Autopilot - Cybersecurity AI Agents
for your business
Discover 100% Autonomous AI Agents for Phishing, GRC, and Threat Intelligence that continuously discover, monitor, and mitigate external threats.
Browse AI Agents
Find the right agents for your security needs
Phishing Simulation Agent
Continuous AI-powered phishing simulations that test and train your employees with realistic attack scenarios.
Attack Surface Agent
Autonomously discovers and monitors your external attack surface, identifying vulnerabilities before attackers do.
Brand Risk Agent
Detects and takes down brand impersonation attempts, fake domains, rogue mobile apps, and social media threats in real-time across the internet.
DMARC+ Agent
Implements and manages email authentication protocols including DMARC, SPF, and DKIM to prevent domain spoofing and protect your brand reputation.
Threat Intel Agent
Aggregates and correlates threat intelligence from multiple global sources to provide contextual, actionable insights tailored to your infrastructure.
Compliance Agent
Automates compliance monitoring, audit evidence collection, and regulatory reporting for RBI, ISO 27001, SOC 2, HIPAA, and other frameworks.
Cloud Security Agent
Continuously monitors cloud infrastructure configurations, detects drift from security baselines, and enforces compliance policies across multi-cloud environments.
Vendor Risk Agent
Automates third-party risk assessments with continuous vendor security posture monitoring, compliance validation, and risk scoring across your supply chain.
Identity Protection Agent
Monitors for compromised credentials in dark web breaches, detects anomalous user behavior patterns, and enforces adaptive access policies across identity providers.
Data Privacy Agent
Automates data mapping, DSAR fulfillment, and privacy compliance workflows for GDPR, CCPA, and CPRA regulations across all data stores.
Shadow AI Discovery Agent
Detects and controls the usage of unauthorized GenAI tools and SaaS LLM services, prevents sensitive data leakage to LLMs, and enforces AI governance policies.
API Security Agent
Continuously discovers APIs across your infrastructure, tests for logic flaws like BOLA/BFLA, detects data leakage, and blocks abusive traffic patterns.
SaaS Security Agent
Monitors and hardens critical SaaS applications to prevent configuration drift, detect unauthorized data exposure, and enforce security best practices.
Supply Chain Security Agent
Analyzes open source dependencies, software bills of materials (SBOM), license compliance, and vulnerability data to block risky packages from production.
SOC Analyst Agent
Tier-1 Autonomous SOC Analyst that triages security alerts, investigates false positives, enriches incidents with threat intelligence, and escalates critical threats.
Understanding Agentic AI
What Are Cybersecurity AI Agents?
Cybersecurity AI agents are autonomous software entities that use artificial intelligence to perform security tasks without continuous human direction. Unlike rule-based automation or SOAR playbooks that follow predetermined scripts, agentic AI operates through a continuous reasoning loop: Sense → Decide → Act → Verify. Each agent perceives its environment (ingesting logs, scanning attack surfaces, monitoring dark web feeds), reasons about what it observes (using large language models and domain-specific training), takes meaningful action (blocking threats, generating evidence, initiating takedowns), and then verifies the outcome to confirm the action was effective.
This architecture represents a fundamental shift from traditional security automation. Where SOAR playbooks break when they encounter a scenario outside their rules, agentic AI adapts. An AI agent investigating an alert it has never seen before can still reason about the indicators, correlate context from multiple sources, and produce an analyst-grade investigation report — because it understands cybersecurity, not just a flowchart.
The practical impact is transformative. Organisations deploying cybersecurity AI agents report 10x faster incident response, 90%+ reduction in false positive noise, and the ability to maintain 24/7 security coverage without scaling headcount. For lean security teams — particularly in mid-market companies, fintechs, and fast-growing startups — this means enterprise-grade protection at a fraction of the traditional cost.
Hunto AI's Autopilot platform deploys a personal suite of cybersecurity AI agents tailored to your organisation's threat landscape, compliance requirements, and infrastructure. Each agent operates autonomously but collaborates with other agents — creating an interconnected security fabric where intelligence from one agent enriches the decisions of another. The result is not just automation, but genuine autonomous cyber defence.
Agent Catalogue
Types of Cybersecurity AI Agents
Each agent is purpose-built for a specific security domain. Together, they provide comprehensive autonomous coverage across your entire threat landscape.
Attack Surface Agent
Continuously discovers and maps your internet-facing assets — subdomains, cloud buckets, exposed APIs, and shadow IT. Identifies vulnerabilities before attackers do by combining active scanning with passive reconnaissance. Prioritises risks based on exploitability, not just CVSS scores.
Brand Protection Agent
Scours the internet for brand impersonation, typosquatting domains, fake mobile apps, and social media fraud using multi-modal AI. Automates the full takedown lifecycle — from detection through legally compliant cease-and-desist to removal confirmation — shutting down entire phishing campaigns.
Phishing Simulation Agent
Generates hyper-realistic, context-aware phishing simulations using generative AI — not static templates. Adapts difficulty per user based on role, behaviour history, and risk profile. Delivers just-in-time training at the moment of failure, reducing phishing susceptibility by 70% in three months.
SOC Analyst Agent
Autonomously triages security alerts, enriches indicators with threat intelligence, correlates events across your SIEM, and produces analyst-grade investigation reports. Replaces tier-1 SOC tasks — filtering noise, escalating real threats, and reducing mean time to detect from hours to seconds.
Threat Intel Agent
Aggregates intelligence from 50+ OSINT, commercial, and dark web sources, then correlates it against your specific environment. Automatically pushes blocking rules to firewalls, enriches internal alerts with attacker context, and produces curated threat landscape reports for your industry.
Vendor Risk Agent
Automates the full third-party risk management lifecycle — from dispatching security questionnaires to AI-grading vendor responses and continuously monitoring external security ratings. Maps fourth-party dependencies to visualise your supply chain's supply chain risk.
Compliance Agent
Transforms compliance from annual audits to continuous monitoring. Maps technical controls to regulatory requirements across ISO 27001, SOC 2, HIPAA, RBI, and GDPR. Auto-collects evidence, tracks control drift, and generates audit-ready packages on demand.
Data Privacy Agent
Scans structured and unstructured data stores to build a dynamic PII inventory. Automates Data Subject Access Requests (DSARs) end-to-end — finding, compiling, and optionally deleting user data across all connected systems — cutting fulfilment from weeks to minutes.
Cloud Security Agent
Audits AWS, Azure, and GCP environments against CIS benchmarks and internal policies in real-time. Detects misconfigurations, overly permissive IAM roles, and infrastructure drift. Scans Infrastructure as Code in git repositories to catch issues before deployment.
API Security Agent
Discovers and inventories every API endpoint — including shadow APIs your team doesn't know exist. Tests for authentication bypass, injection vulnerabilities, and excessive data exposure. Continuously monitors for new endpoints and configuration changes across your API gateway.
Supply Chain Security Agent
Monitors open-source dependencies, third-party libraries, and software supply chain components for vulnerabilities, licence compliance issues, and malicious packages. Detects dependency confusion attacks and generates Software Bill of Materials (SBOM) documentation.
Shadow AI Discovery Agent
Detects unauthorised GenAI tool usage across your organisation — identifying which AI services employees access and what data they share. Enforces acceptable use policies, blocks sensitive data from reaching public LLMs, and enables safe AI adoption without stifling innovation.
DMARC+ Agent
Guides your domain from monitoring (p=none) to full enforcement (p=reject), stopping 100% of direct domain spoofing. Maps your entire email ecosystem, identifies legitimate senders, and automates SPF/DKIM configuration for 100+ services — without breaking deliverability.
Comparative Analysis
Agentic AI vs. Traditional Security Automation
The cybersecurity industry has relied on rule-based automation for over a decade — from SIEM correlation rules to SOAR playbooks. These tools brought meaningful improvements over purely manual operations, but they share a fundamental limitation: they can only handle scenarios that someone has anticipated and coded for. In a threat landscape where attackers constantly evolve their tactics, this rigidity creates dangerous blind spots.
Agentic AI for cybersecurity represents the next evolution. Instead of following pre-written scripts, AI agents use large language models trained on cybersecurity domain knowledge to reason about novel situations. They make autonomous decisions, execute multi-step investigation workflows, generate human-readable evidence, and verify outcomes — all without requiring a playbook for every scenario. This makes them fundamentally more adaptive, scalable, and cost-effective than traditional approaches.
| Capability | Traditional Automation / SOAR | Agentic AI (Hunto AI) |
|---|---|---|
| Decision-Making | Fixed if-then rules | Multi-step LLM reasoning |
| Novel Scenarios | Breaks or escalates | Adapts and investigates autonomously |
| Evidence Generation | Template-based outputs | Context-aware, analyst-grade reports |
| Verification Loop | None — fire and forget | Confirms action effectiveness automatically |
| Maintenance Burden | Constant playbook updates | Self-improving with minimal tuning |
| Cross-Domain Correlation | Siloed per playbook | Inter-agent intelligence sharing |
| Scalability | Linear with engineer effort | Scales autonomously to new threat types |
| Setup Time | Weeks to months of rule writing | 48-hour deployment, pre-trained agents |
Autonomous SOC
AI SOC Agent: Autonomous Security Operations
The Security Operations Centre (SOC) is the nerve centre of cybersecurity — and also its biggest bottleneck. Tier-1 SOC analysts spend 80% of their time on repetitive tasks: triaging alerts, filtering false positives, enriching indicators of compromise (IOCs) with external intelligence, and writing investigation notes. The average SOC receives thousands of alerts per day, and most are noise. This creates analyst fatigue, burnout, and dangerously slow response times for real threats.
Hunto AI's SOC Analyst Agent autonomously handles these tier-1 tasks. It ingests alerts from your SIEM, enriches each one with threat intelligence from 50+ sources, correlates indicators across your environment, determines severity with multi-step reasoning (not just rule matching), and produces analyst-grade investigation reports — complete with evidence, timelines, and recommended response actions. True threats are escalated with full context; false positives are closed with documented reasoning.
For organisations that cannot afford a 24/7 SOC team — or those looking to make their existing analysts dramatically more effective — the AI SOC Agent provides continuous coverage that never sleeps, never fatigues, and processes alerts in seconds rather than hours. It works alongside human analysts as a force multiplier, handling the volume so your team can focus on the threats that truly matter.
Business Impact
How Agentic AI Improves Cybersecurity ROI
The business case for agentic AI in cybersecurity is compelling. Traditional security operations are labour-intensive, with the average enterprise spending $3.5 million annually on SOC staffing alone — and still struggling with coverage gaps during off-hours. Cybersecurity AI agents fundamentally change this cost equation by automating the tasks that consume the most analyst time while delivering measurably better outcomes.
Organisations deploying Hunto AI's autonomous agents report concrete improvements across every key metric: Mean Time to Detect (MTTD) drops from hours to minutes. Mean Time to Respond (MTTR) improves by 10x. False positive noise is reduced by 90%+, freeing analysts to focus on genuine threats. Compliance audit preparation shrinks from weeks to hours through automated evidence collection. And 24/7 coverage is achieved without hiring additional headcount or paying for expensive managed security services.
For mid-market companies and growing enterprises, the ROI calculation is straightforward: replace the need to hire 3–5 additional security analysts with a platform that provides superior coverage, faster response, and continuous compliance monitoring — at a fraction of the cost. The Hunto AI Autopilot platform deploys in 48 hours and starts delivering measurable value from day one.
Available Integrations
Seamlessly integrate with your existing security stack and workflows.
Cybersecurity AI Agents — FAQs
Common questions about agentic AI in cybersecurity
Agentic AI in cybersecurity refers to autonomous AI agents that can independently sense threats, make decisions, take actions, and verify outcomes — without requiring human intervention for every step. Unlike traditional automation that follows rigid playbooks, agentic AI agents use multi-step reasoning, adapt to novel situations, and improve over time. They operate in a continuous Sense → Decide → Act → Verify loop, handling everything from alert triage to compliance evidence generation to automated threat remediation.
SOAR (Security Orchestration, Automation, and Response) platforms require pre-defined playbooks written by security engineers. They execute fixed if-then sequences and break when encountering scenarios outside their rules. Cybersecurity AI agents, by contrast, use large language models and multi-step reasoning to handle novel situations autonomously. They can investigate alerts they've never seen before, generate evidence without templates, and adapt their approach based on context — making them fundamentally more flexible and resilient than traditional SOAR automation.
AI agents are designed to augment human analysts, not replace them entirely. They excel at automating high-volume, repetitive tier-1 SOC tasks — alert triage, log correlation, false positive filtering, and initial investigation. This frees human analysts to focus on strategic decision-making, threat hunting, and complex incident response that requires creativity and business context. Most organisations find that AI agents effectively replace the need to scale headcount while dramatically improving coverage and response times.
Cybersecurity AI agents can automate a wide range of security operations: continuous attack surface discovery, dark web monitoring for leaked credentials, phishing simulation and security training, compliance evidence collection and audit preparation, third-party vendor risk assessment, email authentication enforcement (DMARC/SPF/DKIM), brand impersonation detection and takedown, cloud misconfiguration detection, API security testing, threat intelligence correlation, SOC alert triage and investigation, and data privacy request fulfilment.
Yes, when designed with proper guardrails. Hunto AI's agents operate with human-in-the-loop controls for high-impact actions — meaning they can autonomously investigate and recommend, but destructive or irreversible actions require approval. Every agent action is logged with full audit trails, and agents operate with least-privilege access to your infrastructure. The verification step in the Sense → Decide → Act → Verify loop ensures that agents confirm the effectiveness of their actions before closing an investigation.
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