GenAI Security

AI moves fast, and so do its attackers. We red-team your LLM applications, secure retrieval and agent pipelines, and validate the guardrails that keep your models within bounds.

  • Adversarial Red-Teaming
  • Guardrail Validation
Schedule Assessment
01 / Methodology

Engagement Methodology

A structured lifecycle that maps your AI stack, attacks it like a real adversary, and leaves hardened guardrails behind, aligned with OWASP LLM Top 10 and MITRE ATLAS.

2-3 days
01

Threat Modeling & Scoping

We map your GenAI stack: model endpoints, retrieval pipelines, agents, plugins, and data flows. Together we define use cases, trust boundaries, and the assets that matter most before a single prompt is sent.

1-2 weeks
02

Adversarial Red-Teaming

Hands-on attacks against your LLM applications: direct and indirect prompt injection, jailbreaks, prompt extraction, and output manipulation. We chain real exploits to show business impact, not just theory.

3-5 days
03

Model & Pipeline Review

We review model provenance, weight integrity, fine-tuning data, and retrieval-augmented generation (RAG) controls. Insecure serialization, poisoned datasets, and supply-chain risks in model artifacts are identified and ranked.

3-5 days
04

Guardrail Validation

We pressure-test input/output filters, safety policies, rate limits, and access controls against OWASP LLM Top 10 and MITRE ATLAS, measuring how well your guardrails resist evasion and enforced behavior.

3-5 days
05

Reporting & Roadmap

You receive a prioritized report with reproducible proof-of-concepts, severity ratings, and a concrete remediation roadmap covering guardrail rollout, monitoring, and continuous red-teaming.

02 / Attack Surface

Attack Surface Coverage

From prompt injection to insecure model weights, we cover the full LLM threat landscape across interaction, retrieval, models, and autonomous agents.

Prompt & Interaction

  • Direct prompt injection
  • Indirect injection via data
  • Jailbreak & bypass
  • System prompt extraction

Data & RAG

  • Retrieval poisoning
  • Sensitive data leakage
  • RAG access-control bypass
  • PII exposure in outputs

Model & Supply Chain

  • Insecure model weights
  • Model poisoning
  • Fine-tuning integrity
  • License & provenance

Agents & Tools

  • Excessive agency
  • Plugin & plugin-API abuse
  • Unauthorized actions
  • Tool hijacking

Secure Your AI Stack

Let our team red-team your GenAI applications and harden the guardrails.

Contact Us

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