Find AI vulnerabilities before attackers do
LLM applications introduce attack surfaces that traditional security tools miss — prompt injection, training data extraction, and jailbreak exploits. Our red team assessments find these gaps before they reach production headlines.
Talk to an ExpertAlgofy conducts structured AI security audits covering LLM endpoints, RAG pipelines, agent orchestration, and API integrations. We simulate real-world attacks — prompt injection, indirect injection via documents, role-play jailbreaks, and data exfiltration — then deliver prioritized remediation with implementation support.
AWS Partner Program Benefits
As an AWS Partner with access through an authorized North America distributor channel, we unlock partner-only discounts, funding, credits, and billing resources for qualified customers.
- Free POC for selected projects — Qualified engagements can receive a proof-of-concept built at no charge when you partner with us on AWS — we invest upfront so you validate before you commit.
- AWS partner funding & credits — We tap partner funding programs, marketing development funds, and AWS credits to offset migration, modernization, Well-Architected remediation, and AI workload costs.
- Distributor-channel discounts — Through our authorized North America AWS distributor relationship, eligible customers get partner-level discounts and volume-based pricing beyond standard pay-as-you-go rates.
- Billing, Marketplace & enablement — Consolidated multi-account billing, AWS Marketplace private offers, and partner training and certification resources — support direct customers typically cannot access alone.
Built for enterprise outcomes
Adversarial testing methodology
Structured red team exercises based on OWASP LLM Top 10 and industry attack patterns — not checkbox compliance scans.
RAG-specific assessment
Test vector stores, document ingestion pipelines, and retrieval boundaries for poisoned document attacks and cross-tenant data leakage.
Actionable remediation
Prioritized findings with severity ratings, exploit demonstrations, and specific configuration changes — not vague recommendations.
Ongoing validation
Regression test suites and scheduled reassessments that catch new vulnerabilities as models, prompts, and integrations evolve.
Our proven process
Scope & threat modeling
Map AI system architecture, data flows, user access patterns, and integration points to define the attack surface and threat model.
Automated scanning
Run automated prompt injection, jailbreak, and toxicity tests against LLM endpoints and API gateways to establish baseline vulnerability counts.
Manual red teaming
Expert-led adversarial testing including indirect prompt injection via documents, multi-turn manipulation, and data exfiltration attempts.
Findings & prioritization
Document exploitable vulnerabilities with proof-of-concept demonstrations, severity ratings, and business impact analysis.
Remediation & retest
Implement guardrails, input/output filters, and access controls, then retest to confirm vulnerabilities are closed.
What you receive
AI threat model document
Red team assessment report
Vulnerability findings with PoC evidence
Prioritized remediation roadmap
Implemented security controls & retest results
Common questions
What AI security risks do you test for?
Prompt injection (direct and indirect), jailbreak attacks, training data extraction, PII leakage in outputs, RAG document poisoning, unauthorized API access, model denial-of-service, and excessive agency in AI agent workflows.
How is LLM red teaming different from traditional penetration testing?
LLM applications have unique attack surfaces — natural language inputs that manipulate model behavior, poisoned documents in RAG pipelines, and multi-turn conversation exploits. Traditional scanners miss these; our red team uses AI-specific attack methodologies.
Do you help fix vulnerabilities after the audit?
Yes. Every engagement includes remediation implementation — input/output guardrails, WAF rules, access control hardening, and prompt engineering fixes — followed by retesting to confirm closure.
Ready to get started?
Talk with our AWS and Google Cloud partner team about your ai security audit goals. Qualified AWS engagements may include a free POC, partner funding and credits, and distributor-channel discounts.
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