ZeroFox AI is built directly into the ZeroFox Platform to automate threat intelligence from discovery through disruption. It handles the heavy lifting across triage, investigation, takedowns, and reporting so security teams can keep pace with faster, more complex attacks.
AI has multiplied attackers while overwhelming analysts with low-value alerts and fragmented context. Signals are everywhere, but prioritization is unclear and insight arrives too late to act. Security teams face a new reality: AI multiplies the number of hands that can deploy evolved tactics, overloading analyst workflows. Signals are everywhere, but context is scattered, prioritization is unclear, and insight arrives too late to act.
Here's the reality: threat data keeps growing. Analyst time doesn't. It’s time for AI to do the heavy lifting in your security operations, freeing up time for your team to act.
ZeroFox AI simplifies security operations by automating analysis across billions of threat signals. It delivers prioritized threats through natural language search, smart detection, and human-validated insights teams can act on immediately. Applied correctly, AI reduces complexity, improves accuracy, and enables better decisions across the entire security lifecycle.
ZeroFox embeds AI across the full threat lifecycle with human analysts, unlike bolt-on alert generators. Many security tools bolt AI onto existing workflows, generating more alerts without improving outcomes. ZeroFox takes a different approach. AI is embedded across the full threat lifecycle, working alongside human analysts to surface real risk and take action.
ZeroFox AI continuously monitors domains, social platforms, exposed credentials, executive identities, expired hostnames, and more. As new assets and attack vectors emerge, they are identified in near real time.
AI models and expert analysts transform raw signals into a correlated evidence risk graph, adding context, evidence, and prioritization so teams know what matters and why.
ZeroFox SOC teams coordinate takedowns through the Global Disruption Network, partnering with registrars, platforms, ISPs, and hosts to block abuse and reduce attacker dwell time.
Prioritize critical threats first to reduce noise and dramatically cut analyst triage time.
Detect deepfakes and audio-based abuse that evade traditional text-only security tools.
Identify logo theft, visual impersonation, and brand abuse to prevent revenue and reputational damage.
Continuously improve detection accuracy as attackers evolve tactics and techniques.
Automatically connect activity across platforms to reveal coordinated attacks and shared infrastructure.
Surfaces early warning signals across social channels and identifies potential security or brand threats.
In a reality where deepfakes are predicted to cause $40 billion worth of fraud losses in the United States by 2027, the most relevant question to ask is no longer “Can AI detect deepfakes?”, it's whether organizations can go beyond detection to achieve a unified threat defense.
