Keep API Keys, Source Code, and Infrastructure Secrets Out of Every AI Prompt
Security and engineering teams are under the same pressure everyone else is: use AI to move faster, without handing it the credentials, logs, and source code that actually run the business. Most teams solve this today by hoping nobody pastes a live API key into a prompt. That's not a policy — it's a bet.
Questa AI anonymizes secrets, tokens, license keys, and sensitive technical files before they ever reach a model, so your SecOps, DevSecOps, and platform teams can use AI on real incident data, logs, and code — without that being the incident.
What Actually Gets Anonymized
Not just names and emails — the technical assets that make up the bulk of what a security or platform team actually works with day to day.
Credentials & secrets
- •API keys and access tokens
- •Database and service passwords
- •License keys and signing certificates
- •OAuth tokens and session identifiers
Source code & infrastructure
- •Proprietary source code and internal libraries
- •Infrastructure-as-code and config files
- •Internal hostnames, IPs, and network topology
- •CI/CD pipeline definitions
Logs & operational data
- •Application and security logs
- •Incident timelines and forensic artifacts
- •Vulnerability scan output
- •Customer and employee identifiers embedded in logs
Why This Is a 2026 Problem, Not a Someday One
The exposure is already happening, and the compliance clock is already running.
hardcoded secrets exposed on public GitHub in 2025 — up 34% year over year, the largest single-year jump on record.
growth in leaked AI-service credentials alone, as more teams wire AI tools into real infrastructure.
NIS-2's deadline for essential and important entities to have security measures in place, with personal liability for management bodies.
Sources: GitGuardian, State of Secrets Sprawl 2026 and NIS-2 Enforcement Tracker, 2026.
None of this is hypothetical. If your team has already wired an AI coding assistant into your workflow, there's a good chance a secret has come close to a prompt at some point this year — most teams just haven't found out yet. And if you fall under NIS-2's scope, the window to treat this as a documentation exercise closed a while ago; audits are already underway, and fines run up to €10M or 2% of global turnover for essential entities.
Questa AI doesn't replace your secrets manager or your SAST tooling. It sits in front of the AI layer specifically, so the tools your engineers are already reaching for don't become the leak.
Where Teams Actually Use It
Real workflows security and platform teams run today — with the sensitive parts stripped before AI ever sees them.
Incident reports and postmortems
Generate incident timelines and postmortem summaries from raw logs and chat transcripts, with credentials and internal identifiers stripped before anything reaches the model — so a postmortem doesn't become its own disclosure event.
Code review and vulnerability triage
Let AI assist with reviewing pull requests or triaging scanner output on anonymized code, so proprietary logic and embedded secrets aren't sent to a third-party model just to get a second opinion on a diff.
Querying logs and runbooks
"Which services had the most 5xx errors last week, and what changed before each spike?" — ask directly against anonymized log data instead of exporting raw logs into a chat tool nobody's tracking.
Audit and compliance evidence
Produce the anonymization and access-log evidence NIS-2 audits ask for, without your compliance team needing raw access to every credential and config file it's reviewing.
The Same Privacy Layer, Across the Business
If cyber and critical data is one part of what you're protecting, it's rarely the only part.
Questions we get from security and platform teams
The answers that come up most when SecOps, DevSecOps, and platform teams evaluate Questa.
Contact Us
Have questions or ready to explore how Questa AI can transform your business?