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AI Penetration Testing

Identify vulnerabilities in AI and ML applications. Forgepath exercises your LLMs, agents, and classic ML systems with adversarial testing—from prompt injection and data leakage to tool abuse, model theft, and poisoning—then delivers engineer-ready fixes and an included re-test to prove closure.
AI Penetration Testing
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Validate AI risks before they impact users

Adversarial Testing Built for LLMs, RAG, and Agents

Traditional testing misses AI-specific failure modes—prompt injection, jailbreaks, tool-call abuse, data exfiltration via RAG, model theft, membership inference, and poisoning. Forgepath brings structured adversarial methods to your AI stack: we map your model routes and tools, craft context-aware attacks, and confirm what’s actually exploitable under real policies and guardrails.

We focus on where impact is highest: system prompts and safety rules, retrieval pipelines and embeddings, tool permissioning, data connectors, and output post-processing. You’ll get reproducible findings with attack transcripts, payloads, and mitigations (policy updates, filters, gating, and architectural patterns).

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Focus On What Matters

Inside Your AI Penetration Testing Service

We combine abuse-path modeling with safe, instrumented attacks to expose real risks in prompts, tools, and data flows—then translate results into guardrails your teams can adopt quickly.

Automation gives coverage; expert operators deliver signal.

  • Inputs: system/developer prompts, safety policies, tool manifests, RAG chains, datasets, and logs.
  • Methods: jailbreaks, indirect prompt injection (poisoned docs/links), prompt leaking, prompt-key extraction, sensitive data elicitation, policy evasion, function/tool abuse, and content-filter bypass.
  • Validation: capture full attack transcripts, model/tool responses, and environment states; verify impact with replay in lower environments.
  • Outcome: verified risks with payloads and clear success criteria.

We test the full stack—not just the model endpoint.

  • RAG: retrieval scope/filters, vector store leakage, untrusted content ingestion, chunking/context poisoning, and citation integrity.
  • Agents & Tools: permission design, tool routing, parameter tampering, function-call injection, SSRF via tools, and lateral movement to connected systems.
  • Classic ML: training/feature pipelines, data poisoning feasibility, model extraction, and membership inference risk.
  • Ops & Config: safety policy precedence, allow/deny lists, rate limits, timeouts, logging/redaction, and secrets in prompts or configs.

Show how harm occurs, not just that it could.

  • Chains: poisoned doc → RAG injection → policy bypass → tool call with elevated scope → data exfiltration or state change.
  • Evidence: step-by-step payloads, request/response captures, intermediate embeddings/context windows, and affected tool actions.
  • Impact: mapped to business harms—privacy breach, IP disclosure, fraud/abuse facilitation, brand risk, or compliance exposure.

Outcomes that stick—implementable and verifiable.

  • Policy & Prompting: harden system prompts, isolate roles, add rule precedence and conflict tests; create red-team “canaries.”
  • Input/Output Controls: content-origin labeling, untrusted-content flags, regex/semantic filters, guard classifiers, safety reranking.
  • RAG & Tools: retrieval allowlists, metadata filters, per-tool scopes, confirmation prompts for high-risk actions, and side-effect logging.
  • Ops & Monitoring: prompt/response redaction, secrets isolation, safety telemetry, and automatic block/hold on policy violations.
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Why teams choose Forgepath

Key Benefits You Can Expect

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Complete AI Stack View

End-to-end coverage across prompts, RAG, agents/tools, data connectors, and classic ML pipelines—prioritized by business risk.

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Adversary-Calibrated Validation

Findings reflect realistic attack chains (prompt injection, tool abuse, leakage), not theoretical lists.

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Clear, Reproducible Evidence

Attack transcripts, payloads, and replay steps mapped to impact and remediation.

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Faster Fixes & Re-Tests

Engineer-ready mitigations (policy updates, filters, scopes) and an included re-test to confirm closure.

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Reduced Leakage & Abuse

Guardrails that shrink PII/IP exposure and prevent risky tool actions.

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Operational Guardrails

Monitoring hooks and safety KPIs that keep improvements in place across releases.

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Cloud Systems & Security Manager
Zero.health
Working With Forgepath

Forgepath delivered outstanding service on our network and app security tests.

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Cloud Systems & Security Manager
Zero.health

Forgepath delivered outstanding service on both our network penetration test and application security assessment.

When a critical customer need arose, they quickly adjusted their schedule to meet our urgent timeline without compromising quality.

Their technical expertise, clear guidance, and hands-on remediation support helped us meet our EOY goals efficiently.

We were especially impressed by their flexibility, responsiveness, and professionalism throughout the process.

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Chief Executive Officer
parsysco.com
Working With Forgepath

Forgepath separates themselves from the rest as they’re a true security partner.

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Chief Executive Officer
parsysco.com

Forgepath separates themselves from the rest as they’re a true security partner to Parsysco. They took the time to understand our requirements and how things were working with our previous provider.

We were impressed by how quickly they formulated a new strategy and approach. They helped us identify our challenges and consistently brought forward solutions that were in Parsysco’s best interest.

Most vendors only care about selling something, Forgepath took the personal relationship and partnership approach that we value greatly.

OUR VALUED PARTNERS
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Are You Ready?

Harden Your AI Before It Reaches Customers

Expose and fix real AI abuse paths across models, RAG, agents, and tools—with evidence your teams can act on.
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