Telesource Communications Inc

10/16/2026

https://lnkd.in/p/grA7cRvC

10/15/2026

10/15/2026

10/15/2026

https://lnkd.in/p/g9kDt2e9

The Internet is the world’s most sophisticated digital attack environment. Your organization doesn’t have to be targeted specifically—it only has to be visible, vulnerable and reachable. Modern cybersecurity starts by discovering what attackers can see, eliminating unnecessary...

09/30/2026

09/20/2026

Season 1 of *The Blacklist* offers three strong CISO lessons—despite its dramatization:

1. Identity is the real security perimeter
Red repeatedly exploits trust, aliases, insiders, and assumed identities—not just technology. A CISO must continuously verify users, devices, vendors, and privileged access. “Known” does not mean trustworthy.

2. Intelligence without context creates blind spots
The FBI possesses enormous amounts of data but often cannot connect it quickly enough to prevent an attack. Effective security requires combining threat intelligence, external attack-surface visibility, behavioral signals, and business context—not merely collecting more alerts.

3. Insider and third-party risk can bypass excellent defenses
Compromised employees, contractors, suppliers, and government insiders repeatedly defeat otherwise secure operations. CISOs need least-privilege access, separation of duties, continuous monitoring, vendor-risk controls, and a practiced insider-threat response plan.

The executive takeaway: Season 1’s recurring security failure is not inadequate technology—it is misplaced trust, fragmented intelligence, and unclear ownership.

09/20/2026

https://www.facebook.com/share/v/1EfunitmFV/

05/31/2026

**Executive summary:** OWASP is the **risk language**. Mimecast, Proofpoint, and Akamai are **control platforms** that help reduce those risks in different layers of the stack.

OWASP does **not** sell security products. It defines common risk categories, testing guidance, and secure-development expectations. Mimecast and Proofpoint mainly protect the **human/email/data layer**. Akamai mainly protects the **web application/API/edge layer**. Together, they help translate OWASP risks into enforceable controls.

# # How they align

| Vendor | Primary Layer | How It “Plays” with OWASP | Best OWASP Fit |
| -------------- | ---------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------ |
| **Mimecast** | Email security, BEC, impersonation, URL/attachment defense, DMARC, continuity, DLP | Reduces phishing, credential theft, malware delivery, malicious links, spoofed domains, and outbound data leakage that often lead to OWASP-style application compromise | Identity failures, software/data integrity issues, security monitoring, social engineering around apps |
| **Proofpoint** | Email security, threat protection, user risk, DLP, post-delivery remediation | Protects the people who access applications; blocks phishing, BEC, ransomware, malicious URLs/attachments, and unauthorized data movement | Identity failures, data exposure, monitoring, software/

05/31/2026

**Statistics** and **analytics** are related, but they are not the same.

# # Core Difference

**Statistics** is the discipline of collecting, measuring, modeling, and interpreting data to understand what is true or likely true.

**Analytics** is the practical use of data, statistics, tools, and business context to make decisions, improve performance, or predict outcomes.

Put simply:

> **Statistics asks: “What does the data prove or suggest?”**
> **Analytics asks: “What should we do with what the data shows?”**

# # Side-by-Side Comparison

| Category | Statistics | Analytics |
| ----------------- | ---------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------- |
| Main purpose | Understand patterns, uncertainty, probability, and relationships | Support decisions, actions, forecasting, and business outcomes |
| Focus | Mathematical validity | Practical usefulness |
| Typical questions | “Is this result statistically significant?” “What is the probability?” “Is there correlation?” | “Which customers are likely to churn?” “Where should we invest?” “What campaign worked best?” |
| Methods | Sampling, hypothesis testing, regression, confidence intervals, probability models | Dashboards, KPIs, predictive models, segmentation, attribution, optimization |
| Output | Evidence, inference, probabilities, statistical conclusions | Recommendations, insights, forecasts, action