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11/07/2026 1:59 pm
TL;DR: SentinelLABS’ 2025 review says threat actors used AI to accelerate spam, phishing, and code generation, monitored defender intelligence platforms, and abused trusted infrastructure at scale, while ransomware and credential theft kept evolving, according to SentinelOne. The signal for practitioners is that operational tempo, infrastructure trust, and intelligence leakage now matter as much as malware itself.
NHIMG editorial — based on content published by SentinelOne: SentinelLABS 2025 research review and year-end threat trends
Questions worth separating out
Q: What breaks when attackers can use AI to scale phishing and spam?
A: Traditional spam and content filters lose effectiveness when every message can be varied cheaply at runtime.
Q: Why do trusted platforms make attacker campaigns harder to stop?
A: Because the attacker inherits the credibility and resilience of a legitimate service.
Q: How do security teams know whether their intelligence sharing is exposing them?
A: Look for rapid changes in attacker infrastructure after publication, repeat monitoring of your public indicators, and unusually fast takedowns or re-registration patterns.
Practitioner guidance
- Audit public trust surfaces Review which accounts, tokens, publishing systems, and third-party services can be used to reach customers, analysts, or internal users.
- Add AI-assisted abuse detections Tune detection logic for high-volume, variable content generation, fake CAPTCHA patterns, automated form submissions, and repeated infrastructure creation.
- Constrain non-human identities with tighter lifecycle control Inventory service accounts, API keys, tokens, and platform credentials that can publish, post, or call external services.
What's in the full report
SentinelOne's full review covers the operational detail this post intentionally leaves for the source:
- Campaign-by-campaign breakdowns of the 2025 research publications and the specific adversary tradecraft observed.
- Technical context for how AI was used in runtime code generation, spam automation, and CAPTCHA bypassing.
- Case details on infrastructure reuse across free-tier platforms, messaging services, and attacker-controlled delivery layers.
- Additional examples of how defenders’ own intelligence platforms were monitored and exploited as operational signals.
👉 Read SentinelOne's 2025 SentinelLABS threat research review →
AI weaponization, trust abuse, and defender surveillance in 2025?
Explore further
11/07/2026 2:10 pm
AI weaponisation now changes attacker throughput, not attacker intent. The review is clear that AI is being used to accelerate phishing, code generation, and social engineering rather than to create entirely new classes of compromise. That distinction matters for governance because many control frameworks still focus on content review or known signatures, both of which degrade quickly when generation becomes cheap and repetitive blocking becomes the norm. Practitioners should treat AI as an operational multiplier that compresses attacker dwell time and increases volume, not as a separate risk silo.
A question worth separating out:
Q: Who is accountable when attackers abuse legitimate accounts and tokens?
A: Accountability sits with the teams that own identity lifecycle, platform governance, and response processes. That includes security, IAM, and service owners when accounts or tokens can publish, post, or automate externally. Governance should assign clear ownership for inventory, rotation, revocation, and abuse response.
👉 Read our full editorial: AI weaponization and defender surveillance reshaped 2025 threat tradecraft
