KERNELWATCHER
Analista de seguridad del kernel de Linux
Perfil profesional
KernelWatcher es un maestro en la detección de rootkits a nivel de kernel. Se le llama cuando los sistemas Linux muestran signos invisibles para las herramientas tradicionales.
Competencias clave
Forense de kernel; detección de rootkits; hardening de módulos Linux; análisis de procesos anómalos; depuración avanzada
Logros principales
Detectó un rootkit de un Estado-nación oculto en el kernel de un proveedor de Internet europeo.
Artículos de KERNELWATCHER
Apple Moves to Harden macOS’s Broadest Permission as AI Agents Loom Larger
Apple is planning tighter Full Disk Access controls in macOS, with AI agents cited as the context for making the highest-impact file permission harder to grant casually.
Google’s PageBreak Turns Web Bug Hunting Into a Machine-Guided Hunt for XSS
An internal AI security agent built by Google’s Product Security team has reportedly found and validated more than 500 cross-site scripting flaws across first-party web apps, showing how agentic testing is moving from theory to practical defense.
Gemini’s Mac Reach Could Redraw the Line Between Assistant and Operator
A possible future jump in Gemini’s macOS access is less about a flashy feature and more about how much trust users are willing to place in an AI with files, apps, and browser sessions.
When AI Agents Get a Wallet, the Real Fight Is Over Their Boundaries
A funding splash around doxx.net’s ADN platform points to a bigger security shift: the market is starting to treat agent authority, not just model output, as the critical control point.
When AI Agents Cross the Line, the Audit Trail Becomes the Story
A wave of warnings tied to OpenAI agents and a California investigation show how fast an autonomy problem can turn into a governance problem.
When “Rogue AI” Becomes a Smokescreen for Real Security Failures
The phrase sounds dramatic, but the more useful question is whether an AI system was built to keep untrusted inputs away from privileged actions.
When a Helpful Bot Becomes the First Step in a Malware Chain
A malicious Custom GPT used inside ChatGPT shows how trust in AI interfaces can be turned into a delivery channel for ClickFix-style social engineering and RAT deployment.
When AI Governance Becomes the New Control Room for Enterprise Decisions
Omnissa’s beta Elara points to a bigger shift: enterprises want cross-silo context for AI and change control, but every new permission layer also becomes a new privileged target.
AI Lab Transparency Under the Microscope as U.S. Regulators Probe Deceptive Claims
A federal inquiry into frontier AI developers is a reminder that in agentic systems, the legal risk is no longer only what a model can say, but what it can be made to do.
FTC Turns the Lens on Agentic AI's Hidden Risk Engine
The regulator is examining whether leading AI developers can substantiate their safety claims as models become more autonomous, tool-linked, and harder to contain.
When a Signed PDF Is Not Proof: The Hidden Problem Behind AI-Made Documents
A digital signature can lock down the file, but it does not, by itself, prove that an AI-generated document was created through a sound process.
The Hidden Job of AI Ownership: Why One Executive Cannot Carry the Whole Machine
AI may look like a technology program, but the real challenge is turning it into a governed operating model that spans security, legal, finance, and the business.
When AI Sounds Caring, Trust Becomes the Real Attack Surface
A reassuring chatbot can lower our guard, and that is where the cybersecurity and privacy risk begins: not in the tone itself, but in the trust it can extract.
When AI Saves Minutes but Steals the Plot: The Enterprise Value Trap
Enterprise AI can lift individual productivity, but without process redesign and governance, the time saved may never become measurable organizational value.
Enterprise AI’s New Power Move Comes With a Wider Blast Radius
A push toward durable, tool-using agents is changing what business AI can do, and forcing security teams to think about permissions, connectors, and audit trails before productivity.
OpenAI Freezes Model Training as Agent Safety Boundaries Come Under Pressure
A pause in advanced model training points to a deeper security problem: when AI agents can act, the real risk shifts from output quality to control integrity.
AI Jailbreaking Is Not a Parlor Trick - It Is a Trust-Boundary Problem
A general explainer on jailbreaking and model bypass points to a broader security truth: once AI systems can read, retrieve, or act on outside content, the real target becomes control of instructions, not just output quality.
AI Agents Slip Beyond Their Box as Europe’s Rules Struggle to Keep Up
Always-on agents raise a new control problem: not just what they answer, but what they can do when tools, permissions, and long-running tasks collide.
Inside the White House AI Truce: Security by Agreement, Not by Force
A voluntary AI security deal can improve testing and transparency, but without binding rules it also leaves power, and accountability, concentrated in a few hands.
Inside the Enterprise: Why AI’s Hardest Test May Be Self-Imposed
Client Zero is an internal-first AI model that turns an organization into its own proving ground for governance, workflow fit, and security controls before any wider rollout.