FinSenseFINSENSEAFRICA

Automated Offensive Security

We attack your AI before someone else does.

Continuous penetration testing and red-teaming for AI and classic systems, mapped to the OWASP Top 10 for LLM Applications.

Take the AI readiness testDiscuss your team's needs

For any institution putting AI near customers, money or regulated data

OWASP LLM Top 10Red-teamingRe-testing
From

A pen-test that never looks at the AI

To

AI tested the way a real attacker would test it

What we offer

How we work
  1. Agree scope, data handling and timing in writing
  2. Model the threats worth an attacker's time
  3. Test manually and automatically against the OWASP LLM Top 10
01

AI Red-Teaming

Your AI, attacked the way an adversary would.

The challenge

AI can be tricked into ignoring its instructions, leaking data or trusting poisoned documents. Standard pen-tests miss all three.

What you receive
  • Prompt injection and jailbreak testing
  • Sensitive-data leakage and model extraction tests
  • Excessive agency and insecure output checks
The outcome

You find the weak points before an attacker does.

  1. 01 / 03

    AI Red-Teaming

    Your AI, attacked the way an adversary would.

    The challenge

    AI can be tricked into ignoring its instructions, leaking data or trusting poisoned documents. Standard pen-tests miss all three.

    How we work
    1. Agree scope, data handling and timing in writing
    2. Model the threats worth an attacker's time
    3. Test manually and automatically against the OWASP LLM Top 10
    What you receive
    • Prompt injection and jailbreak testing
    • Sensitive-data leakage and model extraction tests
    • Excessive agency and insecure output checks
    The outcome

    You find the weak points before an attacker does.

  2. 02 / 03

    Classic VAPT, Alongside

    The model, its data sources and the systems around it.

    The challenge

    An AI is only as safe as the applications, APIs and permissions it can reach.

    How we work
    1. Map what your AI can reach
    2. Test applications, APIs and infrastructure together
    3. Trace each finding to its business impact
    What you receive
    • Application, API and infrastructure testing
    • RAG and training-data poisoning checks
    • Severity, likelihood and impact for every finding
    The outcome

    One view of risk across the AI and everything it touches.

  3. 03 / 03

    Report, Fix & Re-test

    A report a risk committee can act on.

    The challenge

    Findings without a plan sit in a PDF until the next audit.

    How we work
    1. Prioritise findings by risk
    2. Work through the fixes with your team
    3. Re-test and confirm each one is closed
    What you receive
    • Executive summary with a risk rating
    • Reproducible steps and a prioritised fix plan
    • Re-test attestation on close-out
    The outcome

    Fewer open risks, and evidence for the regulator that they are closed.

How an engagement runs

Scoped, tested, reported, re-tested.

  1. Scope & rules of engagement

    Scope, data handling and timing agreed in writing first.

  2. Reconnaissance & threat modelling

    What your AI can reach, and which attacks are worth an adversary's time.

  3. Active testing

    Manual and automated testing against the OWASP LLM Top 10.

  4. Report & re-test

    Prioritised findings and a fix plan, then a re-test.

The deliverable

Findings mapped to the OWASP Top 10 for LLM Applications.

Any data in scope is covered by a data-processing agreement.

  • Executive summary with risk rating
  • Findings mapped to OWASP LLM Top 10
  • Severity, likelihood and business impact
  • Re-test attestation on close-out
More in Techset

Where this fits.

All Techset services →

Test the AI before it reaches production.

Not sure where to start? Take the AI readiness check.

Take the AI readiness testDiscuss your team's needs