Cybersecurity
Adversary-grade, AI-adaptive defense.
Attackers now move at machine speed, and every AI feature you ship is a new attack surface. We think like the adversary and defend at their pace: machine-learning models that learn what 'normal' looks like, automation that contains threats in seconds, and guardrails that protect the AI itself. Our approach maps to MITRE ATT&CK and MITRE ATLAS, and our AI-risk work follows the OWASP LLM Top 10 and the NIST AI Risk Management Framework — with a human in the loop wherever it counts.
Discuss your project
Capabilities
What you get with Cybersecurity
AI-driven threat detection
Machine-learning models over your logs, network, and endpoint telemetry catch novel and low-and-slow attacks that signatures miss — every finding mapped to MITRE ATT&CK techniques.
Behavioral analytics & UEBA
User and entity behavior analytics baseline how your people and systems normally act, then flag the deviations that signal account takeover, insider risk, or lateral movement.
Autonomous & adaptive response
SOAR playbooks contain threats in seconds, while adaptive zero-trust tightens access the moment a risk signal spikes — assume-breach by default, human approval on high-impact actions.
AI-SOC analyst copilot
A generative copilot triages alerts, correlates signals across tools, and drafts incident timelines and next steps — so a lean team investigates with the reach of a much larger SOC.
GenAI-assisted red teaming
Adversary emulation and penetration testing across web, API, cloud, and identity — accelerated with generative tooling and aligned to MITRE ATT&CK, with exploit-backed, prioritized findings.
LLM & GenAI application security
We harden the AI you're building against prompt injection, jailbreaks, insecure output handling, training-data and model poisoning, and sensitive-data leakage — assessed against the OWASP LLM Top 10.
AI red teaming & model governance
Adversarial testing of your models and agents, mapped to MITRE ATLAS, plus a model inventory, evals, and guardrails so AI behavior stays safe, monitored, and accountable.
AI risk & compliance
Governance aligned to the NIST AI RMF and ISO/IEC 42001, alongside SOC 2, ISO 27001, and HIPAA controls — mapped, evidenced, and maintained continuously, not bolted on for the audit.
Deliverables
- Attack-surface map, threat model & AI asset inventory
- AI/ML detection & UEBA tuned to your own telemetry
- SOAR playbooks & adaptive zero-trust rollout plan
- LLM/GenAI security assessment (OWASP LLM Top 10)
- AI governance program (NIST AI RMF · ISO/IEC 42001)
- Monitoring, alerting & rehearsed incident-response runbooks
Tools & technologies
Engagement
How the work runs
Discover
We map your goals, constraints, and threat model — then agree on a fixed first milestone.
Design
Architecture, interfaces, and security controls designed before a line of production code.
Build
Senior engineers ship in weekly increments with demos, shared dashboards, and tests.
Operate
Monitoring, incident response, and iteration — we stay accountable after launch.
Ready to build something resilient?
Tell us where you're headed. Within one business day you'll hear back from a senior engineer — with a plan, a timeline, and a fixed first milestone.
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