The most secure endpoints are secure by design, equipped from the outset with a purpose-built security platform that integrates deeply with contextual telemetry across the environment. This integrated, security-by-design foundation minimizes vulnerabilities and establishes a resilient defense against AI-powered cyberattacks.
For decades, cybersecurity operated on signatures and samples. Antivirus engines scanned files, compared them to known malware, and blocked what looked suspicious. But AI-driven adversaries have now rendered that model insufficient. Criminal hackers increasingly use artificial intelligence to craft stealthy, adaptive, non-malware attacks engineered to evade traditional detection. Many of today’s most dangerous intrusions never drop a file at all.
To counter threats that move at machine speed and hide inside legitimate activity, defenders must do the same. That’s why Lenovo’s ThinkShield XDR with SentinelOne brings together behavioral intelligence powered by AI—running both on the device and in the cloud. It’s the combination that provides the speed, context, and adaptability required to keep up with AI-driven attackers.
Why modern defense requires both device and cloud AI
AI-driven attacks demand two complementary capabilities: immediate visibility at the device level and global learning at cloud scale. On-device AI provides real-time behavioral monitoring of processes, memory, scripts, and user activity. Because decisions are made locally, detection and response happen instantly—even offline, roaming, or in air-gapped environments. This speed is critical for stopping fast-moving attacks before they escalate.
But no endpoint operates alone. Attack techniques evolve continuously, and what looks benign in one environment may already be identified as malicious elsewhere. Cloud-based AI aggregates telemetry from millions of endpoints, identifies emerging attack patterns, and distributes that intelligence back to every device, closing the loop.
Imagine a user’s laptop is hit by a new ransomware script in an airport lounge. On-device AI kills the process in milliseconds. Once back online, the device shares the attack DNA with cloud intelligence, which analyzes the threat and vaccinates the global fleet. This hybrid model merges local speed with global perspective—matching the adaptability of modern attackers.
How hackers are leveraging AI
AI has dramatically lowered the barrier to sophisticated cybercrime. Generative models can:
- Write convincing, personalized phishing at scale
- Generate environment-aware attack scripts
- Mutate behaviors to avoid detection
- Probe defenses with machine-driven iteration
More advanced adversaries increasingly use living-off-the-land techniques: PowerShell, Windows Management Instrumentation (WMI), legitimate administrative tools, or cloud APIs, leaving behind no malware and no obvious indicators. What remains looks like normal system activity, making traditional defenses blind to the attack.
Why local intelligence alone is not enough
Static, on-device AI engines excel at pre-execution decisions and blocking known threats. But when attacks unfold over time using legitimate tools, a single endpoint has limited perspective. A PowerShell command, a credential use, or a remote connection may appear harmless in isolation.
Cloud-scale correlation changes that. By analyzing patterns across thousands of environments, cloud AI can connect the dots and identify known attack sequences. Feeding this insight back to devices sharpens local detections and accelerates response, creating an adaptive defense that improves continuously.
Why behavior matters more than signatures
Modern breaches routinely avoid antivirus alarms because fileless attacks execute in memory, scripts are generated dynamically, and credentials are misused rather than stolen via malware.
Behavioral AI focuses on intent and outcome, not artifacts.
A PowerShell launch may be normal, but a 2 a.m. PowerShell process from a finance laptop initiating credential dumping is not. By correlating activity across processes, identities, and time, behavioral engines detect subtle indicators of compromise that no single event would reveal. This is especially effective against zero-day and fileless attacks.
A necessary change in mindset
Too many organizations still optimize for yesterday’s threats. Commodity malware is familiar and visible, while AI-driven, fileless attacks feel abstract, until they succeed.
Most breaches occur not because a security tool is missing, but because tools don’t communicate. A suspicious login, an odd API call, and an unusual file movement may look trivial on their own. Together, they represent data exfiltration in progress.
Solutions like ThinkShield XDR with Sentinel One unify telemetry across endpoint, network, and cloud to turn disconnected noise into intelligent, automated defense. In an AI-driven threat landscape, cybersecurity is no longer about spotting bad files – it’s about understanding behavior and recognizing when something normal is anything but.
