Use Case · Cybersecurity

Red-team AI without provider-side refusals.

Test prompt injection, jailbreak resilience, and model misuse — at scale, with full audit trails.

Off-the-shelf model refusals make legitimate security testing impossible. Policy Gateway gives security teams controlled access to less-restricted inference, with policy-enforced guardrails on outputs and complete audit trails for every test.

The problem

Why teams in cybersecurity hit a wall.

Provider refusals block legitimate testing

Refusal-tuned models won't run prompt injection scenarios, jailbreak probes, or attacker-persona simulations needed for AI red-teaming. Your AppSec team is locked out of its own product.

No audit trail for security exercises

Compliance teams need every test logged with reproducible inputs and outputs. Most LLM APIs return scores or completions — not the decision metadata your evidence-of-testing reviews require.

Sensitive payloads risk leaking out

Pentest prompts often contain real internal artifacts. Provider-side training pipelines and unclear retention create risk you can't accept.

How Policy Gateway helps

Built for cybersecurity workloads.

Less-restricted inference, governed at the edge

Run red-team prompts against the abliterated model with your security team's policy as the guardrail — not the provider's.

Decision metadata on every call

Every test logged with policy ID, reason code, and the input/output pair. Exportable to your SIEM for evidence-of-testing audits.

Zero data retention by default

Prompts and outputs processed transiently. Audit events stream into your SOC tooling — Splunk, Datadog, Elastic, S3, Azure Monitor — never our training set.

Examples

Scenarios from the field.

Prompt injection battery

Run a corpus of injection variants against your production chatbot. Track which prompts bypass your safety layer; export results straight to your AppSec ticketing.

Jailbreak resilience scoring

Continuously evaluate your shipping LLM features against a maintained jailbreak corpus. Get reproducible decision logs across runs and regression-test on every release.

Adversarial training data

Generate red-team examples for fine-tuning your in-house safety classifiers. Same governed API, JSONL output, full provenance.

Compliance & alignment

Designed for the frameworks your auditors care about.

Designed to slot into the frameworks your security and risk teams already report against.

  • OWASP LLM Top 10
    Aligned testing surface across the full top-10 attack categories.
  • NIST AI RMF
    Decision logs map cleanly onto Govern / Map / Measure / Manage functions.
  • MITRE ATLAS
    Reusable tactic/technique tagging on test runs.
  • SOC 2 (in progress)
    Enterprise audits underway.
  • Zero data retention
    Default; prompts and outputs not used for training.
  • Per-project key scoping
    Issue, rotate, and revoke keys per test program.

Ready to bring governance to your cybersecurity stack?

Talk to an engineer about your deployment, or grab an API key and start building today.