This Week in Cyber: Phishing, Data Theft & AI Ransomware

Every week, new threats remind us, cybersecurity isn’t standing still.

The world is evolving at a lightning speed. AI is revolutioning every aspect of the world.

And the best way to stand out?It’s to know what’s happening, and learn how to respond.

Here are 3 stories you need to know,  plus one skill worth building right now.

1. Cybersecurity Firms Added to Salesforce‑Salesloft Drift Breach This Week

What happened:
Cybersecurity vendors, including Proofpoint, SpyCloud, Tenable, and others have confirmed that their Salesforce environments were compromised in the ongoing Salesloft Drift OAuth token abuse campaign. 

Stolen tokens from third-party integrations were used to access sensitive Salesforce data like cloud keys and customer records.

Why it matters:
The breach shows how OAuth token abuse can bypass perimeter defenses, even in highly mature environments. 

It wasn't a Salesforce vulnerability, it was integration risk, and now it's impacting the security sector itself.

How to use it:
Great for GRC or cloud interviews: talk about token rotation, integration audits, and limiting scopes on OAuth permissions. 

It shows you understand the risk beyond just technical misconfigurations.

🔗 Read the full article on SecurityWeek

2. AI‑Powered Supply Chain Threat Demonstrated Against Major Cloud Platforms

What happened:
Researchers revealed an AI model namespace reuse attack, where cloud platforms like Google and Microsoft can be tricked into pulling malicious AI models from public repositories during dependency resolution. 

The flaw affects AI/ML workflows that auto-fetch models by name without validation.

Why it matters:
This is dependency confusion for AI. a new class of supply chain attack. It targets the trust model behind AI deployment pipelines, not the models themselves. 

As enterprises adopt AI tooling, these kinds of blind spots are inevitable.

How to use it:
Excellent for cloud security or DevSecOps interviews: mention model validation, artifact signing, and avoiding blind pulls from public registries. 

Demonstrates foresight into securing AI/ML supply chains.

🔗 Read the full article on SecurityWeek

3. Model Namespace Reuse: AI Supply‑Chain Attack Hits Google & Microsoft

What happened:

Researchers at Palo Alto Networks demonstrated a new AI supply-chain attack method called Model Namespace Reuse. 

Attackers register deleted or transferred model names on platforms like Hugging Face commonly referenced in AI workflows, including those used by Google Vertex AI and Microsoft Azure AI Foundry. 

When those platforms auto-fetch models by name, they can unknowingly deploy malicious ones, enabling arbitrary code execution.

Why it matters:

This is a high-risk vector in AI supply chains. 

Trusting model names without verification allows attackers to slip in malware at deployment without needing to compromise repositories or cloud platforms directly. 

Both enterprise-grade AI services and thousands of public AI projects are vulnerable.

How to use it:

Great for DevSecOps or AI governance interviews: mention pinning models to specific commits, cloning into trusted repos, and scanning for ambiguous model references. 

Demonstrates deep awareness of securing AI pipelines not just runtime environments.

🔗 Read the full article on SecurityWeek

We’re entering an era where AI isn’t just changing attacks, it’s rewriting the entire threat landscape.

If you want to stay ahead, you need to understand how these systems work and how they can go wrong.

I recommend studying the AI Security Fundamentals by Varonis.

This course teaches":

• How AI attacks work

• What risks LLMs introduce

• How to defend modern AI systems

It’s short, clear, and made for defenders like you.
Whether you’re blue team, red team, or GRC  this is a skill worth adding.

👉 Start the AI Fundamentals course 

And one last thing, keep this in mind.

“Your knowledge can save you from misfortune.”

 – Sandra