Agentic Threat Prevention
Predict the attack.
Prevent the breach.
Protect against AI-powered attacks with customized predictions, agentic adaptability, and cloud-native scale.
Today's Challenges
AI attacks now adapt faster than defenses.



01 / 03
The visibility gap
Agentic attackers identify, chain, and exploit weaknesses to execute sophisticated multi-stage attacks.
02 / 03
Attacks are adaptive
Agentic adversaries launch an initial attack, observe the outcome, then pivot techniques to retry in real time.
03 / 03
Attack volume is rising
AI dramatically increases attack volume overwhelming appliances with performance limitations.
Our approach
Stay ahead of AI-powered attacks
Cato Agentic Threat Prevention brings specialized defensive agents into the Single Pass Cloud Engine (SPACE) to anticipate enterprise-specific attack paths, adapt protections autonomously, and scale resources as attack traffic surges. Instead of waiting for manual analysis, static signatures, or appliance updates, Cato adapts prevention to each enterprise’s environment as attacker indicators, behavior, and adaptations change.
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Predict based on context
Apply shared context for a holistic view of network assets and security events that drive accurate predictions of attacker’s likely next steps.
Adapt policies autonomously
Adjust policy at machine speed to block predicted actions and disrupt adaptive, multi-stage attacks.
Scale defenses automatically
Expand cloud-based resources on demand as AI-powered attack traffic surges, avoiding appliance limits and protection-depth tradeoffs.
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Don’t react to AI attacks.
Get ahead of them.
How it works
Agentic Threat Prevention Capabilities
Enterprise-specific threat modeling
Model the attack surface
Customize protection to each enterprise’s real environment, not generic attack patterns.
- Model the attack surface through shared context
- Combines platform telemetry and threat intelligence
- Moves beyond one-size-fits-all detections

Agentic attack-chain reasoning
Anticipate attack paths
Anticipate how AI-powered attackers may combine techniques as attacks unfold.
- Identify how separate signals can chain into a successful attack path
- Model alternate routes, protocols, pivots, and evasion techniques
- Focus on attacker objectives and behaviors, not just known indicators

Agentic adaptation
Autonomous protection creation
Turn threat insight into enterprise-specific protections without waiting on manual rule work.
- Generate custom prevention policies
- Adapt protections as threats evolve
- Expand protection coverage as new attack paths appear

Move at the speed of AI
Prevention at machine speed
Stop adaptive attacks as they change tactics, protocols, or paths in real time.
- Adapt protections as attacker behavior changes
- Move at AI speed without manual interruption
- Block attack progression earlier

Cloud-native inspection capacity
Avoid appliance limitations
Keep prevention effective as AI attacks increase attack volume, decryption requirements, signatures, and inspection depth.
- Scale defensive resources through the cloud-native platform
- Maintain performance as rules, signatures, and attack traffic grow
- Avoid appliance compute limitations, patching, and maintenance outages

Global protection platform
Global SSE Enforcement
Apply new protections everywhere through one inspection engine and one policy framework.
- Enforce protections globally across users, sites, applications, and traffic
- Protection delivered without appliance updates
- Simplify policy, maintenance, and operational burdens

See it in action
Watch how Cato does it
Customer Stories
Customers love Cato
Our SOC alerted us to a malware site accessed by one of our users, but when we checked Cato logs, Cato had already blocked the connection before any infection occurred. Cato’s threat prevention worked faster than our external SOC.
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What to expect
15–30 minute session with a SASE product expert
Discuss your use cases and how we can help
Live product demonstration where applicable
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