposed. GitGuardian's State of Secret Sprawl report shows 64% of valid secrets detected in 2022 were still active and exploitable four years later in an environment where exploitation now collapses to hours. Vulnerabilities get attackers in the door, but credentials decide how far they go. The Mythos-ready briefing , developed b...

Most of the commentary on Anthropic's Claude Mythos Preview has gone in one of two directions: one camp treats it as the civilizational inflection point, the other as marketing dressed up as a research result. Neither read is particularly useful for a security leader who still has a program to run on Monday. The AISLE team's technical response to the Mythos announcement made a fair point worth sitting with: much of what was demonstrated is recoverable on smaller, open-weight models, particularly on the discovery side. Early testing results of OpenAI's GPT 5.5 show CTF performance close to or slightly superior to Mythos; the exclusivity framing is arguable, but the accelerated model improvement in offensive security is undisputable. The UK AI Security Institute found that Mythos can autonomously execute a complete corporate network takeover, succeeding in 30% of its attempts on a complex attack range — a task AISI estimates would require roughly 20 hours for a human e...

We recently worked with an organization that had invested heavily in advanced security tooling, including AI-driven detection and monitoring capabilities. From a technical perspective, the environment appeared mature: alerts were firing, dashboards were populated, and risks were clearly identified.  Yet progress had stalled.  The security team and IT disagreed on ownership. Business leadership perceived cyber risk as "under control," while the security team felt increasingly exposed and unheard. AI surfaced the signals, but no one could agree on what to do with them.  The turning point did not come from additional tooling or deeper analysis. It came from reframing the conversation.  By aligning stakeholders around clear business impact, contextualizing the findings against industry peers, and translating technical gaps into credible, board-level risk narratives that reinforced the internal security team's concerns rather than questioning their judgment, decisions were finally ma...

The conversation around AI in the SOC has mostly centered on efficiency: closing alerts faster, reducing queue backlog, and automating repetitive work that burns out L1 analysts. That framing is directionally right, and it matters because analyst fatigue is real. For teams dealing with high alert volume, analysts are often asked to make good decisions under a fragmented context and time pressure. But that framing is still incomplete. The bigger shift is not just workflow automation or orchestration of predefined playbooks. It is AI's ability to perform contextual, hypothesis-driven investigation across multiple telemetry sources, work that has traditionally depended on experienced L2 or L3 analysts and limited human time. When that capability can be applied consistently across every alert, it changes the operating model, not just the speed of the existing one. Two recent investigations at Prophet Security make that real. In both cases, the attacks were not obvious from signature-bas...

Every few years, a breach happens that security teams study for the wrong reasons. SolarWinds is a good example. When the compromised Orion update started reaching customer environments in early 2020, the signals were already there: unusual DNS requests, unexpected authentication behavior in Azure AD, odd SAML token activity, and lateral movement from on-premises Active Directory into cloud environments.  None of it looked like an attack. Each signal sat at low or medium severity, and they were scattered across domains. The attackers had close to a year of dwell time before FireEye, a victim itself, discovered the breach while investigating a stolen red-team toolkit. We tend to call SolarWinds a one-off. It wasn't.  The real lesson from that breach, and from the ones that have followed it, is structural.  SOCs are designed, staffed, and measured around routine work: phishing, endpoint detections, and user anomalies. The people, processes, dashboards, and tools are ...

OT incidents rarely start with "OT attacks." They start with ordinary enterprise weaknesses: shared credentials, remote access shortcuts, management systems that bridge zones too easily, and monitoring that stops short of operations.  When those weaknesses line up, an initial IT compromise becomes an OT event, and the deciding factor is no longer whether the activity is detected, but whether the environment can be contained and recovered without extended outage. What matters is that these failure patterns repeat across industries, which means they can be anticipated and solved - but only if recovery is treated as a security control, not an afterthought. Recurring OT Security Patterns Across Industries Sygnia is a premier cyber technology and services company, with extensive experience helping organisations' IT/OT environments respond to cyber incidents and strengthen enterprise-wide cyber security..  Across numerous OT security assessments, adversary simulations, and inc...

Insider threats are rising in both number and cost, forcing security teams to seek stronger cybersecurity solutions. At the same time, IT teams face more frequent audits and more complex data security requirements. Add to this a distributed workforce and third-party contractors, and it's clear why managing privileged access and monitoring user activity is so challenging.  Modern cybersecurity solutions must offer streamlined access management, complete oversight of user activity within your network, and a privacy-first approach to monitoring. This article offers practical tips on enhancing your cybersecurity strategy by addressing these three pillars. We'll also explore how Syteca's new release can help security leaders protect sensitive data, secure access, and improve audit readiness without IT overhead.  Monitoring User Activity while Preserving Their Privacy Keeping a close watch on user actions is critical for insider threat defense, but it raises a dilemma: "...

AI SOC Agents are going through a hype cycle. If we're going by Gartner's Hype Cycle for Security Operations, 2025 , this technology is still an "Innovation Trigger", but it's at the cusp of "Peak of Inflated Expectations". Every vendor claims their solution will revolutionize security operations. Every conference features another keynote promising autonomous defense. And every CISO is being asked whether AI will replace their security team. At Redis, implementing AI in the SOC has been more of a measured journey. The model is more of a hybrid SOC, so there's a combination of external service providers as well as internal resources. In this case, Prophet Security is currently proving themselves alongside a more traditional MDR provider.  But let's take a step back.  The Tipping Point for AI Adoption within the SOC Considering an AI solution for Redis' SOC came down to the confluence of three drivers.  On an individual level, there was more value from AI tools an...