Microsoft Confirms Critical Bug in Windows 11 24H2 Causing BSOD Crashes

Microsoft has acknowledged a serious flaw in its recent Windows 11 24H2 updates that is triggering widespread Blue Screen of Death (BSOD) errors. The crash, linked to the stop code SECURE_KERNEL_ERROR (0x18B), is affecting a significant number of users globally.

Escalation Following April 2025 Update

Although initial signs of the issue emerged in March 2025—first noted by Windows Latest—it gained serious traction after the release of the April 2025 Patch Tuesday update. The bug has been traced back to three recent updates:

• KB5053598 (March 11 – Patch Tuesday)
• KB5053656 (March 27 – Optional Update)
• KB5055523 (April 8 – Patch Tuesday)

Users have reported that after installing any of these updates, their systems either crash during reboot or enter an endless restart loop, with some devices becoming completely unbootable.

Root of the Problem: Secure Kernel Failure

The crash points to a malfunction in the Secure Kernel, a core part of Windows responsible for security and virtualization services. Initially, Microsoft did not respond, likely due to the limited number of affected users. However, once the problem escalated in April, the company quietly confirmed it through updates to its official support documentation and began a deeper investigation.

Other Reported Issues

• Windows Hello authentication failures, preventing sign-in via PIN or facial recognition
• App compatibility issues, particularly on ARM devices—e.g., Roblox fails to open, and some Citrix applications won’t install

Microsoft’s Temporary Solution: Known Issue Rollback (KIR)

To address the disruption, Microsoft is using its Known Issue Rollback (KIR) mechanism, which disables the problematic portions of the updates through a server-side patch. This is being rolled out automatically via Windows Update to all consumer and unmanaged business devices. According to Microsoft, full rollout may take up to 24 hours.

Users are advised to:

• Keep their devices connected to the internet
• Restart their PCs multiple times to help apply the KIR patch more quickly

In managed IT environments, system administrators must deploy a Group Policy update to reverse the buggy changes manually. This policy can be found under Computer Configuration > Administrative Templates in the Group Policy Editor, with full steps outlined in Microsoft’s documentation.

Long-Term Fix in Progress

While KIR serves as a temporary remedy, Microsoft is working on a permanent fix expected to arrive in an upcoming update. In the meantime, affected users should regularly check for updates and continue rebooting their systems to ensure the rollback is successfully applied.

Summary of Affected Updates and Issues

Update	Release Date	Main Problems	Mitigation Method
KB5053598	Mar 11, 2025	BSOD (SECURE_KERNEL_ERROR)	Auto KIR (server-side)
KB5053656	Mar 27, 2025	BSOD, Windows Hello issues	KIR / Group Policy
KB5055523	Apr 8, 2025	BSOD, login errors, app failures	KIR / Group Policy

Actionable Steps for Users

• Reboot your PC several times and check for updates to apply the fix faster.
• For business devices, IT teams should implement the Group Policy rollback and restart systems.
• Monitor for future patches from Microsoft, particularly in the May 2025 update.

Final Thoughts

Microsoft’s swift implementation of KIR has helped reduce the disruption, but the situation has reignited debates around the stability of rapid-fire Windows updates. As the company works toward a more permanent resolution, users remain cautious about installing future updates without delays or complications.

A Comprehensive Guide to openpyxl

In the world of Python programming, managing Excel files is a common task. Whether you're automating reports, data analysis, or even developing a small application, openpyxl is an excellent library for reading and writing Excel (xlsx) files. In this article, we'll dive deep into what openpyxl is, why you should use it, and how you can perform various operations with practical code examples.

What is openpyxl?

openpyxl is a popular Python library used to work with Excel 2010 xlsx/xlsm/xltx/xltm files. It allows you to create, modify, and extract data from Excel spreadsheets programmatically. The library is widely appreciated for its ease of use, comprehensive features, and active community support.

Key Features

• Reading and Writing Excel Files: Open and modify existing workbooks or create new ones from scratch.
• Styling: Format cells, add fonts, borders, colors, and more.
• Formulas and Functions: Create cells with formulas and let Excel calculate the results.
• Charts: Generate different types of charts to visualize data.
• Data Validation: Implement drop-down lists and other forms of data validation.
• Conditional Formatting: Apply formatting based on specific conditions.

The Purpose of openpyxl

openpyxl is designed to simplify Excel file manipulation through Python scripts. It is used in various domains such as:

• Data Analysis: Automate the extraction, transformation, and loading (ETL) of data.
• Reporting: Generate reports with dynamic data updates.
• Automation: Replace repetitive manual tasks in Excel with automated scripts.
• Data Visualization: Create charts and graphs to represent data visually.

By automating Excel tasks, openpyxl saves time, reduces errors, and improves productivity, making it an indispensable tool for developers and data analysts alike.

Getting Started with openpyxl

Installation

Before you start using openpyxl, you need to install it. You can easily install openpyxl using pip:

pip install openpyxl

Basic Usage

Let’s begin with a simple example that demonstrates how to create a new Excel workbook and add some data to it.

Creating a New Workbook

from openpyxl import Workbook

# Create a new workbook and select the active worksheet
wb = Workbook()
ws = wb.active

# Add some data to the worksheet
ws['A1'] = "Hello"
ws['B1'] = "World!"

# Save the workbook to a file
wb.save("example.xlsx")

In this snippet, we:

• Imported the Workbook class.
• Created a new workbook and accessed the default worksheet.
• Added data to cells A1 and B1.
• Saved the workbook as "example.xlsx".

Reading from an Excel File

from openpyxl import load_workbook

# Load an existing workbook
wb = load_workbook("example.xlsx")
ws = wb.active

# Read and print the content of a specific cell
print(ws['A1'].value)  # Output: Hello

Advanced Usage and Examples

Styling Cells

from openpyxl import Workbook
from openpyxl.styles import Font, Color, PatternFill

wb = Workbook()
ws = wb.active

# Create a font style
bold_font = Font(bold=True, color="FF0000")  # Red, bold text

# Apply the font style to a cell
ws['A1'].font = bold_font
ws['A1'] = "Styled Text"

# Apply a fill color to another cell
fill = PatternFill(start_color="FFFF00", end_color="FFFF00", fill_type="solid")
ws['B1'].fill = fill
ws['B1'] = "Highlighted"

wb.save("styled_example.xlsx")

Working with Formulas

wb = Workbook()
ws = wb.active

ws['A1'] = 10
ws['A2'] = 20
ws['A3'] = "=SUM(A1:A2)"  # Excel will calculate this sum

wb.save("formula_example.xlsx")

Creating Charts

from openpyxl import Workbook
from openpyxl.chart import LineChart, Reference

wb = Workbook()
ws = wb.active

# Add some sample data
rows = [
    ['Month', 'Sales'],
    ['January', 100],
    ['February', 120],
    ['March', 140],
    ['April', 130],
    ['May', 150],
]
for row in rows:
    ws.append(row)

# Create a line chart
chart = LineChart()
data = Reference(ws, min_col=2, min_row=1, max_row=6)
chart.add_data(data, titles_from_data=True)
chart.title = "Monthly Sales"
chart.x_axis.title = "Month"
chart.y_axis.title = "Sales"

# Place the chart on the worksheet
ws.add_chart(chart, "E2")

wb.save("chart_example.xlsx")

Data Validation

from openpyxl import Workbook
from openpyxl.worksheet.datavalidation import DataValidation

wb = Workbook()
ws = wb.active

# Create a data validation object with a drop-down list
dv = DataValidation(type="list", formula1='"Option1,Option2,Option3"', showDropDown=True)
ws.add_data_validation(dv)

# Apply data validation to a specific range
dv.add(ws["A1"])

ws["A1"] = "Select an option"
wb.save("datavalidation_example.xlsx")

Conditional Formatting

from openpyxl import Workbook
from openpyxl.formatting.rule import CellIsRule
from openpyxl.styles import Font

wb = Workbook()
ws = wb.active

# Populate some data
for i in range(1, 11):
    ws[f"A{i}"] = i * 10

# Apply conditional formatting: Highlight cells greater than 50
red_font = Font(color="FF0000")
rule = CellIsRule(operator='greaterThan', formula=['50'], stopIfTrue=True, font=red_font)
ws.conditional_formatting.add("A1:A10", rule)

wb.save("conditional_formatting_example.xlsx")

Best Practices and Tips

• Modularize Code: When working on larger projects, separate Excel manipulation code into functions or classes for reusability.
• Error Handling: Always include error handling when reading/writing files, as file access issues can cause unexpected errors.
• Documentation: Refer to the openpyxl documentation for detailed information and updates.
• Optimize Performance: For very large files, consider iterating over rows using optimized methods provided by openpyxl.

Conclusion

openpyxl is an incredibly versatile and powerful tool for automating Excel tasks using Python. Whether you're creating complex reports, visualizing data with charts, or ensuring data integrity with validations and conditional formatting, openpyxl offers a comprehensive suite of features to help streamline your workflow.

With a supportive community and detailed documentation, it’s an excellent choice for both beginners and advanced users. Start exploring its features today and see how it can transform your data processing tasks!