Roadmaps Security roadmaps Specialised and emerging

Fraud, Abuse and Trust and Safety

Stop the misuse of legitimate features: account takeover, credential stuffing, bots, payment and promotion fraud, impersonation and deepfakes, and harmful content on platforms.

Estimated time: 15–29 months · At about 10 hours a week.

Learning path

Click a topic to see what to learn and where. Mark topics as you go; your progress is saved in this browser only.

  • Core topic
  • Optional
  1. Beginner · 2–3 months Fraud and abuse fundamentals
  2. Intermediate · 3–6 months Building defences
  3. Advanced · 4–8 months Trust and safety at scale
  4. Expert · 6–12 months Leading fraud and trust

All topics in detail

Beginner, Time: 2–3 months

Fraud and abuse fundamentals

Skills

  • Classify fraud and abuse and their economics.
  • Detect account takeover with basic signals.
  • Write and evaluate fraud rules.

Hands-on projects and labs

  • Analyse a sample login log with SQL to find a credential stuffing attack.
  • Write rules that catch fake signups in a sample dataset and measure their false positive rate.

Done when you can…

  • Detect an account takeover campaign from raw logs.
  • Explain the trade-off between friction and conversion with numbers.

Beginner

Types of fraud and abuse

Account takeover, fake accounts, payment fraud, promotion abuse, scraping, spam, scams and harmful content. Each has its own economics and signals.

Resources

Beginner

Attacker economics

Fraud is a business. Raise the attacker's cost per success above the payoff and they move elsewhere. Think in costs, not only in blocks.

Resources

Beginner

Account takeover

Credential stuffing, phishing, SIM swap and session theft. Detect impossible travel, new devices and bulk failed logins, and push users to passkeys.

Resources

Beginner

Signals and features

IP reputation, device fingerprints, velocity, behaviour and account history. Good signals are the foundation of every fraud defence.

Resources

Beginner

Rules and case review

Start with clear rules, review the cases they flag, and measure false positives. Fraud work is iterative and evidence-driven.

Resources

Beginner

Designing friction

Step-up authentication, rate limits, verification and holds stop abusers but annoy customers. Apply friction by risk, not to everyone.

Resources

Intermediate, Time: 3–6 months

Building defences

Skills

  • Detect and manage bots.
  • Build and monitor risk-scoring models.
  • Defend payments and verify identities.
  • Investigate fraud rings with link analysis.

Hands-on projects and labs

  • Train a simple fraud model on a public transaction dataset and evaluate precision and recall.
  • Build a graph of accounts sharing devices and payment details and find a fraud ring.
  • Design step-up rules that cut account takeover without blocking most good users.

Done when you can…

  • Ship a risk score that reduces fraud with acceptable friction.
  • Uncover a fraud ring through link analysis.

Intermediate

Bot detection and management

Separate good bots from bad ones, detect automation through behaviour and challenges, and keep up as attackers use real browsers and residential proxies.

Resources

Intermediate

Risk scoring and machine learning

Combine signals into a risk score with models, and act on it in real time. Watch for label quality, drift and adversaries probing your thresholds.

Resources

Intermediate

Payment and transaction fraud

Card-not-present fraud, chargebacks, refund abuse and authorised push payment scams. Use 3-D Secure, velocity checks and behavioural analysis.

Resources

Intermediate

Identity verification

Document checks, selfie matching and data verification stop fake accounts, but deepfakes and synthetic identities are improving fast. Layer the checks.

Resources

Intermediate

Investigations and link analysis

Link accounts by shared devices, payment details and behaviour to uncover rings. Graph analysis turns single cases into whole networks.

Resources

Intermediate

Measuring fraud defences

Track fraud loss rate, false positive rate, customer friction and time to detect. Report money saved and customers protected.

Resources

Advanced, Time: 4–8 months

Trust and safety at scale

Skills

  • Run trust and safety policy and enforcement.
  • Defend against AI-enabled fraud.
  • Protect the brand from impersonation.
  • Run healthy review operations.

Hands-on projects and labs

  • Write a content policy and enforcement guide for a sample platform feature.
  • Design a verification flow for high-value requests that resists deepfake calls.
  • Find and document lookalike domains impersonating a sample brand.

Done when you can…

  • Run a trust and safety process with policy, detection, review and appeal.
  • Show defences adapted to AI-enabled scams.

Advanced

Trust and safety

Harmful content, harassment, scams between users and child safety are platform integrity problems. Learn policy, detection, review operations and appeals.

Resources

Advanced

Policy and enforcement

Write clear rules, enforce them consistently, give users notice and appeal, and publish transparency reports. Laws such as the EU Digital Services Act now require it.

Resources

Advanced

AI-enabled fraud and deepfakes

Generated documents, cloned voices, deepfake video calls and mass-personalised scams. Add verification steps that do not rely on what people can see or hear.

Resources

Advanced

Impersonation and brand protection

Fake apps, lookalike domains, impersonating social accounts and scam ads target your customers in your name. Monitor and take them down.

Resources

Advanced

Review operations and wellbeing

Human reviewers see the worst content. Design queues, tools, quality checks and wellbeing support as carefully as the detection.

Resources

Advanced

Industry sharing

Fraudsters and abusers move between platforms. Share signals through industry groups and with banks and telecoms.

Resources

Expert, Time: 6–12 months

Leading fraud and trust

Skills

  • Set fraud and trust strategy.
  • Meet online safety and fraud regulation.

Hands-on projects and labs

  • Write a fraud and trust strategy with loss and friction targets.
  • Run an abuse threat model on a new product feature.

Done when you can…

  • Lead a fraud and trust function with measurable loss reduction.
  • Embed abuse prevention into product design.

Expert

Fraud and trust strategy

Set the appetite for fraud loss and friction, the operating model across product, security, payments and policy, and the investment to match.

Resources

Expert

Regulation and transparency

Online safety and digital services laws, payment fraud reimbursement rules and consumer protection now apply. Build compliance into the programme.

Resources

Expert

Safety by design

The cheapest abuse to fight is the abuse a feature never enabled. Get involved in product design and threat model features for abuse.

Resources

Overview

Fraud and abuse teams fight attackers who use a product exactly as designed, just for the wrong ends: logging in with stolen passwords, creating fake accounts, abusing promotions, scamming users or posting harmful content. There is often no vulnerability to patch, only behaviour to detect.

The field combines security engineering, data science and operations: building signals and risk scores, designing friction that stops abusers but not customers, running investigations, and working with policy and legal on platform rules. Trust and safety extends it to harmful content and user protection.

Why it matters

Fraud and abuse cost companies and their customers billions, and AI is making scams and fake identities cheaper. Every product with accounts, payments or user content needs people who can keep it trustworthy without driving away genuine users.

Typical job roles

  • EntryFraud analyst Investigates cases and tunes rules.
  • Mid-levelAnti-abuse engineer Builds detection signals and defences into products.
  • Mid-levelTrust and safety specialist Handles harmful content and user protection.
  • LeadHead of trust and safety Owns fraud, abuse and platform integrity.

Prerequisites

  • Web and application security basics.
  • SQL and some data analysis.
  • How authentication and payments work.
  • Good judgement and attention to detail.

Cybersecurity fundamentals Data analysis and engineering

Tools and technologies

Certifications

Take them in roughly this order. Costs and details for the ones marked with a link are on the Certifications page.

  1. Intermediate CFE ACFECertified Fraud Examiner.
  2. Intermediate CAMS ACAMSAnti-money-laundering specialist.
  3. Entry Security+ CompTIASecurity baseline.Cost and exam details

Resources

Frameworks and standards

  • NIST SP 800-63-4 Digital Identity Guidelines Requirements for identity proofing, authentication (including passwords and MFA) and federation.
  • OWASP Top 10 The ten most critical web application security risks, updated every few years from real data.
  • PCI DSS The security standard every organisation that stores, processes or sends payment card data must meet.
  • FIDO2 and passkeys Standards for phishing-resistant, passwordless sign-in with security keys and passkeys.
  • GDPR (General Data Protection Regulation) The EU law on personal data: lawful use, people's rights, breach notification and security of processing.

All frameworks and standards

Career path

A common progression. Titles vary between companies.

  1. Analyst in fraud, risk, operations or security0–2 years
  2. Fraud analyst or trust and safety specialist1–4 years
  3. Anti-abuse engineer or fraud manager4–8 years
  4. Head of trust and safety8+ years

Related domains to move into

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