We built JobScamScore because we watched talented, qualified people lose weeks — sometimes months — to fake job postings. Resume submissions vanishing into the void. Interviews with "recruiters" who were never real. In the worst cases, money wired to scammers and personal details handed to identity thieves. We decided to build the tool we wished existed.
JobScamScore is built by a small team of engineers, fraud researchers, and consumer advocates. We don't publicly name our individual team members — the work of actively countering scam operations attracts attention from exactly the wrong people, and keeping a low profile protects the integrity of our research. What matters is our methodology, our data, and our track record — all of which are fully transparent and verifiable.
Our research team monitors emerging scam tactics weekly, tracking FTC and BBB reports, IC3 complaint filings, and community-reported patterns on job boards and social platforms. Our engineering team maintains the AI verification pipeline — a multi-step system combining natural language processing, domain verification, company registry cross-referencing, and real-time fraud database lookups.
Questions about our methodology, scam data, or how to report a new fraud pattern? Reach us directly. We read every message.
JobScamScore's mission is to give every job seeker — regardless of background, location, or technical ability — instant, reliable information about whether a job posting is real or a scam. The job market is complex enough. You shouldn't have to be a fraud investigator on top of everything else.
According to the FTC, employment fraud costs Americans hundreds of millions of dollars each year. The BBB found that 1 in 3 people who encountered a job scam lost money, with a median loss of $1,500. The problem is getting worse as AI tools let scammers produce convincing fake postings at scale. We are building to get ahead of that.
JobScamScore is an AI-powered verification tool that cross-checks any job posting against multiple data sources in real time:
We have a zero-tolerance policy for false certainty. We will never tell you a job is definitively safe if we can't verify it — and we won't generate scary warnings about legitimate jobs. Our system is designed to surface evidence and let you make an informed decision, not to replace your judgment.
Every flag we surface comes with a reason and a source. We're transparent about what we checked, what we found, and what we couldn't verify. No black boxes.
We are actively working to exceed 98% detection accuracy across diverse job types, industries, and geographies — including non-English postings and international scam patterns. We test continuously against known scam cases and update our models as fraud tactics evolve.
We have no commercial relationship with job boards or employers. Our incentive is accurate detection, not volume.
We do not sell your job search data. You can scan jobs without creating an account. We take privacy seriously in a category where it matters.
Our detection logic is informed by FTC guidance, BBB scam research, FBI IC3 reports, and publicly documented fraud cases.
Job scam tactics evolve weekly. We monitor scam pattern databases, community reports, and regulatory updates to keep our detection current.
Our detection pipeline runs 50+ parallel checks every time a job is submitted. Here is exactly how it works:
The submitted job posting is parsed to extract: company name, job title, salary, location, recruiter name, recruiter email, phone numbers, company domain, ATS platform links, and job description text. For URL submissions, we fetch the page and extract structured data. For screenshots, we use OCR to extract text before processing.
We verify the company domain via WHOIS lookup (domain registration date, registrar, ownership history), check SSL certificate validity and issuer, cross-reference against major business registries, verify LinkedIn company page existence and employee count, and check Glassdoor company profile.
We query the company's official careers page — identified via the company domain — and check whether the specific role title exists. We also check major ATS platforms (Greenhouse, Lever, Workday, iCIMS, SmartRecruiters) for the company's active listings. A job that does not appear on any official source is flagged for further review.
The recruiter's email domain is verified against the company's official domain. Free-email domains (Gmail, Yahoo, Outlook, Hotmail, and 200+ known free providers) trigger a critical warning. Where a recruiter name is provided, we cross-reference against LinkedIn to verify employment history at the named company.
Offered salary is compared against market data for the role title, seniority level, and location using aggregated public salary data. Offers more than 50% above the 90th percentile for comparable roles are flagged as potential scam signals.
Recruiter email addresses, phone numbers, and company domains are cross-referenced against FTC Consumer Sentinel complaint data, BBB Scam Tracker reports, IC3 complaint filings, and JobScamScore's own verified scam case database. Known scammer contact details are flagged immediately.
The job description is analyzed by a language model trained on thousands of verified scam and legitimate job postings. The model detects: task scam structures, fake check language patterns, advance fee indicators, urgency manipulation tactics, identity harvest indicators, and ghost job signatures (vague responsibilities, no specific deliverables, generic corporate language).
All signals are weighted and combined into a 0–100 legitimacy score with a Safe / Caution / Risky verdict. Each flag includes its specific evidence and the source it was drawn from. The overall verdict reflects the combined weight of all signals — no single check alone determines the result.
Our detection logic is informed by and cross-referenced against these authoritative sources. We do not invent risk signals — every flag is traceable to a documented fraud pattern from a recognized source.
Federal Trade Commission job and employment scam complaint data and fraud prevention guidance.
Better Business Bureau verified scam reports, median loss data, and employment fraud research.
IC3 annual reports and employment fraud complaint data, including AI-generated fraud trends.
Verified reports from Reddit, job board forums, and direct submissions to JobScamScore by affected job seekers.
Have questions, found a scam we missed, or want to report a new fraud pattern? We read every message.