# fraud Published articles for fraud. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How energy teams turn theft detection into governed action with Genie and AI business processes DevFeed: [How energy teams turn theft detection into governed action with Genie and AI business processes]() Original publisher: [Read original article]() Author: Daniel Zoccali; Jack Yallop Published: 2026-09-15T16:50:00Z Content type: article Language: en Sources: [Databricks]() Topics: [databricks](), [Machine learning](), [Artificial Intelligence]() Tags: [databricks](), [energy](), [fraud](), [industries](), [ml](), [model](), [reporting](), [safety](), [speed]() ### AI overview The article explains how energy teams can operationalize energy-theft detection by connecting model-generated risk signals with investigation, field operations, revenue recovery, and reporting in a governed workflow. It presents a Databricks implementation using a Databricks App, Lakebase, and Unity Catalog. ### Source excerpt Energy theft is the deliberate use of gas or electricity without paying for it, typically... ## Search results are sending people to fake Bitrefill checkouts DevFeed: [Search results are sending people to fake Bitrefill checkouts]() Original publisher: [Read original article]() Author: Stefan Dasic Published: 2026-09-15T08:40:22Z Content type: news Language: en Sources: [Malwarebytes]() Topics: [Cryptocurrency](), [Bitcoin](), [Website]() Tags: [bitcoin](), [cryptocurrency](), [fraud](), [payments](), [phishing](), [qr-code](), [scam](), [scams](), [search](), [threat-intel]() ### AI overview Fake Bitrefill checkout pages are appearing in search results and copying the company's branding and payment flow. They persuade victims to send cryptocurrency to scammer-controlled addresses, with no goods delivered and little chance of recovering the payment. ### Source excerpt Fake Bitrefill checkout pages are appearing in search results and tricking people into sending cryptocurrency directly to scammers. ## Expanding Fraud Strategies Beyond Payment Fraud DevFeed: [Expanding Fraud Strategies Beyond Payment Fraud]() Original publisher: [Read original article]() Author: Sift Trust and Safety Team Published: 2026-08-26T18:08:35Z Content type: article Language: en Sources: [Sift Science]() Topics: [account takeover]() Tags: [account-takeover](), [chargeback-disputes](), [chargebacks](), [compliance](), [customer-trust](), [fraud](), [fraud-and-compliance](), [fraud-prevention](), [fraud-strategy](), [loyalty-point-fraud](), [loyalty-points](), [non-payment-fraud](), [payment-fraud](), [promo-abuse](), [trust-and-safety]() ### AI overview This article explains why fraud programs should address risks across the full customer lifecycle rather than focusing only on payment fraud. It discusses account takeover, fake accounts, promo abuse, loyalty points, giveaways, and coordination between fraud, risk, and compliance teams. ### Source excerpt Most fraud programs start with payment fraud, and for good reason. It's the fastest path to measurable loss. But teams that stop there often miss account takeover, fake account creation, and promo abuse until those problems show up in support tickets, chargeback disputes, or a spike in customer complaints. By the time it's visible, it's [...] The post How to Solve for More Than Just Payment Fraud appeared first on Sift. ## Testing Trust in Prediction Markets | Part 1 DevFeed: [Testing Trust in Prediction Markets | Part 1]() Original publisher: [Read original article]() Author: David Phillips Published: 2026-09-03T13:15:00Z Content type: opinion Language: en Sources: [Sift Science]() Topics: [integrity]() Tags: [data-insights](), [fairness](), [fraud](), [integrity](), [prediction-markets](), [prediction-markets-legislation](), [trust]() ### AI overview Part 1 examines how reported insider trading, irregularities, settlement issues, and operational design choices in prediction markets can undermine claims about fairness, market integrity, collective intelligence, and truth. It argues that gaps between provider claims and market realities can erode public trust and invite political or regulatory responses. ### Source excerpt This April, U.S. federal prosecutors charged an Army sergeant with using sensitive classified information to bet on Polymarket that U.S. forces would enter Venezuela and remove Maduro from power. About the same time, Kalshi disclosed that it had fined and suspended three congressional candidates for five years after they traded on prediction markets tied to [...] The post Testing Trust in Prediction Markets | Part 1 appeared first on Sift. ## How to Build a Fraud Signal-Sharing Strategy Across Teams and Vendors DevFeed: [How to Build a Fraud Signal-Sharing Strategy Across Teams and Vendors]() Original publisher: [Read original article]() Author: Jacob Sanchez Published: 2026-09-04T16:37:55Z Content type: tutorial Language: en Sources: [Sift Science]() Topics: [data](), [Security](), [dashboards](), [Slack]() Tags: [cross-team-fraud-collaboration](), [dashboards](), [data](), [fraud](), [fraud-kpis](), [fraud-prevention-strategy](), [fraud-signal-sharing](), [signal](), [signal-sharing-strategy](), [slack](), [strategy](), [teams](), [trust-and-safety](), [vendor-data-sharing]() ### AI overview This how-to article discusses building fraud signal-sharing programs across internal teams and vendors. It explains how shared signals such as PII, IP addresses, device data, and activity patterns can support fraud prevention, security, legal, compliance, growth, marketing, and customer support. It also compares informal sharing through Slack and email with shared dashboards and reports. ### Source excerpt I recently joined Jerry Hoff, CEO of AppSec Training, for a Blueprint Series session on fraud signal sharing, and it's a topic I keep coming back to. Fraud, trust and safety, and security teams often work from separate systems with no shared view of the same bad actor. That gap slows response time and lets [...] The post How to Build a Fraud Signal-Sharing Strategy Across Teams and Vendors appeared first on Sift. ## Testing Trust in Prediction Markets | Part 2 DevFeed: [Testing Trust in Prediction Markets | Part 2]() Original publisher: [Read original article]() Author: David Phillips Published: 2026-09-10T17:44:43Z Content type: opinion Language: en Sources: [Sift Science]() Topics: [integrity](), [data]() Tags: [analysis](), [comparison](), [data-insights](), [digital-trust](), [fraud](), [integrity](), [prediction-markets](), [trust]() ### AI overview Part 2 examines whether prediction markets can reliably produce trustworthy information. It compares Kalshi's centralized contract resolution with Polymarket's decentralized, oracle-based model and discusses risks involving contract interpretation, voting power, concentrated profits, and market integrity. ### Source excerpt Missed Part 1? Read it here. Prediction markets make a bold claim that they are engines of truth discovery. Proponents argue that by aggregating collective judgment, prediction markets generate forecasts that are far more valuable than traditional gambling or sports betting. While that claim has merit, a prediction market's output is not merely a well [...] The post Testing Trust in Prediction Markets | Part 2 appeared first on Sift. ## What is CIAM in 2026 and why does it matter? DevFeed: [What is CIAM in 2026 and why does it matter?]() Original publisher: [Read original article]() Author: Ravleen Kaur Published: 2026-09-15T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [identity and access management](), [trust](), [ai-governance](), [Security](), [Artificial Intelligence](), [IAM](), [Generative AI]() Tags: [ai-agents](), [ai-governance](), [email](), [fraud](), [fraud-detection](), [identity](), [identity-and-access-management](), [industry-insights](), [messaging](), [mobile](), [trust]() ### AI overview This article explains how customer identity and access management (CIAM) is evolving from point-in-time password checks into a continuous trust and control layer. It describes CIAM's role in authenticating users, governing delegated authority for AI agents, evaluating risk across channels, and balancing low-friction access with fraud detection. It also distinguishes customer identity from workforce IAM. ### Source excerpt Discover how customer identity and access management (CIAM) uses continuous trust, deepfake defense, and agentic AI governance to protect users. ## What Stripe data shows about fraud at AI startups DevFeed: [What Stripe data shows about fraud at AI startups]() Original publisher: [Read original article]() Author: Jacob Meltzer; Samuel Bakouch Published: 2026-09-15T00:00:00Z Content type: article Language: en Sources: [Stripe Blog]() Topics: [Artificial Intelligence](), [stripe](), [Security, Privacy and Abuse Prevention](), [multi-account abuse]() Tags: [ai](), [fraud](), [multi-account-abuse](), [stripe]() ### AI overview Stripe reports that AI startups experienced higher attempted transaction fraud and multi-account abuse than startups overall. Its data found a 4.3x higher attempted transaction fraud rate in Q3 2025, falling to 2.6x by Q1 2026. ### Source excerpt We analyzed attempted fraud rates and customer abuse patterns on Stripe over the past year and found that AI companies faced 4.3x more fraud attempts than startups overall in Q3 2025. ## Android malware creates a hidden copy of your banking app DevFeed: [Android malware creates a hidden copy of your banking app]() Original publisher: [Read original article]() Author: Pieter Arntz Published: 2026-09-11T12:14:55Z Content type: news Language: en Sources: [Malwarebytes]() Topics: [Malware](), [App]() Tags: [android](), [app](), [credential-theft](), [fraud](), [malware](), [mobile](), [news](), [phishing](), [profile](), [security](), [transactions]() ### AI overview Gigabud is an Android banking Trojan that creates a work profile and clones a banking app so operators can conduct fraudulent transactions separately from malware detected in the personal profile. ### Source excerpt The Gigabud banking Trojan can clone a banking app into a separate work profile on an Android device to help hide fraudulent transactions. ## \[Webinar\] Elevating customer engagement with WhatsApp DevFeed: [\[Webinar\] Elevating customer engagement with WhatsApp]() Original publisher: [Read original article]() Author: Twilio Published: 2026-09-11T00:00:00Z Content type: article Language: en Sources: [Twilio Blog]() Topics: [Messaging](), [Authentication](), [End-to-End Encryption](), [Encryption](), [Artificial Intelligence]() Tags: [ai](), [authentication](), [customer-engagement](), [encryption](), [enterprise](), [events-community](), [fraud](), [messaging](), [operational](), [webinar](), [whatsapp]() ### AI overview This webinar explains how businesses can use WhatsApp for secure account verification, operational alerts, two-way customer conversations, and interactive workflows. It also discusses end-to-end encryption, reducing SMS toll fraud risk, and examples of AI-powered HR messaging workflows. ### Source excerpt Stop losing critical messages in the noise. Discover how to deliver secure account verifications and operational updates via WhatsApp. ## Protecting organizations from AI-assisted executive impersonation and invoice fraud DevFeed: [Protecting organizations from AI-assisted executive impersonation and invoice fraud]() Original publisher: [Read original article]() Author: Microsoft Security Research Published: 2026-09-10T17:23:05Z Content type: article Language: en Sources: [Microsoft Security Blog]() Topics: [spoofing]() Tags: [ai](), [enterprise](), [executive](), [fraud](), [generative-ai](), [scam](), [security](), [social-engineering]() ### AI overview Microsoft examines an email-fraud campaign that used AI-assisted executive impersonation, fabricated invoices, and fake supporting conversations to prompt ACH payments. ### Source excerpt Microsoft examines an AI-assisted business email compromise campaign that used executive impersonation and fake invoices to target finance teams with ACH payment fraud. The post Protecting organizations from AI-assisted executive impersonation and invoice fraud appeared first on Microsoft Security Blog. ## Will AI kill us all within the next decade? DevFeed: [Will AI kill us all within the next decade?]() Original publisher: [Read original article]() Author: Pieter Arntz Published: 2026-09-10T12:18:51Z Content type: opinion Language: en Sources: [Malwarebytes]() Topics: [Responsibility & Safety](), [AI Strategy](), [AI Development](), [Vulnerabilities](), [anthropic]() Tags: [ai](), [ai-safety](), [anthropic](), [autonomous](), [fraud](), [models](), [news](), [superintelligence](), [vulnerabilities]() ### AI overview The article discusses warnings about possible future AI risks while noting that current models are described as low risk. It argues for safeguards such as independent testing, limits on high-risk autonomous uses, transparency, and accountability, alongside action against AI-enabled cybercrime. ### Source excerpt AI researchers are warning that the technology could kill us all within the next decade, although they say the risk from current models is low. ## What Is SMS Pumping Fraud and How to Stop It DevFeed: [What Is SMS Pumping Fraud and How to Stop It]() Original publisher: [Read original article]() Author: Twilio Published: 2026-09-10T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [Security](), [Messaging](), [Bot](), [Authentication](), [Forms](), [Chat Bot]() Tags: [authentication](), [automated](), [bots](), [fraud](), [how-to](), [industry-insights](), [messaging](), [otp](), [security](), [verification]() ### AI overview This article explains SMS pumping fraud, also known as SMS toll fraud, in which attackers use bots and fake phone numbers to trigger large volumes of automated SMS messages. It describes impacts such as increased messaging costs and reduced conversion rates, and introduces detection and prevention measures. ### Source excerpt SMS pumping fraud is an urgent problem for businesses that use SMS. Learn more about SMS pumping and how to prevent it. ## Loyalty points fraud is funding hacker holidays (Lock and Code S07E18) DevFeed: [Loyalty points fraud is funding hacker holidays (Lock and Code S07E18)]() Original publisher: [Read original article]() Author: Malwarebytes Labs Published: 2026-09-07T18:23:18Z Content type: article Language: en Sources: [Malwarebytes]() Topics: [Cybercrime](), [passwords]() Tags: [account-takeover](), [airline](), [airline-miles](), [credit-card-points](), [cybercrime](), [fraud](), [hotel-rewards](), [loyalty-account](), [loyalty-points](), [loyalty-points-fraud](), [podcast](), [points](), [rewards-account](), [rewards-points]() ### AI overview A Lock and Code podcast episode examines loyalty-points theft, why criminals target points balances, and ways companies and consumers can protect against fraud. ### Source excerpt This week on the Lock and Code podcast, we speak with Kim Sutherland about loyalty points fraud and how everyday people can stay safe. ## Flirty OnlyFans promoters on X may be using AI to appear human DevFeed: [Flirty OnlyFans promoters on X may be using AI to appear human]() Original publisher: [Read original article]() Author: Pieter Arntz Published: 2026-09-07T11:18:00Z Content type: article Language: en Sources: [Malwarebytes]() Topics: [AI Chat](), [Script](), [Chat Bot](), [Bot](), [ASCII]() Tags: [ai](), [ascii](), [bots](), [fraud](), [generative-ai](), [messaging](), [onlyfans](), [scam](), [scams](), [scripted](), [threat-intel](), [voice]() ### AI overview An investigation examines X accounts promoting OnlyFans pages that combine repetitive flirtatious scripts with dynamic replies, raising the possibility of generative AI-assisted messaging. It warns that personalized responses and voice notes may no longer reliably distinguish people from automated accounts. ### Source excerpt Personalized replies and voice notes make it increasingly difficult to tell whether you're talking to a human, chatbot, or AI agent. ## How to Approve Real Users and Block Fake Accounts at Sign Up with Lookup and Verify in PHP DevFeed: [How to Approve Real Users and Block Fake Accounts at Sign Up with Lookup and Verify in PHP]() Original publisher: [Read original article]() Author: Kelley Robinson, Matthew Setter Published: 2026-08-31T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [PHP](), [API](), [Tutorial](), [data](), [Code]() Tags: [api](), [code](), [developer-insights](), [fake-accounts](), [fraud](), [github](), [how-to](), [lookup](), [onboarding](), [php](), [sign-up](), [verifications-and-identity](), [verify]() ### AI overview This tutorial shows how to use Twilio Lookup and Verify with PHP to collect a user's name and phone number, apply layered phone and identity checks, and block likely fake accounts during sign-up. ### Source excerpt Learn how to collect a user's name and phone number and conduct a multi-step orchestrated identity verification flow with Twilio's Lookup API. ## How to Confirm Phone Number Ownership with Lookup Identity Match DevFeed: [How to Confirm Phone Number Ownership with Lookup Identity Match]() Original publisher: [Read original article]() Author: Kelley Robinson Published: 2026-08-31T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [API](), [Code](), [Command-line interface](), [Serverless](), [JavaScript]() Tags: [api](), [cli](), [code](), [developer-insights](), [fake-accounts](), [fraud](), [how-to](), [javascript](), [reduce](), [request](), [serverless](), [verify]() ### AI overview This tutorial explains how to use Twilio Lookup Identity Match to confirm that a person is linked to a phone number. It covers matching submitted identity details against authoritative data, setting up a JavaScript project with the Twilio CLI and Serverless plugin, and using the result to reduce sign-up fraud. ### Source excerpt Send details like name, address, or date of birth and the Identity Match API will tell you if they match a provided phone number. Reduce fraud and verify identities quickly. ## How to Confirm Phone Number Ownership with Lookup Identity Match in PHP DevFeed: [How to Confirm Phone Number Ownership with Lookup Identity Match in PHP]() Original publisher: [Read original article]() Author: Kelley Robinson, Matthew Setter Published: 2026-08-31T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [PHP](), [API](), [.env]() Tags: [account](), [and-best-practices](), [api](), [code](), [developer-insights](), [fraud](), [how-to](), [lookup](), [php](), [tutorials](), [verification](), [verify](), [zero-knowledge]() ### AI overview This tutorial explains how to use Twilio Lookup Identity Match with PHP to confirm whether details such as a name, address, national ID, or date of birth match a phone number. It covers setup requirements, project configuration, and collecting the information needed for the match. ### Source excerpt Send details like name, address, or date of birth and the Identity Match API will tell you if they match a provided phone number. Reduce fraud and verify identities quickly in PHP. ## How to Approve Real Users and Block Fake Accounts at Sign Up with Lookup and Verify DevFeed: [How to Approve Real Users and Block Fake Accounts at Sign Up with Lookup and Verify]() Original publisher: [Read original article]() Author: Kelley Robinson Published: 2026-08-31T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [Node.js](), [Tutorial](), [API](), [Security](), [JavaScript](), [Bot]() Tags: [api](), [bots](), [developer-insights](), [fake-accounts](), [fraud](), [how-to](), [javascript](), [node-js](), [onboarding](), [tutorial](), [verification]() ### AI overview This tutorial shows JavaScript developers how to build a Node.js onboarding flow with Twilio Lookup and Verify. It combines line type checks, line status checks, name-to-phone identity matching, and SMS OTP verification to filter fake accounts and fraud while minimizing friction for legitimate users. ### Source excerpt Build a secure Node.js onboarding flow with Twilio. This tutorial covers 4 layers of defense: Line Type checks, Line Status, Identity Match (name-to-phone), and SMS OTP verification to stop bots and fraud. ## How to Confirm Phone Number Ownership with Lookup Identity Match in Python DevFeed: [How to Confirm Phone Number Ownership with Lookup Identity Match in Python]() Original publisher: [Read original article]() Author: Kelley Robinson, Dylan Frankcom Published: 2026-08-28T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [API](), [Python](), [Flask](), [Code]() Tags: [account](), [api](), [checkout](), [developer-insights](), [fake-accounts](), [flask](), [fraud](), [how-to](), [python](), [real-time](), [validation](), [verification](), [verify](), [zero-knowledge]() ### AI overview This tutorial explains how to use Twilio Lookup Identity Match with Python to confirm that a person is associated with a provided phone number. It builds a simple Flask application that collects a phone number and name, then uses the API to support fraud reduction and identity verification. ### Source excerpt Send details like name, address, or date of birth and the Identity Match API will tell you if they match a provided phone number. Reduce fraud and verify identities quickly. ## Paddle vs Lemon Squeezy: Same 5% + 50c, Very Different Bets DevFeed: [Paddle vs Lemon Squeezy: Same 5% + 50c, Very Different Bets]() Original publisher: [Read original article]() Author: Deepak Jangir Published: 2026-08-28T00:00:00Z Content type: comparison Language: en Sources: [Dodo Payments Blog]() Topics: [stripe](), [Software as a service]() Tags: [2026](), [comparison](), [digital-products](), [fraud](), [merchant-of-record](), [payments](), [pricing](), [recovery](), [saas](), [support](), [tax]() ### AI overview This comparison argues that Paddle and Lemon Squeezy have the same headline Merchant of Record pricing but target different customers. Paddle is positioned for B2B SaaS at scale, while Lemon Squeezy is aimed at indie makers and digital products. The article also explains how Stripe's acquisition of Lemon Squeezy and the rollout of Stripe Managed Payments change the comparison in 2026. ### Source excerpt Paddle and Lemon Squeezy both charge 5% + 50c as Merchant of Record. Compare who they serve, what changed after Stripe bought Lemon Squeezy, and the real costs. ## How to Approve Real Users and Block Fake Accounts at Sign Up with Lookup and Verify in C# DevFeed: [How to Approve Real Users and Block Fake Accounts at Sign Up with Lookup and Verify in C#]() Original publisher: [Read original article]() Author: Amanda Lange, Dhruv Patel, Kelley Robinson Published: 2026-08-28T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [C#](), [API](), [.NET 9]() Tags: [auth](), [c-sharp](), [developer-insights](), [fake-accounts](), [fraud](), [how-to](), [lookup](), [onboarding](), [sign-up](), [verification](), [verify]() ### AI overview This tutorial shows C# developers how to combine Twilio Lookup and Twilio Verify to screen phone numbers during sign-up, verify identity, and block fake accounts. It covers line-type, reachability, identity-match, and phone-possession checks. ### Source excerpt How to Approve Real Users and Block Fake Accounts at Sign Up with Lookup and Verify in C Sharp ## AI-driven OSINT in the wrong hands - and why everyone could be a target for fraud DevFeed: [AI-driven OSINT in the wrong hands - and why everyone could be a target for fraud]() Original publisher: [Read original article]() Author: Phil Muncaster Published: 2026-08-27T09:00:00Z Content type: article Language: en Sources: [WeLiveSecurity]() Topics: [Artificial Intelligence](), [Reconnaissance](), [Social engineering](), [Web](), [Malware]() Tags: [ai](), [attacks](), [fraud](), [malware](), [phishing](), [privacy](), [research](), [social-engineering](), [vulnerability]() ### AI overview AI-powered OSINT is making it faster and easier for cybercriminals to gather publicly available information about potential victims. By linking accounts, relationships, images, and videos at machine speed, these tools can make fraud and social engineering more convincing and scalable, lowering the barrier to entry for attackers. ### Source excerpt It's getting cheaper and easier for cybercriminals to research potential victims. Here's what's still in your control. ## How to Approve Real Users and Block Fake Accounts at Sign Up with Lookup and Verify in Python DevFeed: [How to Approve Real Users and Block Fake Accounts at Sign Up with Lookup and Verify in Python]() Original publisher: [Read original article]() Author: Kelley Robinson, Dylan Frankcom Published: 2026-08-27T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [Python](), [API](), [Code](), [zero-knowledge]() Tags: [apis](), [code](), [developer-insights](), [fake-accounts](), [fraud](), [how-to](), [identity](), [python](), [verification](), [zero-knowledge]() ### AI overview This tutorial shows how to use Twilio Lookup and Verify APIs in Python to build a multi-step sign-up verification flow. It combines phone line-type, reachability, identity-match, and phone-possession checks to filter fake accounts while maintaining a smooth onboarding experience. ### Source excerpt Utilize Twilio Lookup and Verify APIs to build secure onboarding flow in Python, blocking fake accounts and approving real users. [Next page]()