AP®︎ Cybersecurity: Unit 1 Flashcards

Master key terms and definitions for Unit 1 of AP Cybersecurity – Introduction to Security to help you prep for quizzes and the AP exam.


0%
54 cards total
54 not started
0 learning
0 almost done
0 mastered
Term

Social Engineering

Definition

Using psychological tactics to manipulate a person into taking an action that benefits an adversary

1 / 54
Social Engineering
Not Started

Using psychological tactics to manipulate a person into taking an action that benefits an adversary

1.1.A1.1.A.1
Elicitation
Not Started

Manipulating a person into disclosing information, directly or through a disguised request

1.1.A1.1.A.1
Phishing
Not Started

Message-based social engineering, commonly conducted through email, text, or social media

1.1.A1.1.A.1
Smishing
Not Started

Phishing conducted through SMS or other text messages

Intimidation
Not Started

Threatening a target with negative consequences for failing to comply, using fear to encourage action

1.1.A1.1.A.2
Urgency
Not Started

Creating a reason for a target to act quickly, using time pressure to discourage careful evaluation

1.1.A1.1.A.2
Identity Challenge Questions
Not Started

Knowledge-based authentication questions whose answers are used to verify identity but may be weak if guessable or publicly discoverable

One-Time Password (OTP)
Not Started

A code intended for one authentication attempt that an adversary can use while valid to log in as the victim

1.1.C1.1.C.2
Credential Harvesting
Not Started

Tricking users into submitting usernames, passwords, or other authentication information to an adversary-controlled form or service

Malware
Not Started

Malicious software designed to damage systems, disrupt operations, steal information, or provide unauthorized access

Online Password Attack
Not Started

An adversary’s attempt to log in to a live device or service using common, patterned, or stolen passwords

1.2.A1.2.A.1
Suspicious Login
Not Started

A login attempt that differs from expected activity, indicated by many rapid failures, an unusual time, or an unknown device

1.2.A1.2.A.2
Common Password Pattern
Not Started

A predictable password structure, often one or two familiar words followed by a two-digit number and a special character

1.2.B1.2.B.1
Brute-Force Attack
Not Started

An attack that systematically tries possible passwords or keys until the correct one is found

Credential Stuffing
Not Started

Trying previously stolen username-and-password combinations against other live services

1.2.A1.2.A.1
Strong Password
Not Started

A password that is long, random, unique to one account, and free of predictable or personally meaningful content

1.2.C1.2.C.1
Password Manager
Not Started

A tool that generates and stores strong, unique passwords for a user’s accounts

1.2.C1.2.C.1
Passphrase
Not Started

A long, unique sequence used as a password that is easier to remember but should still avoid predictable or personal content

1.2.C1.2.C.1
Multifactor Authentication (MFA)
Not Started

Authentication requiring proof from more than one independent factor category, such as a password plus a one-time code

1.2.C1.2.C.3
Authentication Factor
Not Started

A category of proof used to verify identity, such as something a person knows, has, or is

Low-Skilled Adversary
Not Started

An adversary who relies on tools made by others, typically to automate attacks against known vulnerabilities

1.3.A1.3.A.1
High-Skilled Adversary
Not Started

An adversary capable of creating or substantially modifying malicious tools, adapting to defenses, or discovering undocumented vulnerabilities

1.3.A1.3.A.1
Zero Day
Not Started

A vulnerability previously undocumented or unknown to those responsible for defending or correcting the affected system

1.3.A1.3.A.1
Adversary Motivations
Not Started

Reasons for attacking, including greed, recognition, dedication to a cause, revenge, politics, or beliefs; motivation is separate from skill level

1.3.A1.3.A.2
Wireless Access Point (WAP or AP)
Not Started

A device that provides network access to wireless devices by radio

1.3.B1.3.B.1
Service Set Identifier (SSID)
Not Started

The displayed name of a wireless network; it identifies the network by name but does not prove who operates it

1.3.B1.3.B.1
Evil Twin Attack
Not Started

An attack in which an adversary-controlled access point uses an identical or similar SSID so users connect and their traffic can be captured; HTTPS-protected contents cannot be read merely from that capture

1.3.B1.3.B.1
Hypertext Transfer Protocol Secure (HTTPS)
Not Started

HTTP protected by encryption and server authentication so the contents exchanged with a website are secured in transit

Jamming Attack
Not Started

Flooding an area with a strong electromagnetic signal in a wireless network's frequency range to disrupt legitimate communication

1.3.B1.3.B.2
Denial-of-Service (DoS) Attack
Not Started

An attack that prevents legitimate users from accessing a system, service, or resource

1.3.B1.3.B.2
War Driving Attack
Not Started

Moving through an area, by driving or walking, to detect wireless beacons and gather network or signal-reach information

1.3.B1.3.B.3
Wireless Network Beacon
Not Started

A radio transmission from a wireless access point that advertises the network’s availability and identifying information such as its SSID

Domain Name System (DNS) Query
Not Started

A request to the Domain Name System for information such as the IP address associated with a domain name

Virtual Private Network (VPN)
Not Started

A service that encrypts all user traffic to the VPN operator's system, hiding it from the local provider while transferring visibility and trust to the VPN provider

1.3.C1.3.C.3
Digital Avatar
Not Started

A synthetic representation of a person created from existing samples of the person’s voice or appearance

1.4.A1.4.A.1
Deepfake
Not Started

Realistic synthetic media that makes someone appear to say or do something they did not say or do

1.4.A1.4.A.1
Voice Cloning
Not Started

Using samples of a person’s voice to generate speech that sounds like that person

1.4.A1.4.A.1
Generative AI
Not Started

AI that produces new content such as language, images, audio, video, or code

1.4.A
Large Language Model (LLM)
Not Started

A type of generative AI trained on large collections of text and other data to produce responses to prompts

1.4.A
AI-Generated Phishing
Not Started

Using generative AI to create polished, localized, or personalized phishing messages at scale

1.4.A1.4.A.2
Prompt Injection
Not Started

A crafted prompt intended to override restrictions or manipulate an AI system’s instructions

1.4.A1.4.A.3
Training-Data Manipulation (Training-Data Poisoning)
Not Started

Placing false information in potential training sources to influence what a future AI model learns and repeats

1.4.A1.4.A.4
AI-Powered Reconnaissance
Not Started

Using AI to rapidly collect, connect, and summarize publicly available information about a target

1.4.A1.4.A.5
AI-Enhanced Coding Tools
Not Started

Tools that use AI to generate or modify code, assist malware development, or search large code bases for vulnerabilities

1.4.A1.4.A.6
Shared Secret
Not Started

A private word or phrase known only to trusted parties and used to verify identity in a high-stakes situation

1.4.B1.4.B.1
Keeping Sensitive Data Out of AI-Powered Tools
Not Started

Do not enter personal, secure, or sensitive information into AI prompts, chats, uploads, or connected files

1.4.B1.4.B.3
Independent Verification of AI Output
Not Started

Check consequential AI claims against reputable, stable, non-AI-based sources before acting on them

1.4.B1.4.B.4
AI Security-Configuration Review
Not Started

AI examination of current security settings to find excessive, conflicting, missing, or policy-inconsistent controls and recommend safer options for a security technician to review

1.5.A1.5.A.1
AI Application-Code Analysis
Not Started

AI inspection of application code to flag possible vulnerabilities and recommend mitigations that a knowledgeable programmer must verify and test

1.5.A1.5.A.2
Detection Rule
Not Started

Conditions an automated detection system treats as suspicious and the action it takes when they occur; AI-suggested rules require review by a detection engineer

1.5.A1.5.A.3
Human Review of AI Recommendations
Not Started

Qualified people must review, verify, and test AI-generated security recommendations before relying on or implementing them

1.5.B
AI-Powered Digital-Event Analysis
Not Started

Machine-scale analysis that sorts and prioritizes digital events by how likely they are to represent malicious activity rather than harmless activity

1.5.B1.5.B.2
Automated Threat Alerting
Not Started

Using automated rules or analytics to identify potentially malicious activity and generate alerts requesting human investigation

1.5.A1.5.A.3
Automated Response
Not Started

A corrective action automatically performed after detection when the organization has authorized that action in advance

1.5.B1.5.B.3