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MISP for Beginners: Sharing Threat Intelligence the Right Way

Hello, aspiring ethical hackers. In our previous blogpost, you learnt in detail about Threat Intelligence. In this article, you will learn about Malware Information Sharing Platform (MISP), which plays an important role in Threat Intelligence. When beginners start learning cybersecurity, most of the focus is on tools that detect or analyze threats. These tools may be SIEMs, scanners or forensic utilities. However, modern security teams also rely heavily on threat intelligence which gives information about attackers, threat indicators and campaigns that helps them prepare before an incident happens.

This is where MISP comes in. It helps organizations collect, organize, share and use threat intelligence in a structured and collaborative way. For beginners, it provides a practical introduction to how intelligence-driven security actually works.

What Is MISP?

MISP (Malware Information Sharing Platform) is an open-source threat intelligence platform designed to store, share and correlate indicators of compromise (IOCs) and related contextual information. It is developed and maintained by the MISP Project and is widely used by:

  • Security operations centers (SOCs)
  • Incident response teams
  • CERTs and CSIRTs
  • Threat intelligence teams

In simple terms, MISP answers this question:
“What do we know about threats, and how can we share that knowledge safely?”

Core Concepts of MISP

If you understand a few key concepts, it will make MISP much easier to grasp. These concepts help beginners understand how intelligence is structured, not just collected.

1. Events:

An event represents a security incident, campaign or investigation. It acts as a container for related information.

2. Attributes:

Attributes are individual pieces of intelligence, such as:

  • IP addresses
  • Domains
  • File hashes
  • URLs
  • Email addresses

Each attribute includes context, such as type, category and confidence.

3. Objects:

Objects group related attributes together. For example, a “file” object may include a filename, hash and size.

4. Tags:

Tags help classify events and attributes into:

  • Malware families
  • Threat actor names
  • Confidence levels
  • Traffic light protocol (TLP) markings

MISP in a SOC Workflow

A simplified SOC workflow involving MISP looks like this:

  1. An incident or suspicious activity is detected
  2. Indicators are identified during investigation
  3. Indicators are added to MISP as an event
  4. Other teams or organizations can reuse that intelligence
  5. Detection systems are updated using shared indicators

This workflow highlights an important lesson: intelligence becomes more valuable when it is shared responsibly.

MISP vs Other Security Tools

Beginners sometimes confuse MISP with SIEMs or detection platforms. But this is wrong. Here are the key differencces.

  • SIEMs focus on log collection and correlation
  • IDS/IPS tools detect suspicious network activity
  • EDR tools focus on endpoint behavior
  • Whereas MISP focuses on organizing and sharing threat intelligence

MISP does not replace these tools. It enhances them by providing context and collective knowledge.

Common Use Cases of MISP

MISP is not a detection tool by itself. Instead, it supports many security workflows including:

  • Threat intelligence sharing between trusted organizations
  • Enriching alerts from SIEMs or IDS systems
  • Incident response investigations, adding context to indicators
  • Threat hunting, using known IOCs to search environments
  • Research and analysis, tracking campaigns over time

For beginners, this shows how intelligence feeds into real operational security. Common Use Cases of this are,

  • Storing IOCs from lab investigations
  • Tracking phishing indicators
  • Sharing indicators between blue-team exercises
  • Learning how threat campaigns evolve
  • Understanding confidence and data quality in intelligence

Challenges Beginners May Face

MISP introduces new concepts that can be challenging to beginners at first. These concepts are,

  • Understanding data quality and false positives
  • Learning when not to share sensitive information
  • Managing large numbers of indicators
  • Interpreting confidence and context correctly

These challenges are normal. Beginners should focus on quality over quantity.

Why Learning MISP is valuable?

MISP is widely used in:

  • SOC and blue-team environments
  • Threat intelligence sharing communities
  • CERT and national cyber defense teams
  • Research and analysis roles

For beginners, learning learning about this builds skills in:

  • Threat intelligence fundamentals
  • Collaboration and information sharing
  • Context-driven security decisions
  • Strategic thinking beyond alerts

Conclusion

Beginners often see security as a purely technical activity that involves running tools and responding to alerts. MISP introduces a broader perspective by showing that information sharing and context are just as important. Mastering Learning it helps beginners understand:

  • What threat intelligence really is (and what it is not)
  • How indicators are collected and enriched
  • How teams collaborate across organizations
  • How intelligence supports detection and response

Instead of working in isolation, MISP encourages a community-driven defense mindset. It teaches beginners a critical cybersecurity lesson: defense improves when knowledge is shared. Instead of reacting to threats alone, teams work together using structured intelligence to detect and prevent attacks earlier.

For beginners, MISP is less about mastering every feature and more about understanding how intelligence is collected, contextualized and responsibly shared. These skills form a strong foundation for careers in SOC operations, threat intelligence and incident response.

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Splunk for Beginners: Making Sense of Logs and Security Data

Hello, aspiring ethical hackers. In our previous blogpost, you learnt about Blue Teaming. In this article, you will learn about Splunk, a platform that plays a vital role in Blue Teaming. When you start learning cybersecurity, one of the first things you hear is: “Check the logs.” But what logs? Where are they stored? And how do you make sense of millions of events generated every day? This is where this platform comes in.

Splunk is a powerful platform that helps organizations collect, search, analyze and visualize machine data. For beginners, it serves as an excellent introduction to how real security teams monitor systems, investigate incidents and find suspicious activity.

What Is Splunk?

Splunk is a data analytics platform that specializes in machine-generated data, such as logs from servers, applications, firewalls, endpoints and cloud services. It is widely used by Security Operations Centers (SOCs), IT teams and incident responders.

It is commonly used for:

  • Log management
  • Security monitoring
  • Incident investigation
  • Operational troubleshooting

In simple terms, Splunk helps answer the question:
“What is happening across my systems right now and what happened in the past?”

How Splunk Works?

At a high level, it works in three main steps. They are,

1. Data Ingestion:

Splunk collects data from many sources, such as:

  • Operating system logs
  • Application logs
  • Network devices
  • Cloud services

This data is indexed so it can be searched quickly.

2. Searching and Analysis:

Once data is indexed, users can search it using the Splunk Search Processing Language (SPL). Beginners don’t need to master SPL immediately. Basic searches are often enough to get started.

3. Visualization and Alerts:

It also allows users to create:

  • Dashboards
  • Charts and graphs
  • Alerts based on conditions

These features help teams spot issues quickly and track trends over time.

Common Security Use Cases of Splunk

It is widely used in cybersecurity for tasks such as:

  • Log analysis – Reviewing authentication attempts, errors and access logs
  • Threat detection – Identifying suspicious behavior or anomalies
  • Incident investigation – Reconstructing timelines during security incidents
  • Compliance monitoring – Tracking access and configuration changes
  • SOC dashboards – Providing real-time visibility into security events

Many SOC analysts spend a large part of their day inside Splunk.

Splunk in a SOC Workflow

This platform is usually part of a larger security ecosystem. A simplified SOC workflow looks like this:

  1. Systems and applications generate logs
  2. Logs are sent to Splunk
  3. Alerts are created based on suspicious patterns
  4. Analysts investigate events in Splunk
  5. Findings are escalated or documented

It helps connect alerts to actual evidence, instead of treating them as isolated warnings.

Splunk Vs SIEM

Beginners often hear Splunk described as a SIEM (Security Information and Event Management) tool. While it can really act as a SIEM, its core strength is data analysis.

  • Traditional SIEMs often focus on predefined security rules
  • Splunk focuses on flexible searching and analysis

Why Splunk Matters for Beginners?

Beginners often focus on individual tools or attacks, but real-world security work is about visibility and context. Splunk teaches beginners how to:

  • Work with large volumes of log data
  • Identify patterns and anomalies
  • Investigate alerts using evidence
  • Think like a SOC analyst

Learning this early helps bridge the gap between theory and real operational security. Moreover, Splunk skills are in high demand across:

Even basic knowledge of this helps beginners understand how organizations monitor and investigate their environments. The skills you learn: log analysis, correlation and investigation transfer easily to other tools.

What Beginners Should Focus On First?

Splunk can feel overwhelming at first. To make learning simple, beginners should focus on a few fundamentals:

  • Understanding what logs are and why they matter
  • Learning basic search queries
  • Reading timestamps and event fields
  • Building simple dashboards
  • Following investigation workflows

You do not need to learn advanced SPL or automation on day one.

Challenges Beginners May Face

It’s normal to face some challenges when learning Splunk, such as:

  • Large volumes of data
  • Complex search syntax
  • Too many dashboards and features
  • Difficulty knowing what is “normal” behavior

These challenges improve with practice and exposure. Labs and sample datasets are especially helpful for beginners.

Conclusion

Splunk is not just a tool. It’s a way of thinking about data and security. For beginners, it provides a practical window into how real-world security teams detect problems, investigate incidents and make decisions based on evidence.

By learning this early, beginners gain confidence working with logs, understanding alerts and seeing the bigger picture of cybersecurity operations. As you progress, this tool becomes not just a platform you use, but a skill that supports almost every area of modern security work.

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TheHive for Beginners: Managing Security Incidents the Smart Way

Hello, aspiring ethical hackers. In our previous blogpost, you have learnt about Blue Teaming. In this article, you will learn about TheHive, a platform that helps manage security incidents the smart way. When learning cybersecurity, many beginners focus on tools that detect threats—alerts, logs and suspicious activity. But detection is only the beginning. Once an alert fires, security teams still need to track, investigate, collaborate and document what happens next. This is where TheHive becomes important.

TheHive is a security incident response platform designed to help teams manage investigations in an organized, repeatable and collaborative way. For beginners, it provides a structured introduction to how real-world security operations centers (SOCs) handle incidents.

What Is TheHive?

TheHive is an open-source Security Incident Response Platform (SIRP) used by SOCs and DFIR teams to manage security alerts and incidents. Instead of relying on spreadsheets, emails or chat messages, teams use TheHive to centralize investigations in one place.

TheHive was developed by TheHive Project and is widely adopted by blue teams because it focuses on workflow, collaboration and documentation, not just tools.

In simple terms, TheHive answers the question:
“How do we handle security incidents in an organized and consistent way?”

Core Concepts of TheHive

If you want to learn about TheHive, you should begin with understanding a few key concepts which make it much easier to learn.

Alerts:

Alerts are raw security signals coming from other tools, such as SIEMs, EDR platforms or scripts. Alerts may indicate suspicious activity, but they are not yet confirmed incidents.

Cases:

A case is created when an alert is worth investigating. A case represents an incident under investigation and contains all related information, tasks and evidence.

Tasks:

Tasks break an investigation into actionable steps, such as:

  • Review logs
  • Analyzing an IP address
  • Collect endpoint data
  • Write a summary

Observables:

Observables are pieces of data related to an incident, such as:

  • IP addresses
  • Domains
  • File hashes
  • Email addresses

How TheHive Fits into a SOC Workflow

TheHive is not a detection tool. It sits after detection in the security workflow. A simplified SOC workflow looks like this:

  1. A security tool generates an alert
  2. The alert is sent to TheHive
  3. An analyst reviews the alert
  4. A case is created if investigation is needed
  5. Tasks are assigned and completed
  6. Findings are documented and closed

For beginners, this provides a clear picture of how alerts turn into real investigations.

Collaboration and Case Management

One of TheHive’s biggest strengths is its collaboration. Using TheHive, multiple analysts can:

  • Work on the same case
  • Add notes and evidence
  • Assign tasks to each other
  • Track progress in real time

This reflects how real SOCs operate.

TheHive Compared to Other Security Tools

Beginners sometimes confuse TheHive with tools like SIEMs or forensic frameworks. However, there is lot of difference between them.

  • SIEMs focus on collecting and correlating logs
  • EDR tools focus on endpoint detection and response
  • Forensic tools focus on deep technical analysis
  • Whereas TheHive focuses on managing the investigation process

TheHive does not replace all the above other tools but it connects them together through workflow.

Why Beginners Should Learn TheHive?

Beginners often learn tools like scanners, SIEMs or forensic utilities, but struggle to understand how investigations are actually managed. TheHive fills this gap by teaching:

  • How alerts become investigations
  • How tasks are assigned and tracked
  • How evidence and notes are documented
  • How multiple people collaborate on the same incident

Learning TheHive helps beginners think like SOC analysts, not just tool operators.

Challenges Beginners May Face

Like any platform, TheHive has a learning curve. Beginners may find:

  • Case workflows unfamiliar at first
  • The number of features overwhelming
  • Integration concepts confusing

These challenges are normal. Beginners should focus on basic case creation, tasks and documentation before exploring automation or integrations.

Conclusion

TheHive teaches one of the most important cybersecurity lessons: handling incidents is as important as detecting them. For beginners, it provides a realistic view of how SOCs and DFIR teams organize investigations, collaborate and learn from incidents.

By learning TheHive early, beginners build strong foundations in incident response thinking—skills that remain valuable regardless of which tools or technologies they use in the future.

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Velociraptor for Beginners: A Tool for Endpoint Forensics

Hello, aspiring Cyber Forensic Investigators. In our previous blogpost, you have learnt about digital forensics in detail. In this article, you will learn about Velociraptor, a tool used in EndPoint Forensics.

As organizations grow and endpoints multiply, digital forensics and incident response (DFIR) teams need ways to investigate systems quickly, remotely and at scale. Traditional forensics tools work well for single machines, but they can struggle in large, distributed environments. This is where this tool comes in.

Velociraptor is a modern DFIR platform designed to help investigators collect evidence and hunt for threats across many endpoints at once. For beginners, it may look complex at first, but its core ideas are surprisingly approachable.

What Is Velociraptor?

It is an endpoint visibility and digital forensics platform that allows investigators to query systems, collect artifacts and respond to incidents in real time. It is commonly used by DFIR teams to perform investigations across Windows, Linux and macOS systems.

Originally developed by Rapid7, it is widely adopted in the security community because it focuses on live response and scalable forensics, rather than traditional disk-only analysis.

At its core, Velociraptor answers a simple question:
“What is happening on my endpoints right now and how can I safely collect evidence?”

How Velociraptor Works?

Velociraptor follows a client–server model in which,

  • Velociraptor clients run on endpoint devices (laptops, servers, workstations)
  • A Velociraptor server manages communication, queries and evidence collection

Investigators send queries or artifact requests from the server and selected endpoints respond with results. This allows evidence collection without interrupting users or shutting systems down.

What Are Artifacts in Velociraptor?

Artifacts are one of the most important concept of Velociraptor tool. An artifact is a predefined set of instructions that tells Velociraptor:

  • What data to collect
  • Where to collect it from
  • How to format the results

Examples of artifacts include:

  • Running processes
  • User logins
  • Browser history
  • Scheduled tasks
  • Autoruns and persistence mechanisms

Instead of writing scripts from scratch, beginners can use existing artifacts to collect common forensic evidence safely and consistently.

Common Use Cases of Velociraptor

Velociraptor is useful in many real-world scenarios. These include:

  • Incident response – Investigating compromised endpoints
  • Threat hunting – Searching for suspicious behavior across systems
  • Live forensics – Collecting volatile data without powering off machines
  • Enterprise investigations – Responding to alerts across hundreds or thousands of endpoints
  • Post-incident review – Understanding what happened and when

Many investigations involve no malware files at all, but instead focus on misuse of credentials, persistence mechanisms or unusual system behavior.

Velociraptor vs Traditional Forensics Tools

Now, let’s see the difference between Velociraptor and Traditional Forensics Tools.

Traditional Forensics Tools:

  • Focus on disk images
  • Often offline
  • Best for deep historical analysis

Velociraptor:

  • Focuses on live endpoints
  • Works remotely and at scale
  • Best for rapid investigation and response

Velociraptor does not replace traditional tools. It complements them.

A Simple Workflow For Beginners

A basic Velociraptor workflow might look like this:

  1. Identify endpoints of interest
  2. Select relevant artifacts
  3. Run queries from the server
  4. Collect and review results
  5. Export evidence for documentation
  6. Correlate findings with logs or disk analysis

Beginners should focus on understanding results, not just memorizing queries.

Why Learning Velociraptor is valuable

Velociraptor is increasingly used in:

  • Incident response teams
  • Blue team operations
  • Threat hunting programs
  • Enterprise DFIR environments

For beginners, learning Velociraptor builds skills in:

  • Endpoint visibility
  • Live response
  • Scalable investigations
  • Modern DFIR workflows

These skills are highly relevant in today’s cloud-connected, remote-work world.

Challenges Beginners Should Expect

Like any powerful tool, Velociraptor comes with learning challenges. These are,

  • Understanding artifacts and query logic
  • Managing large amounts of data
  • Avoiding unnecessary data collection
  • Interpreting results correctly

These challenges are normal. The goal is not perfection, but progressive understanding.

Conclusion

Velociraptor teaches you an important lesson: modern forensics is about asking the right questions at the right time. Instead of focusing only on disks and files, investigators focus on endpoints, behavior and artifacts. As threats continue to evolve, tools like Velociraptor are becoming essential parts of the modern forensic toolkit.

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Beginners guide to Memory forensics

Hello, aspiring Cyber Forensic Investigators. In our previous blogpost, you learnt in detail about digital forensics. In this article, you will learn about Memory Forensics. When most people think about digital forensics, they imagine hard drives, deleted files and disk images. While disk forensics is still important, many modern attacks leave their most valuable evidence somewhere else entirely—in system memory (RAM). This is where memory forensics comes in.

It focuses on analyzing volatile memory to understand what was happening on a system while it was running. For beginners, it can feel intimidating, but the core ideas are easier than they appear to be.

What Is Memory Forensics?

Memory forensics is the process of capturing and analyzing the contents of a system’s RAM to identify malicious activity, suspicious processes or any other unauthorized behavior. RAM contains data that never gets written to disk or only exists briefly, such as running processes, active network connections, encryption keys and injected code.

To put it simply, unlike disk forensics, which looks at what was stored, it looks at what was happening right now or just moments ago.

Why Memory Forensics Is Important?

Modern attacks often avoid writing files to disk. Instead, attackers rely on:

  • In-memory malware
  • Credential theft from running processes
  • Fileless attacks using built-in tools
  • Living-off-the-land techniques

If you only analyze the disk, you may completely miss these activities. Memory analysis helps investigators answer questions like:

  • What processes were running?
  • Was malicious code was injected into a legitimate process?
  • Were there suspicious network connections?
  • Were credentials present in memory?

For incident response, memory evidence is often the most time-sensitive and most revealing.

What Kind of Data Lives in RAM?

For beginners, it is very helpful to know what data RAM typically contains. It contains,

  • Running processes – active programs and services
  • Loaded modules and DLLs – libraries used by processes
  • Network connections – open sockets and connections
  • Command history – commands executed in shells
  • Credentials and tokens – sometimes present in memory
  • Injected or hidden code – common in advanced attacks

Not all of this data is always present, but memory analysis helps reveal relationships that disk analysis cannot.

Memory Forensics vs Disk Forensics

Understanding the difference between disk and memory forensics is critical. Here are the differences between them.

Disk Forensics:

  • Focuses on files and file systems
  • Evidence is persistent
  • Slower to change
  • Good for historical analysis

Memory Forensics:

  • Focuses on processes and activity
  • Evidence is volatile
  • Changes constantly
  • Best for live or recent incidents

Both approaches complement each other. Memory forensics rarely replaces disk forensics. It adds context and visibility.

Common Tools Used In Memory Forensics

One of the most widely used tools for memory analysis is Volatility Framework. It allows investigators to extract structured information from memory dumps, such as process lists, network connections and injected code. Other tools and frameworks exist, but beginners should focus on learning:

  • How memory dumps are captured
  • How analysis tools interpret operating system structures
  • How to correlate memory findings with logs and disk evidence

The goal is to understand concepts, not memorize commands.

Typical Memory Forensics Workflow

A simplified beginner workflow of memory analysis looks like this:

  1. Capture memory from a live system (before shutdown if possible)
  2. Identify the operating system and profile
  3. Analyze running processes
  4. Review network connections and handles
  5. Look for anomalies (hidden processes, unusual parent-child relationships)
  6. Document findings and correlate with other evidence

Each step builds context rather than relying on a single indicator.

Challenges in Memory Forensics

This forensics comes with some real challenges. They are,

  • Volatility of data: Once the system shuts down, RAM is gone
  • Large data size: Memory dumps can be several gigabytes
  • Complex output: Tools return technical results that require interpretation
  • False positives: Not every unusual artifact is malicious

These challenges are normal. Beginners should focus on patterns and behavior, not perfection.

Best Practices for Beginners

If you’re new to memory forensics, you should always keep these principles in mind:

  • Capture memory early during incidents
  • Preserve original dumps and work on copies
  • Correlate memory findings with logs and disk evidence
  • Document assumptions and limitations
  • Practice using labs, not real systems

Remember that this is a skill built through repetition and observation.

Conclusion

As attacks increasingly target identity, credentials and live processes, memory forensics has become a core DFIR skill. It is especially important in:

For beginners, learning memory forensics also builds stronger understanding of operating systems and process behavior, which benefits both red and blue team roles. It teaches investigators to look beyond files and focus on live system behavior. While it may seem complex at first, the fundamentals are straightforward: capture memory, analyze activity and reconstruct what happened. In a world of fileless attacks and in-memory threats, memory forensics is no longer optional. it is an essential part of modern digital investigations.