Monday, September 14, 2026

An analysis of data breach epidemic in Bangladesh


Two news stories have surfaced in the media that NID information with biometric data is being sold on the internet black market, and call histories along with location information of almost any person are available. These highly sensitive data, used by law enforcement agencies, leaked into the wrong hands can lead to more precise, targeted, and sophisticated criminal activities. 

In 2024, the Confidentiality of the National Telecommunications Monitoring Cell (NTMC) – the national-level intelligence agency of Bangladesh – was breached.

Two high-clearance officials used their NTMC credentials to collect personal data of citizens, such as NID details and phone call detail records (CDR), and later sold the data online. The then NTMC DG Ziaul Ahsan said that the Home Ministry asked the RAB and Police to take steps against them. 

The recent news that CDRs of almost any person are being sold on Telegram and Facebook from Tk500 to Tk1,050 may also raise an unverified yet contextual question of whether this access traces back to insiders like the NTMC case above. 

In January 2026, two EC staff were found siphoning 365,608 NID records in a single month to sell on social media. This indicates that access to sensitive national databases carries no meaningful audit trail, no behavioural monitoring, and no alert system for unusual events like bulk downloads. 

As of the date, around 174 entities like banks, ports, and health services are connected to the central NID database via APIs, assuming a secure one-to-one data pipeline, to ensure different types of verification. Instead of returning a secure yes/no validation, the API transfers the full raw profile of the citizen, and the partner organisations store the transferred data on their own local servers indefinitely without audit or deletion schedules. This is called a shadow copy.  

Earlier in 2025, EC confirmed that five organisations with legitimate API access to the NID system, including the DGHS, a major bank, and the Chittagong Port Authority, had leaked data to third parties.

Dismislab, in an investigation, found an unverified claim from a seller that a group is collecting NID data ‘bypassing government servers through an API’ and selling each at Tk2 to Tk3. If it is verified, there is a need for an emergency investigation into whether any third party can collect confidential data directly from government-held systems without authorisation. 

A January 2026 breach leaked personal details of 14,000 journalists, where manipulating the web address path allowed normal users to increase their privileges to admin and access the personal data of other journalists.

This is the textbook example of Broken Function Level Authorisation. These types of flaws can easily be eliminated in a well-structured software development practice. In June 2026, a group of researchers tested a government portal’s password-recovery feature. At one point, the application crashed. It was in debug mode, used during development to find reasons behind any application crash. 

As a result, it exposed plain-text administrative passwords to the master database, the cryptographic keys used to validate all active user sessions, and the login credentials for the government’s official email system. This is also a basic security practice: debug mode must be disabled before deploying any application that goes live.  

In Gopalganj, fraudsters posing as authorised telecom agents lure rural citizens with cheap SIM cards. They collected NID numbers and biometric data from victims and used them to register secondary SIMs or Mobile Financial Service (MFS) accounts for committing crimes. This raises the question of whether these agents and shops, which handle sensitive citizen data, are monitored by the authorities. 

Social engineers hosted six look-alike domains using ‘.news’ extensions instead of ‘.gov.bd’ masquerading as the official myGov e-Apostille service. Citizens and intermediaries were tricked into uploading authentic passports, NIDs, and certificates to these fake sites, resulting in 1,100 fake e-Apostille certificates.

They operated these sites long enough to deceive these people. This points to a lack of regular domain monitoring by the authorities responsible for the official services. The incidents have a common pattern. None were disclosed by the institutions concerned before journalists or researchers found them.

Bangladesh’s Personal Data Protection Act (PDPA) 2026 is meant to protect people’s data rights. However, the act has some loopholes that result in such data breaches being underreported, in comparison with the EU’s General Data Protection Regulation (GDPR). PDPA Section 20(1) requires a data fiduciary to notify the Authority when a breach risks ‘significant damage’ to the data subject. PDPA does not clarify the term significant that can be exploited to silence a data breach. GDPR gives controllers 72 hours to notify regulators. Section 20(1) sets no such deadline. 

GDPR suggests sending notification to affected individuals when the risk is high. Section 20(1) only requires notifying the Authority, not the citizen whose data is exposed. This is a likely reason such breaches are mostly known via activists, independent security researchers, or journalists, without official disclosures keeping citizens in the dark. NTMC and the EC should implement mandatory audit logging and alert systems on any bulk download or unusual user activities. They should monitor and conduct regular audits on staff access logs.

For the API (Application Programming Interface) layer, the same accountability applies. EC should enforce strict security compliance requirements for their 174 API consumers. This includes regular activity reporting and resource-consumption monitoring. Non-compliant parties should face a graduated response. This may start with warnings and remediation deadlines, imposing fines, and reserving service suspension as a last resort. Abrupt cutoffs for critical services like health verification or banking may cause public harm. APIs should transfer minimum necessary data, enforce deletion schedules, and undergo regular independent audits. 

Technical product owners at government-facing engineering firms must ensure minimum security testing like OWASP (Open Worldwide Application Security Project) guidelines before any project goes live. Quality assurance personnel should be trained to at least an intermediate level of hands-on security testing. Automated checks can be implemented to detect misconfigurations, such as debug mode left on, before every deployment. Independent application and network penetration testing should be conducted regularly.

BTRC should bring telecom agents and stationery shops under proper monitoring and a formal licensing procedure that holds these entities accountable for data breach incidents. A public, verified registry of domains authorised to operate government-linked services, regular monitoring of look-alike domains and government DNS records would minimise incidents like fake e-Apostille sites. 

The government should also run public awareness campaigns encouraging people to verify any agent, shop, or website before handing over any confidential data.

PDPA 2026 should include a specific notification timeline for informing both the Authority and affected persons about a breach. The Act should include an explicit provision for notifying affected citizens directly, and a clear legal definition of ‘damage.’

These measures require no new technology or foreign expertise. The country’s own security professionals with hands-on expertise already know the fixes. 

The article was first published on September 13. 2026 on TIMES of Bangladesh

Wednesday, August 26, 2026

Debian turns 33: The universal OS hiding in plain sight






On 16 August 2026, the Debian Project turned 33 years old. Founded in 1993 by Purdue University student Ian Murdock, Debian has grown from a modest Linux-based operating system into one of the most influential free-software projects in the computing world. Its influence, however, is often invisible: People regularly use software derived from Debian without ever installing – or even hearing of – Debian itself.



Debian describes itself as “The Universal Operating System”, a free OS built entirely from free software and maintained by a global community of contributors. Its breadth is evident in the current stable release, Debian 13, codenamed “Trixie,” on which this article was written. Released on 9 August 2025 after more than two years of development, it contains 69,830 packages, including over 14,100 new ones. Another 44,326 packages were updated, while more than 8,840 obsolete packages were removed. Debian 13’s archive represents approximately 403GB of data and 1.46 billion lines of code, according to the official Debian Project website. The release also supports a wide range of CPU architectures, including x86-64, ARM, PowerPC, IBM System z, and – for the first time as an official Debian architecture – 64-bit RISC-V.



That combination is what makes the word “universal” meaningful. Debian can be used on desktops and laptops, but the same project also produces images for cloud platforms and systems ranging from development servers to database, web, and storage servers, as well as everyday users.



Philosophy and ecosystem

Debian’s philosophy is as important as its technical reach. Its Social Contract commits the project to remaining open source and supporting the free-software community. The Debian Free Software Guidelines provide the principles used to determine whether software qualifies as free. This does not mean Debian software comes without legal conditions; software is distributed under licences that grant users specific freedoms, subject to those licences. This philosophy has allowed Debian to remain a community project rather than a conventional commercial operating system.



One of Debian’s most significant contributions is its package-management ecosystem. For newcomers, Debian’s repositories may resemble an app store, but APT – the Advanced Package Tool – is more than a catalogue. It retrieves packages from configured repositories and manages installation, upgrades, and dependencies with remarkable efficiency. APT has helped Debian’s influence extend far beyond computers running Debian itself. Ubuntu is Debian-derived; Kali Linux and Raspberry Pi OS are also built on Debian. Debian’s own documentation notes that the project has spawned over 420 derivatives, with more than 120 described as active at the time of writing.



Measuring the number of Debian users is surprisingly difficult. Debian itself acknowledges that no precise user statistics are available, as the project does not require registration. Instead of seeking a mythical global user count, we can look at its presence in web infrastructure. W3Techs reported Linux on 62.7 per cent of websites whose operating system it could identify. Debian itself was detected on 3.7 per cent of all websites whose operating system was known. The data also showed Debian on 5.5 per cent of the top one million websites, compared with 4.5 per cent of the top 100,000 and 3.9 per cent of the top 10,000 in its July 2026 ranking breakdown. These figures do not prove that Debian runs the internet; they show something more useful: Debian has a measurable and significant presence in the infrastructure behind the web.



In August 1993, Ian Murdock announced a new Linux distribution while an undergraduate at Purdue University. He wanted it to be developed openly, in the spirit of Linux and GNU, rather than by a single individual or company. Debian was officially founded on 16 August 1993. The name Debian came from the names of Murdock and his then-wife, Debra Lynn.



Murdock’s January 1994 Debian Manifesto outlined his ambition for a distribution developed openly by a community. The project quickly became more organised. Its early package-management system evolved into dpkg, while responsibility for individual packages increasingly shifted to different developers. By the Debian 0.93 release in 1995, many developers were maintaining their own packages. This evolution matters because Debian’s longevity was never simply about writing an operating system;; it was also about creating a system for thousands of people to build and maintain software together. Murdock passed away on 28 December 2015. Debian dedicated its Debian 9 “Stretch” release to his memory.



Debian 13 offers an interesting answer to why a project started in 1993 still matters in 2026. It supports both older hardware and modern technologies such as RISC-V, while retaining Debian’s traditional emphasis on stability and broad hardware support. The project also promises five years of support for Debian 13 through the combined efforts of its Security and Long-Term Support teams.



What Debian means to Bangladeshi users

While writing this article, I spoke with a student and a software developer about their experiences with Debian and its best-known descendant. Sajjad Kabir Joy, a student at Shahjalal University of Science and Technology who has been using Debian for over 12 years, started with Ubuntu before moving to Debian, which he calls “the real thing.” What keeps him there is Debian’s flexibility. “It can be a beginner’s desktop or a highly specialised system-built package by package from source,” he said. Compared with Windows, he points to Debian’s stable release cycle and its commitment to software freedom as reasons for his loyalty.


Senior Software Engineer at Penta Global Ltd Arafat Ahmed is a frontend specialist who uses Ubuntu, Debian’s best-known descendant. He says Ubuntu has taught him what happens behind his applications: How Node.js processes run, how network ports are managed, and how data moves through HTTP, WebSocket, and TCP connections. Arafat runs PostgreSQL, MongoDB, and Redis in Docker containers and uses Nginx to recreate production conditions locally. Tools such as curl, netstat, and lsof help him diagnose networking problems. For him, Ubuntu is not simply an operating system; it is part of how he learns and works.



As a working journalist, I also do independent OSINT and cybersecurity research. Much of my personal hardware is what most people would call outdated. A Raspberry Pi 2 server running Raspberry Pi OS (itself a Debian-based operating system) handles my task automation scripts and connects me to home from the office. I do heavier research and analysis on a sixth-generation Core i5 PC with 16GB of DDR4 RAM running Debian 13.



Even my home router, running OpenWrt (a lightweight Linux-based operating system, but not a Debian derivative), continued working long after its WAN port physically failed. I also use my ageing workstation for everyday tasks such as browsing the internet and watching films – and my 6.5-year-old son plays online games on it. For me, that is the real meaning of a “Universal Operating System.”


Debian has spent 33 years building an ecosystem far larger than its own brand. A student can install it on an old computer. A developer can work on Ubuntu without thinking about Debian. A Raspberry Pi can run a Debian-derived operating system. A web developer can encounter Debian somewhere beneath the server stack. A journalist can use it to turn ageing hardware into a research ecosystem. The most remarkable thing about Debian may therefore be that many people can use what Debian helped build without ever knowing its name.


Happy birthday, Debian.


Sunday, July 26, 2026

Your Old Computer Is Not Dead Yet: How Bangladesh users can save money and keep going

First time Published on The Daily Observer on June 26, 2026




For the past few years, two of the world’s biggest technology companies, Apple and Microsoft, are quietly moving to cut off support for millions of computers that still work perfectly well, especially for low to mid income people and those who really need not to run resource heavy AI tools locally. 



Microsoft has made its latest Windows 11 update incompatible with many older processors while Apple is preparing to drop all Intel-based Macs from its next major operating system, macOS 27. 

At the same time, both the companies have recently raised hardware prices significantly, Apple alone has added roughly Tk 50,000 or more to the cost of a new iMac.

For users in Bangladesh, where a mid-range laptop is worth two or three months’ salary, this creates an unavoidable problem. But it also presents a clear opportunity: a free, open-source operating system called Linux can give those same “obsolete” machines several more years of productive life- without spending a taka on new hardware.

 

Why Your Machine Is Not Actually Broken

The honest reason older computers feel slow is not the failing hardware. The truth is operating systems and helping software that have grown too resource hungry. 

Windows or macOS installed on a PC or laptop runs dozens of background programmes that consume RAM and processing power before even we open a browser. 

 

A lightweight version of Linux-based operating system, such as core Debian, Lubuntu, Bodhi Linux etc., uses less than 1 GB of memory when sitting idle. This is roughly one-third of what Windows 11 requires at rest. 

On a machine with 4 or 8 GB of RAM, a lightweight OS can give you comfortable daily use. 

 

What Linux Means for Bangladeshi Users

Linux is not a single product or an operating system. It is the core of a family of operating systems built and maintained by a global community of developers. 


It is entirely free, regularly updated, secure, and legal. Over 90 per cent of desktop malware is written to attack Windows or macOS. Switching to Linux means most of those threats simply cannot run on your machine.

For everyday tasks, writing documents, browsing the web, attending video calls, managing spreadsheets, Linux covers almost everything. 
LibreOffice, which comes pre-installed on most distributions, handles all standard Microsoft Office file formats. Google Chrome, Firefox, Zoom, and Telegram all run on Linux without any additional workarounds. 
In Bangladesh, a student, a small business owner, or a journalist with a tight budget will mostly get the benefit of a Linux-based distribution on their old machines. 

But they  will need some effort to study the official documents and tutorials online. However, installing, managing, and using Linux based distributions is not Rocket Science. 

 

How Long Can Your Device Realistically Last?

To be honest, it depends on the type of machine, but the numbers are encouraging. 

A desktop PC, the kind commonly found in Dhaka offices and residences, has no battery to degrade. Running a lightweight Linux distribution on an older desktop can realistically extend its working life by seven to ten years beyond what Windows would allow, into the 2030s, unless the power supply and motherboard remain physically sound.

Older laptops are a slightly different case. The main limiting factor is the battery. Once lithium-ion cells deteriorate beyond a certain point, the laptop effectively becomes a desktop that requires a constant power connection. 
However, these machines will outlast their chassis. A three-to-six year extension is a realistic and conservative projection for pre-2018 laptops running a lightweight Linux system.

Apple MacBooks from 2019 and 2020 require some intermediate tweakings though. 
A specialised setup through a project called T2 Linux, because Apple uses proprietary security hardware that standard Linux installers cannot read. 
The process might take an hour but, once complete, these machines, which are genuinely high-quality hardware, can run professional workloads for five to eight more years.

On AI: You Do Not Need to Run It Locally
One argument often made in favour of buying powerful new hardware is that artificial intelligence tools require significant processing capacity. But this is not true for most users.

Running a large AI model directly on your own computer demands substantial memory and a modern graphics chip. 
For the vast majority of Bangladeshi users, this is neither necessary nor cost-effective. 

Free tiers of cloud-based AI services such as Google Gemini, Meta AI, and Microsoft Copilot already handle the most common tasks like summarising documents, drafting text, translating content, answering questions. 

 

Where a paid subscription is genuinely useful, entry-level plans from the major providers currently cost between $10 and $20 per month. A small fraction of the cost of even a budget new laptop, and a fraction that covers access to far more capable models than any consumer machine could run locally.

So, keep the older machine, install a Linux-based lightweight distribution, and pay subscription if AI assistance is genuinely needed. For most of our works, free tiers are more than enough. 
That combination costs far less than a new device and delivers more AI capability than running them locally.

 

One Caution 

The only alternative that should be avoided is downloading cracked or pirated copies of Windows or macOS to bypass the new hardware requirements. 

These unofficial releases circulate widely and are a serious security liability. They receive no official security patches and are frequently bundled with malware by the people who distribute them. 

So, for your older machines, a Linux-based distribution is the safest, legal, and technically superior choice.

2,400 Crore Credentials Leaked: Why Bangladeshi users should take this seriously

First time published on The Daily Observer on June 20, 2026





Cybersecurity researchers worldwide discovered a database containing 24 billion or 2,400 crore login records that include usernames, email addresses, passwords, cookies, authentication tokens and login URLs.


As a conscious end user in Bangladesh, you cannot ignore this finding. A good number of us still use the same email address and password across multiple services, including Gmail, Facebook, online banking, mobile financial services, e-commerce platforms and government portals. 


If our credentials are found in the leaked dataset, which is not a surprise that this author himself found his email id in at least three breaches, cybercriminals can launch credential-stuffing attacks, in plain English they can use the same password to gain access to multiple accounts of the same target person.


In reality the risk is amplified by our purchasing power and digital habits. A significant number of Bangladeshi users still have to rely on older computers, unsupported and cracked versions of Windows (like 10, 8, and even still 7 and XP releases are also seen in abundance) and outdated Android smartphones due to our purchasing power and increasing price of quality electronic devices. These devices and installed operating systems often no longer receive security updates, making them easier targets for ‘infostealer malware’ a type of software developed by cybercriminals that steals saved email ids, passwords, along with browser cookies and authentication tokens to mimic the victim.

Another concern is that many users remain logged into the same Google, WhatsApp, Facebook and other accounts across multiple devices, including old smartphones, shared family computers and office PCs. If one of these devices is compromised or lost, attackers may gain access to active sessions without even needing the account password. This could allow criminals to read emails, impersonate users, steal personal data or bypass certain security checks.

 

The widespread use of shared computers in homes, cybercafés, educational institutions and small businesses also increases the risk. If users save passwords in browsers or fail to log out after using a shared device, sensitive accounts can become easy targets.

Cybersecurity experts from Cybernews believe the newly identified database is largely a compilation of credentials stolen over time through infostealer malware, that often target older devices and operating systems, rather than the result of a single company's data breach. However, that does not reduce the threat. Old credentials remain valuable because many people rarely change their passwords or continue using the same password across different services.


What can we do now? 
Let's not rush for new devices and trash the older ones. Here is a universal cyberguideline for Bangladeshi users. 

First, a user can check if her/his data is found in the leak going to this site that the researchers are offering a search option. 
Or, a user can check from Have I Been Pawned a well known site for checking stolen information.  

1. Change passwords for important accounts immediately

2. Enable multi-factor authentication (MFA) using your smart phone- Google and Microsoft Authenticator apps are the most popular and user friendly ones. 

3. Use a password manager like KeepAss or KeepAssDroid to create and maintain unique passwords safely.  

4. Regularly review the list of devices logged into their Google, Facebook, WhatsApp and other online accounts. Any unfamiliar or inactive device should be signed out immediately. Users should also install the latest security updates and replace unsupported operating systems whenever possible.

5. Instead of using cracked and outdated Windows operating systems, users can adopt Linux-based distributions like Debian or Bodhi. Linux-based distributions are optimised for older devices, and focused on user security. 
‘Linux is Hard,’ the myth has been defunct at least for a decade, to be precise from 2013-14 when it increasingly got popularity among the young generation. Moreover, some desktop environments are more user friendly and intuitive than Windows 10 or 11. 
With a little to moderate effort, a security conscious user can make her/his older hardware super fast and safe by installing a Linux distribution without any cost of buying a licence.  

6. However, using Linux based distros on smartphones are still for advanced users. But many companies in Bangladesh are offering budget smartphones with latest hardware and software for mid to low income people. By doing basic googling and consulting advanced users, one can buy a moderately secure smartphone for their daily use. 

 

How AI is reshaping global newsrooms: What Bangladesh journalists can do

First time published in The Daily Observer on June 23, 2026



Global mainstream media organizations like Associated Press, BBC, Wall Street Journal are increasingly integrating artificial intelligence into their daily workflows to increase productivity of journalists, optimize news production, automate repetitive tasks, and execute complex investigations.

However in Bangladesh, there is a significant gap in terms of institutional formalization and less focus on how we can use available free tools in newsrooms to increase our productivity.

In this article we will compare our local newsrooms with the global context. We also have some tips on how we can customize free AI tools until our newsrooms adopt their tailored AI models as per editorial policy. 

 

AI Use in Newsrooms at a glance
Rather than replacing human reporting and sub editing, some mainstream media deploy AI models to manage high-volume data analysis, generate automated copy, and refine content delivery.

Major publications like Bloomberg use proprietary large language models (LLMs) to analyze financial documents and perform sentiment analysis. Semafor uses an AI-powered feed called “Signals” to help journalists search through global news sources in multiple languages.

The Financial Times and the Wall Street Journal use AI models to predict trending topics to help journalists find gaps in their current coverage. 
The Associated Press utilizes natural language generation platforms to automatically ingest financial datasets and draft corporate earnings reports and minor-league sports articles. This enables the agency to scale coverage without draining manual reporter resources.

BBC uses internal generative AI models to reformat stories from the Local Democracy Reporting Service (LDRS) into the standard BBC house style, to generate at a glance summaries, and language translation. 

AI tools, in global media, act as smart assistants that handle, with human intervention, time-consuming tasks, allowing reporters to focus on deeper journalism, for example transcription, translation, drafting and primary editing of a news article, and multimedia creation in rush hours. 

The Digital Divide: AI Integration in Global and Bangladeshi Media
Leading international media outlets have enough budget and RnD teams to deploy custom-built and proprietary large language models in their houses. In Bangladesh, we are still in the exploratory phase of adoption.

In global media, AI adoption is guided by well-defined institutional frameworks, extensive tech budgets, and specialized software engineering teams embedded inside the newsroom. 

Conversely, in Bangladesh, AI adoption is primarily driven by individual usages under tight deadlines rather than a well structured institutional strategy. Bangladeshi journalists and writers extensively use general-purpose tools like Grammarly, Google Translate, and ChatGPT for basic proofreading, text rephrasing,creating news from press releases, and translation from Bangla to English and vice-versa.

Industry leaders at a media dialogue hosted at The Daily Star Centre said that while AI tools are highly affordable, Bangladeshi newsrooms suffer from severe ethical and operational gaps. Most local organizations operate without formal, written AI editorial policies or self-regulating mechanisms.

Editors at New Age newspaper have also noted a growing sense of limitation. They predict that news managers train staff to use generative tools like ChatGPT, however, the output frequently lacks the localized emotion, cultural nuance, and deep historical context required for impactful domestic journalism.

Cautions, Bias, and Human Intervention
The rapid adaptation of AI in journalism also brings some risks worth evaluating. 

Misinformation and Deepfakes: It is nowadays very easy to engineer highly credible fake contents, images, and videos. Without rigorous verification and fact checking, newsrooms risk unintentional risk of spreading state-sponsored propaganda, corporate manipulation, and AI-induced hallucinated facts,which can lead to a post-truth era.

Training Data Bias: Standard commercial AI models are trained on massive, and mostly western-centric datasets that carry inherent linguistic, cultural, and political biases. 
These models frequently misinterpret the historical and socio-political nuances of countries in the Global South, the Middle East, to name a few, leading to produce biased information.

These are only two of many critical problems we face in the newsroom while using AI. 
To counter these, human oversight is mandatory at every stage of the journalistic pipeline. We must prioritize accuracy over speed, quality over quantity, keeping in mind that standard tools like Google Translate, Grammarly, or ChatGPT always require strict human verification before publication.

What can we do now? 
AI, Large Language Models, and AI agents- all these are utility tools like the internet, a keyboard, a typewriter machine, or a smart assistant who can bring the best output under restricted human intervention. 

Here is an example how to chain existing AI solutions in our article writing pipeline. 
Without generating a generic story like ‘write an article on AI use in newsrooms’ and sending it to the subbing desk, we can do the following-
  
Firstly, we can use Google search or Google AI mode to collect data on how AI is used in the mainstream media newsrooms across the world and Bangladesh. This is the research and development phase to collect necessary information. 

Then we will select some five to ten original, authentic, and informative pieces.

Now, we feed NotebookLM with the sources, text, or PDFs. NotebookLM is a Google product used for creating a knowledge base from strictly defined sources so that AI makes few mistakes and does not add hallucinated data.     

Then we will filter out our necessary data (obviously cross check any critical information), and assign it the task to prepare a draft on the topic. 

Secondly, we will go to Gemini, and create an ‘article writer gem,’ a gem is your own custom built AI assistant who is specialised in a specific task like report writing or sub editing. 

Based on the information collected from NotebookLM, we will define the article writer gem how it will structure the final draft. 

After getting the final draft, we will edit and polish the article and send it to the subbing desk for further polishing. 

 

Why Bangladesh newsrooms need an OSINT habit, not just a fact-check desk

First time published on the Daily Observer on July 2, 2026     



Every major newsroom around the globe is now in the verification business to fight misinformation and reconstructing scenes to verify information.

Mainstream media like BBC built a 60-journalist unit named ‘BBC Verify’ in 2023 solely to fact-check video, counter disinformation and show audiences its evidence trail.

The New York Times is running a dedicated team named ‘Visual Investigations’ since 2017, combining digital forensics and traditional reporting. In plain English the team reconstructs crime scenes and conflict zones from cellphone footage and satellite images to verify data and information published in news.

CNN, The Washington Post and Reuters have followed with their own forensics and open-source units. This is not a buzzword, trend, or luxury, rather this is the need for an era where data passes in almost the speed of light.

Information now reaches the public before anyone in a newsroom has checked it, and audiences are increasingly unable, and do not have much time to verify, to tell real footage from fabricated footage on their own.

The verification practice is called Open-Source Intelligence, in short OSINT.

In plain English, OSINT is the practice of gathering and analysing information that is already publicly available on social media posts, satellite images, government records, leaked documents, YouTube videos, even shadows in a photograph. Then piecing them into a verified, defensible account of what actually happened.

It is not black magic, not hacking. It is not ‘espionage’. It is closer to old-fashioned shoe-leather reporting, except the “street” being walked is the internet, and the “eyewitnesses” are the millions of ordinary people filming events on their phones.

For Bangladeshi media, adopting an OSINT mindset is no longer optional and waste of time. It is becoming a rudimentary condition for publishing accurate and authentic news. This practice is equally applied for investigative reporters, as well as for us, the sub-editors who decide, often in minutes, whether a viral photo or video is safe to run under the paper’s name or portal.

A Short History: From wartime filing cabinets to Bellingcat

Interestingly, OSINT is older than the internet. During the WWII, the American Office of Strategic Services, the forerunner of CIA, ran a research branch that analyzed foreign newspapers, radio broadcasts, and even obituaries for collecting information about enemy capabilities.

The practice was intelligence gathering from publicly accessible sources. After the war, the discipline involved into a bureaucratic practice of librarians and archivists.

In 2009, young Iranians used social media to broadcast their protests to the world in near real time during Iran’s Green Revolution.

The outside observers realised that citizen-generated footages can be verified, geolocated, and used as a primary source of information.

The next major leap came from the British blogger Eliot Higgins in 2012. At that time Higgins was an unemployed office administrator. He began analysing YouTube videos of the Syrian civil war from his living room, under the pseudonym “Brown Moses.”

By cross-referencing weapons visible in the footage with satellite imagery and geography, he proved that the Syrian regime was using cluster munitions and chemical weapons, conclusions that mainstream reporters on the ground could not have reached alone.

In 2014, Higgins formalised this work into Bellingcat, a Netherlands-based collective of professional and volunteer investigators.

Bellingcat’s came in lime light within months of its founding, when it used open-source video, satellite images and social media posts to establish that a Russian Buk missile system had shot down Malaysia Airlines Flight MH17 over Ukraine that was later confirmed by an official international investigation.

Bellingcat went on to unmask the Russian agents behind the poisoning of Sergei Skripal and Alexei Navalny, using only publicly available flight records, leaked databases, and passport photos.

Bellingcat’s every step of its method was published. So, readers and rival investigators could check the workflow of the investigations. This transparency is now considered close to a scientific standard in newsrooms, and it directly inspired the large OSINT desks that BBC, the New York Times, Washington Post and others operate today.

How Mainstream Media Actually Uses OSINT

The 60-person BBC Verify brings scattered data analysis, disinformation monitoring, and fact-checking into an organized structured form. The team geolocates footages, analyses satellite imagery, checks metadata (the hidden data embedded in a photo or video file, such as when and where it was created) and cross-checks audio for signs of AI voice-cloning.

The team publishes its evidences alongside stories showing the audience how it knows something, not just what it knows.

The New York Times’ Visual Investigations team, combines traditional reporting with “open source reporting”. It geolocates a video to an exact street corner using landmarks and shadows, cross-referencing “before” and “after” satellite images to establish when a strike happened, and building minute-by-minute timelines from hundreds of scattered video clips.

In 2022, they reconstructed the killings of civilians in Bucha, Ukraine, using Google Street View imagery and metadata analysis to directly contradict Russian government claims about the timing of the killings.

The Washington Post’s Visual Forensics unit and Reuters run comparable operations, and both have collaborated with Bellingcat on cross-border investigations. CNN now runs a formal OSINT training academy for its own journalists, teaching reverse image search (tracing where else a photo has appeared online, and when), geolocation and open-source toolkit-building as baseline skills.

OSINT has two faces. It lets a desk-bound investigator do work that once required physical presence and acts as a filter against publishing fabricated content under the outlet’s name, the risk that has grown sharply with generative AI.

Why This Matters for Bangladesh

The information environment in Bangladesh has been under sustained strain since the July 2024 uprising, and it intensified through the campaign for the 13th parliamentary election held on February 12, 2026.

Rumor Scanner alone verified 310 separate misinformation cases in July 2025, rising to 320 in August and 329 in September, with well over half of all cases in each month tied to political content. Across the country’s fact-checking organisations combined, more than 5,700 fact-check reports were published in 2025 alone, roughly 30 percent more than the year before. Two out of every three of those fact-checks involved political content, and roughly one in ten used artificial intelligence to fabricate the deceptive material in the first place.

The period immediately around the February 2026 election was especially intense. On the single day before voting, three fact-checking organisations, Rumor Scanner, Dismislab and FactWatch, jointly documented 49 unique pieces of election disinformation in under 20 hours, including fabricated “news photocards” mimicking the visual style of established outlets falsely claiming candidates had withdrawn or that results were already decided.

For Bangladeshi editorial desks, the lesson is direct, the country’s evolving political and social climate means that speed, virality and partisanship are now baked into the information environment, and a newsroom that cannot independently verify what is landing in its inbox and its social feeds is at permanent risk of amplifying a fabrication, deliberately planted or not.

The Problem for Reporters and Sub Editors: Old Footage, Deepfakes and Rumour

In Bangladesh, fact checkers documented three recurring and common patterns that every reporter and sub-editor should be able to recognise on sight, even without sophisticated tools. These are the most rudimentary basics of utilizing OSINT in journalism.

Zombie Contents: In plain English, these are old footages recycled as breaking news. This is the single most common tactic documented around the 2026 election.

For example, a viral clip showed an election-day clash in Gopalganj. Fact checkers traced it to an August 2024 rally in Narayanganj.

The defence here is reverse image search. Taking a screenshot from the video or the photo itself and running it through a search engine’s image tools (Google Images, Bing, or specialist tools like TinEye) to see where and when it first appeared online. If the same clip surfaces in a report from a year earlier, it is not a breaking news.

Deepfakes:  Deepfakes are AI generated image, video, or audio contents.  Analysis of the July to September 2025 period found 71 AI-generated posts in circulation, the large majority of them videos, 57, and the rest were 14 images.

A fabricated image can be referred that shows students demanding the return of former prime minister Sheikh Hasina circulated in August 2025. It was entirely synthetic. The basics to identify a deepfake content is to look for unnatural blinking, mismatched lighting or shadows, blurred edges where a face meets hair or background, and audio that doesn’t quite sync with lip movement.

However, AI tools are improving quickly and becoming more natural looking. So, cross-checking against a second, independent source matters more than any single visual clue.

Fabricated “photocards” and impersonated outlets: Photocards are now a trend in social media to attract more user interactions to posts. During the national electionsin 2026, the creation of fake graphics designed to look exactly like a real outlet’s branded news card, like mimicking mainstream Bangladeshi media, was seen to fabricate instant credibility.  Herer the defence is procedural, not technical. Any screenshot of “news” from another outlet should be verified directly on that outlet’s own website or verified social account before republishing or citing it.

Fact-Checkers Exist, So Why Do Newsrooms Still Need OSINT?

Bangladesh already has an established and functioning fact-checking ecosystem. Rumor Scanner, Dismislab, FactWatch, BoomBD, and AFP Fact Check Bangladesh to name a few. So, it is logical to ask why every reporter and sub-editor needs to acquire OSINT skills when specialist teams already do this job.

The answer is a division-of-labour, not a duplication of efforts.

Fact-checkers, by design, work after a claim has already gone viral. Their reports are fast and rigorous and are inherently reactive. Rumor Scanner’s fastest turnaround on election night was still measured in hours, not the seconds it takes for a sub-editor to decide whether to publish a breaking photograph.

A newsroom’s own desk is the only line of defence before a news is printed or goes online. The moment a wire photo, a viral clip or a tip-off first lands in the newsroom, someone on deadline has to decide whether it will be published or not. A fact-checker debunking an outlet’s story the next morning is reputational damage that basic verification, done in-house, could have prevented in the first place.

Bangladesh’s fact-checking organisations are committed but they are a handful of small teams checking a national information ecosystem that produced over 5,700 flagged claims in a single year.

It is unrealistic that they check everything crossing every a newsroom’s desk in real time, nor should reporters expect them to. Basic-to-moderate OSINT literacy like reverse image search, checking metadata, confirming a claim against a primary or official source, knowing how to geolocate a photo is what allows a reporter or sub-editor to filter the truth.

In May 2026, panels of senior editors at Bangladesh’s own Journalism Conference in May 2026 identified that modern investigative journalism needs financial forensics, data analysis, cybersecurity awareness, digital verification, and source protection that many newsrooms still inadequately support.

A newsroom in Bangladesh is right now navigating a volatile political transition and a surge of AI-generated fake contents. The basic layer of in-house scepticism and OSINT skills is no longer a specialist skill, rather, a must for both reporters and sub-editors.


Thursday, June 18, 2026

The Enemy Within: Are substandard devices manipulating you?

An AI generated image


This piece was published in Daily Observer online on June  18, 2026.

In Bangladesh, like other parts around the globe, we use many substandard electronic consumer products like security cameras, smart watches, and Television boxes for their budget price.

These devices, colloquially termed as ‘non-brand’ or ‘copy’ products pose a greater security risk that is almost invisible for a regular consumer. This threat is technically known as secret digital backdoors that cyber criminals often use to hide their identities during committing crimes in the cyberspace.

A recent technical investigation conducted by a Wall Street Journal journalist reveals that these vulnerabilities, particularly prevalent in budget products, allow external actors to hijack a home’s internet connection. This turns ordinary and harmless households into unwitting accomplices in massive, coordinated cyberattacks.

The Anatomy of a Hijack

The technical operation, known as “device jacking,” or device hijacking in plain English, operates on a highly automated lifecycle. Many of these backdoors are pre-installed at the factory level- with manufacturers reportedly embed the malware.

Once connected to a home network with Wi-Fi or Ethernet, the compromised devices quietly dials out to intermediary servers operated by “Residential Proxy” companies. These entities monetize the infection by renting the hijacked IP addresses to paying customers. By routing traffic through a victim’s home network, malicious actors disguise their digital footprints, like our fingerprints, making their activities appear as legitimate residential web traffic. Telemetry data from compromised devices shows external controllers logging in every 10 to 30 minutes to maintain network dominance.

Red Flags on the Home Network

Tests conducted Comcast demonstrate immediate, high-risk network behavior after an infection occurs. Within minutes of activation, compromised devices trigger massive data surges. They quietly attempt to access private platforms like Gmail, Outlook, and Google Voice, while simultaneously routing outbound traffic to high-risk destinations, including cryptocurrency exchanges, gambling networks, and pornography portals.

 

Weaponizing the Smart Home

The proxy networks formed by these hijacked devices are weaponized for high-stakes criminal operations.

DDoS Attacks: By synchronizing millions of infected devices, even smart refrigerators, cyber criminals can flood and paralyze resilient global servers. These botnets, a network of rouge internet devices controlled by cyber criminals, are responsible for some of the largest web outages, known as Distributed Denial of Service, ever recorded.

Financial Fraud: Disguised residential connections provide the perfect mask for bank fraud, ad fraud, and automated ticket scalping, where evading Internet Protocol address or IP address bans are critical.

Nation-State Cyber Warfare: Government-backed hacking groups increasingly use consumer endpoints as proxies to launch international cyberattacks, effectively using civilian homes as shields to mask their origins.

 

What we can do now?

No, we need not to trash or disconnect our devices right now. Readers with some beginner to intermediate technical expertise can monitor their home network with pi-hole, atool that can block such types of malicious internet connections in a homenetwork environment. This is easy to setup and maintain.

However, the author of this article also developed an automated solution that combines the power of Artificial Intelligence to assess the home network traffic and regularly send emails if there are any suspicious network activities that is related to cryptocurrency exchanges, gambling networks, and pornography portals.

 

Source: Wall StreetJournal

Wednesday, April 29, 2026

Debouncing Mechanical Keyboard Chatter on Linux (X11)

Photo Created with Gemini

 

 

Use  xkbset utility to eliminate "key chatter"—a hardware defect where a single keypress registers multiple times—by implementing a software-level debounce filter.

 

1. Overview
Debouncing is a technique that ignores subsequent signals from the same key if they occur within a specific, very short time window (e.g. 50ms). This prevents the "double-tap" effect caused by aging or dirty mechanical switches.

2. Prerequisites

- System: Linux running an X11 session (most common on desktops like XFCE, Cinnamon, and older GNOME/KDE installs).

- Software Package: The xkbset package.

Install on Debian/Ubuntu/Mint: $ sudo apt install xkbset


3. Configuration Commands

A. Enable the Filter
 $ xkbset bouncekeys 50
* 
 bouncekeys: The feature name for debouncing in X11.

* 50: The delay in milliseconds. If 50ms is too aggressive (fast typing), lower it to 30. If you still see chatter, increase it to 70.

B. Disable the Timeout
By default, X11 disables accessibility features like "BounceKeys" after a period of inactivity. Use this command to force the setting to stay active:

$ xkbset exp =bouncekeys

 

 4. Verification
To ensure the settings were applied correctly, run:

$ xkbset q

Expected Output:

Bounce-Keys = On
Debounce Delay = 50

...

 5. Making the Fix Permanent
These commands reset after every logout or reboot. To automate this, add the commands to your Startup Applications (the method varies by desktop environment):

   1. Open your Startup Applications or Autostart menu.
   2. Add a new entry named "Keyboard Debounce" or your choice.
   3. In the command field, enter:
   sh -c "xkbset bo 50; xkbset exp =bo"
   4. Save and restart. 

 6. Troubleshooting

* No effect? Ensure you are not on a Wayland session (run echo $XDG_SESSION_TYPE). Wayland does not support xkbset.
* Keys feel "heavy"? Your delay is likely too high. Reduce the value (e.g., $ xkbset bo 20) until the chatter stops but typing feels responsive.

 

Note Prepared by Gemini 

Friday, April 10, 2026

Socio-financial impact of data breach

This article was first published on New Age on April 09, 2026


THE largest supermarket chain Shwapno, which has more than four million registered consumers, has said that its customer database was breached towards the end of March and cybercriminals demanded $1.5 million, which comes to more than Tk 183 million. The chain shop made the disclosure after its consumer details — names, phone numbers and purchase history — did the rounds on social media. The management of Shwapno, a subsidiary of ACI Limited, worked with forensic experts and the Counter Terrorism and Transnational Crimes unit and took steps to secure its system.

The most dangerous aspect of such breaches remains the casual attitude of customers, many of whom may think it does not matter if names, phone numbers and shopping history do the rounds in the public domain. They are no simple pieces of information. Combined, they form a context-rich ‘target profile’ of people. The shopping history could indicate dietary habits, interests, income range, salary in time, household size, marital status, health choices and even religious or cultural practices.


The purchase pattern analysis can also show the days of financial strain by looking into the switch to low-cost brands or less buying. Research shows that shopping data can also reveal pregnancy before women make the announcement and explore the status of mental health without access to any single medical or personal record. All this can make buyers susceptible to loan scams or emotional manipulation. The leaked information together makes a map that skilled social engineers, scammers or profilers can exploit with remarkable precision. Modern machine learning tools can make startlingly accurate predictions from purchase data alone.

People with declining purchase in the last week of a month, which suggests weak cash flow, might receive predatory loan app advertisements. And the victims would rarely realise the attack was designed specifically for them. They often think that they had bad luck with scammers. But they were, in fact, products of a data-driven targeting exercise. What is the most ominous part of the story is that behavioural profiles that once make it to the market do not expire. They remain there, getting updated with other leaked data and becoming increasingly accurate over time and exploited by criminals, big companies and social engineers.

Physical safety risks are, perhaps, the most overlooked aspect of this. The purchase history, which might show a woman shopping alone late in the evening with young children on specific days, can help criminals in kidnapping, stalking or even targeted home invasion. Criminal networks that buy leaked databases on the darknet not only include scammers, but they also include physical crime rings. Reputation and relationship damage is also possible. Some purchase history might show habits or preferences undisclosed to the family. Shopping patterns could be used to infer or fabricate narratives about private life for blackmail, coercion or harassment. Phishing is also possible by using real data to manufacture trust.

The Cambridge Analytica episode suggests that the most sophisticated exploitation of personal data happens in daylight. Facebook data were harvested and used to build psychological profiles of millions of voters in the United States and the United Kingdom. The profiles identified each person’s fears, aspirations, spending habits and emotional triggers. Targeted political advertisements were then crafted to reach each person with messages tailored to specific psychological profiles. This is a textbook example of behavioural manipulation. A company, which may not operate in Bangladesh, might use the purchase data of the four million people at hand to build detailed profiles of consumption and the way of life. The profiles could be sold to insurance companies, which can price premiums discriminatorily based on inferred health habits. They could be sold to political operatives who want to microtarget voters before elections. They could be sold to lending institutions, which can use the inferred incomes and spending patterns to approve or deny credit. None of the tasks requires ‘hacking.’ The data leaked are more than enough for such tasks.

Mobile financial services are embedded in daily life. Criminals equipped with profiles of likely victims can convincingly deceive them into sharing one-time passwords or personal identification numbers, and the victims can lose their entire mobile wallet balance in minutes. In Bangladesh, the recovery of such funds is extremely difficult. Criminals can also open accounts with the leaked profiles, apply for microloans on digital lending platforms or register for credit services. Given that many digital lending platforms rely primarily on mobile number verification, the risk is real. Victims may only discover the fraudulent accounts when lenders begin making calls for repayment.

Under the European Union’s General Data Protection Regulation, which is the global standard for data protection law, companies that fail to protect customer data can be fined up to €20 million or 4 per cent of their global annual turnover. The regulation also gives individuals the right to claim compensation for both material and non-material damage caused by a data breach. Non-material damage may include distress, anxiety and the loss of control over one’s personal information. In Bangladesh, there is no comprehensive data protection law. The Digital Security Act 2018 and its successor, the Cyber Security Act 2023, criminalise unauthorised data access but they do not offer a private right to claim damages. This is a significant gap that leaves four million Shwapno customers legally unprotected.

Whilst Shwapno faces investigation costs, legal fees for filing cases, fees for domestic and international forensic experts and the cost of rebuilding its cybersecurity architecture, its competitive advantage partly rests on its loyalty programme, which is the database that was breached. When consumers feel that enrolling in a loyalty programme exposes their personal data, they become reluctant to participate. A loyalty programme degradation directly reduces customer value and the company’s ability to run data-driven promotions. Reputational damage of this scale can also affect investor perception of its owning company.

The breach checker that circulated online after the Shwapno hack has already received more than 100,000 page views. Security analysts warn that using such third-party checkers may expose users to further data harvesting. Consumers can also change the passwords of mobile banking apps, e-commerce accounts or any platforms that use the leaked phone numbers as a verification tool. If the number is in the leaked database, attackers know which number to target for one-time password harvesting. Consumers might also be victims of SIM-swap attempts. They can request mobile operators for additional identity verification requirements before any SIM-related changes are processed. Consumers should also be critical about calls that reference personal details even if the caller claims to be from a legitimate company.

The Shwapno breach brings to the fore both a technical failure and a governance failure. On the technical side, companies that handle large volumes of customer data must implement layered security architecture. It may include multi-factor authentication on all administrative access points, end-to-end encryption of stored customer data, routine penetration testing by independent third parties and real-time intrusion detection systems that flag anomalous behaviour in a network immediately. The principle of data minimisation — collecting only what is necessary — should govern every system. If a loyalty programme does not operationally require purchase histories to be stored indefinitely, they should be deleted periodically.

On the governance side, companies need a clear incident response plan, rehearsed regularly, that includes a mandatory, time-bound customer notification protocol. In Shwapno’s case, the details of how the breach occurred have not been made public, but the reality of retail supply chains is that data flow through a large number of people and systems — point-of-sale terminals, third-party logistics partners, marketing agencies, app developers and more. Every person in the chain who has access to customer data is a potential point of breach. Training must, therefore, be continuous, role-specific and treated as a business-critical function rather than an annual compliance check.

The government must put in place a comprehensive personal data protection law modelled on standard practices such as the principles of the European Union’s regulations, but tailored to Bangladesh’s context. Consumers should at least have the right to know what personal data companies hold, mandatory breach notification within a defined time frame, the right to seek compensation for data negligence, mandatory data protection impact assessments before the launch of digital platforms and independent oversight by regulators with genuine investigative and penalising powers.

Bangladesh has already experienced multiple large-scale data exposures — the national identification registry database, birth registry records and now the loyalty database of a private retailer. Data are a responsibility and they are exchanged in trust. Bangladesh, therefore, needs laws, institutions, corporate practices and public awareness to protect personal data. The Shwapno breach is a wake-up call.

      Ishtiaque Foysol is a freelance security researcher and trainer at Decodes Lab Ltd.


Saturday, September 6, 2025

Installing Kali Linux the Easy Way: 5 Minutes instant Home Security Lab

 Introduction

Ever felt the excitement to learn a new penetration testing tool, only to be stopped by the daunting, time-consuming process of setting up a Kali Linux virtual machine? The downloads, the manual ISO installation, the partitioning—it can feel like a hurdle before the real learning even begins.

What if you could bypass all that and have a fully-configured, professional-grade hacking lab running on your machine in the time it takes to brew a coffee?

That's the exact experience the Kali Linux team had in mind when they created their pre-built virtual machine images. These aren't just installation discs; they are complete, ready-to-boot systems packaged for a near-instantaneous setup.

In this step-by-step guide, I’ll show you how to leverage these official images to install Kali Linux on VirtualBox like an instant noodles pack. While I'm demonstrating this on my daily driver (Debian 12), the process is virtually identical for Windows and macOS hosts. Let's turn that installation grind into a single click and get you to the pentest environment faster.


Prerequisites: What You’ll Need

1.  Oracle VM VirtualBox: This is the free, powerful virtualization software we'll use to run Kali. We'll download it in Step 1.

2.  The Kali VirtualBox Image: The pre-configured "virtual appliance" from Kali's official website.

3.  Approximately 15 GB of Free Disk Space: The downloaded image is compressed; you'll need room for the extracted files, to be precise, the virtual disk.

4.  A Curious Mind: That's us!

The "One-Click" Installation Steps


Step 1: Install VirtualBox

First, we need the virtual machine "player." Head to the official Oracle VM VirtualBox Downloads page.




Step 2: Download the Kali Linux VirtualBox Image

Never download Kali from anywhere but the official source! Go to the kali.org Get Kali page  and look for the "Virtual Machines" section.

1.   Click the VirtualBox" tab.
2.   Download the 64-Bit image via the direct link or torrent. This is a large (.7z or .zip) file, so grab a coffee while it downloads.



Step 3: Extract the Downloaded Archive

Once the download is complete, locate the file. You'll need to extract it.

1.   On Windows, you can use 7-Zip or WinRAR.
2.   On Linux/macOS, right-click and extract or use $ 7z x command in the terminal.
3.   This will create a new folder containing the Kali VM files.

Step 4: The Magic Files - .vbox and .vdi



Inside the extracted folder, you'll find two key files:
1.  Kali-Linux-2025.x-vbox-amd64.vdi: This is the Virtual Disk Image. Think of it as the entire hard drive of the Kali Linux machine—the operating system, tools, and all files are stored here.
2.   Kali-Linux-2025.x-vbox-amd64.vbox: This is a small configuration file. It tells VirtualBox exactly how to set up the virtual machine: how much RAM to use, how many CPU cores to assign, and, most importantly, where to find the .vdi hard drive file.

This separation is what makes this method so easy. Kali has already done all the hard configuration work for you.

Step 5: Import the Machine into VirtualBox

Now for the "one-click" part!
1.   Simply double-click the .vbox file or open it with Open With option like the screenshot.
2.   VirtualBox will automatically open and import the machine with all its pre-defined settings. You'll see a new machine named "Kali-Linux-2025..." appear in your VirtualBox Manager list.



That's it! The installation is complete. You've just imported a fully installed operating system.

Step 6: Power On and Login

1.   Select your new Kali VM from the list and click the big Start arrow.
2.   The machine will boot up directly to a login screen.
3.   Log in with the default credentials:
    *   Username: kali
    *   Password: kali



⚠️ Security Note: The first thing you should do after logging in is open a terminal and change the default password using the command `passwd`. This is crucial, especially if this VM will ever be connected to a network.

Congratulations! You now have a fully functional Kali Linux machine. Enjoy your hassle-free environment!

Bonus Tips and Troubleshooting



Fixing the "Kernel Driver Not Installed" Error (Linux Hosts)

If you're on Linux and see an error like “kernel driver not installed (rc=-1908)” when starting VirtualBox, don't panic! This is common and means your system needs the right components to build VirtualBox's kernel modules.

The Fix
1.  Open a terminal on your host machine (NOT the Kali VM).
2.  Update your package list and install the essential build tools and correct kernel headers:
    $ sudo apt update && sudo apt install build-essential dkms linux-headers-$(uname -r)

3.  Once that finishes, reconfigure VirtualBox to build the modules:
    $ sudo /sbin/vboxconfig

4.  After it completes successfully, you can start your Kali VM without any issues.



Why and How to Use Bridged Networking


By default, your Kali VM is behind NAT or Network Address Translation. It can access the internet, but it's hidden from your local network. This is safe but limiting option for your offensive attempts.

For many security tasks like phishing simulations, network scanning, or testing device vulnerabilities, you will need your Kali machine to appear as a real device on your local network, just like your laptop or phone. This is where Bridged Networking comes in the play.

How To enable Bridged Networking

1.  Make sure your Kali VM is fully shut down(not saved or paused).
2.  Select the VM in VirtualBox Manager and click Settings.
3.  Go to Network > Adapter 1.
4.  Ensure Enable Network Adapter is checked.
5.  Change Attached to from "NAT" to "Bridged Adapter". VirtualBox will usually auto-detect your correct network interface (e.g., wlan0 for Wi-Fi, enpX for Ethernet).
6.  Click OK.



When you boot Kali now, your router will assign it its own IP address on your network, making it visible to other devices. Use this power responsibly and only on networks you own or have permission to test!

Note: I've used Deepseek to elaborate and organize this piece of article

Friday, April 18, 2025

Build an AI-Powered DNS Analyzer

An AI-generated image


Note: If you know the product and want to go to the direct step by step setup in your home environment, pleas follow my medium articles A Complete Guide to Setup Pi-hole_AI_Analyzer: Part 1 and A Complete Guide to Setup Pi-hole_AI_Analyzer: Part 2


   


Context 

Due to some geeky security interest I needed a solution to capture and analyze the web traffic of the devices in my home. 

I installed Pi-Hole on an old Raspberry Pi 2 and configured it as a local DNS server to be used by my router. So, every internet connection request by the devices in my local network are logged into this small rpi2 and I can analyze local network traffic with the convenient web user interface of Pi-Hole. 

The process of analyzing logs for a basic network overview is tiresome, especially when I’m just looking for a summary of my local network internet traffic for any anomaly e.g. adware activities and pornography consumption 

Planning

I wanted to automate the process local internet traffic summarization the following way

- Collect network traffic after an X-hour interval

- Filter out unique queries as there might be multiple logs for the same DNS query

- Send the DNS queries to Gemini for a summary 

- Send a notification email to me 


Setup  



- Install Pi-Hole on rpi2

- Assign the rpi2 a static IP address so it has a unique identity as a DNS server in the local network

- Confiture the router to use the rpi2 IP address as its primary DNS server

- Configure the Pi-hole AI Analyzer in a cron job into the rpi2 to do an analysis cycle after X hours.

The analysis cycle is Collecting DNS query from Pi-Hole API endpoint → Sanitizing the Queries → Send it to Gemini for summarization → Send an email to me 


Development 

The implementation is pretty simple that a beginner to intermediate level enthusiast can easily code in Python and deploy the total system in 7days. So, I used Google’s AI studio to generate code. Once done, I reviewed  the code and deployed it into my local rpi2. 


Testing and Findings

The project is for personal use and in the PoC phase. So far it is working fine for the past few weeks without any system crash or major mistakes. 

The language model reads the urls only and try to assume any inconsistent network traffic. So, it misses some dns that can be understood by human analyzers, for example, a content delivery network dns record of a little known adult content website. 


To Dos 

-  Checking dns records against known blacklists, URLhaus and Virustotal before directly sending it to the LLM entity for summarization 

- Put time interval in getting Pi-hole DNS logs

Repository

Pi-hole_AI_Analyzer

 

An analysis of data breach epidemic in Bangladesh

Two news stories have surfaced in the media that NID information with biometric data is being sold on the internet black market, and call hi...