Security Threats - Learning Module

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Threat Categories

Understanding the Adversary Landscape

In the realm of operating system security, the first step toward building robust defenses is understanding what you're defending against. Threat categorization provides the foundational vocabulary and mental framework that security professionals use to analyze, communicate about, and ultimately mitigate security risks.

Without a structured understanding of threats, security efforts become reactive and haphazard—patching holes as they appear rather than architecting systems that resist entire classes of attacks. This page establishes the taxonomic foundation upon which all subsequent security knowledge builds.

What You Will Learn

By the end of this page, you will understand the major categories of security threats, the distinction between different threat actors and their motivations, how threats are classified by their targets and methods, and why proper threat categorization is essential for effective security architecture.

The Need for Threat Taxonomy

Before diving into specific threat categories, we must understand why systematic classification matters. Consider a hospital administrator trying to protect patient records without a structured threat model—they might focus on external hackers while ignoring insider threats, or invest heavily in network firewalls while leaving physical access uncontrolled.

Threat taxonomy serves several critical purposes:

Purpose of Threat Classification

•Comprehensive Coverage — A well-structured taxonomy ensures no major threat category is overlooked during security analysis. Without systematic categorization, defenders inevitably miss entire attack surfaces.
•Resource Allocation — Understanding threat categories helps prioritize security investments. A financial institution faces different primary threats than a social media platform; taxonomy guides where to focus limited resources.
•Communication Standardization — Security teams, executives, vendors, and regulators need shared vocabulary. Threat categories provide this common language for effective communication across stakeholders.
•Pattern Recognition — Many attacks share fundamental characteristics despite surface differences. Categorization reveals these patterns, enabling defenders to address root causes rather than symptoms.
•Regulatory Compliance — Security frameworks like NIST, ISO 27001, and SOC 2 require threat identification. A structured taxonomy maps directly to compliance requirements.

The Military Heritage

Modern computer security threat taxonomies evolved from military intelligence frameworks. Concepts like 'threat actors,' 'attack vectors,' and 'indicators of compromise' originated in Cold War intelligence analysis. This heritage explains the structured, methodical approach that characterizes professional security work.

The CIA Triad: Organizing Principles

The most fundamental framework for categorizing security threats is the CIA Triad—Confidentiality, Integrity, and Availability. Every security threat ultimately targets one or more of these properties. Understanding which property an attack targets clarifies both its impact and appropriate countermeasures.

The three pillars:

The CIA Triad: Security Properties and Their Threats
Property	Definition	Threat Examples	Countermeasures
Confidentiality	Information is accessible only to authorized entities	Data breaches, eavesdropping, information disclosure, social engineering	Encryption, access controls, data classification, need-to-know policies
Integrity	Information and systems are accurate and unaltered	Data tampering, malware injection, man-in-the-middle attacks, unauthorized modifications	Hashing, digital signatures, checksums, version control, audit logs
Availability	Systems and data are accessible when needed	Denial-of-service attacks, ransomware, hardware destruction, resource exhaustion	Redundancy, load balancing, failover systems, rate limiting, backups

The Extended CIA Model:

Modern security frameworks often extend the CIA triad with additional properties:

Authenticity — Ensuring the identity of parties in a transaction can be verified
Non-repudiation — Preventing denial of having performed an action
Accountability — Tracing actions back to the responsible entity
Privacy — Controlling how personal information is collected, used, and shared

These extensions address the growing complexity of modern computing environments where identity, legal liability, and regulatory compliance are paramount concerns.

Threat Analysis Approach

When analyzing any security incident or potential threat, start by asking: 'Which CIA property is being targeted?' This immediately focuses your analysis. A ransomware attack targets availability (and sometimes confidentiality). A data breach targets confidentiality. Defacing a website targets integrity. This framing clarifies both impact assessment and response priorities.

Threat Actor Categories

Threats don't emerge from the void—they originate from threat actors with specific motivations, capabilities, and resources. Understanding who might attack your systems is as important as understanding how they might attack. Different actors require different defensive postures.

The principal threat actor categories:

Threat Actor Taxonomy

•Nation-State Actors (APTs) — Government-sponsored groups with virtually unlimited resources, sophisticated capabilities, and long-term objectives. They conduct espionage, sabotage, and influence operations. Examples: APT28 (Russia), APT41 (China), Lazarus Group (North Korea). Characterized by patience, custom tooling, and zero-day exploits.
•Organized Crime — Financially motivated criminal enterprises operating at scale. They deploy ransomware, conduct fraud, steal data for sale, and operate cybercrime-as-a-service platforms. Examples: REvil, Conti, FIN7. Profit-driven with business-like operations including customer support for victims.
•Hacktivists — Ideologically motivated actors seeking to promote political or social causes through cyber operations. They conduct website defacement, data leaks, and DDoS attacks. Examples: Anonymous, LulzSec. Unpredictable targeting based on current events and causes.
•Insider Threats — Employees, contractors, or partners with legitimate access who misuse it. Motivations include financial gain, revenge, ideology, or coercion. The most dangerous threat because they bypass perimeter defenses and understand internal systems.
•Script Kiddies — Unskilled individuals using pre-built tools without deep understanding. Low capability but high volume—they exploit known vulnerabilities that remain unpatched. Opportunistic rather than targeted.
•Competitors — Business rivals engaging in corporate espionage to steal trade secrets, customer data, or strategic information. Often operate through hired contractors or criminal proxies to maintain deniability.
•Terrorists — Groups seeking to cause fear, disruption, or physical harm through cyber means. Lower current capability but high intent for attacks on critical infrastructure. Growing concern as attack tools become more accessible.

Threat Actor Comparison Matrix
Actor Type	Resources	Sophistication	Persistence	Primary Target
Nation-State	Unlimited	Extremely High	Years	Strategic assets, critical infrastructure
Organized Crime	High	High	Months	Financial systems, valuable data
Hacktivists	Low-Medium	Medium	Days-Weeks	High-visibility targets
Insiders	Low (external)	Varies	Varies	Accessible systems, data
Script Kiddies	Minimal	Low	Hours-Days	Any vulnerable system

The Insider Threat Paradox

While nation-states receive the most media attention, insider threats cause disproportionate damage. A 2023 study found that insider incidents cost organizations an average of $15.4 million annually—higher than external breaches. The Edward Snowden and Chelsea Manning cases demonstrate how a single insider can expose entire national security programs. Never underestimate the privileged threat.

Classification by Attack Target

Another essential categorization dimension is what is being targeted. Operating systems present multiple attack surfaces, and threats targeting different system components require different defensive strategies.

Attack surface categories:

System-Level Targets

•Kernel — The most privileged target; kernel compromise grants complete system control. Attacks include kernel exploits, rootkits, and bootkits.
•Memory — Attacks targeting process memory including buffer overflows, use-after-free, and memory corruption vulnerabilities.
•File System — Attacks on configuration files, binaries, libraries, and data storage including privilege escalation and data tampering.
•Network Stack — Attacks on network protocols and services including packet injection, protocol exploits, and denial-of-service.
•Hardware/Firmware — Low-level attacks on BIOS/UEFI, TPM, and hardware components; extremely persistent and difficult to detect.

Application-Level Targets

•User Applications — Attacks on browsers, email clients, office suites, and other user-facing software; common entry points.
•System Services — Attacks on daemons, system utilities, and background services running with elevated privileges.
•Authentication Systems — Attacks on credential storage, authentication mechanisms, and identity infrastructure.
•Databases — Attacks targeting data stores including SQL injection, privilege escalation, and data exfiltration.
•APIs and Interfaces — Attacks on programmatic interfaces including parameter manipulation and access control bypass.

The Depth Principle:

Attacks deeper in the system stack are generally more dangerous but harder to execute. A kernel vulnerability provides more power than an application vulnerability, but kernel exploits are rarer and require more sophistication. Defenders must balance protection across all levels—focusing only on application security while ignoring kernel hardening leaves critical gaps.

Attack Surface Reduction:

Each exposed interface represents potential attack surface. Modern security emphasizes minimizing this surface through:

Removing unnecessary services and software
Disabling unused features and protocols
Implementing strict access controls
Segmenting networks and systems
Applying least-privilege principles throughout the stack

Classification by Attack Method

Beyond who attacks and what they target, we must consider how attacks are executed. Attack methodology classification helps defenders understand attack patterns and implement appropriate countermeasures.

Major attack methodology categories:

Attack Methodology Classification
Category	Description	Examples	Defense Focus
Exploitation	Leveraging software vulnerabilities to gain unauthorized access or capabilities	Buffer overflow, SQL injection, command injection, format string attacks	Secure coding, input validation, patching, exploit mitigation
Social Engineering	Manipulating humans to bypass technical controls	Phishing, pretexting, baiting, tailgating, quid pro quo	Security awareness, verification procedures, technical controls on human actions
Credential Attacks	Obtaining or circumventing authentication credentials	Brute force, password spraying, credential stuffing, pass-the-hash	Strong authentication, MFA, credential monitoring, account lockout
Denial of Service	Overwhelming resources to prevent legitimate access	DDoS, resource exhaustion, algorithmic complexity attacks	Rate limiting, capacity planning, DDoS mitigation services
Supply Chain	Compromising trusted upstream components or providers	Trojanized updates, dependency confusion, third-party breaches	Vendor security assessment, integrity verification, component isolation
Physical	Attacks requiring physical access to systems	Hardware implants, cold boot attacks, evil maid attacks	Physical security, encryption, tamper detection

Attack Chain Integration:

Real-world attacks rarely use a single method in isolation. A sophisticated attack might combine:

Social engineering to obtain initial credentials via phishing
Exploitation to escalate privileges using a local vulnerability
Credential attacks to move laterally using harvested credentials
Supply chain elements through trusted tools already present

This reality demands defense in depth—no single control can prevent all attack methods. Layered defenses ensure that failure of one control doesn't mean complete compromise.

The Human Element

Despite billions invested in technical security controls, social engineering remains the most successful attack methodology. Verizon's Data Breach Investigation Report consistently shows that human factors contribute to 74%+ of breaches. Technical categorization of threats must always include the human attack surface—arguably the largest and most vulnerable.

The STRIDE Threat Model

Microsoft developed the STRIDE model as a systematic framework for categorizing threats during software design. STRIDE is an acronym where each letter represents a threat category, and each category has a corresponding security property it violates.

The STRIDE framework:

STRIDE Threat Categories
Threat	Description	Violated Property	Example
Spoofing	Impersonating something or someone else	Authentication	Using stolen credentials, IP spoofing, email header forgery
Tampering	Modifying data or code	Integrity	SQL injection to modify database, altering configuration files, MITM attacks
Repudiation	Denying having performed an action	Non-repudiation	Deleting audit logs, claiming transaction never occurred, unsigned actions
Information Disclosure	Exposing information to unauthorized parties	Confidentiality	Data breaches, error messages revealing internals, metadata leakage
Denial of Service	Preventing legitimate access to resources	Availability	DDoS attacks, resource exhaustion, crash-inducing input
Elevation of Privilege	Gaining capabilities beyond authorization	Authorization	Kernel exploits, escaping sandboxes, privilege escalation bugs

Applying STRIDE:

The STRIDE model is applied by examining each component of a system and asking: 'How could this component be subject to each STRIDE threat?' This systematic approach ensures comprehensive threat coverage.

Example STRIDE analysis for a login system:

Spoofing: Could an attacker impersonate a legitimate user? (credential theft, session hijacking)
Tampering: Could an attacker modify authentication data? (password database modification)
Repudiation: Could a user deny a login? (are login events logged with integrity?)
Information Disclosure: Could login attempts leak information? (timing attacks, error messages)
Denial of Service: Could authentication be overwhelmed? (brute force protections?)
Elevation of Privilege: Could any user gain admin rights? (access control review)

STRIDE in Practice

STRIDE is most valuable during the design phase when threats can be addressed architecturally rather than patched after deployment. Many organizations require STRIDE analysis as part of their security design review process. The Microsoft Threat Modeling Tool automates portions of STRIDE analysis for common architectures.

Active vs. Passive Threats

A fundamental distinction in threat categorization is between active and passive threats. This classification affects both detection strategies and legal implications.

Understanding the distinction:

Passive Threats

•Nature: Observation without modification; the attacker monitors but doesn't alter system state
•Examples: Network eavesdropping, traffic analysis, metadata collection, keystroke logging (observation only)
•Detection: Extremely difficult—no direct evidence left. Must be inferred or detected via canary mechanisms
•CIA Impact: Primarily targets Confidentiality
•Countermeasures: Encryption (data in transit and at rest), traffic padding, steganography for covert channels

Active Threats

•Nature: Modification of system state; the attacker changes data, code, or behavior
•Examples: Data modification, malware installation, denial of service, message injection, session hijacking
•Detection: Easier than passive—modifications may leave traces. Integrity checks can detect tampering
•CIA Impact: Targets Integrity and/or Availability (sometimes Confidentiality indirectly)
•Countermeasures: Digital signatures, integrity monitoring, audit logging, intrusion detection

The Detection Asymmetry:

Passive threats are fundamentally harder to detect because they don't modify the target system. A nation-state intelligence service can passively collect encrypted traffic for years, hoping future cryptographic breakthroughs will enable decryption ('harvest now, decrypt later'). The target may never know this collection occurred.

Active threats leave evidence—modified files, new processes, unusual network traffic. While sophisticated actors minimize their footprint, the need to modify system state creates detection opportunities that don't exist for passive threats.

Strategic Implications:

Organizations must assume passive threats are ongoing and design systems accordingly:

Encrypt all sensitive data assuming it may be intercepted
Use forward-secret key exchange assuming recorded traffic may be decrypted later
Minimize metadata exposure assuming traffic patterns are analyzed
Implement data classification to focus protection resources

The Surveillance Economy

Passive threats aren't limited to espionage. Commercial entities conduct massive passive data collection through advertising trackers, analytics services, and IoT devices. While legal under many jurisdictions, this collection creates security risks when aggregated data is breached or misused. The threat model must include legitimate-seeming passive collection, not just malicious actors.

Internal vs. External Threats

The distinction between internal and external threats fundamentally shapes security architecture. These threat categories require different controls, monitoring approaches, and organizational responses.

Defining the boundary:

Internal vs. External Threat Comparison
Dimension	Internal Threats	External Threats
Access Level	Start with legitimate access; bypass perimeter defenses	Must breach perimeter before accessing internal systems
System Knowledge	Deep knowledge of systems, processes, and security controls	Limited knowledge; must conduct reconnaissance
Detection Challenge	Actions appear legitimate; harder to distinguish malicious from normal	Anomalous behavior patterns easier to detect
Attack Duration	Can be gradual, low-and-slow over extended periods	Often time-constrained once detected
Countermeasures	Need-to-know, behavioral monitoring, data loss prevention	Perimeter security, network monitoring, access controls
Trust Model	Challenges traditional trust assumptions; zero-trust essential	Classic boundary-based security often sufficient

The Perimeter Fallacy:

Traditional security models assumed a hard perimeter—external threats are blocked at the boundary while internal users are trusted. This model has catastrophically failed. Modern reality includes:

Remote work — Users access internal resources from external networks
Cloud services — Data and processing occur outside organizational boundaries
BYOD — Personal devices access corporate systems
Supply chain — Partners and vendors require internal access
Insider threats — Internal actors are often the most dangerous

The result is Zero Trust Architecture—the principle that no user, device, or network should be automatically trusted regardless of location. Every access request is verified as if originating from an untrusted network.

Zero Trust Principles

Zero Trust can be summarized as: 'Never trust, always verify.' Every user, device, and network flow must prove its legitimacy for every access request. This eliminates the distinction between internal and external threats—all access is treated with appropriate skepticism. Implementation requires identity verification, device health checks, least-privilege access, and continuous monitoring.

Threat Landscape Evolution

The threat landscape is not static. Understanding how threats evolve over time helps organizations anticipate future challenges rather than perpetually reacting to yesterday's attacks.

Historical evolution of dominant threat categories:

Evolution of Dominant Threat Categories
Era	Primary Threats	Attack Motivation	Defense Focus
1980s-1990s	Viruses, worms, curiosity-driven hacking	Technical challenge, notoriety	Antivirus, access controls
2000s	Spam, phishing, early cybercrime	Financial fraud at scale	Email filtering, user awareness
2010s	APTs, data breaches, ransomware emergence	Espionage, large-scale theft, extortion	Network monitoring, breach detection
2020s	Ransomware-as-a-service, supply chain attacks, AI-enabled threats	Industrialized crime, geopolitical conflict	Zero trust, supply chain security, AI-assisted defense
Future	AI-autonomous attacks, quantum threats, IoT botnets at scale	Unknown—threat actors will exploit new capabilities	Quantum-resistant cryptography, AI-native security

Current Trend Accelerators:

Cybercrime industrialization — Criminal operations now mirror legitimate businesses with specialization (initial access brokers, ransomware operators, money launderers) and service offerings (RaaS, Phishing-as-a-Service)
AI weaponization — Machine learning enables more convincing phishing, faster vulnerability discovery, and adaptive malware that evades detection
Expanded attack surface — Cloud migration, IoT proliferation, and remote work exponentially increase potential entry points
Geopolitical integration — Cyber operations are now standard instruments of state power, blurring lines between criminal and state activity

The Quantum Threat Horizon

Quantum computing threatens current cryptographic standards. While practical quantum computers are years away, data encrypted today may be vulnerable to future quantum attacks ('harvest now, decrypt later'). Organizations with long data protection requirements must begin transitioning to post-quantum cryptography now. NIST has standardized initial post-quantum algorithms (CRYSTALS-Kyber, CRYSTALS-Dilithium).

Summary: Threat Categories Foundation

We've established the foundational taxonomy for understanding security threats. This categorization framework will inform every subsequent topic in this module. Let's consolidate the key concepts:

Key Takeaways

•The CIA Triad provides the foundational framework—every threat targets Confidentiality, Integrity, or Availability (often multiple).
•Threat actors range from nation-states to script kiddies, each with distinct motivations, capabilities, and persistence levels that inform defensive priorities.
•Attack targets span from hardware/firmware through kernel, operating system, and applications—depth of compromise correlates with impact and difficulty.
•Attack methods include exploitation, social engineering, credential attacks, denial of service, supply chain, and physical—layered defense addresses all vectors.
•STRIDE provides systematic threat enumeration: Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege.
•Passive vs. active threats require different detection strategies—passive threats (eavesdropping) leave no direct evidence; active threats (modification) can be detected through integrity monitoring.
•Internal vs. external threats challenge traditional perimeter security—Zero Trust architecture treats all access requests with appropriate verification.
•The threat landscape evolves continuously—yesterday's novel attack becomes tomorrow's commodity tool as techniques diffuse through the attacker ecosystem.

What's Next:

With this taxonomic foundation established, we'll examine specific threat types in detail. The next page explores Malware Types—the primary technical mechanism through which threats materialize. We'll analyze viruses, worms, trojans, ransomware, and other malicious software, understanding both their technical operation and the threat categories they embody.

Page Complete

You now understand the fundamental categories used to classify security threats. This taxonomy—threat actors, targets, methods, and organizing frameworks like CIA and STRIDE—provides the vocabulary and mental models for systematic security thinking. Next, we'll apply this framework to understanding specific malware types.