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AI / ML Platforms

AI / ML Platforms Pentesting & VAPT

Pentesting and red-teaming for LLM apps, RAG pipelines, MLOps and model-serving infrastructure.

Why it matters

AI security is more than prompt injection. StartSecure red-teams the full stack — model serving, RAG retrievers, tool/agent execution, training pipelines and the supply chain — aligned to OWASP LLM Top 10, NIST AI RMF and the EU AI Act.

Top threats we find

Attack patterns specific to AI / ML Platforms

Prompt injection & jailbreak chains

Direct, indirect (via RAG sources), and tool-use chained jailbreaks.

Training-data poisoning

Backdoored embeddings, malicious documents in RAG corpora, fine-tune data abuse.

Model & weights theft

Exposed model endpoints, weights exfil via inference APIs, unscoped service tokens.

Agent / tool execution abuse

SSRF via plugins, RCE through code-interpreter, privilege escalation via MCP tools.

How we pentest

Our ai / ml platforms testing approach

01

OWASP LLM Top 10 coverage

Every category tested against your specific app, not generic scanners.

02

Agent & tool-chain red-teaming

Adversarial agent scenarios — data exfil, lateral movement, tool privilege abuse.

03

MLOps + infra pentest

Training pipelines, feature stores, model registries and inference clusters all in-scope.

Client benefits

What you get

  • Reduce hallucination + jailbreak risk before customer rollout.
  • Evidence pack aligned to NIST AI RMF and EU AI Act.
  • Pre-launch readiness review for high-risk AI features.
Compliance & frameworks

Aligned to

OWASP LLM Top 10NIST AI RMFEU AI ActISO 42001 (AI)
FAQ

AI / ML Platforms pentesting — common questions

AI / ML Platforms

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