Welcome to CyberHoot’s February Cybersecurity Newsletter!
Attackers aren’t just targeting passwords anymore. They’re going after session tokens, misconfigured cloud services, and even the AI tools your team uses every day. The perimeter is getting more porous, and the browser has quietly become another chink in your armor.
And yet, there is good news. Each of the risks outlined this month are preventable. A clear understanding of how they work turns surprise into preventive measures and resilient defenses.
This month at CyberHoot, we’re unpacking four emerging issues that deserve your attention, not because they’re sensational, but because they’re practical, timely, and fixable.
Sneaky browser extensions are stealing ChatGPT session tokens without ever touching a password or triggering MFA. Once an attacker has a valid session token, they can impersonate users as if they logged in legitimately. We’ll explain how this attack works at the technical level, why it bypasses traditional safeguards, and what controls you should implement right now to protect your organization.
A senior cybersecurity leader recently made a costly AI mistake, and it wasn’t due to lack of technical knowledge. It was a lapse in safe usage practices with a public AI tool. The lesson is clear: even experienced professionals can expose sensitive data without guardrails. We’ll break down what happened and outline a practical framework for using AI tools safely and responsibly without banning its use.
Google Workspace remains a cornerstone of modern business operations, yet common security gaps continue to lead to avoidable breaches. From weak admin role segmentation to missing conditional access policies, small misconfigurations can create outsized risk. We’ll identify the most frequent weaknesses we see, explain why they matter, and provide a prioritized remediation checklist.
Finally, MongoBleed exposed 87,000 internet-facing MongoDB databases. This wasn’t a sophisticated zero-day, it was an exposure problem. We’ll cover who’s most at risk, how to determine if you’re vulnerable, the immediate patching steps to take, and the longer-term hardening strategies that protect your data from becoming the next headline.
Read on, stay disciplined, and keep your organization Cyber(Hoot) Smart.
Craig
CEO, Co-Founder CyberHoot




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Data poisoning is an attack in which an adversary deliberately injects malicious, misleading, or biased data into an AI model’s training, fine-tuning, or feedback pipeline to influence how the model behaves. The objective is to cause the model to produce incorrect, unsafe, biased, or attacker-controlled outputs, either broadly or under specific conditions.
Unlike prompt-based attacks, data poisoning targets the learning process itself. Once poisoned data is incorporated, the model may behave maliciously even for normal, legitimate users.

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