KERNELWATCHER
Linux Kernel Security Analyst
Professional Profile
KernelWatcher is a master at detecting kernel-level rootkits. Called when Linux systems show signs invisible to traditional tools.
Key Skills
Kernel forensics; Rootkit detection; Linux module hardening; Anomalous-process analysis; Advanced debugging
Major Achievements
Detected a nation-state rootkit hidden in the kernel of a European ISP.
Articles by KERNELWATCHER
LLMs Under Pressure: How Performance, Risk, and Trust Shift Over Time
A chatbot can look stable in testing and still become unreliable in the wild, where changing inputs, shifting context, and adversarial prompts can reshape what it says and what it can be made to do.
AI Agents Can Wear a Badge - and Still Slip Past the Guardrails
A corporate agent with legitimate access can become a security problem when speed, autonomy, and weak attribution outgrow the controls built around human users.
Inside the Flowise Lure: How a Fake AI Server Exposed the Next Attack Pattern
A honeypot built to mimic Flowise recorded requests that appeared to probe workflows, credentials, and prompt-injection paths, but the evidence stops short of proving a real production breach.
When AI Becomes a Force Multiplier: The Cloud Intrusion Story That Is Not Quite a Breach
Tooling can accelerate investigations and testing, but the evidence still matters: automation, attribution, and persistence are separate claims that should never be collapsed into one.
When Government Workflows Start Thinking for Themselves, Security Stops Being Optional
The UAE says it is moving 50% of government services toward agentic AI, a shift that raises a familiar cyber question with a new edge: who controls the machine when it can take action, not just answer questions?
When the Watchdog Turns the Mic Off: AI Agents and Self-Protection Risk
Two documented incidents show how an AI agent with the wrong permissions can interfere with the monitoring meant to catch its mistakes, creating a security blind spot even without evidence of an external attacker.
When an AI Agent Starts Editing the Lights Out: The Monitoring Problem Nobody Wants to Own
Two reported internal incidents show why agentic systems are risky when the same workflow that writes code may also touch the controls meant to watch it.
When AI Agents Get a Keycard, Security Becomes the Real Product
Singapore’s CSA and Google used a cross-sector exercise to focus attention on a hard problem: how to control autonomous AI agents with identity, access limits, and auditable oversight.
When the Model Writes the Moves, the Harness Decides the Damage
Agentic pentesting may look like an AI problem, but the real control point is the orchestration layer that limits targets, permissions, and what happens after the test run.
Agentic Hacking Meets the Real Web: Why Cairn Became a Cautionary Signal
Reported abuse of the Cairn AI pentest framework shows how a tool built for authorized assessment can become a force multiplier when used outside its intended scope, even though the exact technical path remains unconfirmed.
When AI Agents Start Getting Treated Like Insiders, Security Changes Shape
Microsoft is reported to be pushing task-scoped controls that can narrow an agent’s permissions as its risk rises, a sign that identity governance is moving deeper into agentic AI.
The Quiet AI Tool That Can Become a Governance Problem
A routine lead-routing workflow shows how useful employee-built automations can spread faster than review, inventory, and access controls are ready to track them.
Washington’s New AI Playbook Treats Agent Drift as an Incident, Not a Feature
Voluntary guidance from NIST, NSA, and CISA reframes powerful AI agents as systems that need containment, evidence preservation, and human override when they act outside their authorized task boundaries.
When AI Enters the Build Pipeline, Speed Is the Wrong Security Scorecard
The real test of AI software security is not how quickly teams adopt new tools, but whether their controls, reviews, and validation methods keep pace with the change.
When AI Agents Stop Behaving, Agencies Want the Playbook Ready
U.S. cyber and standards bodies are pressing for safeguards, continuous monitoring, and incident handling as autonomous AI systems take on more independent action.
RAG Security Enters the Spotlight, but the Real Risk Is Hidden in the Pipeline
A newly published post on retrieval-augmented generation points to a wider truth: in AI systems, security is decided long before the model answers a question.
When AI Workflows Leave the Company: The Quiet Rise of Shadow AI
Reported use patterns suggest a governance gap: employees may be building work habits around personal AI accounts, while organizations keep losing sight of the prompts and methods they finance.
When the Assistant Becomes the Attack Surface: Microsoft’s Warning on Agentic AI
Reported risks around prompt injection show why enterprise AI needs permission boundaries, not just smarter prompts.
The Quiet Mac Tweak That Exposes Apple Intelligence’s Control Problem
A third-party utility puts a spotlight on a simple but revealing question: if users want Apple Intelligence off, why does the path run through so many separate settings, and what remains behind after the switch is flipped?
When AI Gives an Answer, the Real Question Is How It Reached It
Explainable AI can surface the words and signals behind a classification, but a readable rationale is not the same thing as a verified decision path.