Sigma provides a backend-neutral detection signature language for logs that can be converted to a variety of different query languages such as Splunk SPL or Sentinel KQL. This post walks through a Sigma rule to explain the components and syntax. It then introduces some more advanced features such as pipelines to resolve mapping issues between rules and data sources and correlation rules to provide stateful detections.
Backline's AI agents act as software and security engineers, analyzing potential vulnerabilities, collecting context, and determining how to optimally address an issue for the customer's specific environment. The agents then autonomously implement the needed code and configuration changes.
YaraMonitor is a tool that monitors malware samples using YARA rules. It continuously analyzes and alerts on new uploads from sources like MalwareBazaar and can be extended to monitor additional sources. Running the main.py script from the root folder will automate the ingestion and scanning process for malware samples.
Cash App's security team devised a Data Safety Levels (DSL) Framework based on the CDC's biosafety levels to utilize for data classification. The framework takes a dataset level approach to devise standardized rubrics for evaluating data based on its usage such as Consumer Personal Data and Payment Card Data. The framework couples with automation to be able to classify data as part of Block teams' regular workflows as well as guidelines on how to handle data of various sensitivity levels.
An executive-level brief on common classes of security issues. The first three focus on vulnerabilities in code such as lack of input validation, lax or missing authentication, and lack of API protections. The last two focus on lack of appropriate tools like WAFs and insufficient or inefficient automations.
DARPA is developing an ambitious project called Red-C that aims to create self-healing firmware capable of automatically detecting, responding to, and recovering from cyberattacks at the bus level of computer systems, though the project faces significant technical and adoption challenges.
Want to go from practitioner to leader? Here's an opportunity to set yourself apart, build strong fundamentals across functions, and gain a global network on par with top traditional B-schools.
Astronomers are calling for a global ban on space advertising, warning that it threatens scientific research and the natural night sky. The American Astronomical Society stated that obtrusive ads in low Earth orbit should be prohibited through international agreements. While the U.S. already bans domestic launches of space billboards, companies in other countries, like Russia's Avant Space and StartRocket, have explored the idea. Privatized spaceflight is growing rapidly, making regulation more complex as private companies prioritize commercial interests. Scientists argue that space billboards would worsen light pollution, interfere with telescopes, and diminish humanity's connection to the night sky.
Meta plans to refresh Facebook in 2025 to attract younger users, as Gen Z engagement has plummeted from 71% in 2014-2015 to 33% in 2024. Mark Zuckerberg warned investors that the changes may impact short-term revenue and hinted at a return to Facebook's early features. Gen Z spends twice as much time on TikTok as the average U.S. adult and prefers platforms like Instagram and Snapchat, making Facebook's revival uncertain. Meta has attempted Gen Z-focused redesigns and other strategies, but younger users continue to move toward decentralized social networks and alternatives like RedNote.
Employee-generated content is reshaping brand social strategies. Brands like Anthropologie, Sotheby's, and the Philadelphia Eagles are using employees to create high-performing content. A well-structured EGC program involves selecting employees who naturally enjoy content creation, providing guidelines without stifling creativity, and integrating EGC into broader brand storytelling. When done right, EGC fosters deeper audience connections and enhances authenticity, making brands more relatable and approachable to the customer.
The trend toward long-term influencer partnerships is growing, with 63% of brands favoring sustained collaborations. As a result, 62% are working with more than 10 influencers. Brands are also prioritizing content quality, with 37% ranking content production as their top selection factor. This shift reflects a deeper focus on building lasting relationships and measuring the direct impact on sales.
Your marketing drives clicks—but what about calls? If you're not tracking inbound phone leads, you're missing a major piece of the performance puzzle. CallRail connects every conversation back to your marketing, helping you spend smarter and convert more leads. Here's what you need to know:
This guide goes beyond a standard calendar by categorizing key opportunities into calendar moments (fixed events), seasonal themes, and life moments (personal milestones) to help businesses plan campaigns. It includes relevant search keywords for each category and offers insights into when Pinterest users start engaging with these topics.
Marketing leaders can use allocation models to prioritize resources effectively and align teams. Explicit numerical allocations (e.g., 80/20 or 70/30) clarify strategy and prevent teams from making conflicting trade-offs. Growth potential, market opportunity, strategic importance, and competition should influence allocations beyond revenue alone. The article includes an example template of a strategy investment allocation model.
Dutch Bros stands out by doing the opposite of Starbucks, focusing on fast, cold, high-energy drinks and an experience built on personal connections. Its employees, called "bro-istas," create a friendly, high-energy atmosphere that makes the drive-thru feel like a social event. The brand drives loyalty with a generous rewards program, limited-edition merch and drink drops, and engaging social media that feels authentic. Dutch Bros' approach has turned customers into diehard fans who see it as more than just a coffee shop. Its success comes from selling not just drinks, but hype, energy, and a sense of belonging.
Consumers don't have a fixed “consideration set” - instead, brand choices are fluid and shaped by context. Research shows that buyers often consider just 1-3 brands, with decisions driven by immediate needs, environments, and prior experiences rather than a predefined list. Marketers can better influence purchasing behavior by focusing on Category Entry Points (CEPs), which are mental cues that link consumer situations to brands, rather than outdated consideration metrics.
Google is airing 50 Super Bowl commercials, each featuring a small business that uses AI through Google Workspace. The campaign shows how the businesses use Gemini for tasks like drafting content, managing inventory, and marketing. Produced in 10 weeks, the commercials highlight real entrepreneurs who use AI to streamline operations and focus on what they love.
The next frontier of marketing lies in AI-powered personalization, which allows brands to optimize promotions, tailor messaging, and improve engagement with precision.
Business fraud is growing rapidly in volume and sophistication as criminals incorporate advanced AI + automation. Companies that don't understand it are sitting 🦆 (or 🐟 in a barrel), risking profits, reputation, and lawsuits.
Product operations lacks a single definition, as its role varies across companies, encompassing strategy enablement, scaling product management, improving PM experiences, and shaping product culture. This diversity is a strength, allowing teams to adapt product ops to their needs and ensuring its impact remains flexible and valuable.
The focus is shifting from AI infrastructure spending to what can be built with it, exposing underwhelming results from generative AI products despite the hype. Cheaper AI could drive innovation, but its future utility and advancement remain uncertain.
Going viral on social media often brings a surge of low-quality users, or "Looky-Loos," who don't stick, making such spikes unsustainable. True success lies in durable growth, scalable channels, and high-intent users, measured by retention and long-term engagement, not fleeting DAU increases.
The Product Operating Model encompasses three dimensions: product strategy, product discovery, and product delivery, with Agile primarily contributing to the third. While Agile principles remain valuable, the product model extends beyond Agile's scope by focusing on solving the right problems and achieving outcomes, making experience in product strategy and discovery more critical than certifications.
Successful companies drive AI adoption through clear websites, strategic pricing, personalized onboarding, and seamless workflow integration. They highlight AI's value with free resources, tailored trials, premium add-ons, and timely feature discoverability to build lasting user engagement.
Assumption testing replaces guesswork with evidence, ensuring product decisions align with user needs and business goals. It prevents costly mistakes, fosters innovation, and drives better outcomes by validating ideas before development.
AI regulation should target harmful uses, not development, to protect consumers and promote innovation. Regulating model creation burdens startups, stifles competition, and fails to address harms. Strengthening enforcement of existing laws ensures accountability without hindering innovation.
Many professionals face career stagnation despite strong performance due to factors like managerial turnover, unclear promotion paths, or insufficient advocacy.
Let's Encrypt, a free certificate authority, faced challenges scaling its rate-limiting system to handle over 550 million websites and 340,000 certificate requests per hour. Its initial MariaDB-based system wasn't enough, as it caused slowdowns and frustrated users with long wait times. To address this, the company migrated to a Redis-based system that used the Generic Cell Rate Algorithm (GCRA), allowing it to handle a billion active certificates and even addressing the issue of "zombie clients" making repeated failed requests.
In React, the Open-Closed Principle (OCP) means that components should be designed in a way that allows them to be extended with new functionality without modifying their existing code. As an example, the article shows the contrast between a closed, modification-heavy button component with an open, composition-based approach that uses base components and extending variants. There's an alignment between OCP and React's "composition over inheritance" philosophy, where OCP leads to more flexibility.
One should pause before making a decision, since taking time allows for better perspective and the chance to avoid regrettable actions. This author shares personal anecdotes that illustrate how pausing prevents rushed estimations and impulsive responses to emails.
This developer criticizes Rust's nightly `core::io::BorrowedBuf` feature, arguing it's a complex and flawed solution to the problem of unnecessary buffer initialization in I/O operations. The feature aims to allow reading into uninitialized memory, but its integration with existing code is poor and requires explicit support from various APIs, which could lead to potential misuse.
Greenmask is an open-source tool for PostgreSQL database backup, anonymization, synthetic data generation, and restoration. It has features like deterministic transformers, dynamic parameters, and parallel execution, and it supports various storage options.
Ruck is an open-source, buildless React framework for Deno that uses ESM, dynamic imports, and import maps to create React web apps without build steps. It has features like dynamic routing, server-side rendering with component-level data fetching, and declarative CSS management.
Jane Street initially created Jenga, an OCaml build system, but its limited reach and platform incompatibility led to its un-open-sourcing. It then developed Jbuilder, a simpler, cross-platform tool, which unexpectedly gained popularity due to its speed. Jbuilder evolved into Dune, a more robust build system, after a name change and significant community contributions.
2024 saw a resurgence in decompilation research, with nearly 30% of all top-tier publications in the field's history appearing that year. This surge included advancements in defining "good" decompilation, the incorporation of AI techniques for tasks like symbol prediction, and a significant increase in open-source implementations of academic work.