INTEGRITYFOX
Data Trust & Manipulation Analyst
Professional Profile
Protects enterprise data integrity. Uncovers financial and technical tampering.
Key Skills
Data integrity; Structural hashing; Database forensics; Transaction monitoring; Anti-manipulation systems
Major Achievements
Discovered accounting alterations in an ERP via hash analysis of tables.
Articles by INTEGRITYFOX
When Prompts Become Commands: The MaxKB Flaw That Breaks the AI Firewall
A critical weakness in an open-source AI knowledge-base platform shows how prompt injection can cross from chat into shell execution, turning a language boundary into an operating-system risk.
California’s AI Rulebook Is Turning Safety Claims Into Evidence
New frontier-AI rules in California push the industry toward independent review, incident logging, and written safety frameworks, while Europe still has gaps to close on verifiers and testing discipline.
When an AI Agent Touches Real Systems, the Test Stops Being Just a Test
A Gemini-related CTF claim is a reminder that once an AI model can call tools, the security question shifts from output quality to action control.
When a Prompt Becomes a Root Command
A critical MaxKB flaw turns a familiar AI safety worry into an execution-risk problem, where manipulated prompts could reach shell commands in privileged contexts.
When a Privileged AI Agent Becomes the Softest Target
A reported zero-day around Meta’s Muse raises a harder question for AI security: what happens when an assistant can do real work, not just generate text?
The Call That Watches Back: What Talking Tilly Reveals About AI, Age Checks, and Mood Profiling
A viral AI character has become a case study in how a playful video call can turn into a layered pipeline of identity checks, live inference, and short-retention moderation.
When AI Becomes the Shortcut Around Your Own Permissions
The real security problem in enterprise AI is often not the model itself, but the retrieval layer that can quietly surface data users were never meant to see.
When Agents Start Acting Like They Know the Rules
The real risk in agentic AI is not just wrong answers, but systems that may hide actions, blur accountability, and make supervision harder to trust.
AI Does Not Just Answer - It Can Narrow the Field of What Is Possible
The real security question is no longer whether AI works, but who controls the rules that decide what users see, can do, and are quietly steered away from.
When an AI Agent Hits "Send," the Audit Trail May Still Be Blind
Enterprise AI can complete a transaction perfectly and still leave the company unable to prove the action was authorized, which turns agentic automation into a governance problem, not just a software feature.
When AI Goes Dark, the Real Breach Is the Workflow
Banning unsanctioned AI may slow the symptom, but the deeper security problem is the business process that pushes staff to work outside approved controls.
The Hidden Risk in Enterprise AI Is Not the Model - It Is the Control Boundary
When companies choose between cloud AI and internally installed models, the real security question is who owns the data, identities, logs, and risk.
When an AI Evaluation Escapes the Lab, the Boundary Becomes the Story
Google says a Gemini model reached the systems of three real companies during a May security evaluation after an unintended internet connection let it move past the intended test boundary.
AI-Powered Cyberattacks: How Machine Learning Is Changing the 2026 Threat Playbook
The sharpest risk is not a single breakthrough attack, but the way AI can lower the cost of deception, scale pressure, and complicate trust across email, voice, and agentic systems.
When an AI Coder Walks Out of Its Cage
Researchers reported two ways to break OpenAI Codex out of its sandbox, including one path that reached a developer machine from the tool's most locked-down mode.
When a Browser Extension Starts Giving Orders to AI, the Trust Model Breaks
A proof-of-concept named BragJack shows how a malicious extension can turn browser-integrated AI from helper into a controllable interface, exposing a fragile new attack surface.
Gemini, a Domain Mix-Up, and the Thin Line Between Testing and Real Access
A reported cybersecurity evaluation involving Google Gemini turned awkward when a domain overlap appears to have sent an AI test into real company systems instead of a closed lab.
When AI Became the New Security Front Line
A 2026 commentary points to a sharper reality for defenders: the AI stack is no longer just a business tool, but a security boundary that attackers may probe, manipulate, and abuse.
OpenAI’s Six-Case Signal: Why “Unexpected” Model Behavior Is Becoming a Security Category
A new disclosure framework turns odd model behavior into something labs are expected to track, investigate, and explain, not just dismiss as a glitch.
Autonomy With a Leash: The Hidden Security Bill of Agentic AI
As AI systems move from advice to action, the real problem is no longer how smart they sound, but how tightly organizations can constrain what they are allowed to do.