Forensiq API
You set up the forensiq api by sending click and impression details to its web endpoint. The service checks each event for ad fraud and returns a risk score. Engineering teams often build a backend job to send traffic logs and store these scores. When teams use shared keys or broad database roles, any bug can expose raw user records. How the forensiq api works in your app Ad tech teams use this service to spot bots, click farms, and fake installs. Your app collects basic request data when a u
API Key Management: the complete guide
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You set up the forensiq api by sending click and impression details to its web endpoint. The service checks each event for ad fraud and returns a risk score. Engineering teams often build a backend job to send traffic logs and store these scores. When teams use shared keys or broad database roles, any bug can expose raw user records.
How the forensiq api works in your app
Ad tech teams use this service to spot bots, click farms, and fake installs. Your app collects basic request data when a user views an ad or clicks a link. Then your backend sends those request traits to the scoring endpoint over a secure web call. The remote server compares the event against known fraud patterns and network signals.
After the check finishes, the service sends back a response with risk scores and flags. Your app reads the score and decides whether to block the click or count it. Most teams also write the full response into a local database for billing audits. Analysts and support engineers later query those tables to check campaign quality and dispute bad charges.
What native API keys solve and what they leave open
The vendor requires a secret key on every request to prove your account identity. This setup makes sure only your servers can use your paid fraud check quota. You can also set up basic account roles in the vendor dashboard for your staff. Those roles control who can view summary reports or rotate the secret key.
Still, account keys only check who connects to the vendor endpoint. They do not control how your engineers query the fraud logs stored in your own database. Also, vendor keys sit inside your app settings and often get shared across test servers. When developers debug failed API calls, they often query production tables with broad admin roles.
Those production tables hold raw event data alongside the fraud scores. They often include user emails, phone numbers, card numbers, or national IDs from conversion forms. A static database role decides who can log in, not what individual queries return in flight. One broad select statement can pull thousands of raw customer records onto a developer laptop.
API Key Management: architecture patterns and best practices
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Securing backend workflows and audit data
To reduce risk, teams should separate the scoring worker from human debug sessions. Background workers need narrow write permissions so they can only insert new score records. Human engineers who check failed events should not use the same database user as the app. Each person needs individual accountability when they run queries against stored event logs.
Teams also need controls that work on individual queries and commands in real time. Instead of giving developers full read rights on raw tables, apply data masking to results. Data masking rewrites matched fields like emails and phone numbers in query results. Engineers can still check the fraud score and timestamp without pulling raw personal fields.
You should also require peer reviews before anyone runs an update or delete on audit tables. Keeping a clean log of every query helps you pass partner audits with less effort. When you combine strict key storage with query-level controls, your fraud pipeline stays safe.
Check database and API queries on the wire
Identity tools, roles, and network rules decide who opens a session. Setup alone cannot check what each query does or mask sensitive values in a response once a session starts. When workflows touch Postgres, MySQL, SQL Server, MongoDB, ClickHouse, Kubernetes APIs, SSH, or internal HTTP APIs, hoop.dev sits inline in the wire protocol beside those services as an open-source proxy, a sidecar for your Postgres or API. On every query an AI agent or engineer runs against production, hoop.dev decides to pass, mask, block, or hold it for human review.
Your login details and client tools stay as they are while hoop.dev guardrails refuse bad deletes or drops before they run, and hoop.dev data masking rewrites matched sensitive values in responses in memory. Furthermore, hoop.dev holds SOC 2 Type II, is MIT licensed, and writes every query and decision to an audit trail that generates evidence for HIPAA, GDPR, and PCI DSS. See the source on GitHub.
Frequently asked questions
What data does the forensiq api check for fraud?
The service checks network signals, device traits, and session timing from ad views and clicks. It uses these details to calculate the chance that a bot generated the traffic.
How should teams store the secret key for the scoring endpoint?
Store the secret key in a dedicated secret manager rather than in source code files. Give only the background scoring worker permission to read that secret at runtime.
Why do ad fraud logs create data privacy risks for engineers?
Teams often join fraud score logs with user conversion tables to check campaign value. When engineers query those joined tables, raw emails and phone numbers appear in the results.