AI Red Teaming & Prompt Injection
Adversarial probing of LLM apps, agents and copilots. Direct & indirect prompt injection, jailbreaks, tool-use abuse, data exfiltration and supply-chain attacks.
AI/ML SECURITY · ACTIVITIES
Securing the
Securing the
AI-native enterprise.
From LLM-powered products to production ML pipelines — we red-team your AI, harden your models, and align your governance to EU AI Act, NIST AI RMF and ISO/IEC 42001. One practice, end-to-end.
120+
40+
3
24/7
Activities
Six disciplines. One AI security practice.
Built for teams shipping LLM products, deploying ML in production, or preparing for AI regulation.
LLM Application Security
Full coverage of the OWASP LLM Top 10 — insecure output handling, training-data poisoning, model DoS, sensitive disclosure, plugin/tool abuse and SSRF in RAG.
ML Model Security & Robustness
Evasion, model stealing, membership inference and backdoor testing against your production models. Adversarial robustness baselines and drift monitoring.
MLSecOps & Pipeline Hardening
Secure the supply chain from data to deployment: lineage, signed artifacts, model registry hardening, container scanning, IAM least-privilege and audit telemetry.
AI Governance & Compliance
EU AI Act risk classification, NIST AI RMF mapping and ISO/IEC 42001 readiness — operationalized through the DJAC platform.
AI-Augmented Threat Detection
ML-powered detection engineering inside our 24/7 SOC — anomaly models, alert triage copilots and automated enrichment workflows.
Strategy
Our four-pillar approach to AI security.
A repeatable lifecycle — from first model in pre-prod to regulator-ready in production.
Find every model and AI surface.
Shadow-AI discovery, third-party LLM usage inventory, training data lineage and embedded ML in vendor SaaS. You can't govern what you can't see.
Break it before adversaries do.
Adversarial testing across prompt, model, pipeline and integration layers — mapped to OWASP LLM Top 10, MITRE ATLAS and our internal AI kill-chain.
Make compliance continuous.
Map controls to EU AI Act, NIST AI RMF and ISO/IEC 42001 inside DJAC. Evidence collection, risk registers and audit-ready reports — generated, not assembled.
Watch the model in flight.
Drift, abuse and prompt-injection telemetry streamed into the Yalla Hack SOC. AI incidents triaged with the same rigor as a network intrusion.
Who it's for
Built for teams already shipping AI.
Banks & Fintech
Fraud-scoring models, KYC copilots, customer-facing assistants — under regulator scrutiny and adversary pressure.
Government & Defense
Sovereign AI deployments, classified-data RAG systems, decision-support models in high-stakes environments.
Healthcare & Pharma
Diagnostic models, clinical decision tools and patient-facing assistants where bias and leakage are existential.
SaaS & AI-Native Startups
LLM products shipping fast — need security baked in before enterprise procurement asks for it.
Energy & Industrial
Predictive-maintenance models, autonomous-system controls and OT/AI convergence risks.
Telcos & Critical Infra
Network-anomaly ML, customer copilots and regulator-mandated AI risk programs.
Frameworks we map to
Speak the language regulators & adversaries speak.
EU AI Act
NIST AI RMF
ISO/IEC 42001
OWASP LLM Top 10
MITRE ATLAS
UAE AI Charter
KSA SDAIA
SOC 2 / ISO 27001
Insights
Latest AI/ML write-ups from the field.
Hand-picked from the Yalla Hack blog — filtered for AI, LLM and ML security topics.
Loading AI/ML insights…
New AI/ML posts coming soon
Our team is publishing field notes on LLM red-teaming, MLSecOps and AI governance. Browse the full blog in the meantime.
Visit the blog
START WITH AN AI RISK BASELINE
Ship AI fast. Ship it secure.
A two-week AI risk baseline maps your models, surfaces top adversarial risks and outputs an EU AI Act / NIST AI RMF gap analysis. Fixed scope, fixed price.