SAST scanners miss it
They find known CVEs and hardcoded secrets. They don't find the system prompt your user can extract in three messages, or the RAG pipeline that surfaces another tenant's documents.
Prompt injection. RAG leakage. Agentic tool misuse. Broken authorisation. Standard penetration tests don't cover these. We do — using OWASP LLM Top 10, MITRE ATLAS, and a custom testing harness built for production AI systems.
They find known CVEs and hardcoded secrets. They don't find the system prompt your user can extract in three messages, or the RAG pipeline that surfaces another tenant's documents.
Traditional web app pen testers test HTTP surfaces. They don't test prompt injection vectors, indirect injection via retrieved content, or an agent that will delete your database if you construct the right tool call.
Your customer's security team will ask about AI in the procurement questionnaire. If you haven't tested it, that question stalls your deal. We give you the attestation letter that answers it.
“Your AI feature is live. Let's find the obvious holes before someone else does.”
Non-technical founders who built with Lovable, Cursor, Bolt, or v0. SaaS MVPs with LLM features not yet through a security review. Teams preparing for a first enterprise conversation.
Not a comprehensive penetration test. Not a compliance certification.
“You're shipping to real users. Your enterprise buyers are asking questions. Let's make sure the answers are good.”
Funded SaaS startups with LLM features in production. Teams facing enterprise security questionnaires with AI-specific sections. Founders preparing SOC 2 or ISO 27001 that now need to cover their AI surface.
“You're in fintech, you're scaling, or your AI is making decisions that affect real people. This is the audit that holds up in a boardroom.”
Fintech on RBI-regulated rails. Series A+ SaaS with enterprise contracts. Companies building multi-agent or agentic AI systems. Any business with DPDP Act exposure.
30 minutes. We confirm scope, tier, and timeline. Sign the agreement.
Read-only codebase access + test environment. Deep Audit: threat-modelling session.
We run the audit. Critical findings flagged immediately — not at report time.
Shared for factual review — not to soften findings. Findings walkthrough call included.
Attestation letter issued. Retest after remediation. Updated report on resolved issues.
We flag Critical findings immediately. If we find your production database is publicly readable, you hear about it within the hour — not at the end-of-week report.
Your Stripe webhook doesn't verify signatures. Anyone can POST a fake invoice.paid event and flip their own account to paid.
Insufficient input validation.
Your RAG retrieves documents using a tenant_id from the user-supplied JWT — but the JWT signature is unverified, so any tenant can read any other tenant's documents.
Broken access control.
The agent has a delete_user tool. There's no confirmation gate. A crafted user message triggers it on the wrong user_id with no human review.
Excessive agency.
The engineers who run the audit explain the findings. No account manager relay.
Enterprise procurement teams accept it. It answers the AI section of the security questionnaire.
We don't charge separately to confirm you fixed what we found.
Automated scanners catch known CVEs. They don't catch inverted auth logic, cross-tenant RAG leakage, or an agent that will delete your database on a crafted input.
| Framework | What it covers | Tiers |
|---|---|---|
| OWASP LLM Top 10 (2025) | Prompt injection, insecure output, training data poisoning, supply chain, sensitive data disclosure, excessive agency, model theft | All tiers |
| MITRE ATLAS | AI-specific adversarial tactics, threat modelling | Production + Deep |
| OWASP Agentic AG01–AG10 | Tool misuse, memory poisoning, identity spoofing, excessive permissions, observability bypass | Deep only |
| NIST AI RMF | Govern, Map, Measure, Manage — AI risk lifecycle | Deep only |
| DPDP Act 2023 | Data Fiduciary obligations, consent, breach notification, right to erasure | Deep only (India) |
| RBI FREE-AI | 7 Sutras, Annex V/VI templates, 4-phase rollout | Deep only (fintech) |
| ISO/IEC 42001 | AI management system | Deep only |
We found the holes. We can fix them and harden the full codebase to production standard. Scoped and priced after the audit.
Explore →You passed. Now stay passing as you keep shipping. Quarterly red team, continuous monitoring, on-demand engineering support.
Explore →Your DPDP gap register needs remediation and ongoing monitoring. We build the documentation layer and maintain it.
Explore →OWASP LLM Top 10 (2025), MITRE ATLAS, OWASP Agentic AG01–AG10, NIST AI RMF, plus DPDP Act 2023, RBI FREE-AI Annex V/VI, and ISO/IEC 42001 mapping on Deep Audit engagements.
Yes on the Production Audit and Deep Audit. Signed, scoped, dated, and accepted by enterprise procurement teams as evidence for the AI section of the security questionnaire.
Read-only access to the codebase (GitHub/GitLab/Bitbucket) and a test environment. For agentic systems we also need access to the tool registry and any third-party integrations the agent can call.
Yes. One retest within 60 days for the Production Audit, two within 90 days for the Deep Audit. We don't charge separately to confirm you fixed what we found.
Immediately. If we find your production database is publicly readable, you hear about it within the hour — not at the end-of-week report.
Yes. NDAs are signed before any codebase access or implementation discussion. Standard practice.