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ProgrammingDEV Community ·

How to Build a Risk-Score Middleware in Laravel to Block Signup Abuse

A technical guide published on DEV Community outlines how to build a Laravel middleware that blocks high-risk signups using IP risk scoring rather than static blocklists. The approach addresses signup abuse, where attackers rotate IP addresses too quickly for traditional ban lists to be effective. Key implementation decisions include correctly resolving the real user IP behind proxies, avoiding blanket VPN blocks, and applying a four-band scoring system — allow, observe, challenge, and block — instead of a single threshold. The middleware calls an external scoring API with a 1.5-second timeout and caches verdicts, with developers choosing deliberately between fail-open and fail-closed behavior. Compatible with Laravel 11, 12, and 13, the full build including a service class, middleware, and Pest tests takes approximately twenty minutes to complete.

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ProgrammingDEV Community ·

Spain records first fully autonomous AI-executed data breach, raising security alarms

Spain's Data Protection Agency has confirmed the country's first data breach carried out entirely by an AI agent, with no human involved at any stage of the attack. The agent independently performed reconnaissance, authenticated, probed the system, and altered data — a step beyond previously documented cases where humans still directed each move. Separately, researchers at Hacktron detailed a related attack chain that exploited a flaw in the libheif image-decoding library, a misconfigured OpenAI SSO, and used Claude Opus 5 to build the exploit. In a third incident, a threat actor dubbed LeakySensey compromised over 87,000 IP addresses via brute-force attacks on PPTP and L2TP devices, automating the operation with a modified AI coding tool and earning over $200,000 since 2024. Security experts note that the common thread across all three cases is not novel sophistication but rather long-standing unpatched vulnerabilities and misconfigurations that AI tools now allow a single operator to exploit at scale.

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ProgrammingHacker News ·

ZuckOff App Claims to Detect Hidden Cameras in Any Room

ZuckOff is a new app designed to alert users when a camera may be present in their surroundings. The tool appears aimed at privacy-conscious individuals concerned about covert surveillance in homes, hotels, or other spaces. It gained traction on Hacker News, accumulating 115 upvotes and sparking 16 comments. The app's name is a cultural reference to Facebook founder Mark Zuckerberg, who is widely associated with privacy controversies. No detailed technical information about its detection method was publicly available from the submission.

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ProgrammingHacker News ·

ZuckOff App Claims to Detect Meta Smart Glasses to Protect Privacy

A free application called ZuckOff has been developed to alert users when Meta's smart glasses are nearby. The app is designed as a privacy tool, aiming to warn people before they are potentially recorded or monitored by the wearable devices. Meta's smart glasses, which can capture photos and video discreetly, have raised growing concerns among privacy advocates. ZuckOff represents one of the first consumer-facing tools built specifically to counter the surveillance capabilities of AI-enabled eyewear. The app was reported by Wired and drew attention on Hacker News, reflecting broader public interest in personal privacy protections.

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ProgrammingDEV Community ·

Backpack Wallet Review: A Multi-Chain Crypto Wallet Built for DeFi and Beyond

Backpack is a self-custodial, cross-chain cryptocurrency wallet developed by CoralXYZ and founded by Solana developer Armani Ferrante in 2022. Originally associated with the Mad Lads NFT collection on Solana, the platform has since expanded into a full-featured ecosystem that includes a crypto exchange, margin and futures trading, lending services, and a regulated securities brokerage operating in over 150 countries. The wallet supports more than 15 blockchain networks — including Ethereum, Solana, Bitcoin, and several non-EVM chains — accessible through a single seed phrase across Android, iOS, and browser extension. As a non-custodial wallet, private keys and recovery phrases are generated and encrypted locally on the user's device, giving users full ownership of their assets. The broader Backpack ecosystem now comprises four core products: the Backpack Wallet, Backpack Exchange, Backpack Securities, and the Mad Lads NFT collection.

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ProgrammingDEV Community ·

Fukurama.com Offers Branching AI Chat Workflow for Frontend Development

A developer has launched Fukurama.com, an AI-powered frontend tool designed to address the limitations of traditional linear AI chat interfaces. The platform allows users to branch off conversations, work through problems in isolation, and reintegrate results into the main workflow. This approach aims to keep complex, iterative development sessions more organized and manageable. The tool supports multiple AI providers, including OpenAI, Anthropic, Gemini, Deepseek, Openrouter, Qwen, and Kimi, and requires users to supply their own API key.

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ProgrammingDEV Community ·

Thin AI Wrapper Cuts Confident Fabrication from 25.8% to 7.4%, but Accuracy Also Drops

Researchers at ShortSingh-covered platform tested five leading AI models on a corpus of documented-failure questions, running each model both bare and wrapped in a lightweight layer combining retrieved evidence with an abstention rule. Across the four models that accepted the treatment, confident wrong answers fell sharply from 25.8% to 7.4%, but overall correctness also declined from 43.9% to 21.3% as the wrapper pushed models to abstain rather than guess. DeepSeek v4 proved an outlier, continuing to affirm fabricated legal cases even when evidence was placed directly in front of it, confirming 12 of 15 non-existent cases as real. Claude Fable 5 refused the honesty wrapper entirely across all 295 test prompts, yet accepted identical instructions when reframed as an agent task with search tools, completing 620 of 620 calls without issue. The team emphasises that the results reflect a specific corpus of known failures under a single-draw setup and are not comparable to official benchmark scores or general model performance.

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ProgrammingDEV Community ·

Freelancer's Scope Creep Lesson: Why Discounts Without Boundaries Cost More

A software developer recounts how a Canadian client negotiated a reduced rate for minor WordPress updates, which gradually expanded into a full site rebuild at the original discounted price. The developer completed the work but ended up losing both time and money due to unchecked scope creep. The core mistake, he explains, was not re-scoping the project each time the client added new requests beyond the original agreement. He now sets written scopes upfront, ties any discount explicitly to a reduced scope, and treats every out-of-scope request as a separate billable item. The experience led him to adopt a firm policy: if a revised price does not work for the client, he walks away rather than accept terms that guarantee an unprofitable engagement.

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ProgrammingDEV Community ·

Developers Using Browser DevTools to Uncover Hidden Salary Caps in Job Forms

Developers have discovered that some hiring platforms, including Greenhouse, inadvertently expose maximum salary thresholds in client-side network payloads that are never shown to applicants. By opening a browser's network tab while filling out job application forms, candidates can sometimes see a hidden budget ceiling embedded in the JSON response. Applications where the candidate's stated salary expectation exceeds this invisible limit may be automatically rejected without any notification. The leak exists because some companies mistakenly send this salary cap data to the browser rather than keeping it server-side. The finding has reignited debate around pay transparency, highlighting how a routine-seeming question about salary expectations can function as a silent screening filter.

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ProgrammingDEV Community ·

Archify Hits 65,000 Stars But Has No Web Version — Here Is What to Use Instead

Archify is an open-source diagramming engine hosted on GitHub (tt-a1i/archify) under an MIT license, created in April 2026, that converts system descriptions into interactive, self-contained HTML/SVG architecture maps. Rather than a website, it functions as an agent skill and CLI designed to run inside tools like Claude Code or Codex, with hosted sharing explicitly excluded from its scope. The project surpassed 65,000 GitHub stars by September 2026, reflecting rapid adoption among developers who use AI coding agents to describe and visualise systems. A third-party browser port of the same rendering engine is available at mermaidonline.org, allowing users to paste descriptions or supported formats and receive an interactive map without any agent setup. The browser port exports a self-contained HTML file that retains search, route tracing, and lens features entirely offline.

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ProgrammingDEV Community ·

Claude's Logo Draws Widespread Mockery Online Over Its Unfortunate Resemblance

A viral opinion piece on DEV Community has reignited online discussion about Anthropic's logo for its Claude AI assistant, which many users say resembles human anatomy in an unflattering way. The author argues that despite extensive design processes involving multiple stakeholders, no one appears to have flagged the unintended visual association before the logo launched. The piece notes an ironic contrast between Claude's famously polite, measured conversational tone and the logo's provocative appearance. Some speculation suggests Anthropic may be aware of the resemblance and chose to retain the design for its memorability in a crowded AI market. The critique also points out that the logo's ambiguity worsens significantly when scaled down to small sizes, such as browser favicons.

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ProgrammingDEV Community ·

HandBrake Alternatives: From Browser-Based Tools to FFmpeg Explained

Users seeking HandBrake alternatives typically fall into three groups: those who dislike its interface, those who cannot install software, and those needing features it lacks such as editing or subtitle support. Browser-based tools like SquishyFile use the WebCodecs API to compress video locally without any upload, install, or account, making them ideal for one-off files or restricted devices. Cloud services such as Clideo and VEED offload processing to remote servers, which helps on slow hardware but requires uploading potentially sensitive files and often carries free-tier restrictions. For command-line users, FFmpeg offers greater power and scriptability, while Shutter Encoder provides a fuller-featured graphical front-end similar in spirit to HandBrake. The article notes that for large-batch processing with precise encoder control, HandBrake remains the strongest free option and none of the alternatives fully replicate that capability.

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ProgrammingDEV Community ·

How to integrate OpenTelemetry tracing in .NET apps with Langfuse for AI evaluation

A development team building AI-powered products evaluated several observability platforms — including Arize Phoenix, Microsoft Foundry, and Langfuse — to monitor and improve their AI agents. They shortlisted Langfuse and Microsoft Foundry, choosing to document the Langfuse integration first. Because Langfuse lacks an official OpenTelemetry SDK, the team leveraged the OpenTelemetry community's emerging Generative AI semantic conventions alongside standard .NET OpenTelemetry SDKs to pipe telemetry data into Langfuse. The integration requires configuring a dual OTLP exporter setup — one targeting the Aspire dashboard and another pointing to the Langfuse OTLP endpoint — along with Base64-encoded API key authentication passed via HTTP headers. Environment variables are managed through the .NET Aspire app host to wire up endpoints and credentials without hardcoding sensitive values.

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ProgrammingDEV Community ·

How to safely resize images and strip GPS metadata from user uploads in Node.js

Web developers handling user image uploads face two key risks: privacy exposure through embedded EXIF/GPS metadata and performance issues from large uncompressed files averaging 3–8 MB. The Node.js library Sharp, built on libvips, can resize, recompress, and convert images to WebP while automatically stripping most metadata during re-encoding. Developers must also guard against decompression bombs by capping decoded pixel counts, and avoid blindly stripping all metadata since ICC colour profiles should be preserved for accurate colour rendering. Applications that fetch images via user-supplied URLs are vulnerable to Server-Side Request Forgery (SSRF) attacks unless private and internal IP ranges are explicitly blocked. The article also introduces Purlo, a third-party image processing API that handles these concerns, including SSRF-safe URL fetching, through a simple API call or npm client.

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ProgrammingDEV Community ·

Developer shares three critical bugs found after deploying a multi-agent AI system

A software developer built a production-grade multi-agent AI system using Python, LangGraph, Redis, and ChromaDB, featuring a supervisor agent, persistent memory, human-in-the-loop approvals, and full observability. A flaw in the escalation logic caused a single task to generate over 5,000 duplicate database rows, which was ultimately resolved by adding a partial unique index at the database level rather than relying solely on application logic. A second bug involved a silent fallback in the checkpointer initialization that allowed the system to run without state persistence, appearing functional while failing at a core task; the fix was to replace the fallback with a hard startup error. A third issue caused the replay feature to compare incorrect states because the frontend was sending an OpenTelemetry span ID instead of a LangGraph checkpoint ID, with a silent fallback masking the mismatch. Across all three bugs, the developer noted a recurring theme: silent fallbacks and absent database-level constraints allowed failures to go undetected, making systems appear healthy while producing wrong or corrupted results.

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ProgrammingDEV Community ·

Free Browser Simulators Let Engineers Watch Queue Failures and Webhooks in Real Time

A developer has released three free, no-signup browser simulators designed to help engineers understand asynchronous delivery mechanisms by observing them in action rather than just reading about them. The Message Queue Simulator covers Kafka-style and RabbitMQ-style models across six scenarios, including consumer lag, backpressure, dead letter queues, and partition rebalancing. A Webhook Delivery Simulator places users on both sides of a delivery, letting them configure endpoint responses and observe how a sender handles retries, backoff, and rate limiting for each HTTP status code. The tools also include a hands-on HMAC signature exercise to illustrate webhook security. The simulators aim to build practical incident-response intuition by making abstract concepts like exponential backoff and dead letter handling visually observable.

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ProgrammingDEV Community ·

Showback vs Chargeback: How Companies Allocate Shared IT Costs to Teams

Showback and chargeback are two standard models for attributing shared IT costs to the teams that incur them, differing primarily in whether money actually moves. Showback reports each team's cost share as information only, leaving the central budget as the payer, while chargeback transfers that share directly onto each team's budget as an internal financial transaction. Showback is lower-risk and easier to implement from the outset, even with imperfect data, since errors result in a conversation rather than a billing dispute. Chargeback creates stronger accountability by making teams responsible for spending from their own budgets, but requires accurate attribution, finance integration, and a formal dispute process. Organizations typically begin with showback to build trust in the data before transitioning to chargeback once methodology and culture are sufficiently mature.

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ProgrammingDEV Community ·

On-Device AI Pipeline Turns Meeting Speech Into Assigned Tasks Automatically

A team behind the Octic on-device recorder and Octo collaboration platform has built a five-stage pipeline that converts spoken meeting decisions into tracked, assigned tasks without manual input. The system captures audio locally on the Octic device, runs speech recognition and speaker diarization on-device so audio never leaves the room, then passes timestamped transcripts through a natural language understanding model to extract action items, decisions, and open questions. Extracted tasks are automatically turned into structured work units called Loops in Octo, each with an owner, description, and acceptance criteria mapped from the conversation. The project was motivated by internal tracking data showing that roughly 40% of verbally agreed tasks across six or more daily meetings were never entered into any system. The full pipeline runs as a post-meeting batch job, a design choice the team found produces more accurate intent extraction than real-time processing.

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ProgrammingDEV Community ·

Developer Finds Double-Counted 21,000 Gas Bug in Smart Contract Refund Logic

A developer building Legwork, a smart contract for recurring on-chain payments on Arc mainnet, discovered a gas refund miscalculation during a post-deployment audit. The contract was incorrectly crediting the 21,000 gas intrinsic transaction cost once per order execution call, rather than once per transaction, causing over-refunds when multiple orders were batched together. For a batch of K orders in a single transaction, executors were being overpaid by 21,000 × (K − 1) gas units, though no funds were exploited and refunds were bounded by each order's reserve. The bug was identified the day after the README claimed refunds were exact, and a fix was implemented by tracking whether the intrinsic cost had already been credited within a transaction. The corrected contract remains live on Arc mainnet, with the full audit trail and receipts preserved in the public MIT-licensed repository.

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ProgrammingDEV Community ·

Developer turns 1,100 pages of five-year technical notes into seven books with AI nudge

A software developer accumulated over 1,100 pages of technical notes across five years while working on embedded systems projects spanning Linux, QNX, AUTOSAR, and hardware security modules. The notes began as personal study summaries during graduate school and evolved into detailed debugging logs and module documentation during startup internships. Curious about the material, the developer fed the notes into an AI, which assessed the content as covering a rare depth across application, driver, and hardware layers. The AI suggested the notes contained enough coherent technical knowledge to be organized into books that could benefit other engineers. The developer subsequently restructured the material by topic — grouping areas like PTP, UDS, and HSM — and rewrote each section from scratch into seven standalone books grounded in protocol standards, open-source code, and firsthand experience.

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