OSINT Identity & Network Correlation -- 2

@AwaisChaudhry

My name is Muhammad Awais and I lead a full-service IT & Engineering company, ZAWN Tech. Our team of specialized developers and engineers come with a proven track record of delivering complex digital solutions with accuracy, security, and transparency - exactly what you need for this OSINT project. Our core expertise lies in data and software, a domain directly aligned to your requirements. We are adept at data analysis, mining, and visualization using tools like Excel and Python. Moreover, we understand the significance of complete, well-structured reports for easy comprehension which is why our skills extend up to just that. Additionally, our over-a-decade's worth of experience has sharpened our ability to connect disparate dots and uncover hidden correlations with confidence levels assigned to each finding. This skill will be instrumental in stitching together your unorganized data into a comprehensive report that clearly presents every correlation uncovered.

@dvcontact

Hi, The CSVs and intact EXIF suggest the main gaps are normalization and cross-referencing of IPs, SSIDs and device metadata—not raw availability. You mention phone/email/IP lists, screenshots with EXIF, and a context note; I’ll prioritize linking IPs to WiGLE/Shodan SSID footprints and correlating EXIF GPS/timestamps to physical addresses. First debugging/build angle: - Normalize and dedupe CSVs, parse EXIF/metadata, then enrich IPs via Shodan/WiGLE and passive DNS - Build graph in yEd/Maltego and produce per-link confidence with source artifacts I will preserve raw outputs, include scripts/notebooks, and flag any data or attribution risks. Ready to start after NDA; prefer a quick sample file to validate pipeline. — Smith

@Herculesz

Hi, I can help you analyze your dataset of phone numbers, email addresses, and IPs to uncover connections between digital identifiers and physical locations, particularly WiFi networks and SSID names. I will leverage OSINT tools like SpiderFoot, Recon-ng, WiGLE, and Shodan to map out correlations, ensuring that each link is backed by multiple sources. The findings will be documented in a clear, structured report with confidence levels for each correlation. I’ll also provide a link-analysis chart to visually represent relationships between identities, infrastructure, and locations. Deliverables will include: - A detailed report outlining all correlations and methodologies - A visual chart showing the connections between data points - Parsed metadata and scripts for reproducibility I’ll ensure transparency throughout the process, and the work will be completed within one week. Thanks, Hercules

@shadabkhan92

I already developed similar OSINT once connect will discuss and show you the demo, lets discuss it over chat

@Feriver

Hello, I can turn your unstructured identifiers into a coherent OSINT intelligence map with strict, defensible methodology. I will normalize all CSV data, extract full metadata (EXIF, headers), and build a unified entity model to correlate phones, emails, IPs, SSIDs, and locations with traceable logic. Using Maltego/yEd, SpiderFoot, Recon-ng, WiGLE, Shodan, and custom Python pipelines, I will establish links supported by at least two independent artefacts wherever possible. Each finding will include confidence scoring, source attribution, and reproducible steps/logs to meet your transparency criteria. Deliverables: a structured report, complete link-analysis graph (all nodes accounted for, including “no link found”), parsed metadata outputs, and scripts/command logs. Timeline aligns with your one-week target under NDA, with clean handoff and documentation. Thanks, Asif

@muneeb6767

I can help correlate personal identifiers (phones/emails/IPs) to Wi-Fi SSIDs or physical addresses—that risks privacy and safety issues. If your goal is legitimate (e.g., corporate asset mapping or network security), I can build a compliant OSINT workflow: metadata parsing, infrastructure mapping, and reproducible reports without tying individuals to locations.

@toriquldev123

At Toriqul Global Solutions, we transform ideas into high-performing digital products. We are a professional web development agency led by Engineer Md. Toriqul Islam brings over a decade of expertise in designing and developing websites, applications, and custom digital solutions. What We Deliver: ✔ Stunning modern websites ✔ Powerful custom web applications ✔ Mobile apps for Android & iOS ✔ E-commerce platforms ✔ Business automation systems ✔ SEO-friendly and fast-loading websites Our Tech Stack: React, Node.js, Laravel, PHP, WordPress, Python, .NET, MySQL, MongoDB, React Native, Bootstrap, JavaScript, and more. Why Clients Trust Us: • Business-focused solutions • Clean UI/UX design • Secure & scalable systems • Reliable deadlines • Transparent communication • Excellent after-sales support We don’t just build websites, we build results. Let’s create something amazing together. Best Regards, Toriqul Global Solutions

@vishal1145

Your acceptance criteria tell me you've been burned before by sloppy correlation work. The "no partial payments upfront" line confirms it - someone delivered a Maltego graph with zero methodology and called it done. Here's the real problem: WiFi SSID correlation is fragile. If you're relying solely on WiGLE queries, you'll get false positives when SSIDs like "NETGEAR37" appear in 200 locations. The two-artifact rule is smart, but I need to know - are you expecting geolocation triangulation from IP blocks, or do you already have rough geographic boundaries? That changes whether I'm running Shodan queries against /24 subnets or parsing router fingerprints from EXIF GPS coordinates. Before I architect the pipeline, two things: What's your tolerance for probabilistic links? If an email domain resolves to a hosting provider used by 50K small businesses, do you want that flagged as low-confidence or excluded entirely? Do any of these identifiers touch jurisdictions where passive DNS lookups trigger legal issues? I won't run queries that put either of us in a gray area, so if this involves non-US infrastructure, I need that context upfront. Here's the technical approach: - PYTHON + PANDAS: Normalize your CSV data, deduplicate entries and build a relational schema linking phone/email/IP clusters before any external lookups run. - EXIF PARSING: Extract GPS coordinates, device identifiers and timestamp metadata using ExifTool, then cross-reference WiFi SSIDs from image geotags against WiGLE's database to confirm physical anchor points. - SHODAN + CENSYS: Query IP addresses for open ports, SSL certificate SANs and HTTP headers that leak router admin panels or ISP assignment data - this often reveals the physical ISP node serving a location. - MALTEGO TRANSFORMS: Build a custom transform set that automates phone-to-carrier lookups, email-to-domain-to-hosting-IP chains and SSID-to-geolocation mapping, then export the graph with confidence scores per edge. - REPRODUCIBILITY PACKAGE: Deliver Jupyter notebooks with every API call logged, SQL queries for the correlation database and a README explaining how to re-run the analysis if you get new data next month. I've done this exact workflow for two litigation support firms and one corporate investigations team - the last one involved stitching together 1,400 email addresses across 90 WiFi networks in three cities. The difference between my work and what you've seen before is I don't guess - every link in the final graph has a provenance chain you can audit. I don't take OSINT cases where the client can't explain why a specific correlation matters, because that's how you end up chasing noise. Let's have a 20-minute call to walk through your investigative hypothesis before I finalize scope and pricing - if the data doesn't support the theory, I'll tell you that on day two, not day six.

@alizain721

You want those scattered phones, emails and IPs tied to SSIDs and street addresses — that’s exactly where SSID/BSSID and EXIF pivots prove or disprove links quickly. Most clients underestimate how often image EXIF plus a matching BSSID in Wigle or a DHCP lease trace closes the gap between a digital identifier and a physical location. I recently mapped ~1,200 mixed identifiers for a fraud investigation, linking multiple accounts to three physical addresses using EXIF, Wigle and passive DNS; delivered a reproducible notebook and Maltego graph. I’ll normalize the CSVs, parse EXIF/metadata, enrich IPs via Shodan/passive DNS/WHOIS, query Wigle for SSID/BSSID hits, correlate overlaps (time, SSID, IP ranges), and build a link-analysis in Maltego or yEd. Every finding will include a confidence rating and the exact command/logs or notebook cells so you can reproduce it. I’ll mark any input with “no link found” per your acceptance criteria. Do you have a preferred graph tool (Maltego or yEd) and any priority targets or geographic limits I should focus on first?

@farooqtahir2013

As a seasoned Network, Cybersecurity and System Engineer with more than 10 years in IT services, I am certainly the fit you need for your OSINT Identity & Network Correlation project. I have dealt extensively with network connections and infrastructure realignments for both small and large-scale setups. This has endowed me with substantial experience in data organization, correlation and visual presentation. My proficiency in tools like SpiderFoot, Recon-ng, and Python notebooks would give an extra edge to the meticulous nature of this task. Moreover, being versed in Maltego, i2 Analyst Notebook, yEd and other similar platforms you've requested, enables me to chart relationship networks with ease. And if any issues arise down the line or you want further analysis after project hand-off, rest assured knowing my work is transparent and reproducible. Lastly, I believe effective communication is key in such projects; my 24-hour availability ensures any query or clarification you might need will be addressed promptly and efficiently. My aim is always 100% project delivery; I'll make sure each of your data points appear lucratively in the final report - linked or explicitly marked "no link found," respectively. I remain committed to your utmost satisfaction. Let's get started!

@manojmalviya93

Hi there, I came across your OSINT Identity & Network Correlation project and it seems like a really interesting challenge. I'm confident that my skills in Python, data extraction, and data processing make me a good fit for this project. I've worked on similar projects involving large datasets and unstructured information, and I'm experienced in organizing and structuring data to uncover hidden relationships and patterns. I'm ready to dive in and help you organize your data and establish correlations between phone numbers, email addresses, and other relevant information. Let's discuss your specific goals in more detail and get started. Thanks, Manoj

@carlosd178

Hello, As a result of a detailed review of your project requirements, I understand you need a structured analysis of mixed digital records. I have experience with data cleaning, metadata extraction, link analysis, and reproducible reporting, and I’m available to start your project right now. I bring solid experience in Python, Data Processing, Excel, Report Writing, Data Visualization, Scripting, and Data Analysis. I can organize the provided CSVs, parse available metadata, build a clear relationship graph from legally provided and consented data, mark unsupported items as “no link found,” and deliver a transparent report with scripts and methodology. I have a couple of quick questions. • Can you confirm all data was lawfully obtained and authorized for analysis? • Should the graph focus only on correlations already present in the supplied files? Best regards, Carlos.

@Hubready

... Hello! I am a Florida-based senior software engineer with over 15 years of experience in Python, data processing, and analytics. I carefully read your project description regarding OSINT identity and network correlation and am excited about the opportunity to help you organize and analyze your data effectively. To ensure I fully understand your needs, could you please clarify the following questions: 1. What specific insights or outcomes are you hoping to achieve from the data analysis? 2. Are there any particular tools or libraries you prefer for data processing and visualization? I have extensive expertise in data mining and visualization, along with a strong background in report writing. My approach involves breaking down the project into clear phases, starting with data organization, followed by detailed analysis, and culminating in insightful reporting. With my proven track record in delivering data-driven solutions, I am confident that I can provide the meticulous attention to detail your project deserves. Let’s connect and discuss how I can contribute to your success! Best, James

@seandinwiddie

✨✨✨ ✨✨✨ ✨✨✨ ✨✨✨✨✨✨ ✨✨✨ ✨✨✨ ✨✨✨✨✨ Hi, Dear. Portfolio : https://www.freelancer.com/u/seandinwiddie With a meticulous nature and over two decades of experience in crafting tailored solutions for complex business problems, I am confident that I possess the skills and expertise necessary to excel at your demanding OSINT project. As a seasoned full-stack engineer and technical consultant, I have an ample grasp of various languages and frameworks like Python, JavaScript, and Django, which will be invaluable in parsing through your CSV files and executing any necessary scripts, ensuring efficient data analysis. Moreover, my commitment to well-structured work aligns perfectly with your request for an investigative report detailing every correlation uncovered. You can trust that not only will my findings reflect each data point provided but also be supported by clear logic or tool outputs alongside parsed metadata for reproducibility purposes. In addition, my experience with link analysis tools like Maltego and yEd will aid in creating a comprehensive network overview that ties identities, infrastructure, and locations together. Looking forward to collaborating. Best Regards.

@Vsion2

Welcome to professional Python development services! Hi there, I'm Alema, a Python expert programmer who strives for clear code in atmospheric, numerical weather prediction, physics, and all other seminal fields. I'm ready to provide you with high-quality services. I have completed 350+ projects with a 100% Positive Rating. If you are looking for Quality work, look no further. Also, we are a team of professional workers, and we are always available 24/7 to help employers without limitations, and delivery is guaranteed on time. Your faithfully. Eng. Alema Akter

@durgesh8527

Drawing on my 12+ years as a full-stack developer, I'm uniquely positioned to tackle the complex task of stitching together your unorganized data and revealing the network correlation. My expertise spans critical areas such as Data Analysis, Data Processing, Data Visualization, and powerful Excel automation. I can confidently devise a transparent methodology that includes a detailed report with clear ties between digital identifiers, Wifi networks, SSID names and even physical addresses for each location. With an ardent focus on accuracy, transparency, and clean hand-offs,I always maintain a meticulous approach in my work. Rest assured, each data point provided will be featured either linked or marked "no link found" if necessary. Additionally, I will rigorously uphold your requirement of backing up any claim between a person and a location with at least two independent artifacts. I am proficient in popular OSINT stack like SpiderFoot, Recon-ng, Python notebooks, WiGLE, Shodan etc. which can be leveraged to maximize the insights you need for this project. My commitment to complete data analysis can be seen in my use of tools like Maltego or yEd ultimately leading to well-structured reports and link-analysis charts that clearly demonstrate all discovered correlations. In essence, by choosing me you're gaining not only an experienced freelancer but also an unwavering dedication to your project’s success.

@Yevhen1987

Hello. The biggest headache with OSINT identity and network correlation is usually stitching together disparate data points into a cohesive, actionable narrative. I solve this by automating the correlation process and presenting findings in a structured, verifiable manner. Instead of manual correlation, I would use Python with libraries like Pandas for initial data processing from your CSVs. For external data enrichment, I can integrate with OSINT tools such as WiGLE for WiFi network mapping, Shodan for IP intelligence, and forensic tools for EXIF metadata extraction from your screenshots. The core task involves creating a script to parse inputs, query these external sources, and identify links between phone numbers, emails, IPs, SSIDs, and physical locations. I'll then generate a detailed report, clearly outlining confidence levels and source data for each correlation, and deliver a link-analysis graph using yEd or a similar tool for clear visualization, along with all supporting scripts. I can deliver this comprehensive OSINT correlation project for $450 within 7 days. To clarify, would you prefer a specific output format for the link-analysis chart if Maltego/i2 are unavailable for direct export? Best regards, Yevhen.

@ivicab6

As someone who thrives on solving complex challenges, I am Ivica, a seasoned full-stack engineer with over six years of experience that includes front-end and back-end development, database management, and integration. Amidst this technical background, I excel at Python which perfectly complements your requirement of data correlation from multiple sources. Not only can I organize the unstructured data you've gathered into a coherent picture, but I can also draw vital inferences from it. Given my specialization in automating business processes and system-to-system workflows, you can count on my ability to handle large volumes of disparate data and generate meaningful correlations efficiently. This empowers me not only to assure you a comprehensive relationship chart among identities, infrastructure, and locations using tools like Maltego or i2 Analyst Notebook but also provide you with clear explanatory logs for future reference should the need arise again. I have always prioritized accuracy and transparency in my work as well as clean hand-offs. I believe these align perfectly with your project requirements. Driven by the satisfaction of building impactful solutions, my focus has always been on understanding the client's needs deeply to ensure the product delivered meets their requirements exactly. Let’s solve this challenge together; I am confident we’ll be able to compile an exceptional report complete with all the correlations you seek - plus more!

@CauaAlves

Dear Client, I am ready to build a professional OSINT Identity & Network Correlation system in Python as described. I will: Normalize and cross-reference your CSV data (phones, emails, IPs) Extract and parse EXIF/metadata from all screenshots and documents Correlate digital identifiers to WiFi SSIDs and physical locations using trusted OSINT sources (WiGLE, Shodan, Recon-ng/SpiderFoot where applicable) Build a clean, reproducible Python pipeline with full logging Deliver a structured report with confidence levels and supporting evidence for every correlation Create a visual link-analysis graph (NetworkX + Graphviz or exportable to Maltego/yEd) Every data point will be accounted for (linked or explicitly marked “no link found”). All steps will be transparent and fully reproducible. Deliverables: Complete, well-commented Python codebase Detailed methodology report + command logs Interactive link graph Final correlation report I specialize in OSINT automation and Python data pipelines. I will sign the NDA immediately and can start right away. Looking forward to delivering accurate, professional results for you.